# APIContext — Full Content Index Full canonical content of every page in the APIContext website. For a concise index with links, see /llms.txt. For a structured JSON index with per-page AI endpoint URLs, see /ai/index.json. --- # Home Canonical URL: https://apicontext.com Source: static Description: From cloud node to edge, to origin, to payload — APIContext is the only platform that walks the entire path, and hands you OTEL signal at every hop\. ## Summary Simulate the full customer journey\. End\-to\-end\. From cloud node to edge, to origin, to payload — APIContext is the only platform that walks the entire path, and hands you OTEL signal at every hop\. ## Stats - 125\+ global nodes - OAuth mTLS · JWT · HMAC supported - SLO \+ SLA real\-time service level reporting - OTEL native on every call ## Page sections ### Reachability, availability & latency Know when your digital services respond — and when they don't — from every region, every network, every carrier\. Globally consistent, continuously\. - 125\+ locations - Every 30s - Sub\-second alerts ### Verify contracts from the outside\-in Assert that multi\-step, fully\-authenticated transactions are doing what they're supposed to do — not just returning 200\. Catch schema drift before your customers do\. - JSON Schema - Side\-effect checks - OAuth · mTLS · JWT ### One journey\. Eleven spans\. Full request and response captured\. Category: Trace end\-to\-end The same checkout flow, running synthetically from 125\+ locations\. Every span is native OTEL, every assertion is evaluated outside\-in\. ### Every synthetic check ships as native OTEL\. We're not another data silo\. Consume our signal inside APIContext, or stream it into the APM you already pay for — traces, metrics, and logs, spec\-compliant, at source\. - Traces - Metrics - Logs - Profiles - Events - Datadog \(native\) - Dynatrace \(native\) - TrafficPeak \(partner\) - Grafana \(OTEL\) - Splunk \(OTEL\) - New Relic \(OTEL\) - Your collector \(OTLP\) - Honeycomb \(OTEL\) ### Your APM tells you what users did\. We tell you what's waiting for them\. API blind spots: Endpoints your APM can't see because no user hit them today\. We hit them for you — every 30 seconds, from everywhere\. Browser blind spots: JS that breaks on a customer's device but loads fine on yours\. Real\-browser checks from real geographies\. MCP blind spots: AI clients hit your MCP server differently than humans hit your API\. We verify tool responses match the contract\. Transaction blind spots: Multi\-step flows with auth, side effects, and contract guarantees — not just a ping against /healthz\. Regional blind spots: The customer in São Paulo sees a different internet than your NYC monitor\. We check from both — and 123 more\. Topology blind spots: Where did the latency actually come from? Cloud, edge, origin, or payload\. We show every hop\. ### Keep your SLOs honest\. Category: Site Reliability Burn\-rate alerts fired against real customer paths — not pings against a load balancer\. Root\-cause in one trace instead of five dashboards\. - Full MELT on every check, auto\-shipped to your APM - Fault injection on the synthetic path - Error budget tied to journey\-level SLIs ### See every hop your users take\. Category: Platform / Infra Cloud → edge → origin → payload, in one topology view\. Correlate cloud provider incidents with real\-customer impact in seconds\. - Traces span CDN, edge, origin and 3rd\-party APIs - Correlate to AWS / GCP / Azure status automatically - Push signals to Datadog, Dynatrace or TrafficPeak ### Verify contracts, not just 200s\. Category: API owners Multi\-step flows with full auth, request and response assertions\. Catch schema drift, hallucinated fields and broken side\-effects before customers do\. - JSON Schema, JSONPath & custom assertions - OAuth, mTLS, JWT, signed HMAC — no glue code - Reproducible transactions across regions ### Ship features customers can actually reach\. Category: Product managers Measure the feature, not the microservice\. Funnel drop\-offs map to the exact hop in the journey that broke\. - Journey\-level availability by feature - Weekly drift reports across regions - Status pages your execs will actually read ### Strategic partners Category: Strategic partners We stream native signal into the APMs and edge platforms your business already runs on\. - Akamai — TrafficPeak partner - Datadog — Native OTEL destination - Dynatrace — Certified integration - AWS — ISV Accelerate partner ## Key facts - 125\+ global nodes - OAuth mTLS · JWT · HMAC supported - SLO \+ SLA real\-time service level reporting - OTEL native on every call - Reachability, availability & latency: Know when your digital services respond — and when they don't — from every region, every network, every carrier\. Globally consistent, continuously\. - Verify contracts from the outside\-in: Assert that multi\-step, fully\-authenticated transactions are doing what they're supposed to do — not just returning 200\. Catch schema drift before your customers do\. - The same checkout flow, running synthetically from 125\+ locations\. Every span is native OTEL, every assertion is evaluated outside\-in\. - We're not another data silo\. Consume our signal inside APIContext, or stream it into the APM you already pay for — traces, metrics, and logs, spec\-compliant, at source\. - Datadog \(native\) - Dynatrace \(native\) - TrafficPeak \(partner\) - Grafana \(OTEL\) - Splunk \(OTEL\) - New Relic \(OTEL\) - Your collector \(OTLP\) - Honeycomb \(OTEL\) - Your APM tells you what users did\. We tell you what's waiting for them\. - Site Reliability: Keep your SLOs honest\. Burn\-rate alerts fired against real customer paths — not pings against a load balancer\. Root\-cause in one trace instead of five dashboards\. - Platform / Infra: See every hop your users take\. Cloud → edge → origin → payload, in one topology view\. Correlate cloud provider incidents with real\-customer impact in seconds\. - API owners: Verify contracts, not just 200s\. Multi\-step flows with full auth, request and response assertions\. Catch schema drift, hallucinated fields and broken side\-effects before customers do\. - Product managers: Ship features customers can actually reach\. Measure the feature, not the microservice\. Funnel drop\-offs map to the exact hop in the journey that broke\. - Akamai — TrafficPeak partner - Datadog — Native OTEL destination - Dynatrace — Certified integration - AWS — ISV Accelerate partner ## Primary entities - APIContext - API monitoring - synthetic journeys - OpenTelemetry - API blind spots ## Audience - API owners - SRE teams - product teams - platform teams ## Primary links - [Start free](https://client.apimetrics.io/register) - [Watch a 2\-min journey](/resources) --- # About Us Canonical URL: https://apicontext.com/about Source: static Description: APIContext monitors resilience in every connection, combining outside\-in reliability testing with runtime conformance validation\. ## Summary Resilience in Every Connection\. APIContext monitors resilience in every connection, combining outside\-in reliability testing with runtime conformance validation\. We are built for modern enterprise ecosystems to ensure that you see your application performance and conformance like your machine users\. ## Page sections ### About APIContext Category: Company APIContext monitors resilience in every connection, combining outside\-in reliability testing with runtime conformance validation\. We are built for modern enterprise ecosystems to ensure that you see your application performance and conformance like your machine users\. ### Monitoring Performance and Conformance Category: What we monitor Our solutions are designed to prove resilience across hybrid and cloud ecosystems and throughout the digital transformation journey\. We provide the verification layer for machine resilience, catching silent failures so systems perform and conform at scale\. ### Leadership Category: Leadership Jamie Beckland, CMO / CPO; Mayur Upadhyaya, CEO; Lelah Manz, Board Chair; Nick Denny, Chief Engineer; Niall Burns, CTO; David O'Neill, COO / CCO ## Key facts - APIContext monitors resilience in every connection, combining outside\-in reliability testing with runtime conformance validation\. We are built for modern enterprise ecosystems to ensure that you see your application performance and conformance like your machine users\. - Our solutions are designed to prove resilience across hybrid and cloud ecosystems and throughout the digital transformation journey\. - We provide the verification layer for machine resilience, catching silent failures so systems perform and conform at scale\. - Jamie Beckland — CMO / CPO - Mayur Upadhyaya — CEO - Lelah Manz — Board Chair - Nick Denny — Chief Engineer - Niall Burns — CTO - David O'Neill — COO / CCO ## Primary entities - APIContext - API monitoring - API conformance - leadership team ## Audience - API teams - SRE teams - prospective customers ## Primary links - [Contact us](/contact) --- # Akamai Subscription Agreement Canonical URL: https://apicontext.com/akam-subscription-agreement Source: static Description: APIContext subscription agreement terms and conditions for Akamai subscribers\. ## Summary This agreement governs your subscription to APIContext API monitoring services\. ## Page sections ### Subscription Agreement for Akamai Subscribers Category: Legal This Agreement is between the entity entering this Agreement \(“Subscriber”\) and APIContext Inc\. \(“APIContext”\) \(collectively the “Parties” and each a “Party”\)\. Under this Agreement, Subscriber has a limited and revocable right to subscribe to, access and use the Services defined below, as described by and limited by this Agreement\. Notwithstanding any provision of this Subscription Agreement, any existing contractual terms agreed in Subscriber's current licensing agreement with Akamai shall take precedence and supersede the terms set forth herein, where applicable\. SUBSCRIBER AGREES TO BE BOUND BY THE TERMS OF THIS AGREEMENT BY REGISTERING FOR AN ACCOUNT WITH APICONTEXT OR ORDERING A SERVICE PROVIDED BY APICONTEXT\. THIS AGREEMENT WILL BE EFFECTIVE ON THE DATE SUBSCRIBER COMPLETES REGISTRATION FOR AN ACCOUNT OR ORDERS THE SERVICE \(“EFFECTIVE DATE”\)\. 1\. Selected Definitions “Agreement” means this Subscription Agreement, any Invoices, and any materials available on the APIContext website specifically incorporated by reference herein, including APIContext’s Website Terms of Service at https://apicontext\.com/tos and Privacy Policy at https://apicontext\.com/privacy, as such materials, including the terms of this Agreement, may be updated by APIContext from time to time in its sole discretion\. “APIContext Technology” means all of APIContext’s proprietary technology \(including software, hardware, products, processes, algorithms, user interfaces, know\-how, techniques, designs, and other tangible or intangible technical material or information\) made available to Subscriber by APIContext in providing the Service\. “Content” means the audio and visual information, documents, software, products, data and services contained or made available to Subscriber in the course of using the Service\. “Data Content” means the test results, performance metrics, reports, and other outputs generated by the Services from Subscriber Data or Subscriber’s use of the Services\. “Initial Term” means the Initial Term identified on any Invoice or the Subscription Management Page\. The Initial Term is free unless indicated otherwise in the Invoice or Subscription Management Page\. “Intellectual Property Rights” means any unpatented inventions, patent applications, patents, design rights, copyrights, trademarks, service marks, trade names, domain name rights, mask work rights, know\-how and other trade secret rights, and all other intellectual property rights, derivatives thereof, and forms of protection of a similar nature anywhere in the world\. “Invoice\(s\)” means the form evidencing the initial subscription for the Service and any subsequent Invoices submitted online or in written form, specifying, among other things, the number of Licenses and Services contracted for, the applicable fees, and other charges as agreed to between the Parties, each such Invoice to be incorporated into and to become a part of this Agreement \(in the event of any conflict between the terms of this Agreement and the terms of any such Invoice, the terms of this Agreement shall prevail except as otherwise stated in this Agreement\)\. The Invoice will be on the Subscription Management Page, unless the Parties have entered a separate, signed and written Invoice\. APIContext may or may not send an Invoice to Subscriber based on the type of Service that Subscriber has ordered\. All Service pricing is online unless a separate agreement has been reached\. “License Administrator\(s\)” means those Users designated by Subscriber who are authorized to purchase Licenses by executing written Invoices and to create User accounts and otherwise administer Subscriber’s use of the Service\. “Renewal Term\(s\)” means any Term after the Initial Term\. “Service\(s\)” means the specific edition of APIContext's online service identified during the ordering process, developed, operated, and maintained by APIContext and made available to Subscriber under this Agreement, including APIContext Technology and applicable Content, whether accessed through apicontext\.com, any APIContext\-owned or operated website, domain or subdomain, or any other location designated by APIContext for delivery of the Services\. The scope of the Services depends on the subscription plan or services contracted by Subscriber at agreement execution\. “Subscriber Data” means any data, information, or other materials provided or submitted by Subscriber to the Services, together with Data Content generated from Subscriber’s use of the Services, but excluding APIContext Technology and Aggregate Data as defined in Section 4\(c\)\. “Subscription Management Page” means APIContext’s online application that allows the License Administrator, among other things, to add additional Users to the Service\. The invoice and other Service details are available on the Subscription Management Page\. “Term\(s\)” means the period\(s\) during which a specified number of Users are licensed to use the Service pursuant to the Invoices\(s\)\. Term includes both the Initial Term and Renewal Term\(s\)\. “User\(s\)” means Subscriber employees, representatives, consultants, contractors, or agents who are authorized to use the Service and have been supplied user identifications and passwords by Subscriber \(or by APIContext at Subscriber’s request\)\. 2\. Service License Grant and Restrictions a\. APIContext hereby grants Subscriber a limited, revocable, nonexclusive, nontransferable, right to use the Service globally to create, store, and run the Service within the bounds of the Service level chosen by Subscriber, for the Term, solely for Subscriber’s own internal business purposes, subject to the terms and conditions of this Agreement \(“License”\)\. All rights not expressly granted to Subscriber are reserved by APIContext and its licensors\. Subscriber may not access the Service if Subscriber is a direct competitor of APIContext, except with APIContext’s prior written consent\. In addition, Subscriber may not access API Monitor for purposes of monitoring the Services’ availability, performance or functionality, or for any other benchmarking or competitive purposes except pursuant to a separate, written and executed agreement between the Parties\. The License is subject to the limitations in Section 3 below\. b\. Subscriber shall not \(i\) license, sublicense, sell, resell, transfer, assign, distribute, or otherwise commercially exploit or make available to any third party the Service or the Content in any way; \(ii\) modify or make derivative works based upon the Service or the Content; \(iii\) create Internet links to the Service or frame or mirror any Content on any other server or wireless or Internet\-based device; or \(iv\) reverse engineer or access the Service in order to \(a\) build a competitive product or service, \(b\) build a product using similar ideas, features, functions or graphics of the Service, or \(c\) copy any ideas, features, functions or graphics of the Service\. For purposes of this Section 2\(b\), neither the Service nor Content includes Subscriber Data or Data Content owned by Subscriber under Section 3\(a\)\. The permission to use Subscriber Data and Data Content does not authorize Subscriber to resell, sublicense, or provide the Services as a managed service without a separate written agreement with APIContext\. User Licenses cannot be shared or used by more than one individual User but may be reassigned from time to time to new Users who are replacing former Users who have terminated employment or otherwise changed job status or function and no longer use the Service\. c\. Subscriber shall not use the Service to: \(i\) send spam or otherwise duplicative or unsolicited messages in violation of applicable laws, or otherwise violate any law in connection with the Services or this Agreement; \(ii\) send or store infringing, obscene, threatening, libelous, or otherwise unlawful or tortuous material, including material harmful to children or that violates third party privacy rights; \(iii\) send or store material containing software viruses, worms, Trojan horses, or other harmful computer code, files, scripts, agents, or programs; \(iv\) interfere with or disrupt the integrity or performance of the Service or the data contained therein; or \(v\) attempt to gain unauthorized access to the Service or its related systems or networks\. d\. This Agreement entitles the Subscriber the limited, revocable right to access the Service through the use of a single Subscriber account\. One License grants the Subscriber one \(1\) License Administrator account to access the Service and one \(1\) sub\-License for each User designated by the Subscriber\. Subscriber is responsible for conforming all User activities to Subscriber’s obligations and restrictions under this Agreement and is responsible for all User activities related to the Service as if they were Subscriber’s own activities\. e\. The License Administrator may add Users by updating User information on the User Admin page of the Service\. Added User Licenses will be coterminous with the preexisting Term \(either Initial Term or Renewal Term\)\. 3\. Data Content Accessed Through the Services a\. Subscribers to the Services can upload their Subscriber Data, access Data Content developed using their Subscriber Data, and download Data Content developed using their Subscriber Data\. Subscriber shall retain full right, title and interest in and to all of its Subscriber Data and Data Content generated by the Services, and may use, reproduce, modify, distribute, and share such Data Content for its lawful business purposes, including reporting, audits, compliance, and assessing or enforcing agreements or service level obligations with third parties, without APIContext’s prior approval, subject to APIContext’s rights under Section 4\(c\)\. APIContext reserves the right to publish, display, distribute, or otherwise use the results of API Monitor tests run by Subscribers registered for a free trial account\. Identifying information \(e\.g\. user name, company name, and address\) will not be made available at any time to any other Subscriber subscribing to the Service\. b\. Subscriber, not APIContext, shall have sole responsibility for the accuracy, quality, integrity, legality, reliability, appropriateness, and intellectual property ownership or right to use Subscriber Data uploaded to the Services\. APIContext shall not be responsible or liable for the deletion, correction, destruction, damage, or loss of any Subscriber Data\. c\. APIContext’s Privacy Policy further describes APIContext’s collection and use of Subscriber’s information\. d\. APIContext will use reasonable technical, physical and administrative measures to prevent unauthorized access and use of Subscriber’s Subscriber Data\. 4\. Intellectual Property Ownership a\. APIContext \(and its licensors, where applicable\) shall exclusively own all right, title, and interest, including all related Intellectual Property Rights, in and to the APIContext Technology, the Content and the Service, excluding Subscriber Data and Data Content owned by Subscriber under Section 3\(a\)\. Subscriber assigns to APIContext all ownership and intellectual property rights including any copyrights in any suggestions, ideas, enhancement requests, feedback, recommendations, or other information provided by Subscriber or its Users to APIContext related to the Service\. b\. This Agreement is not a sale and does not convey to Subscriber any rights of ownership in or related to the Service, the APIContext Technology, or the Intellectual Property Rights owned by APIContext\. APIContext’s name, APIContext’s logo, and the product names associated with the Service are trademarks of APIContext or third parties, and no right or license is granted to use them\. c\. Aggregate Data\. APIContext owns all rights to aggregated or de\-identified data and metadata generated by or derived from the Service \(“Aggregate Data”\) and may use such Aggregate Data for any purpose, provided that it does not identify Subscriber or disclose Subscriber test results or configurations\. 5\. Subscriber Responsibilities; Prohibited Data a\. Subscriber is responsible for all activity occurring under Subscriber’s License Administrator and User accounts and shall abide by all applicable local, state, national, and foreign, laws, treaties and regulations in connection with Subscriber’s use of the Service, including those related to data privacy, international communications, and the transmission of technical or personal data\. Subscriber shall: \(i\) notify APIContext as soon as possible but no less than three \(3\) days after discovery of any unauthorized use of any password or account or any other known or suspected breach of security; \(ii\) report to APIContext as soon as possible \(but no less than three \(3\) days after discovery\) and use reasonable efforts to stop immediately any copying or distribution of Content that is known or suspected by Subscriber or Subscriber Users; and \(iii\) not impersonate another APIContext user or provide false identity information to gain access to or use the Service\. b\. Subscriber will not upload or submit any personally\-identifiable information or other sensitive information to the Service other the limited technical data required to use the Service\. 6\. Third Party Interactions a\. Subscriber recognizes that certain third party providers of ancillary software, hardware, or services may require Subscriber’s agreement to additional or different licenses or other terms prior to Subscriber’s use of or access to such software, hardware or services\. APIContext and its licensors shall have no liability, obligation, or responsibility for any such agreement between Subscriber and any such third party\. 8\. Availability, Support, and Service Updates a\. Subject to the terms of this Agreement, APIContext will use commercially reasonable efforts to provide 99\.99% monthly uptime availability, exclusive of any Maintenance Events, for use by Subscriber\. b\. Support is available from 8 a\.m\. to 8 p\.m\. U\.S\. Eastern Standard Time, Monday through Friday, exclusive of U\.S\. holidays\. APIContext will take commercially reasonable efforts to resolve Service Issues in accordance to the following guidelines: • Service Issues with Severity 1, which cause a critical function or component of the APIContext platform to \(i\) be not available, not functional, or substantially unusable; or \(ii\) to have materially adverse effect on the ability to utilize the Service, will have a target response time of 30 minutes and a target mitigation time of 2 hours\. • Service Issues with Severity 2, which case the performance or functionality of the Service, or a critical function or component therein, to be materially degraded under ordinary workloads, will have a target response time of 1 hour and a target mitigation time of 4 hours\. • Service Issues with Severity 3, which are Service Issues that do not qualify as Severity 1 or Severity 2, will have a target response time of 4 hours and a target resolution time of 1 business day\. • Request with Severity 4, which are any requests that are not Service Issues, including without limitation, feature requests, will have a target response time of 8 hours and a target resolution time of 2 business days\. c\. APIContext reserves the right to update, modify, or discontinue features of the Service at any time without notice\. If APIContext materially decreases functionality of the Service, then Subscriber may terminate this Agreement upon thirty \(30\) days advance written notice\. 8\. Availability and Service Updates a\. Subject to the terms of this Agreement, APIContext will use commercially reasonable efforts to provide access to the Service twenty\-four \(24\) hours a day, seven \(7\) days a week for use by Subscriber\. b\. APIContext reserves the right to update, modify, or discontinue features of the Service at any time without notice\. If APIContext materially decreases functionality of the Service, then Subscriber may terminate this Agreement upon thirty \(30\) days advance written notice\. 9\. Nonpayment and Suspension a\. In addition to any other rights granted to APIContext herein, APIContext reserves the right to suspend or terminate this Agreement and Subscriber’s access to the Service if Subscriber’s account has an outstanding subscription balance beyond the payment terms shown on the Subscriber’s Invoice\. Delinquent payments and accounts are subject to interest of 1\.0 percent per month on any outstanding balance, or the maximum permitted by law, whichever is less, plus all expenses of collection\. Subscriber will continue to be charged for Service during any period of suspension\. If Subscriber or APIContext initiates termination of this Agreement, Subscriber will be obligated to pay the balance due on Subscriber’s account\. Subscriber agrees that APIContext may bill Subscriber for such unpaid fees\. APIContext reserves the right to impose a reconnection fee in the event Subscriber is suspended and thereafter requests access to the Service\. 10\. Termination upon Expiration/Reduction in Number of Licenses a\. The Initial Term will be one month or as otherwise mutually agreed upon in an Invoice, commencing on the date of the APIContext’s Invoice\. b\. Upon the expiration of the Initial Term, this Agreement will automatically renew for successive one\-month \(unless otherwise indicated in the Invoice\) Renewal Terms at APIContext’s then current fees\. Either Party may terminate this Agreement or reduce the number of Licenses, effective only upon the expiration of the then\-current Term, by notifying the other Party in writing at least ten \(10\) days prior to the expiration of the Term\. In the case of free trials, notifications provided through the Service indicating the remaining number of days in the free trial shall constitute notice of termination\. c\. If this Agreement is terminated \(other than by reason of Subscriber’s breach as described in Section 11\), APIContext will make available to Subscriber a file of the Subscriber Data within 30 days of termination if Subscriber so requests at the time of termination\. Subscriber agrees and acknowledges that APIContext has no obligation to retain the Subscriber Data, and may delete such Subscriber Data, more than 30 days after termination\. 11\. Termination for Cause a\. Any breach of Subscriber’s payment obligations or unauthorized use of the APIContextTechnology or Service will be deemed a material breach of this Agreement\. APIContext, in its sole discretion, may terminate Subscriber’s password, account or use of the Service on written notice if Subscriber breaches or otherwise fails to comply with this Agreement\. In addition, APIContext may terminate a free account at any time in its sole discretion\. b\. Subscriber agrees and acknowledges that APIContext has no obligation to retain the Subscriber Data, and may delete such Subscriber Data, if Subscriber has materially breached this Agreement, including but not limited to failure to pay outstanding fees, and such breach has not been cured within 10 days of notice of such breach\. 12\. Representations and Warranties a\. Each Party represents and warrants that it has the legal power and authority to enter into this Agreement\. APIContext represents and warrants that it will provide the Service in a manner substantially in accordance with the online APIContext help documentation under normal use and circumstances\. Subscriber represents and warrants that Subscriber has not falsely identified Subscriber nor provided any false information to gain access to the Service and that Subscriber’s billing information is correct\. 13\. Mutual Indemnification a\. Subscriber shall indemnify and hold APIContext, its licensors and each such entity’s parent organizations, subsidiaries, affiliates, officers, directors, employees, attorneys, and agents harmless from and against any and all claims, costs, damages, losses, liabilities, and expenses \(including attorneys’ fees and costs\) arising out of or in connection with: \(i\) a claim alleging that use of the Subscriber Data infringes the rights of, or has caused harm to, a third party; \(ii\) a claim, which if true, would constitute a violation by Subscriber of Subscriber’s representations and warranties; and \(iii\) the breach by Subscriber or Subscriber Users of this Agreement\. b\. APIContext shall indemnify and hold Subscriber and Subscriber’s parent organizations, subsidiaries, affiliates, officers, directors, employees, attorneys, and agents harmless from and against any and all claims, costs, damages, losses, liabilities, and expenses \(including attorneys’ fees and costs\) to the extent arising out of or in connection with a claim alleging that the Service directly infringes a copyright, a U\.S\. patent issued as of the Effective Date, or a trademark of a third party; provided that Subscriber \(a\) promptly gives written notice of the claim to APIContext; \(b\) gives APIContext sole control of the defense and settlement of the claim; \(c\) provides to APIContext all available information and assistance; and \(d\) has not compromised or settled such claim\. APIContext shall have no indemnification obligation, and Subscriber shall indemnify APIContext pursuant to this Agreement, for claims arising from any infringement arising from the combination of the Services with any Subscriber or third party products, service, hardware or business process\(s\)\. 14\. Disclaimer of Warranties A\. APICONTEXT AND ITS LICENSORS MAKE NO REPRESENTATION, WARRANTY, OR GUARANTY AS TO THE RELIABILITY, TIMELINESS, QUALITY, SUITABILITY, TRUTH, AVAILABILITY, ACCURACY, OR COMPLETENESS OF THE SERVICE OR ANY CONTENT\. APICONTEXT AND ITS LICENSORS DO NOT REPRESENT OR WARRANT THAT \(A\) THE USE OF THE SERVICE WILL BE SECURE, TIMELY, UNINTERRUPTED, OR ERROR\-FREE OR OPERATE IN COMBINATION WITH ANY OTHER HARDWARE, SOFTWARE, SYSTEM, OR DATA; \(B\) THE SERVICE WILL MEET SUBSCRIBER’S REQUIREMENTS OR EXPECTATIONS; \(C\) ANY DATA STORED OR GENERATED THROUGH THE SERVICE WILL BE ACCURATE OR RELIABLE; \(D\) THE QUALITY OF ANY PRODUCTS, SERVICES, DATA, INFORMATION, OR OTHER MATERIAL OBTAINED BY SUBSCRIBER THROUGH THE SERVICE WILL MEET SUBSCRIBER’S REQUIREMENTS OR EXPECTATIONS; \(E\) ERRORS OR DEFECTS WILL BE CORRECTED; OR \(F\) THE SERVICE OR THE SERVER\(S\) THAT MAKE THE SERVICE AVAILABLE ARE FREE OF VIRUSES OR OTHER HARMFUL COMPONENTS\. THE SERVICE AND ALL CONTENT ARE PROVIDED TO SUBSCRIBER STRICTLY ON AN “AS IS” BASIS\. ALL CONDITIONS, REPRESENTATIONS AND WARRANTIES, WHETHER EXPRESS, IMPLIED, STATUTORY OR OTHERWISE, INCLUDING, WITHOUT LIMITATION, ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NON\-INFRINGEMENT OF THIRD PARTY RIGHTS, ARE HEREBY DISCLAIMED TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW BY APICONTEXT AND ITS LICENSORS\. APICONTEXT IS NOT LIABLE FOR DATA LOSS\. 15\. Internet Delays A\. APICONTEXT’S SERVICES MAY BE SUBJECT TO LIMITATIONS, DELAYS, OUTAGES, AND OTHER PROBLEMS INHERENT IN THE USE OF THE INTERNET AND ELECTRONIC COMMUNICATIONS\. APICONTEXT IS NOT RESPONSIBLE FOR ANY DELAYS, DELIVERY FAILURES, OR OTHER DAMAGE RESULTING FROM SUCH PROBLEMS\. 16\. Limitation of Liability A\. IN NO EVENT SHALL APICONTEXT’S AGGREGATE LIABILITY UNDER THIS AGREEMENT FOR ANY REASON \(INCLUDING INDEMNIFICATION\) EXCEED THE AMOUNTS ACTUALLY PAID BY AND/OR DUE FROM SUBSCRIBER DURING THE INITIAL TERM\. IN NO EVENT SHALL APICONTEXT AND/OR ITS LICENSORS BE LIABLE TO SUBSCRIBER OR ANYONE ELSE FOR ANY INDIRECT, PUNITIVE, SPECIAL, EXEMPLARY, INCIDENTAL, CONSEQUENTIAL, OR OTHER DAMAGES OF ANY TYPE OR KIND \(INCLUDING LOSS OF DATA, REVENUE, PROFITS, USE, OR OTHER ECONOMIC ADVANTAGE\) ARISING OUT OF, OR IN ANY WAY CONNECTED WITH THIS SERVICE OR AGREEMENT, INCLUDING BUT NOT LIMITED TO THE USE OR INABILITY TO USE THE SERVICE, OR FOR ANY CONTENT OBTAINED FROM OR THROUGH THE SERVICE, ANY INTERRUPTION, INACCURACY, ERROR, OR OMISSION, REGARDLESS OF CAUSE IN THE CONTENT, EVEN IF APICONTEXT OR APICONTEXT’S LICENSORS HAVE BEEN PREVIOUSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES\. 17\. Confidentiality a\. During the Term of this Agreement, APIContext may provide non\-public information \(“Confidential Information”\) to Subscriber\. Subscriber will not disclose the Confidential Information publically or use it for purposes unrelated to this Agreement\. Confidential Information includes but is not limited to this Agreement and any associated pricing terms\. Information provided by APIContext is presumed to be Confidential Information unless APIContext states otherwise\. Subscriber shall return any Confidential Information to APIContext within ten \(10\) days after written request by APIContext or upon termination or expiration of this Agreement\. Subscriber will inform APIContext in writing within three \(3\) business days after it has knowledge of a violation of this section and provide sufficient facts to enable APIContext to take necessary precautionary actions\. Subscriber will delete or destroy all Customer Confidential Information within thirty \(30\) days after termination of this Agreement\. 18\. Notices a\. APIContext may give notice related to this Agreement by means of a general notice on the Service or the Subscription Management Page, email to the Subscriber address on record in APIContext’s account information, or by written communication sent by first class mail or pre\-paid post to Subscriber address on record in APIContext’s account information\. Such notice shall be deemed to have been given upon the expiration of 48 hours after mailing or posting \(if sent by first class mail or pre\-paid post\) or 12 hours after sending \(if sent by email\)\. Subscriber will give notices to APIContext \(such notice shall be deemed given when received by APIContext\) by nationally\-recognized overnight delivery service or United States Postal Service Certified Mail, return receipt requested, to APIContext, Inc\., 8 The Green, Ste R, Dover, DE 19901\. 19\. Modification to Terms a\. APIContext reserves the right to modify the terms and conditions of this Agreement or its policies relating to the Service at any time, effective upon posting of an updated version of this Agreement on the Service or on its website\. 20\. Assignment; Change in Control a\. This Agreement may not be assigned by Subscriber without the prior written approval of APIContext\. An unapproved assignment is void\. APIContext may assign this Agreement to a third party on written notice to Subscriber\. Any actual or proposed change in control of Subscriber that results or would result in a direct competitor of APIContext directly or indirectly owning or controlling 50 percent or more of Subscriber shall entitle APIContext to terminate this Agreement for cause immediately upon written notice\. 21\. Publicity a\. APIContext may use Subscriber’s name, logo and other marks to identify Subscriber as a user of the Services on APIContext’s website, marketing materials and other publicity materials\. 22\. Limitation of Remedies and Damages a\. Subscriber’s sole remedy for a breach of this Agreement is the correction or replacement of the Service by APIContext\. The decision to repair or replace the Service shall be solely at the discretion of APIContext\. APIContext reserves the right to substitute a functionally equivalent copy of the Service as a replacement\. If APIContext is unable to provide a suitable replacement or substitute Service or corrections to the Service within thirty \(30\) days of Service’ failure to perform, Subscriber’s sole alternate remedy shall be a refund for the days or months that the Subscriber was charged fees for access to the Service while it was not functioning properly\. Any claim of Subscriber under this section must be made within thirty \(30\) days after the event giving rise to the claim\. 23\. Governing Law, Jurisdiction, and Dispute Resolution a\. This Agreement is governed by the laws of the State of Delaware, without regard to Delaware’s conflict or choice of law provisions\. Disputes shall be resolved by binding arbitration as provided in Section 23\(b\)\. b\. In the event that at any time during the term of this Agreement a disagreement, dispute, controversy or claim should arise out of, or relating to, the interpretation, performance, breach, or invalidity of this Agreement, the Parties will attempt in good faith to resolve their differences\. Any dispute which is not resolvable by the Parties shall be referred to binding arbitration in accordance with the then\-applicable rules of the American Arbitration Association and judgment on the award may be entered in any court having jurisdiction\. 24\. General a\. No text or information set forth on any other purchase order, preprinted form, or document \(other than an Invoice issued by APIContext\) shall add to or vary the terms and conditions of this Agreement\. If any provision of this Agreement is held by a court of competent jurisdiction to be invalid or unenforceable, then such provision\(s\) shall be construed, as nearly as possible, to reflect the intentions of the invalid or unenforceable provision\(s\), with all other provisions remaining in full force and effect\. No joint venture, partnership, employment, or agency relationship exists between Subscriber and APIContext as a result of this Agreement or use of the Service\. The failure of APIContext to enforce any right or provision in this Agreement shall not constitute a waiver of such right or provision unless acknowledged and agreed to by APIContext in writing\. This Agreement, together with any applicable Invoices, comprises the entire agreement between Subscriber and APIContext and supersedes all prior or contemporaneous negotiations, discussions or agreements, whether written or oral, between the Parties regarding the subject matter contained herein\. APIContext is not liable for its failure to perform due to forces beyond its control\. Sections 1, 3, 4, 6, 7, 9 and 12 to 23 of this Agreement will survive termination, as well as any other provisions that by their nature are reasonably intended to survive\. To the extent there is an express conflict between the Privacy Policy at https://apicontext\.com/privacy , the Website Terms of Service at https://apicontext\.com/tos , and this Agreement, this Agreement will have highest precedence, followed by the Website Terms of Service, then the Privacy Policy\. Last updated: October 19, 2026 ## Key facts - This agreement governs your subscription to APIContext API monitoring services\. ## Primary entities - APIContext - Subscription Agreement for Akamai Subscribers ## Audience - customers - legal teams - procurement teams ## Primary links - [Contact APIContext](/contact) --- # API Conformance \(root\) Canonical URL: https://apicontext.com/api-conformance Source: static Description: Compare production and pre\-production APIs against your own schemas, OpenAPI specifications, and open standards so compliance can be proven internally and externally\. ## Summary Demonstrate API compliance continuously\. Compare production and pre\-production APIs against your own schemas, OpenAPI specifications, and open standards so compliance can be proven internally and externally\. ## Stats - OpenAPI schema conformance checks - FAPI open\-standard gap analysis - 24/7 continuous drift monitoring - 100% call\-level audit history ## Page sections ### Real API calls\. Real workflows\. Real results\. Category: Compliance from real traffic shape APIContext builds sequenced workflows that replicate user scenarios, then shows how dependencies, security requirements, reliability, and response details affect compliance\. ### Compare live APIs against the contract they promised\. Category: Verify API compliance Run conformance checks against OpenAPI specifications in production or pre\-production\. Ongoing analysis alerts teams as soon as a deviation against spec is published\. - Compare requests and responses to OpenAPI specs - Validate production and pre\-production environments - Alert immediately when an endpoint drifts from contract ### Show compliance across schema, security, and reliability\. Category: Security and performance posture Schemas capture important requirements, but regulators and internal teams also care about uptime, availability, response time, auth posture, and reliability reporting\. - Consolidated security and performance reporting - Track uptime, availability, and response\-time mandates - Demonstrate posture in one auditable tool ### Compliance at launch is not enough\. Category: Guard against API drift Engineers keep iterating, and small changes accumulate\. Continuous conformance checks catch drift, preserve audit trails, and route remediation tasks to the teams that can fix them\. - Continuous drift detection across releases - Flag and mark individual compliance issues - Send remediation tasks into existing workflows ### Everything you need in production\. Category: Key Features - OpenAPI conformance: Measure whether live APIs match their published schemas and expected behavior\. - Security by design: Track auth, schema, and policy requirements as part of the same conformance posture\. - Performance evidence: Report reliability metrics such as uptime, availability, latency, and response time alongside compliance\. - Workflow validation: Sequence calls to reproduce real user scenarios and dependency chains\. - Audit trails: Review the details of every API call and preserve evidence for internal or external stakeholders\. - Remediation handoff: Send issues and tasks to existing systems and teams for resolution\. ### Conformance evidence flows into security, compliance, DevOps, and reporting workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - OpenAPI checks - API posture - Drift detection - Audit trails - Remediation workflows - OpenAPI schema conformance checks - FAPI open\-standard gap analysis - 24/7 continuous drift monitoring - 100% call\-level audit history - OpenAPI conformance: Measure whether live APIs match their published schemas and expected behavior\. - Security by design: Track auth, schema, and policy requirements as part of the same conformance posture\. - Performance evidence: Report reliability metrics such as uptime, availability, latency, and response time alongside compliance\. - Workflow validation: Sequence calls to reproduce real user scenarios and dependency chains\. - Audit trails: Review the details of every API call and preserve evidence for internal or external stakeholders\. - Remediation handoff: Send issues and tasks to existing systems and teams for resolution\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - OpenAPI checks - API posture - Drift detection - Audit trails - Remediation workflows ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start proving API conformance continuously\.](/contact) ## FAQs ### What is API conformance testing? API conformance testing verifies that a live API's behavior — response schemas, status codes, headers, and error formats — matches its declared specification, such as an OpenAPI document\. It is a complement to API contract testing, but more expansive: it tests not only the technical contract but also the business rules that need to be enforced by the API in context\. An API can be available and returning 200 status while still failing conformance — returning incorrect field types, omitting required headers, or violating documented business logic\. ### How does APIContext detect conformance failures? APIContext compares live API responses against an OpenAPI specification or custom schema on every synthetic check\. When a response deviates — a field type changes, a required property is missing, or a security header is dropped — the platform flags the drift with a diff view showing exactly what changed\. Checks also validate against regulatory security profiles including FAPI 2\.0 for financial APIs\. ### What standards does APIContext support for conformance? APIContext supports OpenAPI 3\.x, custom JSON schemas, and financial\-grade security standards including FAPI 1\.0 Baseline, FAPI 1\.0 Advanced, FAPI 2\.0, and many more\. This covers security and payload requirements applicable to open banking APIs under UK, EU, Australian, and US regulatory frameworks\. ### Can conformance testing run against pre\-production environments? Yes\. APIContext runs conformance checks against production and staging endpoints simultaneously, making it possible to catch regressions before they are promoted to production\. Teams can enforce a never\-ship\-a\-breaking\-change policy by gating deployments on conformance pass rates\. --- # API Directory Canonical URL: https://apicontext.com/api-directory Source: static Updated: 2026-10-19T15:15:15.051Z Description: Independent weekly benchmark intelligence for machine\-facing services, including latency, reliability, infrastructure, geography, and operational signal layers\. ## Summary APIContext Benchmark Intelligence turns weekly synthetic monitoring into citable infrastructure intelligence for machine\-facing services, with human pages and machine\-readable JSON for latency, reliability, geography, and provider delivery paths\. ## Stats - 124 benchmark subjects - 21 benchmark categories - 78 validated domain files - W2026\-10\-12 latest snapshot ## Page sections ### What the API directory provides Category: Overview The API directory is a machine\-readable benchmark intelligence hub for APIs and machine\-facing services\. It combines verified synthetic measurements with catalog metadata so people and agents can compare reliability, latency, infrastructure, and operational signals\. - Weekly verified benchmark snapshots - Normalized provider, category, and subject records - Latency, pass\-rate, CASC, and infrastructure signals - Human pages plus JSON data surfaces for agents ### Top performing providers Category: Rankings The landing page ranks providers by CASC score across monitored endpoints and regions so teams can quickly identify strong operational signals and compare API quality across peers\. - [Anthropic — 9\.77 CASC, 167 ms median](/api-directory/artificialintelligence/anthropic) - [RBS Sandbox — 9\.67 CASC, 167 ms median](/api-directory/openbankinguk/rbs-sandbox) - [Zempler Bank V4 — 9\.64 CASC, 178 ms median](/api-directory/openbankingv4ukproduction/zempler-bank-v4) - [Danske Bank V4 — 9\.58 CASC, 263 ms median](/api-directory/openbankingv4ukproduction/danske-bank-v4) - [Natwest V4 — 9\.54 CASC, 266 ms median](/api-directory/openbankingv4ukproduction/natwest-v4) - [Santander — 9\.53 CASC, 55 ms median](/api-directory/ukbanks/santander) - [RBS V4 — 9\.50 CASC, 276 ms median](/api-directory/openbankingv4ukproduction/rbs-v4) - [Coinbase — 9\.49 CASC, 133 ms median](/api-directory/exchanges/coinbase) - [Zempler Bank — 9\.47 CASC, 170 ms median](/api-directory/openbankingukproduction/zempler-bank) - [Ulster Bank V4 — 9\.46 CASC, 285 ms median](/api-directory/openbankingv4ukproduction/ulster-bank-v4) ### Primary benchmark data files Category: Data Use these canonical JSON files when an agent needs structured benchmark data rather than prose\. - [Latest benchmark catalog](/api-directory/data/latest/catalog.json) - [Snapshot metadata](/api-directory/data/latest/metadata.json) - [All subjects JSON](/api-directory/data/latest/subjects.json) - [All categories JSON](/api-directory/data/latest/categories.json) - [Benchmark comparison view](/api-directory/compare) ### Benchmark categories Category: Browse Start with a category to inspect the APIs and services measured in the latest snapshot\. - [Artificial Intelligence — 3 providers, avg CASC 9\.08, median 434\.67 ms](/api-directory/artificialintelligence) - [Cloud Infrastructure — 1 providers, avg CASC 9\.40, median 487 ms](/api-directory/cloud) - [CMA9 Open Banking — 5 providers, avg CASC 8\.82, median 330\.8 ms](/api-directory/cma9) - [Corporate Infrastructure — 15 providers, avg CASC 8\.90, median 383\.53 ms](/api-directory/corpinfra) - [Corporate Messaging — 3 providers, avg CASC 8\.41, median 439 ms](/api-directory/corporatemessaging) - [UK Digital Government — 3 providers, avg CASC 8\.67, median 107\.33 ms](/api-directory/digitalgovernmentukgov) - [Enterprise Messaging — 3 providers, avg CASC 8\.20, median 425 ms](/api-directory/enterprisemessaging) - [Cryptocurrency Exchanges — 11 providers, avg CASC 8\.89, median 327 ms](/api-directory/exchanges) - [Fintech — 12 providers, avg CASC 8\.96, median 479\.33 ms](/api-directory/fintech) - [IP Geolocation — 3 providers, avg CASC 9\.14, median 107 ms](/api-directory/ipgeolocators) - [Open Banking UK — 7 providers, avg CASC 8\.21, median 789\.71 ms](/api-directory/openbankinguk) - [Open Banking UK Production — 19 providers, avg CASC 8\.95, median 304\.79 ms](/api-directory/openbankingukproduction) - [openbankingv4ukproduction — 14 providers, avg CASC 9\.14, median 265\.36 ms](/api-directory/openbankingv4ukproduction) - [PSD2 Institutions — 2 providers, avg CASC 8\.60, median 820 ms](/api-directory/psd2institutions) - [Search Platforms — 2 providers, avg CASC 8\.85, median 264 ms](/api-directory/search) - [Social Platforms — 5 providers, avg CASC 9\.17, median 272\.2 ms](/api-directory/social) - [UK Banks — 9 providers, avg CASC 8\.78, median 341\.67 ms](/api-directory/ukbanks) - [Weather Services — 2 providers, avg CASC 8\.71, median 231\.5 ms](/api-directory/weather) ### What the landing page highlights Category: Signals The human page surfaces top performers, featured benchmark categories, CASC score interpretation, and methodology\. The Markdown view mirrors those decision points so agents can cite the same operational context without scraping UI components\. - Fastest median latency signal: Contentful at 37 ms\. - Strongest CASC signal: Anthropic at 9\.77 CASC\. - Lowest outlier signal: DEFRA at 0\.2% outliers\. - CASC score blends consistency, pass rate, errors, and outlier behavior into a comparable quality signal\. ### How to interpret the directory Category: Methodology APIContext benchmark pages are generated from verified synthetic monitoring snapshots\. They are not live status pages; they are citable weekly intelligence for comparing machine\-facing services\. - Use category pages to compare peer providers within a market or service type\. - Use subject pages for domain, CASC, pass rate, p95 latency, regional, and infrastructure detail\. - Use the comparison view to preserve selected subjects in a shareable URL\. - Use JSON endpoints when building agents, reports, or external analyses\. ## Key facts - 124 benchmark subjects are normalized in the latest snapshot\. - 21 benchmark categories are available\. - 78 valid domain files were parsed for enrichment fields and infrastructure metadata\. - Latest snapshot: W2026\-10\-12\. - Public data surfaces include raw mirrors, normalized catalogs, latest datasets, JSON\-LD Dataset markup, and llms references\. - Fastest median latency signal: Contentful at 37 ms\. - Strongest CASC signal: Anthropic at 9\.77 CASC\. ## Primary entities - APIContext - Benchmark Intelligence - Machine Service Benchmarks - Infrastructure Intelligence - Operational Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems - technology leaders ## Primary links - [Explore benchmarks](/api-directory#browse-categories) - [Latest benchmark catalog](/api-directory/data/latest/catalog.json) - [Snapshot metadata](/api-directory/data/latest/metadata.json) - [Benchmark comparison](/api-directory/compare) --- # APIContext Quality of Service Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/apimetricsqos Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 2 benchmark subjects in APIContext Quality of Service, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 2 benchmark subjects in APIContext Quality of Service, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 2 benchmark subjects - 8\.36 average CASC - 541\.5 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### APIContext Quality of Service benchmark slice Category: Category Latest verified snapshot covers 2 benchmark subjects in APIContext Quality of Service, with median latency signals and reliability measurements normalized for comparison\. - 2 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.97%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [\! Prod APImetrics v2 APIs — 8\.70 CASC, 99\.94% pass, 1,722 ms p95](/api-directory/apimetricsqos/prod-apimetrics-v2-apis) - [\! Prod APImetrics v3 APIs — 8\.01 CASC, 100\.00% pass, 2,068 ms p95](/api-directory/apimetricsqos/prod-apimetrics-v3-apis) ## Key facts - 2 benchmark subjects are included in APIContext Quality of Service\. - Average CASC score: 835\.5\. - Average median latency: 541\.5 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - APIContext Quality of Service - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/apimetricsqos.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # \! Prod APImetrics v2 APIs Operational Intelligence Canonical URL: https://apicontext.com/api-directory/apimetricsqos/prod-apimetrics-v2-apis Source: static Updated: 2026-10-19T15:15:15.051Z Description: \! Prod APImetrics v2 APIs benchmark detail for client\.apimetrics\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary \! Prod APImetrics v2 APIs is a api\-provider benchmark subject in APIContext Quality of Service\. Latest snapshot metrics include 8\.70 CASC score, 99\.94% pass rate, 316 ms median latency, and 1,722 ms p95 latency\. ## Stats - 8\.70 CASC score - 99\.94% pass rate - 316 ms median latency - 1,722 ms p95 latency - stable operational state ## Page sections ### \! Prod APImetrics v2 APIs benchmark detail Category: Subject \! Prod APImetrics v2 APIs is measured as part of APIContext Quality of Service\. This page summarizes operational signals for client\.apimetrics\.io, including quality, reliability, latency, and infrastructure context\. - Domain: client\.apimetrics\.io\. - Category: APIContext Quality of Service\. - Benchmark subject type: api\-provider\. - Monitored count: 30\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6\.77 ms\. - TCP connection: 5 ms\. - TLS handshake: 9\.23 ms\. - Processing: 266\.45 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Cloudflare, Inc\.\. - Server: Google Frontend\. - [Subject JSON](/api-directory/data/latest/subjects/apimetricsqos/prod-apimetrics-v2-apis.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - \! Prod APImetrics v2 APIs recorded 99\.94% pass rate in the latest verified snapshot\. - The p95 latency signal is 1722 ms, with median latency at 316 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - \! Prod APImetrics v2 APIs domain: client\.apimetrics\.io\. - Operational state: stable\. - CASC score: 8\.70\. - Pass rate: 99\.94%\. - p95 latency: 1,722 ms\. ## Primary entities - APIContext - \! Prod APImetrics v2 APIs - client\.apimetrics\.io - APIContext Quality of Service - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/apimetricsqos/prod-apimetrics-v2-apis.json) --- # \! Prod APImetrics v3 APIs Operational Intelligence Canonical URL: https://apicontext.com/api-directory/apimetricsqos/prod-apimetrics-v3-apis Source: static Updated: 2026-10-19T15:15:15.051Z Description: \! Prod APImetrics v3 APIs benchmark detail for client\.apimetrics\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary \! Prod APImetrics v3 APIs is a api\-provider benchmark subject in APIContext Quality of Service\. Latest snapshot metrics include 8\.01 CASC score, 100\.00% pass rate, 767 ms median latency, and 2,068 ms p95 latency\. ## Stats - 8\.01 CASC score - 100\.00% pass rate - 767 ms median latency - 2,068 ms p95 latency - stable operational state ## Page sections ### \! Prod APImetrics v3 APIs benchmark detail Category: Subject \! Prod APImetrics v3 APIs is measured as part of APIContext Quality of Service\. This page summarizes operational signals for client\.apimetrics\.io, including quality, reliability, latency, and infrastructure context\. - Domain: client\.apimetrics\.io\. - Category: APIContext Quality of Service\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 8\.73 ms\. - TCP connection: 5\.64 ms\. - TLS handshake: 9\.55 ms\. - Processing: 692\.23 ms\. - Download: 1\.64 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/apimetricsqos/prod-apimetrics-v3-apis.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - \! Prod APImetrics v3 APIs recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 2068 ms, with median latency at 767 ms\. ## Key facts - \! Prod APImetrics v3 APIs domain: client\.apimetrics\.io\. - Operational state: stable\. - CASC score: 8\.01\. - Pass rate: 100\.00%\. - p95 latency: 2,068 ms\. ## Primary entities - APIContext - \! Prod APImetrics v3 APIs - client\.apimetrics\.io - APIContext Quality of Service - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/apimetricsqos/prod-apimetrics-v3-apis.json) --- # Artificial Intelligence Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/artificialintelligence Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 3 benchmark subjects in Artificial Intelligence, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 3 benchmark subjects in Artificial Intelligence, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 3 benchmark subjects - 9\.08 average CASC - 434\.67 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Artificial Intelligence benchmark slice Category: Category Latest verified snapshot covers 3 benchmark subjects in Artificial Intelligence, with median latency signals and reliability measurements normalized for comparison\. - 3 subjects are normalized in this category\. - Benchmark subject type: ai\-provider\. - Average pass rate: 100\.00%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [OpenAI — 8\.12 CASC, 100\.00% pass, 1,707 ms p95](/api-directory/artificialintelligence/openai) - [Anthropic — 9\.77 CASC, 100\.00% pass, 320 ms p95](/api-directory/artificialintelligence/anthropic) - [Google PaLM — 9\.34 CASC, 100\.00% pass, 549 ms p95](/api-directory/artificialintelligence/google-palm) ## Key facts - 3 benchmark subjects are included in Artificial Intelligence\. - Average CASC score: 907\.67\. - Average median latency: 434\.67 ms\. - Benchmark subject type: ai\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Artificial Intelligence - Benchmark Intelligence - Operational Intelligence - ai\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/artificialintelligence.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Anthropic Operational Intelligence Canonical URL: https://apicontext.com/api-directory/artificialintelligence/anthropic Source: static Updated: 2026-10-19T15:15:15.051Z Description: Anthropic benchmark detail for api\.anthropic\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Anthropic is a ai\-provider benchmark subject in Artificial Intelligence\. Latest snapshot metrics include 9\.77 CASC score, 100\.00% pass rate, 167 ms median latency, and 320 ms p95 latency\. ## Stats - 9\.77 CASC score - 100\.00% pass rate - 167 ms median latency - 320 ms p95 latency - healthy operational state ## Page sections ### Anthropic benchmark detail Category: Subject Anthropic is measured as part of Artificial Intelligence\. This page summarizes operational signals for api\.anthropic\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.anthropic\.com\. - Category: Artificial Intelligence\. - Benchmark subject type: ai\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 2\.86 ms\. - TCP connection: 3\.27 ms\. - TLS handshake: 6\.05 ms\. - Processing: 186 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/artificialintelligence/anthropic.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Anthropic recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 320 ms, with median latency at 167 ms\. ## Key facts - Anthropic domain: api\.anthropic\.com\. - Operational state: healthy\. - CASC score: 9\.77\. - Pass rate: 100\.00%\. - p95 latency: 320 ms\. ## Primary entities - APIContext - Anthropic - api\.anthropic\.com - Artificial Intelligence - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/artificialintelligence/anthropic.json) --- # Google PaLM Operational Intelligence Canonical URL: https://apicontext.com/api-directory/artificialintelligence/google-palm Source: static Updated: 2026-10-19T15:15:15.051Z Description: Google PaLM benchmark detail for generativelanguage\.googleapis\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Google PaLM is a ai\-provider benchmark subject in Artificial Intelligence\. Latest snapshot metrics include 9\.34 CASC score, 100\.00% pass rate, 128 ms median latency, and 549 ms p95 latency\. ## Stats - 9\.34 CASC score - 100\.00% pass rate - 128 ms median latency - 549 ms p95 latency - healthy operational state ## Page sections ### Google PaLM benchmark detail Category: Subject Google PaLM is measured as part of Artificial Intelligence\. This page summarizes operational signals for generativelanguage\.googleapis\.com, including quality, reliability, latency, and infrastructure context\. - Domain: generativelanguage\.googleapis\.com\. - Category: Artificial Intelligence\. - Benchmark subject type: ai\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 20\.41 ms\. - TCP connection: 4 ms\. - TLS handshake: 53\.27 ms\. - Processing: 203\.86 ms\. - Download: 0\.05 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: scaffolding on HTTPServer2\. - [Subject JSON](/api-directory/data/latest/subjects/artificialintelligence/google-palm.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Google PaLM recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 549 ms, with median latency at 128 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Google PaLM domain: generativelanguage\.googleapis\.com\. - Operational state: healthy\. - CASC score: 9\.34\. - Pass rate: 100\.00%\. - p95 latency: 549 ms\. ## Primary entities - APIContext - Google PaLM - generativelanguage\.googleapis\.com - Artificial Intelligence - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/artificialintelligence/google-palm.json) --- # OpenAI Operational Intelligence Canonical URL: https://apicontext.com/api-directory/artificialintelligence/openai Source: static Updated: 2026-10-19T15:15:15.051Z Description: OpenAI benchmark detail for api\.openai\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary OpenAI is a ai\-provider benchmark subject in Artificial Intelligence\. Latest snapshot metrics include 8\.12 CASC score, 100\.00% pass rate, 1,009 ms median latency, and 1,707 ms p95 latency\. ## Stats - 8\.12 CASC score - 100\.00% pass rate - 1,009 ms median latency - 1,707 ms p95 latency - stable operational state ## Page sections ### OpenAI benchmark detail Category: Subject OpenAI is measured as part of Artificial Intelligence\. This page summarizes operational signals for api\.openai\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.openai\.com\. - Category: Artificial Intelligence\. - Benchmark subject type: ai\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 3\.27 ms\. - TCP connection: 5\.86 ms\. - TLS handshake: 8\.73 ms\. - Processing: 1,010\.64 ms\. - Download: 0\.36 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Microsoft Corporation\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/artificialintelligence/openai.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - OpenAI recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1707 ms, with median latency at 1009 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - OpenAI domain: api\.openai\.com\. - Operational state: stable\. - CASC score: 8\.12\. - Pass rate: 100\.00%\. - p95 latency: 1,707 ms\. ## Primary entities - APIContext - OpenAI - api\.openai\.com - Artificial Intelligence - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/artificialintelligence/openai.json) --- # Cloud Infrastructure Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/cloud Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 1 benchmark subjects in Cloud Infrastructure, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 1 benchmark subjects in Cloud Infrastructure, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 1 benchmark subjects - 9\.40 average CASC - 487 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Cloud Infrastructure benchmark slice Category: Category Latest verified snapshot covers 1 benchmark subjects in Cloud Infrastructure, with median latency signals and reliability measurements normalized for comparison\. - 1 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 100\.00%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Amazon — 9\.40 CASC, 100\.00% pass, 922 ms p95](/api-directory/cloud/amazon) ## Key facts - 1 benchmark subjects are included in Cloud Infrastructure\. - Average CASC score: 940\. - Average median latency: 487 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Cloud Infrastructure - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/cloud.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Amazon Operational Intelligence Canonical URL: https://apicontext.com/api-directory/cloud/amazon Source: static Updated: 2026-10-19T15:15:15.051Z Description: Amazon benchmark detail for api\.amazon\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Amazon is a api\-provider benchmark subject in Cloud Infrastructure\. Latest snapshot metrics include 9\.40 CASC score, 100\.00% pass rate, 487 ms median latency, and 922 ms p95 latency\. ## Stats - 9\.40 CASC score - 100\.00% pass rate - 487 ms median latency - 922 ms p95 latency - healthy operational state ## Page sections ### Amazon benchmark detail Category: Subject Amazon is measured as part of Cloud Infrastructure\. This page summarizes operational signals for api\.amazon\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.amazon\.com\. - Category: Cloud Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 21\.45 ms\. - TCP connection: 136\.41 ms\. - TLS handshake: 139\.45 ms\. - Processing: 275\.86 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: Server\. - [Subject JSON](/api-directory/data/latest/subjects/cloud/amazon.json) - [Developer documentation](https://developer.amazonservices.com/) - [Postman collection](https://www.postman.com/api-evangelist/workspace/amazon-web-services-aws/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Amazon recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 922 ms, with median latency at 487 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. ## Key facts - Amazon domain: api\.amazon\.com\. - Operational state: healthy\. - CASC score: 9\.40\. - Pass rate: 100\.00%\. - p95 latency: 922 ms\. - Developer documentation: https://developer\.amazonservices\.com/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/amazon\-web\-services\-aws/overview\. ## Primary entities - APIContext - Amazon - api\.amazon\.com - Cloud Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/cloud/amazon.json) - [Developer documentation](https://developer.amazonservices.com/) --- # CMA9 Open Banking Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/cma9 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 5 benchmark subjects in CMA9 Open Banking, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 5 benchmark subjects in CMA9 Open Banking, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 5 benchmark subjects - 8\.82 average CASC - 330\.8 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### CMA9 Open Banking benchmark slice Category: Category Latest verified snapshot covers 5 benchmark subjects in CMA9 Open Banking, with median latency signals and reliability measurements normalized for comparison\. - 5 subjects are normalized in this category\. - Benchmark subject type: banking\-api\. - Average pass rate: 99\.77%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Bank of Ireland \(UK\) Plc — 8\.62 CASC, 99\.22% pass, 428 ms p95](/api-directory/cma9/bank-of-ireland-uk-plc) - [Barclays Personal — 8\.80 CASC, 99\.89% pass, 664 ms p95](/api-directory/cma9/barclays-personal) - [HSBC Bank \(Personal\) — 8\.88 CASC, 99\.95% pass, 778 ms p95](/api-directory/cma9/hsbc-bank-personal) - [HSBC Bank \(Business\) — 8\.90 CASC, 99\.98% pass, 784 ms p95](/api-directory/cma9/hsbc-bank-business) - [Barclays Business — 8\.90 CASC, 99\.81% pass, 630 ms p95](/api-directory/cma9/barclays-business) ## Key facts - 5 benchmark subjects are included in CMA9 Open Banking\. - Average CASC score: 882\. - Average median latency: 330\.8 ms\. - Benchmark subject type: banking\-api\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - CMA9 Open Banking - Benchmark Intelligence - Operational Intelligence - banking\-api ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/cma9.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Bank of Ireland \(UK\) Plc Operational Intelligence Canonical URL: https://apicontext.com/api-directory/cma9/bank-of-ireland-uk-plc Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bank of Ireland \(UK\) Plc benchmark detail for api\.obapi\.bankofireland\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bank of Ireland \(UK\) Plc is a banking\-api benchmark subject in CMA9 Open Banking\. Latest snapshot metrics include 8\.62 CASC score, 99\.22% pass rate, 294 ms median latency, and 428 ms p95 latency\. ## Stats - 8\.62 CASC score - 99\.22% pass rate - 294 ms median latency - 428 ms p95 latency - degraded operational state ## Page sections ### Bank of Ireland \(UK\) Plc benchmark detail Category: Subject Bank of Ireland \(UK\) Plc is measured as part of CMA9 Open Banking\. This page summarizes operational signals for api\.obapi\.bankofireland\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.obapi\.bankofireland\.com\. - Category: CMA9 Open Banking\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 12\.5 ms\. - TCP connection: 21\.75 ms\. - TLS handshake: 57 ms\. - Processing: 200\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/cma9/bank-of-ireland-uk-plc.json) - [Developer documentation](https://developer.bankofireland.com) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bank of Ireland \(UK\) Plc recorded 99\.22% pass rate in the latest verified snapshot\. - The p95 latency signal is 428 ms, with median latency at 294 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Bank of Ireland \(UK\) Plc domain: api\.obapi\.bankofireland\.com\. - Operational state: degraded\. - CASC score: 8\.62\. - Pass rate: 99\.22%\. - p95 latency: 428 ms\. - Developer documentation: https://developer\.bankofireland\.com\. ## Primary entities - APIContext - Bank of Ireland \(UK\) Plc - api\.obapi\.bankofireland\.com - CMA9 Open Banking - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/cma9/bank-of-ireland-uk-plc.json) - [Developer documentation](https://developer.bankofireland.com) --- # Barclays Business Operational Intelligence Canonical URL: https://apicontext.com/api-directory/cma9/barclays-business Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays Business benchmark detail for telesto\.api\.barclays, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays Business is a banking\-api benchmark subject in CMA9 Open Banking\. Latest snapshot metrics include 8\.90 CASC score, 99\.81% pass rate, 264 ms median latency, and 630 ms p95 latency\. ## Stats - 8\.90 CASC score - 99\.81% pass rate - 264 ms median latency - 630 ms p95 latency - stable operational state ## Page sections ### Barclays Business benchmark detail Category: Subject Barclays Business is measured as part of CMA9 Open Banking\. This page summarizes operational signals for telesto\.api\.barclays, including quality, reliability, latency, and infrastructure context\. - Domain: telesto\.api\.barclays\. - Category: CMA9 Open Banking\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 39\.5 ms\. - TCP connection: 19\.5 ms\. - TLS handshake: 63\.25 ms\. - Processing: 124\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Barclays Bank Plc\.\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/cma9/barclays-business.json) - [Developer documentation](https://developer.barclays.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays Business recorded 99\.81% pass rate in the latest verified snapshot\. - The p95 latency signal is 630 ms, with median latency at 264 ms\. - Infrastructure fingerprinting identifies Barclays Bank Plc\. in the observed delivery path\. ## Key facts - Barclays Business domain: telesto\.api\.barclays\. - Operational state: stable\. - CASC score: 8\.90\. - Pass rate: 99\.81%\. - p95 latency: 630 ms\. - Developer documentation: https://developer\.barclays\.com/\. ## Primary entities - APIContext - Barclays Business - telesto\.api\.barclays - CMA9 Open Banking - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/cma9/barclays-business.json) - [Developer documentation](https://developer.barclays.com/) --- # Barclays Personal Operational Intelligence Canonical URL: https://apicontext.com/api-directory/cma9/barclays-personal Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays Personal benchmark detail for telesto\.api\.barclays, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays Personal is a banking\-api benchmark subject in CMA9 Open Banking\. Latest snapshot metrics include 8\.80 CASC score, 99\.89% pass rate, 263 ms median latency, and 664 ms p95 latency\. ## Stats - 8\.80 CASC score - 99\.89% pass rate - 263 ms median latency - 664 ms p95 latency - stable operational state ## Page sections ### Barclays Personal benchmark detail Category: Subject Barclays Personal is measured as part of CMA9 Open Banking\. This page summarizes operational signals for telesto\.api\.barclays, including quality, reliability, latency, and infrastructure context\. - Domain: telesto\.api\.barclays\. - Category: CMA9 Open Banking\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 41\.25 ms\. - TCP connection: 21\.5 ms\. - TLS handshake: 65\.25 ms\. - Processing: 124\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: Google Frontend\. - [Subject JSON](/api-directory/data/latest/subjects/cma9/barclays-personal.json) - [Developer documentation](https://developer.barclays.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays Personal recorded 99\.89% pass rate in the latest verified snapshot\. - The p95 latency signal is 664 ms, with median latency at 263 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Barclays Personal domain: telesto\.api\.barclays\. - Operational state: stable\. - CASC score: 8\.80\. - Pass rate: 99\.89%\. - p95 latency: 664 ms\. - Developer documentation: https://developer\.barclays\.com/\. ## Primary entities - APIContext - Barclays Personal - telesto\.api\.barclays - CMA9 Open Banking - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/cma9/barclays-personal.json) - [Developer documentation](https://developer.barclays.com/) --- # HSBC Bank \(Business\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/cma9/hsbc-bank-business Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC Bank \(Business\) benchmark detail for api\.ob\.business\.hsbc\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC Bank \(Business\) is a banking\-api benchmark subject in CMA9 Open Banking\. Latest snapshot metrics include 8\.90 CASC score, 99\.98% pass rate, 435 ms median latency, and 784 ms p95 latency\. ## Stats - 8\.90 CASC score - 99\.98% pass rate - 435 ms median latency - 784 ms p95 latency - healthy operational state ## Page sections ### HSBC Bank \(Business\) benchmark detail Category: Subject HSBC Bank \(Business\) is measured as part of CMA9 Open Banking\. This page summarizes operational signals for api\.ob\.business\.hsbc\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ob\.business\.hsbc\.co\.uk\. - Category: CMA9 Open Banking\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 32\.75 ms\. - TCP connection: 3\.25 ms\. - TLS handshake: 15\.25 ms\. - Processing: 366\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/cma9/hsbc-bank-business.json) - [Developer documentation](https://develop.hsbc.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC Bank \(Business\) recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 784 ms, with median latency at 435 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - HSBC Bank \(Business\) domain: api\.ob\.business\.hsbc\.co\.uk\. - Operational state: healthy\. - CASC score: 8\.90\. - Pass rate: 99\.98%\. - p95 latency: 784 ms\. - Developer documentation: https://develop\.hsbc\.com/\. ## Primary entities - APIContext - HSBC Bank \(Business\) - api\.ob\.business\.hsbc\.co\.uk - CMA9 Open Banking - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/cma9/hsbc-bank-business.json) - [Developer documentation](https://develop.hsbc.com/) --- # HSBC Bank \(Personal\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/cma9/hsbc-bank-personal Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC Bank \(Personal\) benchmark detail for api\.ob\.hsbc\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC Bank \(Personal\) is a banking\-api benchmark subject in CMA9 Open Banking\. Latest snapshot metrics include 8\.88 CASC score, 99\.95% pass rate, 398 ms median latency, and 778 ms p95 latency\. ## Stats - 8\.88 CASC score - 99\.95% pass rate - 398 ms median latency - 778 ms p95 latency - healthy operational state ## Page sections ### HSBC Bank \(Personal\) benchmark detail Category: Subject HSBC Bank \(Personal\) is measured as part of CMA9 Open Banking\. This page summarizes operational signals for api\.ob\.hsbc\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ob\.hsbc\.co\.uk\. - Category: CMA9 Open Banking\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 31 ms\. - TCP connection: 4 ms\. - TLS handshake: 14\.25 ms\. - Processing: 327\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/cma9/hsbc-bank-personal.json) - [Developer documentation](https://develop.hsbc.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC Bank \(Personal\) recorded 99\.95% pass rate in the latest verified snapshot\. - The p95 latency signal is 778 ms, with median latency at 398 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - HSBC Bank \(Personal\) domain: api\.ob\.hsbc\.co\.uk\. - Operational state: healthy\. - CASC score: 8\.88\. - Pass rate: 99\.95%\. - p95 latency: 778 ms\. - Developer documentation: https://develop\.hsbc\.com/\. ## Primary entities - APIContext - HSBC Bank \(Personal\) - api\.ob\.hsbc\.co\.uk - CMA9 Open Banking - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/cma9/hsbc-bank-personal.json) - [Developer documentation](https://develop.hsbc.com/) --- # APIContext Benchmark Comparison Canonical URL: https://apicontext.com/api-directory/compare Source: static Updated: 2026-10-19T15:15:15.051Z Description: Side\-by\-side Benchmark Intelligence comparison for machine\-facing services using the latest verified snapshot\. ## Summary APIContext Benchmark Comparison provides shareable side\-by\-side comparisons across CASC score, pass rate, outliers, tail latency, latency anatomy, infrastructure metadata, and citation links\. ## Page sections ### Side\-by\-side operational intelligence Category: Comparison The comparison page preserves selected benchmark subjects in the URL and displays CASC score, pass rate, outliers, tail latency, latency anatomy, and infrastructure fingerprints together\. - Compare two to four benchmark subjects in one shareable view\. - Use category pages to select peers before opening a comparison\. - Cite the latest catalog or subject JSON files for evidence\. - [Browse Benchmark Intelligence](/api-directory) - [Latest benchmark catalog](/api-directory/data/latest/catalog.json) - [Snapshot metadata](/api-directory/data/latest/metadata.json) ## Key facts - Comparison pages use the same normalized BenchmarkSubject data as category and detail pages\. - Comparison URLs can preserve selected benchmark subjects through query parameters\. - Latest snapshot: W2026\-10\-12\. - Comparison measurements are generated from weekly verified snapshot intelligence, not continuous status monitoring\. ## Primary entities - APIContext - Benchmark Comparison - Benchmark Intelligence - Machine Service Benchmarks - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems - technology leaders ## Primary links - [Latest benchmark catalog](/api-directory/data/latest/catalog.json) - [Browse Benchmark Intelligence](/api-directory) --- # Corporate Infrastructure Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 15 benchmark subjects in Corporate Infrastructure, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 15 benchmark subjects in Corporate Infrastructure, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 15 benchmark subjects - 8\.90 average CASC - 383\.53 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Corporate Infrastructure benchmark slice Category: Category Latest verified snapshot covers 15 benchmark subjects in Corporate Infrastructure, with median latency signals and reliability measurements normalized for comparison\. - 15 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 100\.00%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Contentful — 8\.89 CASC, 100\.00% pass, 275 ms p95](/api-directory/corpinfra/contentful) - [Radar — 9\.17 CASC, 100\.00% pass, 832 ms p95](/api-directory/corpinfra/radar) - [PubNub — 9\.24 CASC, 100\.00% pass, 739 ms p95](/api-directory/corpinfra/pubnub) - [Docusign — 9\.20 CASC, 100\.00% pass, 1,242 ms p95](/api-directory/corpinfra/docusign) - [Microsoft Graph \(Sharepoint\) — 8\.78 CASC, 99\.98% pass, 1,257 ms p95](/api-directory/corpinfra/microsoft-graph-sharepoint) - [Github — 9\.24 CASC, 100\.00% pass, 589 ms p95](/api-directory/corpinfra/github) - [Salesforce — 9\.24 CASC, 100\.00% pass, 844 ms p95](/api-directory/corpinfra/salesforce) - [Auth0 — 8\.62 CASC, 100\.00% pass, 690 ms p95](/api-directory/corpinfra/auth0) - [Box — 8\.54 CASC, 100\.00% pass, 1,074 ms p95](/api-directory/corpinfra/box) - [Google Workspace — 8\.78 CASC, 100\.00% pass, 895 ms p95](/api-directory/corpinfra/google-workspace) - [Dropbox — 9\.06 CASC, 99\.98% pass, 935 ms p95](/api-directory/corpinfra/dropbox) - [Sendgrid — 9\.27 CASC, 100\.00% pass, 895 ms p95](/api-directory/corpinfra/sendgrid) - [Merge — 8\.16 CASC, 100\.00% pass, 2,295 ms p95](/api-directory/corpinfra/merge) - [Microsoft Graph \(Office\) — 8\.99 CASC, 99\.99% pass, 1,115 ms p95](/api-directory/corpinfra/microsoft-graph-office) - [Adobe — 8\.32 CASC, 100\.00% pass, 1,281 ms p95](/api-directory/corpinfra/adobe) ## Key facts - 15 benchmark subjects are included in Corporate Infrastructure\. - Average CASC score: 890\. - Average median latency: 383\.53 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Corporate Infrastructure - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/corpinfra.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Adobe Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/adobe Source: static Updated: 2026-10-19T15:15:15.051Z Description: Adobe benchmark detail for stock\.adobe\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Adobe is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.32 CASC score, 100\.00% pass rate, 620 ms median latency, and 1,281 ms p95 latency\. ## Stats - 8\.32 CASC score - 100\.00% pass rate - 620 ms median latency - 1,281 ms p95 latency - stable operational state ## Page sections ### Adobe benchmark detail Category: Subject Adobe is measured as part of Corporate Infrastructure\. This page summarizes operational signals for stock\.adobe\.io, including quality, reliability, latency, and infrastructure context\. - Domain: stock\.adobe\.io\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 106\.62 ms\. - TCP connection: 148\.57 ms\. - TLS handshake: 157\.62 ms\. - Processing: 299\.95 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: openresty\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/adobe.json) - [Developer documentation](https://www.bankofapis.com) - [OpenAPI specification](https://s4r5s3t9.stackpathcdn.com/AdobeDocs/analytics-2.0-apis/master/docs/swagger.json) - [Postman collection](https://www.postman.com/api-evangelist/workspace/adobe/collection/35240-99b807d0-abac-481e-a509-d69785137b6b?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Adobe recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1281 ms, with median latency at 620 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Adobe domain: stock\.adobe\.io\. - Operational state: stable\. - CASC score: 8\.32\. - Pass rate: 100\.00%\. - p95 latency: 1,281 ms\. - Developer documentation: https://www\.bankofapis\.com\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/adobe/collection/35240\-99b807d0\-abac\-481e\-a509\-d69785137b6b?ctx=documentation\. - OpenAPI specification: https://s4r5s3t9\.stackpathcdn\.com/AdobeDocs/analytics\-2\.0\-apis/master/docs/swagger\.json\. ## Primary entities - APIContext - Adobe - stock\.adobe\.io - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/adobe.json) - [Developer documentation](https://www.bankofapis.com) - [OpenAPI specification](https://s4r5s3t9.stackpathcdn.com/AdobeDocs/analytics-2.0-apis/master/docs/swagger.json) --- # Auth0 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/auth0 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Auth0 benchmark detail for apimetrics\.auth0\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Auth0 is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.62 CASC score, 100\.00% pass rate, 273 ms median latency, and 690 ms p95 latency\. ## Stats - 8\.62 CASC score - 100\.00% pass rate - 273 ms median latency - 690 ms p95 latency - healthy operational state ## Page sections ### Auth0 benchmark detail Category: Subject Auth0 is measured as part of Corporate Infrastructure\. This page summarizes operational signals for apimetrics\.auth0\.com, including quality, reliability, latency, and infrastructure context\. - Domain: apimetrics\.auth0\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 7\.41 ms\. - TCP connection: 5\.32 ms\. - TLS handshake: 11\.32 ms\. - Processing: 247\.77 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/auth0.json) - [Developer documentation](https://auth0.com/docs/api) - [Postman collection](https://www.postman.com/galactic-desert-2289/workspace/auth0-mhc-poc-s-public-workspace/collection/7808391-11ccbb48-3a79-43d3-977f-01f39c992a8c?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Auth0 recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 690 ms, with median latency at 273 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - Auth0 domain: apimetrics\.auth0\.com\. - Operational state: healthy\. - CASC score: 8\.62\. - Pass rate: 100\.00%\. - p95 latency: 690 ms\. - Developer documentation: https://auth0\.com/docs/api\. - Postman collection: https://www\.postman\.com/galactic\-desert\-2289/workspace/auth0\-mhc\-poc\-s\-public\-workspace/collection/7808391\-11ccbb48\-3a79\-43d3\-977f\-01f39c992a8c?ctx=documentation\. ## Primary entities - APIContext - Auth0 - apimetrics\.auth0\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/auth0.json) - [Developer documentation](https://auth0.com/docs/api) --- # Box Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/box Source: static Updated: 2026-10-19T15:15:15.051Z Description: Box benchmark detail for api\.box\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Box is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.54 CASC score, 100\.00% pass rate, 306 ms median latency, and 1,074 ms p95 latency\. ## Stats - 8\.54 CASC score - 100\.00% pass rate - 306 ms median latency - 1,074 ms p95 latency - healthy operational state ## Page sections ### Box benchmark detail Category: Subject Box is measured as part of Corporate Infrastructure\. This page summarizes operational signals for api\.box\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.box\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 4\.45 ms\. - TCP connection: 5\.5 ms\. - TLS handshake: 8\.86 ms\. - Processing: 408\.09 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Box\.com\. - Nameserver: NSONE Inc\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/box.json) - [Developer documentation](https://developer.box.com/) - [OpenAPI specification](https://raw.githubusercontent.com/box/box-openapi/en/openapi.json) - [Postman collection](https://www.postman.com/api-evangelist/workspace/box/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Box recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1074 ms, with median latency at 306 ms\. - Infrastructure fingerprinting identifies Box\.com in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Box domain: api\.box\.com\. - Operational state: healthy\. - CASC score: 8\.54\. - Pass rate: 100\.00%\. - p95 latency: 1,074 ms\. - Developer documentation: https://developer\.box\.com/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/box/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/box/box\-openapi/en/openapi\.json\. ## Primary entities - APIContext - Box - api\.box\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/box.json) - [Developer documentation](https://developer.box.com/) - [OpenAPI specification](https://raw.githubusercontent.com/box/box-openapi/en/openapi.json) --- # Contentful Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/contentful Source: static Updated: 2026-10-19T15:15:15.051Z Description: Contentful benchmark detail for cdn\.contentful\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Contentful is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.89 CASC score, 100\.00% pass rate, 37 ms median latency, and 275 ms p95 latency\. ## Stats - 8\.89 CASC score - 100\.00% pass rate - 37 ms median latency - 275 ms p95 latency - healthy operational state ## Page sections ### Contentful benchmark detail Category: Subject Contentful is measured as part of Corporate Infrastructure\. This page summarizes operational signals for cdn\.contentful\.com, including quality, reliability, latency, and infrastructure context\. - Domain: cdn\.contentful\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 10\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 20\.23 ms\. - TCP connection: 5 ms\. - TLS handshake: 8 ms\. - Processing: 11\.27 ms\. - Download: 0\.09 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/contentful.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Contentful recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 275 ms, with median latency at 37 ms\. ## Key facts - Contentful domain: cdn\.contentful\.com\. - Operational state: healthy\. - CASC score: 8\.89\. - Pass rate: 100\.00%\. - p95 latency: 275 ms\. ## Primary entities - APIContext - Contentful - cdn\.contentful\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/contentful.json) --- # Docusign Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/docusign Source: static Updated: 2026-10-19T15:15:15.051Z Description: Docusign benchmark detail for demo\.docusign\.net, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Docusign is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.20 CASC score, 100\.00% pass rate, 709 ms median latency, and 1,242 ms p95 latency\. ## Stats - 9\.20 CASC score - 100\.00% pass rate - 709 ms median latency - 1,242 ms p95 latency - healthy operational state ## Page sections ### Docusign benchmark detail Category: Subject Docusign is measured as part of Corporate Infrastructure\. This page summarizes operational signals for demo\.docusign\.net, including quality, reliability, latency, and infrastructure context\. - Domain: demo\.docusign\.net\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 41\.55 ms\. - TCP connection: 141\.86 ms\. - TLS handshake: 284\.18 ms\. - Processing: 267\.68 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Docusign, Inc\. - Nameserver: Docusign, Inc\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/docusign.json) - [Developer documentation](https://developers.docusign.com/) - [OpenAPI specification](https://raw.githubusercontent.com/docusign/OpenAPI-Specifications/master/esignature.rest.swagger-v2.1.json) - [Postman collection](https://www.postman.com/docusign/workspace/docusign-s-public-workspace/collection/14257714-4f84ce44-7fbe-46ea-9b0d-4c095e78cb22?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Docusign recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1242 ms, with median latency at 709 ms\. - Infrastructure fingerprinting identifies Docusign, Inc in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Docusign domain: demo\.docusign\.net\. - Operational state: healthy\. - CASC score: 9\.20\. - Pass rate: 100\.00%\. - p95 latency: 1,242 ms\. - Developer documentation: https://developers\.docusign\.com/\. - Postman collection: https://www\.postman\.com/docusign/workspace/docusign\-s\-public\-workspace/collection/14257714\-4f84ce44\-7fbe\-46ea\-9b0d\-4c095e78cb22?ctx=documentation\. - OpenAPI specification: https://raw\.githubusercontent\.com/docusign/OpenAPI\-Specifications/master/esignature\.rest\.swagger\-v2\.1\.json\. ## Primary entities - APIContext - Docusign - demo\.docusign\.net - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/docusign.json) - [Developer documentation](https://developers.docusign.com/) - [OpenAPI specification](https://raw.githubusercontent.com/docusign/OpenAPI-Specifications/master/esignature.rest.swagger-v2.1.json) --- # Dropbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/dropbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Dropbox benchmark detail for api\.dropboxapi\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Dropbox is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.06 CASC score, 99\.98% pass rate, 463 ms median latency, and 935 ms p95 latency\. ## Stats - 9\.06 CASC score - 99\.98% pass rate - 463 ms median latency - 935 ms p95 latency - healthy operational state ## Page sections ### Dropbox benchmark detail Category: Subject Dropbox is measured as part of Corporate Infrastructure\. This page summarizes operational signals for api\.dropboxapi\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.dropboxapi\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6\.27 ms\. - TCP connection: 46\.18 ms\. - TLS handshake: 48\.32 ms\. - Processing: 378\.18 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Dropbox, Inc\.\. - Nameserver: Dropbox, Inc\.\. - Server: envoy\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/dropbox.json) - [Developer documentation](https://dropbox.tech/developers) - [OpenAPI specification](https://raw.githubusercontent.com/stomakun/DropboxSwagger/master/swaggers/team_v2.json) - [Postman collection](https://www.postman.com/dropbox-api/workspace/dropbox-s-public-workspace/collection/576034-3957ea99-234e-43e6-959d-adc7312b7a80?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Dropbox recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 935 ms, with median latency at 463 ms\. - Infrastructure fingerprinting identifies Dropbox, Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Dropbox domain: api\.dropboxapi\.com\. - Operational state: healthy\. - CASC score: 9\.06\. - Pass rate: 99\.98%\. - p95 latency: 935 ms\. - Developer documentation: https://dropbox\.tech/developers\. - Postman collection: https://www\.postman\.com/dropbox\-api/workspace/dropbox\-s\-public\-workspace/collection/576034\-3957ea99\-234e\-43e6\-959d\-adc7312b7a80?ctx=documentation\. - OpenAPI specification: https://raw\.githubusercontent\.com/stomakun/DropboxSwagger/master/swaggers/team\_v2\.json\. ## Primary entities - APIContext - Dropbox - api\.dropboxapi\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/dropbox.json) - [Developer documentation](https://dropbox.tech/developers) - [OpenAPI specification](https://raw.githubusercontent.com/stomakun/DropboxSwagger/master/swaggers/team_v2.json) --- # Github Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/github Source: static Updated: 2026-10-19T15:15:15.051Z Description: Github benchmark detail for api\.github\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Github is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.24 CASC score, 100\.00% pass rate, 258 ms median latency, and 589 ms p95 latency\. ## Stats - 9\.24 CASC score - 100\.00% pass rate - 258 ms median latency - 589 ms p95 latency - healthy operational state ## Page sections ### Github benchmark detail Category: Subject Github is measured as part of Corporate Infrastructure\. This page summarizes operational signals for api\.github\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.github\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 10\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 2\.55 ms\. - TCP connection: 11\.32 ms\. - TLS handshake: 12\.77 ms\. - Processing: 232\.82 ms\. - Download: 1\.32 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: GitHub, Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: GitHub\.com\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/github.json) - [Developer documentation](https://developer.github.com/program/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Github recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 589 ms, with median latency at 258 ms\. - Infrastructure fingerprinting identifies GitHub, Inc\. in the observed delivery path\. ## Key facts - Github domain: api\.github\.com\. - Operational state: healthy\. - CASC score: 9\.24\. - Pass rate: 100\.00%\. - p95 latency: 589 ms\. - Developer documentation: https://developer\.github\.com/program/\. ## Primary entities - APIContext - Github - api\.github\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/github.json) - [Developer documentation](https://developer.github.com/program/) --- # Google Workspace Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/google-workspace Source: static Updated: 2026-10-19T15:15:15.051Z Description: Google Workspace benchmark detail for www\.googleapis\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Google Workspace is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.78 CASC score, 100\.00% pass rate, 290 ms median latency, and 895 ms p95 latency\. ## Stats - 8\.78 CASC score - 100\.00% pass rate - 290 ms median latency - 895 ms p95 latency - healthy operational state ## Page sections ### Google Workspace benchmark detail Category: Subject Google Workspace is measured as part of Corporate Infrastructure\. This page summarizes operational signals for www\.googleapis\.com, including quality, reliability, latency, and infrastructure context\. - Domain: www\.googleapis\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 11\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10\.32 ms\. - TCP connection: 4\.09 ms\. - TLS handshake: 53\.68 ms\. - Processing: 327\.59 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: ESF\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/google-workspace.json) - [Developer documentation](https://developers.google.com/custom-search) - [Postman collection](https://www.postman.com/api-evangelist/workspace/google/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Google Workspace recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 895 ms, with median latency at 290 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Google Workspace domain: www\.googleapis\.com\. - Operational state: healthy\. - CASC score: 8\.78\. - Pass rate: 100\.00%\. - p95 latency: 895 ms\. - Developer documentation: https://developers\.google\.com/custom\-search\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/google/overview\. ## Primary entities - APIContext - Google Workspace - www\.googleapis\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/google-workspace.json) - [Developer documentation](https://developers.google.com/custom-search) --- # Merge Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/merge Source: static Updated: 2026-10-19T15:15:15.051Z Description: Merge benchmark detail for api\.merge\.dev, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Merge is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.16 CASC score, 100\.00% pass rate, 756 ms median latency, and 2,295 ms p95 latency\. ## Stats - 8\.16 CASC score - 100\.00% pass rate - 756 ms median latency - 2,295 ms p95 latency - recovering operational state ## Page sections ### Merge benchmark detail Category: Subject Merge is measured as part of Corporate Infrastructure\. This page summarizes operational signals for api\.merge\.dev, including quality, reliability, latency, and infrastructure context\. - Domain: api\.merge\.dev\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 75\.82 ms\. - TCP connection: 3\.5 ms\. - TLS handshake: 8\.41 ms\. - Processing: 823\.32 ms\. - Download: 22\.41 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/merge.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Merge recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 2295 ms, with median latency at 756 ms\. ## Key facts - Merge domain: api\.merge\.dev\. - Operational state: recovering\. - CASC score: 8\.16\. - Pass rate: 100\.00%\. - p95 latency: 2,295 ms\. ## Primary entities - APIContext - Merge - api\.merge\.dev - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/merge.json) --- # Microsoft Graph \(Office\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/microsoft-graph-office Source: static Updated: 2026-10-19T15:15:15.051Z Description: Microsoft Graph \(Office\) benchmark detail for graph\.microsoft\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Microsoft Graph \(Office\) is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.99 CASC score, 99\.99% pass rate, 296 ms median latency, and 1,115 ms p95 latency\. ## Stats - 8\.99 CASC score - 99\.99% pass rate - 296 ms median latency - 1,115 ms p95 latency - recovering operational state ## Page sections ### Microsoft Graph \(Office\) benchmark detail Category: Subject Microsoft Graph \(Office\) is measured as part of Corporate Infrastructure\. This page summarizes operational signals for graph\.microsoft\.com, including quality, reliability, latency, and infrastructure context\. - Domain: graph\.microsoft\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 16\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 2\.64 ms\. - TCP connection: 6\.18 ms\. - TLS handshake: 16\.09 ms\. - Processing: 328\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Microsoft Corporation\. - Nameserver: Microsoft Corporation\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/microsoft-graph-office.json) - [Developer documentation](https://developer.microsoft.com/en-us/graph) - [OpenAPI specification](https://raw.githubusercontent.com/microsoftgraph/microsoft-graph-openapi/master/v1.0.json) - [Postman collection](https://www.postman.com/microsoftgraph/workspace/microsoft-graph/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Microsoft Graph \(Office\) recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 1115 ms, with median latency at 296 ms\. - Infrastructure fingerprinting identifies Microsoft Corporation in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Microsoft Graph \(Office\) domain: graph\.microsoft\.com\. - Operational state: recovering\. - CASC score: 8\.99\. - Pass rate: 99\.99%\. - p95 latency: 1,115 ms\. - Developer documentation: https://developer\.microsoft\.com/en\-us/graph\. - Postman collection: https://www\.postman\.com/microsoftgraph/workspace/microsoft\-graph/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/microsoftgraph/microsoft\-graph\-openapi/master/v1\.0\.json\. ## Primary entities - APIContext - Microsoft Graph \(Office\) - graph\.microsoft\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/microsoft-graph-office.json) - [Developer documentation](https://developer.microsoft.com/en-us/graph) - [OpenAPI specification](https://raw.githubusercontent.com/microsoftgraph/microsoft-graph-openapi/master/v1.0.json) --- # Microsoft Graph \(Sharepoint\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/microsoft-graph-sharepoint Source: static Updated: 2026-10-19T15:15:15.051Z Description: Microsoft Graph \(Sharepoint\) benchmark detail for graph\.microsoft\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Microsoft Graph \(Sharepoint\) is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 8\.78 CASC score, 99\.98% pass rate, 688 ms median latency, and 1,257 ms p95 latency\. ## Stats - 8\.78 CASC score - 99\.98% pass rate - 688 ms median latency - 1,257 ms p95 latency - healthy operational state ## Page sections ### Microsoft Graph \(Sharepoint\) benchmark detail Category: Subject Microsoft Graph \(Sharepoint\) is measured as part of Corporate Infrastructure\. This page summarizes operational signals for graph\.microsoft\.com, including quality, reliability, latency, and infrastructure context\. - Domain: graph\.microsoft\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 2\.59 ms\. - TCP connection: 6\.45 ms\. - TLS handshake: 16\.55 ms\. - Processing: 681\.14 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Microsoft Corporation\. - Nameserver: Microsoft Corporation\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/microsoft-graph-sharepoint.json) - [Developer documentation](https://developer.microsoft.com/en-us/graph) - [OpenAPI specification](https://raw.githubusercontent.com/microsoftgraph/microsoft-graph-openapi/master/v1.0.json) - [Postman collection](https://www.postman.com/microsoftgraph/workspace/microsoft-graph/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Microsoft Graph \(Sharepoint\) recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 1257 ms, with median latency at 688 ms\. - Infrastructure fingerprinting identifies Microsoft Corporation in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Microsoft Graph \(Sharepoint\) domain: graph\.microsoft\.com\. - Operational state: healthy\. - CASC score: 8\.78\. - Pass rate: 99\.98%\. - p95 latency: 1,257 ms\. - Developer documentation: https://developer\.microsoft\.com/en\-us/graph\. - Postman collection: https://www\.postman\.com/microsoftgraph/workspace/microsoft\-graph/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/microsoftgraph/microsoft\-graph\-openapi/master/v1\.0\.json\. ## Primary entities - APIContext - Microsoft Graph \(Sharepoint\) - graph\.microsoft\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/microsoft-graph-sharepoint.json) - [Developer documentation](https://developer.microsoft.com/en-us/graph) - [OpenAPI specification](https://raw.githubusercontent.com/microsoftgraph/microsoft-graph-openapi/master/v1.0.json) --- # PubNub Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/pubnub Source: static Updated: 2026-10-19T15:15:15.051Z Description: PubNub benchmark detail for ps\.pndsn\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary PubNub is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.24 CASC score, 100\.00% pass rate, 198 ms median latency, and 739 ms p95 latency\. ## Stats - 9\.24 CASC score - 100\.00% pass rate - 198 ms median latency - 739 ms p95 latency - healthy operational state ## Page sections ### PubNub benchmark detail Category: Subject PubNub is measured as part of Corporate Infrastructure\. This page summarizes operational signals for ps\.pndsn\.com, including quality, reliability, latency, and infrastructure context\. - Domain: ps\.pndsn\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 2\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.18 ms\. - TCP connection: 73\.64 ms\. - TLS handshake: 146\.59 ms\. - Processing: 102\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/pubnub.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - PubNub recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 739 ms, with median latency at 198 ms\. ## Key facts - PubNub domain: ps\.pndsn\.com\. - Operational state: healthy\. - CASC score: 9\.24\. - Pass rate: 100\.00%\. - p95 latency: 739 ms\. ## Primary entities - APIContext - PubNub - ps\.pndsn\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/pubnub.json) --- # Radar Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/radar Source: static Updated: 2026-10-19T15:15:15.051Z Description: Radar benchmark detail for api\.radar\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Radar is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.17 CASC score, 100\.00% pass rate, 231 ms median latency, and 832 ms p95 latency\. ## Stats - 9\.17 CASC score - 100\.00% pass rate - 231 ms median latency - 832 ms p95 latency - healthy operational state ## Page sections ### Radar benchmark detail Category: Subject Radar is measured as part of Corporate Infrastructure\. This page summarizes operational signals for api\.radar\.io, including quality, reliability, latency, and infrastructure context\. - Domain: api\.radar\.io\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 57\.5 ms\. - TCP connection: 5\.32 ms\. - TLS handshake: 9\.32 ms\. - Processing: 203\.86 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/radar.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Radar recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 832 ms, with median latency at 231 ms\. ## Key facts - Radar domain: api\.radar\.io\. - Operational state: healthy\. - CASC score: 9\.17\. - Pass rate: 100\.00%\. - p95 latency: 832 ms\. ## Primary entities - APIContext - Radar - api\.radar\.io - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/radar.json) --- # Salesforce Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/salesforce Source: static Updated: 2026-10-19T15:15:15.051Z Description: Salesforce benchmark detail for na1\.salesforce\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Salesforce is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.24 CASC score, 100\.00% pass rate, 317 ms median latency, and 844 ms p95 latency\. ## Stats - 9\.24 CASC score - 100\.00% pass rate - 317 ms median latency - 844 ms p95 latency - healthy operational state ## Page sections ### Salesforce benchmark detail Category: Subject Salesforce is measured as part of Corporate Infrastructure\. This page summarizes operational signals for na1\.salesforce\.com, including quality, reliability, latency, and infrastructure context\. - Domain: na1\.salesforce\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 53\.5 ms\. - TCP connection: 140\.27 ms\. - TLS handshake: 142\.59 ms\. - Processing: 144\.14 ms\. - Download: 1 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Salesforce\.com, Inc\.\. - Nameserver: Salesforce\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/salesforce.json) - [Developer documentation](https://developer.salesforce.com/) - [OpenAPI specification](http://resources.docs.salesforce.com/rel1/doc/en-us/static/misc/iot-connect-api-swagger-45.0.yaml) - [Postman collection](https://www.postman.com/salesforce-developers/workspace/salesforce-developers/collection/12721794-67cb9baa-e0da-4986-957e-88d8734647e2?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Salesforce recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 844 ms, with median latency at 317 ms\. - Infrastructure fingerprinting identifies Salesforce\.com, Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Salesforce domain: na1\.salesforce\.com\. - Operational state: healthy\. - CASC score: 9\.24\. - Pass rate: 100\.00%\. - p95 latency: 844 ms\. - Developer documentation: https://developer\.salesforce\.com/\. - Postman collection: https://www\.postman\.com/salesforce\-developers/workspace/salesforce\-developers/collection/12721794\-67cb9baa\-e0da\-4986\-957e\-88d8734647e2?ctx=documentation\. - OpenAPI specification: http://resources\.docs\.salesforce\.com/rel1/doc/en\-us/static/misc/iot\-connect\-api\-swagger\-45\.0\.yaml\. ## Primary entities - APIContext - Salesforce - na1\.salesforce\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/salesforce.json) - [Developer documentation](https://developer.salesforce.com/) - [OpenAPI specification](http://resources.docs.salesforce.com/rel1/doc/en-us/static/misc/iot-connect-api-swagger-45.0.yaml) --- # Sendgrid Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corpinfra/sendgrid Source: static Updated: 2026-10-19T15:15:15.051Z Description: Sendgrid benchmark detail for api\.sendgrid\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Sendgrid is a api\-provider benchmark subject in Corporate Infrastructure\. Latest snapshot metrics include 9\.27 CASC score, 100\.00% pass rate, 311 ms median latency, and 895 ms p95 latency\. ## Stats - 9\.27 CASC score - 100\.00% pass rate - 311 ms median latency - 895 ms p95 latency - healthy operational state ## Page sections ### Sendgrid benchmark detail Category: Subject Sendgrid is measured as part of Corporate Infrastructure\. This page summarizes operational signals for api\.sendgrid\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.sendgrid\.com\. - Category: Corporate Infrastructure\. - Benchmark subject type: api\-provider\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6\.86 ms\. - TCP connection: 84\.86 ms\. - TLS handshake: 86\.55 ms\. - Processing: 298\.82 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: SendGrid, Inc\.\. - Nameserver: Tiggee LLC\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/sendgrid.json) - [Developer documentation](https://sendgrid.com/docs/api-reference/) - [OpenAPI specification](https://raw.githubusercontent.com/sendgrid/sendgrid-oai/main/oai_stoplight.json) - [Postman collection](https://www.postman.com/api-evangelist/workspace/messaging/collection/35240-6135048e-d8f2-4063-a921-e9f54a73ef03?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Sendgrid recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 895 ms, with median latency at 311 ms\. - Infrastructure fingerprinting identifies SendGrid, Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Sendgrid domain: api\.sendgrid\.com\. - Operational state: healthy\. - CASC score: 9\.27\. - Pass rate: 100\.00%\. - p95 latency: 895 ms\. - Developer documentation: https://sendgrid\.com/docs/api\-reference/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/messaging/collection/35240\-6135048e\-d8f2\-4063\-a921\-e9f54a73ef03?ctx=documentation\. - OpenAPI specification: https://raw\.githubusercontent\.com/sendgrid/sendgrid\-oai/main/oai\_stoplight\.json\. ## Primary entities - APIContext - Sendgrid - api\.sendgrid\.com - Corporate Infrastructure - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corpinfra/sendgrid.json) - [Developer documentation](https://sendgrid.com/docs/api-reference/) - [OpenAPI specification](https://raw.githubusercontent.com/sendgrid/sendgrid-oai/main/oai_stoplight.json) --- # Corporate Messaging Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/corporatemessaging Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 3 benchmark subjects in Corporate Messaging, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 3 benchmark subjects in Corporate Messaging, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 3 benchmark subjects - 8\.41 average CASC - 439 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Corporate Messaging benchmark slice Category: Category Latest verified snapshot covers 3 benchmark subjects in Corporate Messaging, with median latency signals and reliability measurements normalized for comparison\. - 3 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.90%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Africa's Talking — 7\.18 CASC, 99\.70% pass, 2,142 ms p95](/api-directory/corporatemessaging/africa-s-talking) - [Twilio — 9\.10 CASC, 100\.00% pass, 787 ms p95](/api-directory/corporatemessaging/twilio) - [Vonage \(formerly Nexmo\) — 8\.95 CASC, 100\.00% pass, 1,462 ms p95](/api-directory/corporatemessaging/vonage-formerly-nexmo) ## Key facts - 3 benchmark subjects are included in Corporate Messaging\. - Average CASC score: 841\. - Average median latency: 439 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Corporate Messaging - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/corporatemessaging.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Africa's Talking Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corporatemessaging/africa-s-talking Source: static Updated: 2026-10-19T15:15:15.051Z Description: Africa's Talking benchmark detail for api\.sandbox\.africastalking\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Africa's Talking is a api\-provider benchmark subject in Corporate Messaging\. Latest snapshot metrics include 7\.18 CASC score, 99\.70% pass rate, 787 ms median latency, and 2,142 ms p95 latency\. ## Stats - 7\.18 CASC score - 99\.70% pass rate - 787 ms median latency - 2,142 ms p95 latency - recovering operational state ## Page sections ### Africa's Talking benchmark detail Category: Subject Africa's Talking is measured as part of Corporate Messaging\. This page summarizes operational signals for api\.sandbox\.africastalking\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.sandbox\.africastalking\.com\. - Category: Corporate Messaging\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 98\.1 ms\. - TCP connection: 144\.05 ms\. - TLS handshake: 148\.9 ms\. - Processing: 448\.76 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Cloud Loadbalancing as a Service\-LBaaS \(LON\) IP Space\. - Nameserver: NeuStar, Inc\.\. - Server: akka\-http\. - [Subject JSON](/api-directory/data/latest/subjects/corporatemessaging/africa-s-talking.json) - [Developer documentation](https://developers.africastalking.com/) - [Postman collection](https://www.postman.com/africastalking/workspace/africa-s-talking-apis/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Africa's Talking recorded 99\.7% pass rate in the latest verified snapshot\. - The p95 latency signal is 2142 ms, with median latency at 787 ms\. - Infrastructure fingerprinting identifies Cloud Loadbalancing as a Service\-LBaaS \(LON\) IP Space in the observed delivery path\. ## Key facts - Africa's Talking domain: api\.sandbox\.africastalking\.com\. - Operational state: recovering\. - CASC score: 7\.18\. - Pass rate: 99\.70%\. - p95 latency: 2,142 ms\. - Developer documentation: https://developers\.africastalking\.com/\. - Postman collection: https://www\.postman\.com/africastalking/workspace/africa\-s\-talking\-apis/overview\. ## Primary entities - APIContext - Africa's Talking - api\.sandbox\.africastalking\.com - Corporate Messaging - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corporatemessaging/africa-s-talking.json) - [Developer documentation](https://developers.africastalking.com/) --- # Twilio Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corporatemessaging/twilio Source: static Updated: 2026-10-19T15:15:15.051Z Description: Twilio benchmark detail for api\.twilio\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Twilio is a api\-provider benchmark subject in Corporate Messaging\. Latest snapshot metrics include 9\.10 CASC score, 100\.00% pass rate, 250 ms median latency, and 787 ms p95 latency\. ## Stats - 9\.10 CASC score - 100\.00% pass rate - 250 ms median latency - 787 ms p95 latency - healthy operational state ## Page sections ### Twilio benchmark detail Category: Subject Twilio is measured as part of Corporate Messaging\. This page summarizes operational signals for api\.twilio\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.twilio\.com\. - Category: Corporate Messaging\. - Benchmark subject type: api\-provider\. - Monitored count: 8\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 11\.86 ms\. - TCP connection: 11\.68 ms\. - TLS handshake: 15 ms\. - Processing: 228\.05 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/corporatemessaging/twilio.json) - [Developer documentation](https://www.twilio.com/docs) - [OpenAPI specification](https://raw.githubusercontent.com/twilio/twilio-oai/main/spec/json/twilio_api_v2010.json) - [Postman collection](https://www.postman.com/twilio/workspace/twilio-api/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Twilio recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 787 ms, with median latency at 250 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Twilio domain: api\.twilio\.com\. - Operational state: healthy\. - CASC score: 9\.10\. - Pass rate: 100\.00%\. - p95 latency: 787 ms\. - Developer documentation: https://www\.twilio\.com/docs\. - Postman collection: https://www\.postman\.com/twilio/workspace/twilio\-api/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/twilio/twilio\-oai/main/spec/json/twilio\_api\_v2010\.json\. ## Primary entities - APIContext - Twilio - api\.twilio\.com - Corporate Messaging - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corporatemessaging/twilio.json) - [Developer documentation](https://www.twilio.com/docs) - [OpenAPI specification](https://raw.githubusercontent.com/twilio/twilio-oai/main/spec/json/twilio_api_v2010.json) --- # Vonage \(formerly Nexmo\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/corporatemessaging/vonage-formerly-nexmo Source: static Updated: 2026-10-19T15:15:15.051Z Description: Vonage \(formerly Nexmo\) benchmark detail for rest\.nexmo\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Vonage \(formerly Nexmo\) is a api\-provider benchmark subject in Corporate Messaging\. Latest snapshot metrics include 8\.95 CASC score, 100\.00% pass rate, 280 ms median latency, and 1,462 ms p95 latency\. ## Stats - 8\.95 CASC score - 100\.00% pass rate - 280 ms median latency - 1,462 ms p95 latency - healthy operational state ## Page sections ### Vonage \(formerly Nexmo\) benchmark detail Category: Subject Vonage \(formerly Nexmo\) is measured as part of Corporate Messaging\. This page summarizes operational signals for rest\.nexmo\.com, including quality, reliability, latency, and infrastructure context\. - Domain: rest\.nexmo\.com\. - Category: Corporate Messaging\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 80\.59 ms\. - TCP connection: 2\.77 ms\. - TLS handshake: 104 ms\. - Processing: 101\.45 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Vonage Business Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: envoy\. - [Subject JSON](/api-directory/data/latest/subjects/corporatemessaging/vonage-formerly-nexmo.json) - [Developer documentation](https://developer.nexmo.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Vonage \(formerly Nexmo\) recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1462 ms, with median latency at 280 ms\. - Infrastructure fingerprinting identifies Vonage Business Inc\. in the observed delivery path\. ## Key facts - Vonage \(formerly Nexmo\) domain: rest\.nexmo\.com\. - Operational state: healthy\. - CASC score: 8\.95\. - Pass rate: 100\.00%\. - p95 latency: 1,462 ms\. - Developer documentation: https://developer\.nexmo\.com/\. ## Primary entities - APIContext - Vonage \(formerly Nexmo\) - rest\.nexmo\.com - Corporate Messaging - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/corporatemessaging/vonage-formerly-nexmo.json) - [Developer documentation](https://developer.nexmo.com/) --- # COVID\-19 Data Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/covid19 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 1 benchmark subjects in COVID\-19 Data, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 1 benchmark subjects in COVID\-19 Data, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 1 benchmark subjects - 8\.57 average CASC - 245 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### COVID\-19 Data benchmark slice Category: Category Latest verified snapshot covers 1 benchmark subjects in COVID\-19 Data, with median latency signals and reliability measurements normalized for comparison\. - 1 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.85%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [The COVID Tracking Project — 8\.57 CASC, 99\.85% pass, 656 ms p95](/api-directory/covid19/the-covid-tracking-project) ## Key facts - 1 benchmark subjects are included in COVID\-19 Data\. - Average CASC score: 857\. - Average median latency: 245 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - COVID\-19 Data - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/covid19.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # The COVID Tracking Project Operational Intelligence Canonical URL: https://apicontext.com/api-directory/covid19/the-covid-tracking-project Source: static Updated: 2026-10-19T15:15:15.051Z Description: The COVID Tracking Project benchmark detail for api\.covidtracking\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary The COVID Tracking Project is a api\-provider benchmark subject in COVID\-19 Data\. Latest snapshot metrics include 8\.57 CASC score, 99\.85% pass rate, 245 ms median latency, and 656 ms p95 latency\. ## Stats - 8\.57 CASC score - 99\.85% pass rate - 245 ms median latency - 656 ms p95 latency - recovering operational state ## Page sections ### The COVID Tracking Project benchmark detail Category: Subject The COVID Tracking Project is measured as part of COVID\-19 Data\. This page summarizes operational signals for api\.covidtracking\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.covidtracking\.com\. - Category: COVID\-19 Data\. - Benchmark subject type: api\-provider\. - Monitored count: 2\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6 ms\. - TCP connection: 8\.6 ms\. - TLS handshake: 15\.1 ms\. - Processing: 213\.5 ms\. - Download: 4\.9 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/covid19/the-covid-tracking-project.json) - [Developer documentation](https://covidtracking.com/) - [Postman collection](https://www.postman.com/postman/workspace/covid-19/collection/12959542-9dc21a44-57b2-4e31-862e-1d7e9c95db44) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - The COVID Tracking Project recorded 99\.85% pass rate in the latest verified snapshot\. - The p95 latency signal is 656 ms, with median latency at 245 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. ## Key facts - The COVID Tracking Project domain: api\.covidtracking\.com\. - Operational state: recovering\. - CASC score: 8\.57\. - Pass rate: 99\.85%\. - p95 latency: 656 ms\. - Developer documentation: https://covidtracking\.com/\. - Postman collection: https://www\.postman\.com/postman/workspace/covid\-19/collection/12959542\-9dc21a44\-57b2\-4e31\-862e\-1d7e9c95db44\. ## Primary entities - APIContext - The COVID Tracking Project - api\.covidtracking\.com - COVID\-19 Data - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/covid19/the-covid-tracking-project.json) - [Developer documentation](https://covidtracking.com/) --- # UK Digital Government Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/digitalgovernmentukgov Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 3 benchmark subjects in UK Digital Government, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 3 benchmark subjects in UK Digital Government, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 3 benchmark subjects - 8\.67 average CASC - 107\.33 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### UK Digital Government benchmark slice Category: Category Latest verified snapshot covers 3 benchmark subjects in UK Digital Government, with median latency signals and reliability measurements normalized for comparison\. - 3 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.97%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Police\.UK — 7\.99 CASC, 99\.96% pass, 1,381 ms p95](/api-directory/digitalgovernmentukgov/police-uk) - [DEFRA — 9\.33 CASC, 100\.00% pass, 327 ms p95](/api-directory/digitalgovernmentukgov/defra) - [NHS — 8\.68 CASC, 99\.96% pass, 1,147 ms p95](/api-directory/digitalgovernmentukgov/nhs) ## Key facts - 3 benchmark subjects are included in UK Digital Government\. - Average CASC score: 866\.67\. - Average median latency: 107\.33 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - UK Digital Government - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/digitalgovernmentukgov.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # DEFRA Operational Intelligence Canonical URL: https://apicontext.com/api-directory/digitalgovernmentukgov/defra Source: static Updated: 2026-10-19T15:15:15.051Z Description: DEFRA benchmark detail for environment\.data\.gov\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary DEFRA is a api\-provider benchmark subject in UK Digital Government\. Latest snapshot metrics include 9\.33 CASC score, 100\.00% pass rate, 128 ms median latency, and 327 ms p95 latency\. ## Stats - 9\.33 CASC score - 100\.00% pass rate - 128 ms median latency - 327 ms p95 latency - recovering operational state ## Page sections ### DEFRA benchmark detail Category: Subject DEFRA is measured as part of UK Digital Government\. This page summarizes operational signals for environment\.data\.gov\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: environment\.data\.gov\.uk\. - Category: UK Digital Government\. - Benchmark subject type: api\-provider\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.5 ms\. - TCP connection: 6 ms\. - TLS handshake: 17\.5 ms\. - Processing: 69\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/digitalgovernmentukgov/defra.json) - [Developer documentation](https://environment.data.gov.uk/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - DEFRA recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 327 ms, with median latency at 128 ms\. ## Key facts - DEFRA domain: environment\.data\.gov\.uk\. - Operational state: recovering\. - CASC score: 9\.33\. - Pass rate: 100\.00%\. - p95 latency: 327 ms\. - Developer documentation: https://environment\.data\.gov\.uk/\. ## Primary entities - APIContext - DEFRA - environment\.data\.gov\.uk - UK Digital Government - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/digitalgovernmentukgov/defra.json) - [Developer documentation](https://environment.data.gov.uk/) --- # NHS Operational Intelligence Canonical URL: https://apicontext.com/api-directory/digitalgovernmentukgov/nhs Source: static Updated: 2026-10-19T15:15:15.051Z Description: NHS benchmark detail for digital\.nhs\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary NHS is a api\-provider benchmark subject in UK Digital Government\. Latest snapshot metrics include 8\.68 CASC score, 99\.96% pass rate, 92 ms median latency, and 1,147 ms p95 latency\. ## Stats - 8\.68 CASC score - 99\.96% pass rate - 92 ms median latency - 1,147 ms p95 latency - healthy operational state ## Page sections ### NHS benchmark detail Category: Subject NHS is measured as part of UK Digital Government\. This page summarizes operational signals for digital\.nhs\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: digital\.nhs\.uk\. - Category: UK Digital Government\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6\.33 ms\. - TCP connection: 4\.67 ms\. - TLS handshake: 11 ms\. - Processing: 55\.67 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/digitalgovernmentukgov/nhs.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - NHS recorded 99\.96% pass rate in the latest verified snapshot\. - The p95 latency signal is 1147 ms, with median latency at 92 ms\. ## Key facts - NHS domain: digital\.nhs\.uk\. - Operational state: healthy\. - CASC score: 8\.68\. - Pass rate: 99\.96%\. - p95 latency: 1,147 ms\. ## Primary entities - APIContext - NHS - digital\.nhs\.uk - UK Digital Government - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/digitalgovernmentukgov/nhs.json) --- # Police\.UK Operational Intelligence Canonical URL: https://apicontext.com/api-directory/digitalgovernmentukgov/police-uk Source: static Updated: 2026-10-19T15:15:15.051Z Description: Police\.UK benchmark detail for data\.police\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Police\.UK is a api\-provider benchmark subject in UK Digital Government\. Latest snapshot metrics include 7\.99 CASC score, 99\.96% pass rate, 102 ms median latency, and 1,381 ms p95 latency\. ## Stats - 7\.99 CASC score - 99\.96% pass rate - 102 ms median latency - 1,381 ms p95 latency - stable operational state ## Page sections ### Police\.UK benchmark detail Category: Subject Police\.UK is measured as part of UK Digital Government\. This page summarizes operational signals for data\.police\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: data\.police\.uk\. - Category: UK Digital Government\. - Benchmark subject type: api\-provider\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 49\.5 ms\. - TCP connection: 12\.25 ms\. - TLS handshake: 15 ms\. - Processing: 25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/digitalgovernmentukgov/police-uk.json) - [Developer documentation](https://data.police.uk/docs/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Police\.UK recorded 99\.96% pass rate in the latest verified snapshot\. - The p95 latency signal is 1381 ms, with median latency at 102 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Police\.UK domain: data\.police\.uk\. - Operational state: stable\. - CASC score: 7\.99\. - Pass rate: 99\.96%\. - p95 latency: 1,381 ms\. - Developer documentation: https://data\.police\.uk/docs/\. ## Primary entities - APIContext - Police\.UK - data\.police\.uk - UK Digital Government - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/digitalgovernmentukgov/police-uk.json) - [Developer documentation](https://data.police.uk/docs/) --- # Enterprise Messaging Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/enterprisemessaging Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 3 benchmark subjects in Enterprise Messaging, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 3 benchmark subjects in Enterprise Messaging, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 3 benchmark subjects - 8\.20 average CASC - 425 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Enterprise Messaging benchmark slice Category: Category Latest verified snapshot covers 3 benchmark subjects in Enterprise Messaging, with median latency signals and reliability measurements normalized for comparison\. - 3 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.95%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Cisco — 6\.95 CASC, 99\.87% pass, 8,592 ms p95](/api-directory/enterprisemessaging/cisco) - [Slack — 9\.38 CASC, 99\.99% pass, 484 ms p95](/api-directory/enterprisemessaging/slack) - [Zoom — 8\.27 CASC, 99\.98% pass, 870 ms p95](/api-directory/enterprisemessaging/zoom) ## Key facts - 3 benchmark subjects are included in Enterprise Messaging\. - Average CASC score: 820\. - Average median latency: 425 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Enterprise Messaging - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/enterprisemessaging.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Cisco Operational Intelligence Canonical URL: https://apicontext.com/api-directory/enterprisemessaging/cisco Source: static Updated: 2026-10-19T15:15:15.051Z Description: Cisco benchmark detail for api\.ciscospark\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Cisco is a api\-provider benchmark subject in Enterprise Messaging\. Latest snapshot metrics include 6\.95 CASC score, 99\.87% pass rate, 764 ms median latency, and 8,592 ms p95 latency\. ## Stats - 6\.95 CASC score - 99\.87% pass rate - 764 ms median latency - 8,592 ms p95 latency - stable operational state ## Page sections ### Cisco benchmark detail Category: Subject Cisco is measured as part of Enterprise Messaging\. This page summarizes operational signals for api\.ciscospark\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ciscospark\.com\. - Category: Enterprise Messaging\. - Benchmark subject type: api\-provider\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 12\.32 ms\. - TCP connection: 76\.77 ms\. - TLS handshake: 154\.41 ms\. - Processing: 503\.91 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Cisco Webex LLC\. - Nameserver: Amazon\.com, Inc\.\. - Server: Redacted\. - [Subject JSON](/api-directory/data/latest/subjects/enterprisemessaging/cisco.json) - [Developer documentation](https://developer.webex.com/) - [OpenAPI specification](https://api.apis.guru/v2/specs/cisco.com/0.0.3/swagger.json) - [Postman collection](https://www.postman.com/ciscodevnet/workspace/cisco-devnet-s-public-workspace/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Cisco recorded 99\.87% pass rate in the latest verified snapshot\. - The p95 latency signal is 8592 ms, with median latency at 764 ms\. - Infrastructure fingerprinting identifies Cisco Webex LLC in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Cisco domain: api\.ciscospark\.com\. - Operational state: stable\. - CASC score: 6\.95\. - Pass rate: 99\.87%\. - p95 latency: 8,592 ms\. - Developer documentation: https://developer\.webex\.com/\. - Postman collection: https://www\.postman\.com/ciscodevnet/workspace/cisco\-devnet\-s\-public\-workspace/overview\. - OpenAPI specification: https://api\.apis\.guru/v2/specs/cisco\.com/0\.0\.3/swagger\.json\. ## Primary entities - APIContext - Cisco - api\.ciscospark\.com - Enterprise Messaging - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/enterprisemessaging/cisco.json) - [Developer documentation](https://developer.webex.com/) - [OpenAPI specification](https://api.apis.guru/v2/specs/cisco.com/0.0.3/swagger.json) --- # Slack Operational Intelligence Canonical URL: https://apicontext.com/api-directory/enterprisemessaging/slack Source: static Updated: 2026-10-19T15:15:15.051Z Description: Slack benchmark detail for slack\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Slack is a api\-provider benchmark subject in Enterprise Messaging\. Latest snapshot metrics include 9\.38 CASC score, 99\.99% pass rate, 216 ms median latency, and 484 ms p95 latency\. ## Stats - 9\.38 CASC score - 99\.99% pass rate - 216 ms median latency - 484 ms p95 latency - healthy operational state ## Page sections ### Slack benchmark detail Category: Subject Slack is measured as part of Enterprise Messaging\. This page summarizes operational signals for slack\.com, including quality, reliability, latency, and infrastructure context\. - Domain: slack\.com\. - Category: Enterprise Messaging\. - Benchmark subject type: api\-provider\. - Monitored count: 11\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 4\.5 ms\. - TCP connection: 10\.68 ms\. - TLS handshake: 12\.55 ms\. - Processing: 181\.18 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: Apache\. - [Subject JSON](/api-directory/data/latest/subjects/enterprisemessaging/slack.json) - [Developer documentation](https://api.slack.com/) - [OpenAPI specification](https://raw.githubusercontent.com/slackapi/slack-api-specs/master/web-api/slack_web_openapi_v2.json) - [Postman collection](https://www.postman.com/api-evangelist/workspace/slack/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Slack recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 484 ms, with median latency at 216 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Slack domain: slack\.com\. - Operational state: healthy\. - CASC score: 9\.38\. - Pass rate: 99\.99%\. - p95 latency: 484 ms\. - Developer documentation: https://api\.slack\.com/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/slack/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/slackapi/slack\-api\-specs/master/web\-api/slack\_web\_openapi\_v2\.json\. ## Primary entities - APIContext - Slack - slack\.com - Enterprise Messaging - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/enterprisemessaging/slack.json) - [Developer documentation](https://api.slack.com/) - [OpenAPI specification](https://raw.githubusercontent.com/slackapi/slack-api-specs/master/web-api/slack_web_openapi_v2.json) --- # Zoom Operational Intelligence Canonical URL: https://apicontext.com/api-directory/enterprisemessaging/zoom Source: static Updated: 2026-10-19T15:15:15.051Z Description: Zoom benchmark detail for api\.zoom\.us, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Zoom is a api\-provider benchmark subject in Enterprise Messaging\. Latest snapshot metrics include 8\.27 CASC score, 99\.98% pass rate, 295 ms median latency, and 870 ms p95 latency\. ## Stats - 8\.27 CASC score - 99\.98% pass rate - 295 ms median latency - 870 ms p95 latency - stable operational state ## Page sections ### Zoom benchmark detail Category: Subject Zoom is measured as part of Enterprise Messaging\. This page summarizes operational signals for api\.zoom\.us, including quality, reliability, latency, and infrastructure context\. - Domain: api\.zoom\.us\. - Category: Enterprise Messaging\. - Benchmark subject type: api\-provider\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 9\.18 ms\. - TCP connection: 5\.95 ms\. - TLS handshake: 11\.5 ms\. - Processing: 246\.14 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Zoom Video Communications, Inc\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/enterprisemessaging/zoom.json) - [Developer documentation](https://marketplace.zoom.us/docs/api-reference/zoom-api) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Zoom recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 870 ms, with median latency at 295 ms\. - Infrastructure fingerprinting identifies Zoom Video Communications, Inc in the observed delivery path\. ## Key facts - Zoom domain: api\.zoom\.us\. - Operational state: stable\. - CASC score: 8\.27\. - Pass rate: 99\.98%\. - p95 latency: 870 ms\. - Developer documentation: https://marketplace\.zoom\.us/docs/api\-reference/zoom\-api\. ## Primary entities - APIContext - Zoom - api\.zoom\.us - Enterprise Messaging - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/enterprisemessaging/zoom.json) - [Developer documentation](https://marketplace.zoom.us/docs/api-reference/zoom-api) --- # Cryptocurrency Exchanges Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 11 benchmark subjects in Cryptocurrency Exchanges, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 11 benchmark subjects in Cryptocurrency Exchanges, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 11 benchmark subjects - 8\.89 average CASC - 327 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Cryptocurrency Exchanges benchmark slice Category: Category Latest verified snapshot covers 11 benchmark subjects in Cryptocurrency Exchanges, with median latency signals and reliability measurements normalized for comparison\. - 11 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.89%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Bitfinex — 8\.85 CASC, 100\.00% pass, 680 ms p95](/api-directory/exchanges/bitfinex) - [Bancor Network — 8\.52 CASC, 100\.00% pass, 2,037 ms p95](/api-directory/exchanges/bancor-network) - [Gemini — 8\.01 CASC, 99\.97% pass, 1,557 ms p95](/api-directory/exchanges/gemini) - [Coinbase — 9\.49 CASC, 100\.00% pass, 441 ms p95](/api-directory/exchanges/coinbase) - [Binance — 9\.13 CASC, 100\.00% pass, 490 ms p95](/api-directory/exchanges/binance) - [Coincheck — 9\.13 CASC, 100\.00% pass, 985 ms p95](/api-directory/exchanges/coincheck) - [KuCoin — 9\.23 CASC, 100\.00% pass, 539 ms p95](/api-directory/exchanges/kucoin) - [Binance US — 8\.12 CASC, 99\.97% pass, 1,303 ms p95](/api-directory/exchanges/binance-us) - [Bitstamp — 8\.84 CASC, 99\.28% pass, 1,170 ms p95](/api-directory/exchanges/bitstamp) - [OKEx — 9\.20 CASC, 99\.55% pass, 424 ms p95](/api-directory/exchanges/okex) - [Kraken — 9\.27 CASC, 100\.00% pass, 449 ms p95](/api-directory/exchanges/kraken) ## Key facts - 11 benchmark subjects are included in Cryptocurrency Exchanges\. - Average CASC score: 889\. - Average median latency: 327 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Cryptocurrency Exchanges - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/exchanges.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Bancor Network Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/bancor-network Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bancor Network benchmark detail for api\-v2\.bancor\.network, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bancor Network is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 8\.52 CASC score, 100\.00% pass rate, 391 ms median latency, and 2,037 ms p95 latency\. ## Stats - 8\.52 CASC score - 100\.00% pass rate - 391 ms median latency - 2,037 ms p95 latency - healthy operational state ## Page sections ### Bancor Network benchmark detail Category: Subject Bancor Network is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\-v2\.bancor\.network, including quality, reliability, latency, and infrastructure context\. - Domain: api\-v2\.bancor\.network\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 68\.82 ms\. - TCP connection: 4\.86 ms\. - TLS handshake: 11\.05 ms\. - Processing: 557\.77 ms\. - Download: 0\.14 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/bancor-network.json) - [Developer documentation](https://docs.bancor.network/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bancor Network recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 2037 ms, with median latency at 391 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - Bancor Network domain: api\-v2\.bancor\.network\. - Operational state: healthy\. - CASC score: 8\.52\. - Pass rate: 100\.00%\. - p95 latency: 2,037 ms\. - Developer documentation: https://docs\.bancor\.network/\. ## Primary entities - APIContext - Bancor Network - api\-v2\.bancor\.network - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/bancor-network.json) - [Developer documentation](https://docs.bancor.network/) --- # Binance Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/binance Source: static Updated: 2026-10-19T15:15:15.051Z Description: Binance benchmark detail for api\.binance\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Binance is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 9\.13 CASC score, 100\.00% pass rate, 243 ms median latency, and 490 ms p95 latency\. ## Stats - 9\.13 CASC score - 100\.00% pass rate - 243 ms median latency - 490 ms p95 latency - healthy operational state ## Page sections ### Binance benchmark detail Category: Subject Binance is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\.binance\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.binance\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 30\.61 ms\. - TCP connection: 2\.89 ms\. - TLS handshake: 5\.78 ms\. - Processing: 199\.28 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: amazon\_cloudfront\_cdn\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/binance.json) - [Developer documentation](https://developers.binance.com/docs/binance-apis/apis.html) - [OpenAPI specification](https://raw.githubusercontent.com/binance-exchange/binance-api-swagger/master/spot_api.yaml) - [Postman collection](https://www.postman.com/api-noob/workspace/binance-apis/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Binance recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 490 ms, with median latency at 243 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Binance domain: api\.binance\.com\. - Operational state: healthy\. - CASC score: 9\.13\. - Pass rate: 100\.00%\. - p95 latency: 490 ms\. - Developer documentation: https://developers\.binance\.com/docs/binance\-apis/apis\.html\. - Postman collection: https://www\.postman\.com/api\-noob/workspace/binance\-apis/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/binance\-exchange/binance\-api\-swagger/master/spot\_api\.yaml\. ## Primary entities - APIContext - Binance - api\.binance\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/binance.json) - [Developer documentation](https://developers.binance.com/docs/binance-apis/apis.html) - [OpenAPI specification](https://raw.githubusercontent.com/binance-exchange/binance-api-swagger/master/spot_api.yaml) --- # Binance US Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/binance-us Source: static Updated: 2026-10-19T15:15:15.051Z Description: Binance US benchmark detail for api\.binance\.us, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Binance US is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 8\.12 CASC score, 99\.97% pass rate, 620 ms median latency, and 1,303 ms p95 latency\. ## Stats - 8\.12 CASC score - 99\.97% pass rate - 620 ms median latency - 1,303 ms p95 latency - volatile operational state ## Page sections ### Binance US benchmark detail Category: Subject Binance US is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\.binance\.us, including quality, reliability, latency, and infrastructure context\. - Domain: api\.binance\.us\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 61\.09 ms\. - TCP connection: 3\.64 ms\. - TLS handshake: 6\.64 ms\. - Processing: 565\.41 ms\. - Download: 11\.64 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: amazon\_cloudfront\_cdn\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/binance-us.json) - [Developer documentation](https://developers.binance.com/docs/binance-apis/apis.html) - [OpenAPI specification](https://docs.kraken.com/rest/) - [Postman collection](https://www.postman.com/solar-capsule-443692/workspace/crypto-apis/request/581196-780dccaf-3dea-4664-9ddb-3dc2a093be2c) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Binance US recorded 99\.97% pass rate in the latest verified snapshot\. - The p95 latency signal is 1303 ms, with median latency at 620 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Binance US domain: api\.binance\.us\. - Operational state: volatile\. - CASC score: 8\.12\. - Pass rate: 99\.97%\. - p95 latency: 1,303 ms\. - Developer documentation: https://developers\.binance\.com/docs/binance\-apis/apis\.html\. - Postman collection: https://www\.postman\.com/solar\-capsule\-443692/workspace/crypto\-apis/request/581196\-780dccaf\-3dea\-4664\-9ddb\-3dc2a093be2c\. - OpenAPI specification: https://docs\.kraken\.com/rest/\. ## Primary entities - APIContext - Binance US - api\.binance\.us - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/binance-us.json) - [Developer documentation](https://developers.binance.com/docs/binance-apis/apis.html) - [OpenAPI specification](https://docs.kraken.com/rest/) --- # Bitfinex Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/bitfinex Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bitfinex benchmark detail for api\-pub\.bitfinex\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bitfinex is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 8\.85 CASC score, 100\.00% pass rate, 231 ms median latency, and 680 ms p95 latency\. ## Stats - 8\.85 CASC score - 100\.00% pass rate - 231 ms median latency - 680 ms p95 latency - healthy operational state ## Page sections ### Bitfinex benchmark detail Category: Subject Bitfinex is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\-pub\.bitfinex\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\-pub\.bitfinex\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 68\.95 ms\. - TCP connection: 5\.36 ms\. - TLS handshake: 9\.77 ms\. - Processing: 205\.27 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/bitfinex.json) - [Developer documentation](https://docs.bitfinex.com/docs/introduction) - [Postman collection](https://www.postman.com/solar-capsule-443692/workspace/crypto-apis/request/581196-b99cfa8d-bc67-4018-96db-a0fbc9a5b8da) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bitfinex recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 680 ms, with median latency at 231 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - Bitfinex domain: api\-pub\.bitfinex\.com\. - Operational state: healthy\. - CASC score: 8\.85\. - Pass rate: 100\.00%\. - p95 latency: 680 ms\. - Developer documentation: https://docs\.bitfinex\.com/docs/introduction\. - Postman collection: https://www\.postman\.com/solar\-capsule\-443692/workspace/crypto\-apis/request/581196\-b99cfa8d\-bc67\-4018\-96db\-a0fbc9a5b8da\. ## Primary entities - APIContext - Bitfinex - api\-pub\.bitfinex\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/bitfinex.json) - [Developer documentation](https://docs.bitfinex.com/docs/introduction) --- # Bitstamp Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/bitstamp Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bitstamp benchmark detail for www\.bitstamp\.net, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bitstamp is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 8\.84 CASC score, 99\.28% pass rate, 223 ms median latency, and 1,170 ms p95 latency\. ## Stats - 8\.84 CASC score - 99\.28% pass rate - 223 ms median latency - 1,170 ms p95 latency - degraded operational state ## Page sections ### Bitstamp benchmark detail Category: Subject Bitstamp is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for www\.bitstamp\.net, including quality, reliability, latency, and infrastructure context\. - Domain: www\.bitstamp\.net\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 47\.36 ms\. - TCP connection: 3\.82 ms\. - TLS handshake: 6\.45 ms\. - Processing: 214\.27 ms\. - Download: 0\.05 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: imperva\_cdn\. - Hosting provider: Incapsula Inc\. - Nameserver: Incapsula Inc\. - Server: Apache\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/bitstamp.json) - [Developer documentation](https://www.bitstamp.net/api/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bitstamp recorded 99\.28% pass rate in the latest verified snapshot\. - The p95 latency signal is 1170 ms, with median latency at 223 ms\. - Infrastructure fingerprinting identifies Incapsula Inc in the observed delivery path\. ## Key facts - Bitstamp domain: www\.bitstamp\.net\. - Operational state: degraded\. - CASC score: 8\.84\. - Pass rate: 99\.28%\. - p95 latency: 1,170 ms\. - Developer documentation: https://www\.bitstamp\.net/api/\. ## Primary entities - APIContext - Bitstamp - www\.bitstamp\.net - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/bitstamp.json) - [Developer documentation](https://www.bitstamp.net/api/) --- # Coinbase Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/coinbase Source: static Updated: 2026-10-19T15:15:15.051Z Description: Coinbase benchmark detail for api\.coinbase\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Coinbase is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 9\.49 CASC score, 100\.00% pass rate, 133 ms median latency, and 441 ms p95 latency\. ## Stats - 9\.49 CASC score - 100\.00% pass rate - 133 ms median latency - 441 ms p95 latency - healthy operational state ## Page sections ### Coinbase benchmark detail Category: Subject Coinbase is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\.coinbase\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.coinbase\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 44\.09 ms\. - TCP connection: 5\.73 ms\. - TLS handshake: 9\.32 ms\. - Processing: 158\.68 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/coinbase.json) - [Developer documentation](https://developers.coinbase.com/api/v2) - [OpenAPI specification](https://www.postman.com/api-evangelist/workspace/blockchain/api/71975c40-8ace-4b85-bcfa-7187de4a2e8f?version=a8ce208c-d355-4c0a-93d5-b40acdae0dda&tab=define) - [Postman collection](https://www.postman.com/api-evangelist/workspace/blockchain/collection/35240-ec28091e-f6f6-43a6-824d-f11b2c097b73?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Coinbase recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 441 ms, with median latency at 133 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Coinbase domain: api\.coinbase\.com\. - Operational state: healthy\. - CASC score: 9\.49\. - Pass rate: 100\.00%\. - p95 latency: 441 ms\. - Developer documentation: https://developers\.coinbase\.com/api/v2\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/blockchain/collection/35240\-ec28091e\-f6f6\-43a6\-824d\-f11b2c097b73?ctx=documentation\. - OpenAPI specification: https://www\.postman\.com/api\-evangelist/workspace/blockchain/api/71975c40\-8ace\-4b85\-bcfa\-7187de4a2e8f?version=a8ce208c\-d355\-4c0a\-93d5\-b40acdae0dda&tab=define\. ## Primary entities - APIContext - Coinbase - api\.coinbase\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/coinbase.json) - [Developer documentation](https://developers.coinbase.com/api/v2) - [OpenAPI specification](https://www.postman.com/api-evangelist/workspace/blockchain/api/71975c40-8ace-4b85-bcfa-7187de4a2e8f?version=a8ce208c-d355-4c0a-93d5-b40acdae0dda&tab=define) --- # Coincheck Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/coincheck Source: static Updated: 2026-10-19T15:15:15.051Z Description: Coincheck benchmark detail for coincheck\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Coincheck is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 9\.13 CASC score, 100\.00% pass rate, 484 ms median latency, and 985 ms p95 latency\. ## Stats - 9\.13 CASC score - 100\.00% pass rate - 484 ms median latency - 985 ms p95 latency - healthy operational state ## Page sections ### Coincheck benchmark detail Category: Subject Coincheck is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for coincheck\.com, including quality, reliability, latency, and infrastructure context\. - Domain: coincheck\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 92\.67 ms\. - TCP connection: 44\.57 ms\. - TLS handshake: 48\.05 ms\. - Processing: 481 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: amazon\_cloudfront\_cdn\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/coincheck.json) - [Developer documentation](https://coincheck.com/documents/exchange/api) - [Postman collection](https://www.postman.com/solar-capsule-443692/workspace/crypto-apis/request/581196-e0593efb-ee5f-4dd0-8111-08ae4dd4883a) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Coincheck recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 985 ms, with median latency at 484 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Coincheck domain: coincheck\.com\. - Operational state: healthy\. - CASC score: 9\.13\. - Pass rate: 100\.00%\. - p95 latency: 985 ms\. - Developer documentation: https://coincheck\.com/documents/exchange/api\. - Postman collection: https://www\.postman\.com/solar\-capsule\-443692/workspace/crypto\-apis/request/581196\-e0593efb\-ee5f\-4dd0\-8111\-08ae4dd4883a\. ## Primary entities - APIContext - Coincheck - coincheck\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/coincheck.json) - [Developer documentation](https://coincheck.com/documents/exchange/api) --- # Gemini Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/gemini Source: static Updated: 2026-10-19T15:15:15.051Z Description: Gemini benchmark detail for api\.gemini\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Gemini is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 8\.01 CASC score, 99\.97% pass rate, 593 ms median latency, and 1,557 ms p95 latency\. ## Stats - 8\.01 CASC score - 99\.97% pass rate - 593 ms median latency - 1,557 ms p95 latency - stable operational state ## Page sections ### Gemini benchmark detail Category: Subject Gemini is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\.gemini\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.gemini\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 91\.41 ms\. - TCP connection: 135\.27 ms\. - TLS handshake: 272\.18 ms\. - Processing: 210\.23 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/gemini.json) - [Developer documentation](https://docs.gemini.com/rest-api/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Gemini recorded 99\.97% pass rate in the latest verified snapshot\. - The p95 latency signal is 1557 ms, with median latency at 593 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. ## Key facts - Gemini domain: api\.gemini\.com\. - Operational state: stable\. - CASC score: 8\.01\. - Pass rate: 99\.97%\. - p95 latency: 1,557 ms\. - Developer documentation: https://docs\.gemini\.com/rest\-api/\. ## Primary entities - APIContext - Gemini - api\.gemini\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/gemini.json) - [Developer documentation](https://docs.gemini.com/rest-api/) --- # Kraken Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/kraken Source: static Updated: 2026-10-19T15:15:15.051Z Description: Kraken benchmark detail for api\.kraken\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Kraken is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 9\.27 CASC score, 100\.00% pass rate, 181 ms median latency, and 449 ms p95 latency\. ## Stats - 9\.27 CASC score - 100\.00% pass rate - 181 ms median latency - 449 ms p95 latency - healthy operational state ## Page sections ### Kraken benchmark detail Category: Subject Kraken is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\.kraken\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.kraken\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 18\.55 ms\. - TCP connection: 3\.32 ms\. - TLS handshake: 7\.45 ms\. - Processing: 191\.95 ms\. - Download: 0\.05 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/kraken.json) - [Developer documentation](https://www.kraken.com/en-gb/features/api) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Kraken recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 449 ms, with median latency at 181 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - Kraken domain: api\.kraken\.com\. - Operational state: healthy\. - CASC score: 9\.27\. - Pass rate: 100\.00%\. - p95 latency: 449 ms\. - Developer documentation: https://www\.kraken\.com/en\-gb/features/api\. ## Primary entities - APIContext - Kraken - api\.kraken\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/kraken.json) - [Developer documentation](https://www.kraken.com/en-gb/features/api) --- # KuCoin Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/kucoin Source: static Updated: 2026-10-19T15:15:15.051Z Description: KuCoin benchmark detail for api\.kucoin\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary KuCoin is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 9\.23 CASC score, 100\.00% pass rate, 265 ms median latency, and 539 ms p95 latency\. ## Stats - 9\.23 CASC score - 100\.00% pass rate - 265 ms median latency - 539 ms p95 latency - healthy operational state ## Page sections ### KuCoin benchmark detail Category: Subject KuCoin is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for api\.kucoin\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.kucoin\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 77\.55 ms\. - TCP connection: 3\.18 ms\. - TLS handshake: 7\.05 ms\. - Processing: 206\.77 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/kucoin.json) - [Developer documentation](https://docs.kucoin.com/) - [Postman collection](https://www.postman.com/solar-capsule-443692/workspace/crypto-apis/request/581196-7af98792-9801-4f0f-9854-3b2957fe4021) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - KuCoin recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 539 ms, with median latency at 265 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - KuCoin domain: api\.kucoin\.com\. - Operational state: healthy\. - CASC score: 9\.23\. - Pass rate: 100\.00%\. - p95 latency: 539 ms\. - Developer documentation: https://docs\.kucoin\.com/\. - Postman collection: https://www\.postman\.com/solar\-capsule\-443692/workspace/crypto\-apis/request/581196\-7af98792\-9801\-4f0f\-9854\-3b2957fe4021\. ## Primary entities - APIContext - KuCoin - api\.kucoin\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/kucoin.json) - [Developer documentation](https://docs.kucoin.com/) --- # OKEx Operational Intelligence Canonical URL: https://apicontext.com/api-directory/exchanges/okex Source: static Updated: 2026-10-19T15:15:15.051Z Description: OKEx benchmark detail for www\.okx\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary OKEx is a api\-provider benchmark subject in Cryptocurrency Exchanges\. Latest snapshot metrics include 9\.20 CASC score, 99\.55% pass rate, 233 ms median latency, and 424 ms p95 latency\. ## Stats - 9\.20 CASC score - 99\.55% pass rate - 233 ms median latency - 424 ms p95 latency - stable operational state ## Page sections ### OKEx benchmark detail Category: Subject OKEx is measured as part of Cryptocurrency Exchanges\. This page summarizes operational signals for www\.okx\.com, including quality, reliability, latency, and infrastructure context\. - Domain: www\.okx\.com\. - Category: Cryptocurrency Exchanges\. - Benchmark subject type: api\-provider\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 34\.68 ms\. - TCP connection: 5\.86 ms\. - TLS handshake: 8\.82 ms\. - Processing: 209\.55 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/exchanges/okex.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - OKEx recorded 99\.55% pass rate in the latest verified snapshot\. - The p95 latency signal is 424 ms, with median latency at 233 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - OKEx domain: www\.okx\.com\. - Operational state: stable\. - CASC score: 9\.20\. - Pass rate: 99\.55%\. - p95 latency: 424 ms\. ## Primary entities - APIContext - OKEx - www\.okx\.com - Cryptocurrency Exchanges - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/exchanges/okex.json) --- # Fintech Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/fintech Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 12 benchmark subjects in Fintech, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 12 benchmark subjects in Fintech, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 12 benchmark subjects - 8\.96 average CASC - 479\.33 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Fintech benchmark slice Category: Category Latest verified snapshot covers 12 benchmark subjects in Fintech, with median latency signals and reliability measurements normalized for comparison\. - 12 subjects are normalized in this category\. - Benchmark subject type: banking\-api\. - Average pass rate: 99\.97%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Finicity — 8\.96 CASC, 99\.93% pass, 1,028 ms p95](/api-directory/fintech/finicity) - [Belvo — 8\.46 CASC, 99\.76% pass, 1,794 ms p95](/api-directory/fintech/belvo) - [Modern Treasury — 8\.90 CASC, 100\.00% pass, 1,321 ms p95](/api-directory/fintech/modern-treasury) - [Stripe — 9\.39 CASC, 100\.00% pass, 712 ms p95](/api-directory/fintech/stripe) - [Truelayer — 8\.75 CASC, 100\.00% pass, 1,590 ms p95](/api-directory/fintech/truelayer) - [Stripe \(Sandbox\) — 9\.38 CASC, 100\.00% pass, 589 ms p95](/api-directory/fintech/stripe-sandbox) - [Paypal \(Sandbox\) — 8\.86 CASC, 99\.95% pass, 1,467 ms p95](/api-directory/fintech/paypal-sandbox) - [Plaid — 9\.13 CASC, 100\.00% pass, 1,946 ms p95](/api-directory/fintech/plaid) - [Intuit — 9\.24 CASC, 100\.00% pass, 824 ms p95](/api-directory/fintech/intuit) - [Plaid \(Sandbox\) — 9\.10 CASC, 100\.00% pass, 2,208 ms p95](/api-directory/fintech/plaid-sandbox) - [Railsbank — 8\.70 CASC, 99\.98% pass, 3,007 ms p95](/api-directory/fintech/railsbank) - [Yapily — 8\.60 CASC, 100\.00% pass, 333 ms p95](/api-directory/fintech/yapily) ## Key facts - 12 benchmark subjects are included in Fintech\. - Average CASC score: 895\.58\. - Average median latency: 479\.33 ms\. - Benchmark subject type: banking\-api\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Fintech - Benchmark Intelligence - Operational Intelligence - banking\-api ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/fintech.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Belvo Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/belvo Source: static Updated: 2026-10-19T15:15:15.051Z Description: Belvo benchmark detail for sandbox\.belvo\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Belvo is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.46 CASC score, 99\.76% pass rate, 521 ms median latency, and 1,794 ms p95 latency\. ## Stats - 8\.46 CASC score - 99\.76% pass rate - 521 ms median latency - 1,794 ms p95 latency - recovering operational state ## Page sections ### Belvo benchmark detail Category: Subject Belvo is measured as part of Fintech\. This page summarizes operational signals for sandbox\.belvo\.com, including quality, reliability, latency, and infrastructure context\. - Domain: sandbox\.belvo\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 19\.59 ms\. - TCP connection: 3\.32 ms\. - TLS handshake: 12\.05 ms\. - Processing: 585\.45 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/belvo.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Belvo recorded 99\.76% pass rate in the latest verified snapshot\. - The p95 latency signal is 1794 ms, with median latency at 521 ms\. ## Key facts - Belvo domain: sandbox\.belvo\.com\. - Operational state: recovering\. - CASC score: 8\.46\. - Pass rate: 99\.76%\. - p95 latency: 1,794 ms\. ## Primary entities - APIContext - Belvo - sandbox\.belvo\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/belvo.json) --- # Finicity Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/finicity Source: static Updated: 2026-10-19T15:15:15.051Z Description: Finicity benchmark detail for api\.finicity\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Finicity is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.96 CASC score, 99\.93% pass rate, 295 ms median latency, and 1,028 ms p95 latency\. ## Stats - 8\.96 CASC score - 99\.93% pass rate - 295 ms median latency - 1,028 ms p95 latency - stable operational state ## Page sections ### Finicity benchmark detail Category: Subject Finicity is measured as part of Fintech\. This page summarizes operational signals for api\.finicity\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.finicity\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 23\.33 ms\. - TCP connection: 7\.33 ms\. - TLS handshake: 10\.33 ms\. - Processing: 271 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: imperva\_cdn\. - Hosting provider: Incapsula Inc\. - Nameserver: Incapsula Inc\. - Server: openresty\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/finicity.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Finicity recorded 99\.93% pass rate in the latest verified snapshot\. - The p95 latency signal is 1028 ms, with median latency at 295 ms\. - Infrastructure fingerprinting identifies Incapsula Inc in the observed delivery path\. ## Key facts - Finicity domain: api\.finicity\.com\. - Operational state: stable\. - CASC score: 8\.96\. - Pass rate: 99\.93%\. - p95 latency: 1,028 ms\. ## Primary entities - APIContext - Finicity - api\.finicity\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/finicity.json) --- # Intuit Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/intuit Source: static Updated: 2026-10-19T15:15:15.051Z Description: Intuit benchmark detail for creditkarma\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Intuit is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 9\.24 CASC score, 100\.00% pass rate, 462 ms median latency, and 824 ms p95 latency\. ## Stats - 9\.24 CASC score - 100\.00% pass rate - 462 ms median latency - 824 ms p95 latency - recovering operational state ## Page sections ### Intuit benchmark detail Category: Subject Intuit is measured as part of Fintech\. This page summarizes operational signals for creditkarma\.com, including quality, reliability, latency, and infrastructure context\. - Domain: creditkarma\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 2\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 13\.73 ms\. - TCP connection: 4\.41 ms\. - TLS handshake: 7\.14 ms\. - Processing: 471\.27 ms\. - Download: 15\.59 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: envoy\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/intuit.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Intuit recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 824 ms, with median latency at 462 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. ## Key facts - Intuit domain: creditkarma\.com\. - Operational state: recovering\. - CASC score: 9\.24\. - Pass rate: 100\.00%\. - p95 latency: 824 ms\. ## Primary entities - APIContext - Intuit - creditkarma\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/intuit.json) --- # Modern Treasury Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/modern-treasury Source: static Updated: 2026-10-19T15:15:15.051Z Description: Modern Treasury benchmark detail for app\.moderntreasury\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Modern Treasury is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.90 CASC score, 100\.00% pass rate, 740 ms median latency, and 1,321 ms p95 latency\. ## Stats - 8\.90 CASC score - 100\.00% pass rate - 740 ms median latency - 1,321 ms p95 latency - healthy operational state ## Page sections ### Modern Treasury benchmark detail Category: Subject Modern Treasury is measured as part of Fintech\. This page summarizes operational signals for app\.moderntreasury\.com, including quality, reliability, latency, and infrastructure context\. - Domain: app\.moderntreasury\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 24\.18 ms\. - TCP connection: 2\.73 ms\. - TLS handshake: 446\.09 ms\. - Processing: 314\.68 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/modern-treasury.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Modern Treasury recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1321 ms, with median latency at 740 ms\. ## Key facts - Modern Treasury domain: app\.moderntreasury\.com\. - Operational state: healthy\. - CASC score: 8\.90\. - Pass rate: 100\.00%\. - p95 latency: 1,321 ms\. ## Primary entities - APIContext - Modern Treasury - app\.moderntreasury\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/modern-treasury.json) --- # Paypal \(Sandbox\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/paypal-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Paypal \(Sandbox\) benchmark detail for api\.sandbox\.paypal\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Paypal \(Sandbox\) is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.86 CASC score, 99\.95% pass rate, 602 ms median latency, and 1,467 ms p95 latency\. ## Stats - 8\.86 CASC score - 99\.95% pass rate - 602 ms median latency - 1,467 ms p95 latency - healthy operational state ## Page sections ### Paypal \(Sandbox\) benchmark detail Category: Subject Paypal \(Sandbox\) is measured as part of Fintech\. This page summarizes operational signals for api\.sandbox\.paypal\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.sandbox\.paypal\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 19\.1 ms\. - TCP connection: 97\.33 ms\. - TLS handshake: 196\.1 ms\. - Processing: 367 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: PayPal, Inc\.\. - Nameserver: PayPal, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/paypal-sandbox.json) - [Developer documentation](https://developer.paypal.com/docs/api/overview/) - [OpenAPI specification](https://raw.githubusercontent.com/jayavaidy/PayPalFinalProject/master/Histcyclopedia.yaml) - [Postman collection](https://www.postman.com/api-evangelist/workspace/paypal/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Paypal \(Sandbox\) recorded 99\.95% pass rate in the latest verified snapshot\. - The p95 latency signal is 1467 ms, with median latency at 602 ms\. - Infrastructure fingerprinting identifies PayPal, Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Paypal \(Sandbox\) domain: api\.sandbox\.paypal\.com\. - Operational state: healthy\. - CASC score: 8\.86\. - Pass rate: 99\.95%\. - p95 latency: 1,467 ms\. - Developer documentation: https://developer\.paypal\.com/docs/api/overview/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/paypal/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/jayavaidy/PayPalFinalProject/master/Histcyclopedia\.yaml\. ## Primary entities - APIContext - Paypal \(Sandbox\) - api\.sandbox\.paypal\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/paypal-sandbox.json) - [Developer documentation](https://developer.paypal.com/docs/api/overview/) - [OpenAPI specification](https://raw.githubusercontent.com/jayavaidy/PayPalFinalProject/master/Histcyclopedia.yaml) --- # Plaid Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/plaid Source: static Updated: 2026-10-19T15:15:15.051Z Description: Plaid benchmark detail for sandbox\.plaid\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Plaid is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 9\.13 CASC score, 100\.00% pass rate, 815 ms median latency, and 1,946 ms p95 latency\. ## Stats - 9\.13 CASC score - 100\.00% pass rate - 815 ms median latency - 1,946 ms p95 latency - healthy operational state ## Page sections ### Plaid benchmark detail Category: Subject Plaid is measured as part of Fintech\. This page summarizes operational signals for sandbox\.plaid\.com, including quality, reliability, latency, and infrastructure context\. - Domain: sandbox\.plaid\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 87\.23 ms\. - TCP connection: 137\.59 ms\. - TLS handshake: 274\.18 ms\. - Processing: 337\.91 ms\. - Download: 35\.05 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/plaid.json) - [Developer documentation](https://plaid.com/docs/) - [OpenAPI specification](https://raw.githubusercontent.com/plaid/plaid-openapi/master/2020-09-14.yml) - [Postman collection](https://www.postman.com/api-evangelist/workspace/plaid/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Plaid recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1946 ms, with median latency at 815 ms\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Plaid domain: sandbox\.plaid\.com\. - Operational state: healthy\. - CASC score: 9\.13\. - Pass rate: 100\.00%\. - p95 latency: 1,946 ms\. - Developer documentation: https://plaid\.com/docs/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/plaid/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/plaid/plaid\-openapi/master/2020\-09\-14\.yml\. ## Primary entities - APIContext - Plaid - sandbox\.plaid\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/plaid.json) - [Developer documentation](https://plaid.com/docs/) - [OpenAPI specification](https://raw.githubusercontent.com/plaid/plaid-openapi/master/2020-09-14.yml) --- # Plaid \(Sandbox\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/plaid-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Plaid \(Sandbox\) benchmark detail for sandbox\.plaid\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Plaid \(Sandbox\) is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 9\.10 CASC score, 100\.00% pass rate, 1,016 ms median latency, and 2,208 ms p95 latency\. ## Stats - 9\.10 CASC score - 100\.00% pass rate - 1,016 ms median latency - 2,208 ms p95 latency - healthy operational state ## Page sections ### Plaid \(Sandbox\) benchmark detail Category: Subject Plaid \(Sandbox\) is measured as part of Fintech\. This page summarizes operational signals for sandbox\.plaid\.com, including quality, reliability, latency, and infrastructure context\. - Domain: sandbox\.plaid\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 78\.18 ms\. - TCP connection: 136\.77 ms\. - TLS handshake: 272\.95 ms\. - Processing: 332\.91 ms\. - Download: 145\.86 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/plaid-sandbox.json) - [Developer documentation](https://plaid.com/docs/) - [OpenAPI specification](https://raw.githubusercontent.com/plaid/plaid-openapi/master/2020-09-14.yml) - [Postman collection](https://www.postman.com/api-evangelist/workspace/plaid/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Plaid \(Sandbox\) recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 2208 ms, with median latency at 1016 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Plaid \(Sandbox\) domain: sandbox\.plaid\.com\. - Operational state: healthy\. - CASC score: 9\.10\. - Pass rate: 100\.00%\. - p95 latency: 2,208 ms\. - Developer documentation: https://plaid\.com/docs/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/plaid/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/plaid/plaid\-openapi/master/2020\-09\-14\.yml\. ## Primary entities - APIContext - Plaid \(Sandbox\) - sandbox\.plaid\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/plaid-sandbox.json) - [Developer documentation](https://plaid.com/docs/) - [OpenAPI specification](https://raw.githubusercontent.com/plaid/plaid-openapi/master/2020-09-14.yml) --- # Railsbank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/railsbank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Railsbank benchmark detail for play\.railsbank\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Railsbank is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.70 CASC score, 99\.98% pass rate, 151 ms median latency, and 3,007 ms p95 latency\. ## Stats - 8\.70 CASC score - 99\.98% pass rate - 151 ms median latency - 3,007 ms p95 latency - recovering operational state ## Page sections ### Railsbank benchmark detail Category: Subject Railsbank is measured as part of Fintech\. This page summarizes operational signals for play\.railsbank\.com, including quality, reliability, latency, and infrastructure context\. - Domain: play\.railsbank\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 16 ms\. - TCP connection: 13\.75 ms\. - TLS handshake: 28\.75 ms\. - Processing: 62\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/railsbank.json) - [Developer documentation](https://docs.railsbank.com/api/endusers) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Railsbank recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 3007 ms, with median latency at 151 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Railsbank domain: play\.railsbank\.com\. - Operational state: recovering\. - CASC score: 8\.70\. - Pass rate: 99\.98%\. - p95 latency: 3,007 ms\. - Developer documentation: https://docs\.railsbank\.com/api/endusers\. ## Primary entities - APIContext - Railsbank - play\.railsbank\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/railsbank.json) - [Developer documentation](https://docs.railsbank.com/api/endusers) --- # Stripe Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/stripe Source: static Updated: 2026-10-19T15:15:15.051Z Description: Stripe benchmark detail for api\.stripe\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Stripe is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 9\.39 CASC score, 100\.00% pass rate, 314 ms median latency, and 712 ms p95 latency\. ## Stats - 9\.39 CASC score - 100\.00% pass rate - 314 ms median latency - 712 ms p95 latency - healthy operational state ## Page sections ### Stripe benchmark detail Category: Subject Stripe is measured as part of Fintech\. This page summarizes operational signals for api\.stripe\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.stripe\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 26\.14 ms\. - TCP connection: 53\.64 ms\. - TLS handshake: 55\.55 ms\. - Processing: 270\.27 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/stripe.json) - [Developer documentation](https://stripe.com/docs/api) - [OpenAPI specification](https://github.com/stripe/openapi/tree/master/openapi) - [Postman collection](https://www.postman.com/stripedev/workspace/stripe-developers/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Stripe recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 712 ms, with median latency at 314 ms\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Stripe domain: api\.stripe\.com\. - Operational state: healthy\. - CASC score: 9\.39\. - Pass rate: 100\.00%\. - p95 latency: 712 ms\. - Developer documentation: https://stripe\.com/docs/api\. - Postman collection: https://www\.postman\.com/stripedev/workspace/stripe\-developers/overview\. - OpenAPI specification: https://github\.com/stripe/openapi/tree/master/openapi\. ## Primary entities - APIContext - Stripe - api\.stripe\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/stripe.json) - [Developer documentation](https://stripe.com/docs/api) - [OpenAPI specification](https://github.com/stripe/openapi/tree/master/openapi) --- # Stripe \(Sandbox\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/stripe-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Stripe \(Sandbox\) benchmark detail for api\.stripe\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Stripe \(Sandbox\) is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 9\.38 CASC score, 100\.00% pass rate, 263 ms median latency, and 589 ms p95 latency\. ## Stats - 9\.38 CASC score - 100\.00% pass rate - 263 ms median latency - 589 ms p95 latency - healthy operational state ## Page sections ### Stripe \(Sandbox\) benchmark detail Category: Subject Stripe \(Sandbox\) is measured as part of Fintech\. This page summarizes operational signals for api\.stripe\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.stripe\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10\.27 ms\. - TCP connection: 52\.82 ms\. - TLS handshake: 54\.86 ms\. - Processing: 230\.55 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/stripe-sandbox.json) - [Developer documentation](https://stripe.com/docs/api) - [OpenAPI specification](https://github.com/stripe/openapi/tree/master/openapi) - [Postman collection](https://www.postman.com/stripedev/workspace/stripe-developers/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Stripe \(Sandbox\) recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 589 ms, with median latency at 263 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Stripe \(Sandbox\) domain: api\.stripe\.com\. - Operational state: healthy\. - CASC score: 9\.38\. - Pass rate: 100\.00%\. - p95 latency: 589 ms\. - Developer documentation: https://stripe\.com/docs/api\. - Postman collection: https://www\.postman\.com/stripedev/workspace/stripe\-developers/overview\. - OpenAPI specification: https://github\.com/stripe/openapi/tree/master/openapi\. ## Primary entities - APIContext - Stripe \(Sandbox\) - api\.stripe\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/stripe-sandbox.json) - [Developer documentation](https://stripe.com/docs/api) - [OpenAPI specification](https://github.com/stripe/openapi/tree/master/openapi) --- # Truelayer Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/truelayer Source: static Updated: 2026-10-19T15:15:15.051Z Description: Truelayer benchmark detail for api\.truelayer\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Truelayer is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.75 CASC score, 100\.00% pass rate, 398 ms median latency, and 1,590 ms p95 latency\. ## Stats - 8\.75 CASC score - 100\.00% pass rate - 398 ms median latency - 1,590 ms p95 latency - healthy operational state ## Page sections ### Truelayer benchmark detail Category: Subject Truelayer is measured as part of Fintech\. This page summarizes operational signals for api\.truelayer\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.truelayer\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 31\.18 ms\. - TCP connection: 6\.05 ms\. - TLS handshake: 11\.09 ms\. - Processing: 521 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: cloudflare\_cdn\. - Hosting provider: Cloudflare, Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: cloudflare\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/truelayer.json) - [Developer documentation](https://truelayer.com/data-api/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Truelayer recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1590 ms, with median latency at 398 ms\. - Infrastructure fingerprinting identifies Cloudflare, Inc\. in the observed delivery path\. ## Key facts - Truelayer domain: api\.truelayer\.com\. - Operational state: healthy\. - CASC score: 8\.75\. - Pass rate: 100\.00%\. - p95 latency: 1,590 ms\. - Developer documentation: https://truelayer\.com/data\-api/\. ## Primary entities - APIContext - Truelayer - api\.truelayer\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/truelayer.json) - [Developer documentation](https://truelayer.com/data-api/) --- # Yapily Operational Intelligence Canonical URL: https://apicontext.com/api-directory/fintech/yapily Source: static Updated: 2026-10-19T15:15:15.051Z Description: Yapily benchmark detail for api\.yapily\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Yapily is a banking\-api benchmark subject in Fintech\. Latest snapshot metrics include 8\.60 CASC score, 100\.00% pass rate, 175 ms median latency, and 333 ms p95 latency\. ## Stats - 8\.60 CASC score - 100\.00% pass rate - 175 ms median latency - 333 ms p95 latency - recovering operational state ## Page sections ### Yapily benchmark detail Category: Subject Yapily is measured as part of Fintech\. This page summarizes operational signals for api\.yapily\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.yapily\.com\. - Category: Fintech\. - Benchmark subject type: banking\-api\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10\.5 ms\. - TCP connection: 3\.25 ms\. - TLS handshake: 16\.25 ms\. - Processing: 113\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/fintech/yapily.json) - [Developer documentation](https://docs.yapily.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Yapily recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 333 ms, with median latency at 175 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Yapily domain: api\.yapily\.com\. - Operational state: recovering\. - CASC score: 8\.60\. - Pass rate: 100\.00%\. - p95 latency: 333 ms\. - Developer documentation: https://docs\.yapily\.com/\. ## Primary entities - APIContext - Yapily - api\.yapily\.com - Fintech - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/fintech/yapily.json) - [Developer documentation](https://docs.yapily.com/) --- # IP Geolocation Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/ipgeolocators Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 3 benchmark subjects in IP Geolocation, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 3 benchmark subjects in IP Geolocation, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 3 benchmark subjects - 9\.14 average CASC - 107 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### IP Geolocation benchmark slice Category: Category Latest verified snapshot covers 3 benchmark subjects in IP Geolocation, with median latency signals and reliability measurements normalized for comparison\. - 3 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 100\.00%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [ipgeolocator — 9\.02 CASC, 100\.00% pass, 443 ms p95](/api-directory/ipgeolocators/ipgeolocator) - [ipwhois — 9\.14 CASC, 100\.00% pass, 264 ms p95](/api-directory/ipgeolocators/ipwhois) - [ipdata — 9\.25 CASC, 100\.00% pass, 386 ms p95](/api-directory/ipgeolocators/ipdata) ## Key facts - 3 benchmark subjects are included in IP Geolocation\. - Average CASC score: 913\.67\. - Average median latency: 107 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - IP Geolocation - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/ipgeolocators.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # ipdata Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ipgeolocators/ipdata Source: static Updated: 2026-10-19T15:15:15.051Z Description: ipdata benchmark detail for api\.ipdata\.co, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary ipdata is a api\-provider benchmark subject in IP Geolocation\. Latest snapshot metrics include 9\.25 CASC score, 100\.00% pass rate, 122 ms median latency, and 386 ms p95 latency\. ## Stats - 9\.25 CASC score - 100\.00% pass rate - 122 ms median latency - 386 ms p95 latency - healthy operational state ## Page sections ### ipdata benchmark detail Category: Subject ipdata is measured as part of IP Geolocation\. This page summarizes operational signals for api\.ipdata\.co, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ipdata\.co\. - Category: IP Geolocation\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 44\.43 ms\. - TCP connection: 15\.33 ms\. - TLS handshake: 17\.57 ms\. - Processing: 65\.29 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ipgeolocators/ipdata.json) - [Developer documentation](https://docs.ipdata.co/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - ipdata recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 386 ms, with median latency at 122 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - ipdata domain: api\.ipdata\.co\. - Operational state: healthy\. - CASC score: 9\.25\. - Pass rate: 100\.00%\. - p95 latency: 386 ms\. - Developer documentation: https://docs\.ipdata\.co/\. ## Primary entities - APIContext - ipdata - api\.ipdata\.co - IP Geolocation - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ipgeolocators/ipdata.json) - [Developer documentation](https://docs.ipdata.co/) --- # ipgeolocator Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ipgeolocators/ipgeolocator Source: static Updated: 2026-10-19T15:15:15.051Z Description: ipgeolocator benchmark detail for api\.ipgeolocation\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary ipgeolocator is a api\-provider benchmark subject in IP Geolocation\. Latest snapshot metrics include 9\.02 CASC score, 100\.00% pass rate, 130 ms median latency, and 443 ms p95 latency\. ## Stats - 9\.02 CASC score - 100\.00% pass rate - 130 ms median latency - 443 ms p95 latency - healthy operational state ## Page sections ### ipgeolocator benchmark detail Category: Subject ipgeolocator is measured as part of IP Geolocation\. This page summarizes operational signals for api\.ipgeolocation\.io, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ipgeolocation\.io\. - Category: IP Geolocation\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 51\.64 ms\. - TCP connection: 56\.55 ms\. - TLS handshake: 59\.82 ms\. - Processing: 56\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Cloudflare, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/ipgeolocators/ipgeolocator.json) - [Developer documentation](https://ipgeolocation.io/documentation.html) - [Postman collection](https://www.postman.com/bigdatacloud/workspace/bigdatacloud-api-s-public-workspace/collection/10684407-3369ce87-fd01-423c-a38f-335da4db520b?ctx=documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - ipgeolocator recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 443 ms, with median latency at 130 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - ipgeolocator domain: api\.ipgeolocation\.io\. - Operational state: healthy\. - CASC score: 9\.02\. - Pass rate: 100\.00%\. - p95 latency: 443 ms\. - Developer documentation: https://ipgeolocation\.io/documentation\.html\. - Postman collection: https://www\.postman\.com/bigdatacloud/workspace/bigdatacloud\-api\-s\-public\-workspace/collection/10684407\-3369ce87\-fd01\-423c\-a38f\-335da4db520b?ctx=documentation\. ## Primary entities - APIContext - ipgeolocator - api\.ipgeolocation\.io - IP Geolocation - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ipgeolocators/ipgeolocator.json) - [Developer documentation](https://ipgeolocation.io/documentation.html) --- # ipwhois Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ipgeolocators/ipwhois Source: static Updated: 2026-10-19T15:15:15.051Z Description: ipwhois benchmark detail for ipwhois\.app, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary ipwhois is a api\-provider benchmark subject in IP Geolocation\. Latest snapshot metrics include 9\.14 CASC score, 100\.00% pass rate, 69 ms median latency, and 264 ms p95 latency\. ## Stats - 9\.14 CASC score - 100\.00% pass rate - 69 ms median latency - 264 ms p95 latency - healthy operational state ## Page sections ### ipwhois benchmark detail Category: Subject ipwhois is measured as part of IP Geolocation\. This page summarizes operational signals for ipwhois\.app, including quality, reliability, latency, and infrastructure context\. - Domain: ipwhois\.app\. - Category: IP Geolocation\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 80\.23 ms\. - TCP connection: 3\.73 ms\. - TLS handshake: 0 ms\. - Processing: 19\.55 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: OVH US LLC\. - Nameserver: not available\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/ipgeolocators/ipwhois.json) - [Developer documentation](https://ipwhois.io/documentation) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - ipwhois recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 264 ms, with median latency at 69 ms\. - Infrastructure fingerprinting identifies OVH US LLC in the observed delivery path\. ## Key facts - ipwhois domain: ipwhois\.app\. - Operational state: healthy\. - CASC score: 9\.14\. - Pass rate: 100\.00%\. - p95 latency: 264 ms\. - Developer documentation: https://ipwhois\.io/documentation\. ## Primary entities - APIContext - ipwhois - ipwhois\.app - IP Geolocation - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ipgeolocators/ipwhois.json) - [Developer documentation](https://ipwhois.io/documentation) --- # New Zealand Government Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/mbienz Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 2 benchmark subjects in New Zealand Government, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 2 benchmark subjects in New Zealand Government, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 2 benchmark subjects - 8\.31 average CASC - 573 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### New Zealand Government benchmark slice Category: Category Latest verified snapshot covers 2 benchmark subjects in New Zealand Government, with median latency signals and reliability measurements normalized for comparison\. - 2 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.91%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [MBIE Sandbox — 8\.29 CASC, 99\.91% pass, 5,116 ms p95](/api-directory/mbienz/mbie-sandbox) - [MBIE Production — 8\.34 CASC, 99\.90% pass, 2,665 ms p95](/api-directory/mbienz/mbie-production) ## Key facts - 2 benchmark subjects are included in New Zealand Government\. - Average CASC score: 831\.5\. - Average median latency: 573 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - New Zealand Government - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/mbienz.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # MBIE Production Operational Intelligence Canonical URL: https://apicontext.com/api-directory/mbienz/mbie-production Source: static Updated: 2026-10-19T15:15:15.051Z Description: MBIE Production benchmark detail for api\.business\.govt\.nz, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary MBIE Production is a api\-provider benchmark subject in New Zealand Government\. Latest snapshot metrics include 8\.34 CASC score, 99\.90% pass rate, 492 ms median latency, and 2,665 ms p95 latency\. ## Stats - 8\.34 CASC score - 99\.90% pass rate - 492 ms median latency - 2,665 ms p95 latency - stable operational state ## Page sections ### MBIE Production benchmark detail Category: Subject MBIE Production is measured as part of New Zealand Government\. This page summarizes operational signals for api\.business\.govt\.nz, including quality, reliability, latency, and infrastructure context\. - Domain: api\.business\.govt\.nz\. - Category: New Zealand Government\. - Benchmark subject type: api\-provider\. - Monitored count: 11\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 20\.5 ms\. - TCP connection: 2\.5 ms\. - TLS handshake: 12\.5 ms\. - Processing: 408 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/mbienz/mbie-production.json) - [Developer documentation](https://api.business.govt.nz/api/welcome) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - MBIE Production recorded 99\.9% pass rate in the latest verified snapshot\. - The p95 latency signal is 2665 ms, with median latency at 492 ms\. ## Key facts - MBIE Production domain: api\.business\.govt\.nz\. - Operational state: stable\. - CASC score: 8\.34\. - Pass rate: 99\.90%\. - p95 latency: 2,665 ms\. - Developer documentation: https://api\.business\.govt\.nz/api/welcome\. ## Primary entities - APIContext - MBIE Production - api\.business\.govt\.nz - New Zealand Government - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/mbienz/mbie-production.json) - [Developer documentation](https://api.business.govt.nz/api/welcome) --- # MBIE Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/mbienz/mbie-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: MBIE Sandbox benchmark detail for api\.business\.govt\.nz, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary MBIE Sandbox is a api\-provider benchmark subject in New Zealand Government\. Latest snapshot metrics include 8\.29 CASC score, 99\.91% pass rate, 654 ms median latency, and 5,116 ms p95 latency\. ## Stats - 8\.29 CASC score - 99\.91% pass rate - 654 ms median latency - 5,116 ms p95 latency - stable operational state ## Page sections ### MBIE Sandbox benchmark detail Category: Subject MBIE Sandbox is measured as part of New Zealand Government\. This page summarizes operational signals for api\.business\.govt\.nz, including quality, reliability, latency, and infrastructure context\. - Domain: api\.business\.govt\.nz\. - Category: New Zealand Government\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 58\.75 ms\. - TCP connection: 2\.5 ms\. - TLS handshake: 14\.5 ms\. - Processing: 422\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/mbienz/mbie-sandbox.json) - [Developer documentation](https://api.business.govt.nz/api/welcome) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - MBIE Sandbox recorded 99\.91% pass rate in the latest verified snapshot\. - The p95 latency signal is 5116 ms, with median latency at 654 ms\. ## Key facts - MBIE Sandbox domain: api\.business\.govt\.nz\. - Operational state: stable\. - CASC score: 8\.29\. - Pass rate: 99\.91%\. - p95 latency: 5,116 ms\. - Developer documentation: https://api\.business\.govt\.nz/api/welcome\. ## Primary entities - APIContext - MBIE Sandbox - api\.business\.govt\.nz - New Zealand Government - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/mbienz/mbie-sandbox.json) - [Developer documentation](https://api.business.govt.nz/api/welcome) --- # Open Banking UK Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 7 benchmark subjects in Open Banking UK, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 7 benchmark subjects in Open Banking UK, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 7 benchmark subjects - 8\.21 average CASC - 789\.71 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Open Banking UK benchmark slice Category: Category Latest verified snapshot covers 7 benchmark subjects in Open Banking UK, with median latency signals and reliability measurements normalized for comparison\. - 7 subjects are normalized in this category\. - Benchmark subject type: banking\-api\. - Average pass rate: 99\.33%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Bank of Ireland Sandbox — 6\.25 CASC, 95\.7% pass, 2,630 ms p95](/api-directory/openbankinguk/bank-of-ireland-sandbox) - [Barclays Personal Sandbox — 7\.80 CASC, 99\.85% pass, 1,933 ms p95](/api-directory/openbankinguk/barclays-personal-sandbox) - [Allied Irish Bank Sandbox — 9\.26 CASC, 99\.89% pass, 520 ms p95](/api-directory/openbankinguk/allied-irish-bank-sandbox) - [RBS Sandbox — 9\.67 CASC, 100\.00% pass, 550 ms p95](/api-directory/openbankinguk/rbs-sandbox) - [Danske Sandbox — 6\.62 CASC, 99\.93% pass, 1,475 ms p95](/api-directory/openbankinguk/danske-sandbox) - [OBIE Sandbox — 9\.24 CASC, 99\.97% pass, 827 ms p95](/api-directory/openbankinguk/obie-sandbox) - [Monzo Bank Sandbox — 8\.66 CASC, 100\.00% pass, 533 ms p95](/api-directory/openbankinguk/monzo-bank-sandbox) ## Key facts - 7 benchmark subjects are included in Open Banking UK\. - Average CASC score: 821\.43\. - Average median latency: 789\.71 ms\. - Benchmark subject type: banking\-api\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Open Banking UK - Benchmark Intelligence - Operational Intelligence - banking\-api ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/openbankinguk.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Allied Irish Bank Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/allied-irish-bank-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Allied Irish Bank Sandbox benchmark detail for sandbox\.aibgb\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Allied Irish Bank Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 9\.26 CASC score, 99\.89% pass rate, 325 ms median latency, and 520 ms p95 latency\. ## Stats - 9\.26 CASC score - 99\.89% pass rate - 325 ms median latency - 520 ms p95 latency - recovering operational state ## Page sections ### Allied Irish Bank Sandbox benchmark detail Category: Subject Allied Irish Bank Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for sandbox\.aibgb\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: sandbox\.aibgb\.co\.uk\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 11\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 12 ms\. - TCP connection: 22\.5 ms\. - TLS handshake: 71\.25 ms\. - Processing: 201\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/allied-irish-bank-sandbox.json) - [Developer documentation](https://developer.aibgb.co.uk) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Allied Irish Bank Sandbox recorded 99\.89% pass rate in the latest verified snapshot\. - The p95 latency signal is 520 ms, with median latency at 325 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Allied Irish Bank Sandbox domain: sandbox\.aibgb\.co\.uk\. - Operational state: recovering\. - CASC score: 9\.26\. - Pass rate: 99\.89%\. - p95 latency: 520 ms\. - Developer documentation: https://developer\.aibgb\.co\.uk\. ## Primary entities - APIContext - Allied Irish Bank Sandbox - sandbox\.aibgb\.co\.uk - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/allied-irish-bank-sandbox.json) - [Developer documentation](https://developer.aibgb.co.uk) --- # Bank of Ireland Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/bank-of-ireland-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bank of Ireland Sandbox benchmark detail for api\-sandbox\.bankofireland\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bank of Ireland Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 6\.25 CASC score, 95\.7% pass rate, 2,390 ms median latency, and 2,630 ms p95 latency\. ## Stats - 6\.25 CASC score - 95\.7% pass rate - 2,390 ms median latency - 2,630 ms p95 latency - degraded operational state ## Page sections ### Bank of Ireland Sandbox benchmark detail Category: Subject Bank of Ireland Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for api\-sandbox\.bankofireland\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\-sandbox\.bankofireland\.com\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 48\.25 ms\. - TCP connection: 22\.5 ms\. - TLS handshake: 2,058\.5 ms\. - Processing: 256\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: NeuStar, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/bank-of-ireland-sandbox.json) - [Developer documentation](https://developer.bankofireland.com) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bank of Ireland Sandbox recorded 95\.68% pass rate in the latest verified snapshot\. - The p95 latency signal is 2630 ms, with median latency at 2390 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Bank of Ireland Sandbox domain: api\-sandbox\.bankofireland\.com\. - Operational state: degraded\. - CASC score: 6\.25\. - Pass rate: 95\.7%\. - p95 latency: 2,630 ms\. - Developer documentation: https://developer\.bankofireland\.com\. ## Primary entities - APIContext - Bank of Ireland Sandbox - api\-sandbox\.bankofireland\.com - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/bank-of-ireland-sandbox.json) - [Developer documentation](https://developer.bankofireland.com) --- # Barclays Personal Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/barclays-personal-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays Personal Sandbox benchmark detail for token\.sandbox\.barclays\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays Personal Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 7\.80 CASC score, 99\.85% pass rate, 936 ms median latency, and 1,933 ms p95 latency\. ## Stats - 7\.80 CASC score - 99\.85% pass rate - 936 ms median latency - 1,933 ms p95 latency - recovering operational state ## Page sections ### Barclays Personal Sandbox benchmark detail Category: Subject Barclays Personal Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for token\.sandbox\.barclays\.com, including quality, reliability, latency, and infrastructure context\. - Domain: token\.sandbox\.barclays\.com\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 76\.25 ms\. - TCP connection: 2\.75 ms\. - TLS handshake: 455\.5 ms\. - Processing: 354\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/barclays-personal-sandbox.json) - [Developer documentation](https://developer.barclays.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays Personal Sandbox recorded 99\.85% pass rate in the latest verified snapshot\. - The p95 latency signal is 1933 ms, with median latency at 936 ms\. ## Key facts - Barclays Personal Sandbox domain: token\.sandbox\.barclays\.com\. - Operational state: recovering\. - CASC score: 7\.80\. - Pass rate: 99\.85%\. - p95 latency: 1,933 ms\. - Developer documentation: https://developer\.barclays\.com/\. ## Primary entities - APIContext - Barclays Personal Sandbox - token\.sandbox\.barclays\.com - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/barclays-personal-sandbox.json) - [Developer documentation](https://developer.barclays.com/) --- # Danske Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/danske-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Danske Sandbox benchmark detail for sandbox\-obp\-api\.danskebank\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Danske Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 6\.62 CASC score, 99\.93% pass rate, 904 ms median latency, and 1,475 ms p95 latency\. ## Stats - 6\.62 CASC score - 99\.93% pass rate - 904 ms median latency - 1,475 ms p95 latency - stable operational state ## Page sections ### Danske Sandbox benchmark detail Category: Subject Danske Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for sandbox\-obp\-api\.danskebank\.com, including quality, reliability, latency, and infrastructure context\. - Domain: sandbox\-obp\-api\.danskebank\.com\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 2\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10\.75 ms\. - TCP connection: 29\.5 ms\. - TLS handshake: 33\.75 ms\. - Processing: 814\.25 ms\. - Download: 1 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: NeuStar, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/danske-sandbox.json) - [Developer documentation](https://developers.danskebank.com/api_products/danske_bank_apis) - [OpenAPI specification](https://developers.danskebank.com/api_products/danske_bank_apis/od?view=reference) - [Postman collection](https://www.postman.com/api-evangelist/workspace/uk-public-banking/environment/35240-337c6ef5-76c9-4d52-ad7b-041075dc4de5) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Danske Sandbox recorded 99\.93% pass rate in the latest verified snapshot\. - The p95 latency signal is 1475 ms, with median latency at 904 ms\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Danske Sandbox domain: sandbox\-obp\-api\.danskebank\.com\. - Operational state: stable\. - CASC score: 6\.62\. - Pass rate: 99\.93%\. - p95 latency: 1,475 ms\. - Developer documentation: https://developers\.danskebank\.com/api\_products/danske\_bank\_apis\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/uk\-public\-banking/environment/35240\-337c6ef5\-76c9\-4d52\-ad7b\-041075dc4de5\. - OpenAPI specification: https://developers\.danskebank\.com/api\_products/danske\_bank\_apis/od?view=reference\. ## Primary entities - APIContext - Danske Sandbox - sandbox\-obp\-api\.danskebank\.com - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/danske-sandbox.json) - [Developer documentation](https://developers.danskebank.com/api_products/danske_bank_apis) - [OpenAPI specification](https://developers.danskebank.com/api_products/danske_bank_apis/od?view=reference) --- # Monzo Bank Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/monzo-bank-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Monzo Bank Sandbox benchmark detail for openbanking\.s101\.nonprod\-ffs\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Monzo Bank Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 8\.66 CASC score, 100\.00% pass rate, 297 ms median latency, and 533 ms p95 latency\. ## Stats - 8\.66 CASC score - 100\.00% pass rate - 297 ms median latency - 533 ms p95 latency - healthy operational state ## Page sections ### Monzo Bank Sandbox benchmark detail Category: Subject Monzo Bank Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for openbanking\.s101\.nonprod\-ffs\.io, including quality, reliability, latency, and infrastructure context\. - Domain: openbanking\.s101\.nonprod\-ffs\.io\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 11\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 8\.75 ms\. - TCP connection: 25\.5 ms\. - TLS handshake: 29\.25 ms\. - Processing: 220 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/monzo-bank-sandbox.json) - [Developer documentation](https://monzo.com/docs) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Monzo Bank Sandbox recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 533 ms, with median latency at 297 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. ## Key facts - Monzo Bank Sandbox domain: openbanking\.s101\.nonprod\-ffs\.io\. - Operational state: healthy\. - CASC score: 8\.66\. - Pass rate: 100\.00%\. - p95 latency: 533 ms\. - Developer documentation: https://monzo\.com/docs\. ## Primary entities - APIContext - Monzo Bank Sandbox - openbanking\.s101\.nonprod\-ffs\.io - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/monzo-bank-sandbox.json) - [Developer documentation](https://monzo.com/docs) --- # OBIE Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/obie-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: OBIE Sandbox benchmark detail for matls\-sso\.openbankingtest\.org\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary OBIE Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 9\.24 CASC score, 99\.97% pass rate, 509 ms median latency, and 827 ms p95 latency\. ## Stats - 9\.24 CASC score - 99\.97% pass rate - 509 ms median latency - 827 ms p95 latency - healthy operational state ## Page sections ### OBIE Sandbox benchmark detail Category: Subject OBIE Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for matls\-sso\.openbankingtest\.org\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: matls\-sso\.openbankingtest\.org\.uk\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 5\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 20\.75 ms\. - TCP connection: 26\.5 ms\. - TLS handshake: 56\.5 ms\. - Processing: 393\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: hidden\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/obie-sandbox.json) - [Developer documentation](https://standards.openbanking.org.uk/api-specifications/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - OBIE Sandbox recorded 99\.97% pass rate in the latest verified snapshot\. - The p95 latency signal is 827 ms, with median latency at 509 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - OBIE Sandbox domain: matls\-sso\.openbankingtest\.org\.uk\. - Operational state: healthy\. - CASC score: 9\.24\. - Pass rate: 99\.97%\. - p95 latency: 827 ms\. - Developer documentation: https://standards\.openbanking\.org\.uk/api\-specifications/\. ## Primary entities - APIContext - OBIE Sandbox - matls\-sso\.openbankingtest\.org\.uk - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/obie-sandbox.json) - [Developer documentation](https://standards.openbanking.org.uk/api-specifications/) --- # RBS Sandbox Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankinguk/rbs-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: RBS Sandbox benchmark detail for ob\.rbs\.useinfinite\.io, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary RBS Sandbox is a banking\-api benchmark subject in Open Banking UK\. Latest snapshot metrics include 9\.67 CASC score, 100\.00% pass rate, 167 ms median latency, and 550 ms p95 latency\. ## Stats - 9\.67 CASC score - 100\.00% pass rate - 167 ms median latency - 550 ms p95 latency - healthy operational state ## Page sections ### RBS Sandbox benchmark detail Category: Subject RBS Sandbox is measured as part of Open Banking UK\. This page summarizes operational signals for ob\.rbs\.useinfinite\.io, including quality, reliability, latency, and infrastructure context\. - Domain: ob\.rbs\.useinfinite\.io\. - Category: Open Banking UK\. - Benchmark subject type: banking\-api\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 81\.75 ms\. - TCP connection: 24\.5 ms\. - TLS handshake: 58\.25 ms\. - Processing: 43\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/rbs-sandbox.json) - [Developer documentation](https://www.bankofapis.com) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - RBS Sandbox recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 550 ms, with median latency at 167 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - RBS Sandbox domain: ob\.rbs\.useinfinite\.io\. - Operational state: healthy\. - CASC score: 9\.67\. - Pass rate: 100\.00%\. - p95 latency: 550 ms\. - Developer documentation: https://www\.bankofapis\.com\. ## Primary entities - APIContext - RBS Sandbox - ob\.rbs\.useinfinite\.io - Open Banking UK - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankinguk/rbs-sandbox.json) - [Developer documentation](https://www.bankofapis.com) --- # Open Banking UK Production Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 19 benchmark subjects in Open Banking UK Production, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 19 benchmark subjects in Open Banking UK Production, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 19 benchmark subjects - 8\.95 average CASC - 304\.79 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Open Banking UK Production benchmark slice Category: Category Latest verified snapshot covers 19 benchmark subjects in Open Banking UK Production, with median latency signals and reliability measurements normalized for comparison\. - 19 subjects are normalized in this category\. - Benchmark subject type: banking\-api\. - Average pass rate: 99\.86%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Cater Allen Private Bank — 9\.43 CASC, 100\.00% pass, 624 ms p95](/api-directory/openbankingukproduction/cater-allen-private-bank) - [Zempler Bank — 9\.47 CASC, 99\.96% pass, 669 ms p95](/api-directory/openbankingukproduction/zempler-bank) - [Monzo Bank — 8\.96 CASC, 99\.99% pass, 424 ms p95](/api-directory/openbankingukproduction/monzo-bank) - [Bank of Ireland \(UK\) Plc — 8\.62 CASC, 99\.22% pass, 428 ms p95](/api-directory/openbankingukproduction/bank-of-ireland-uk-plc) - [Vanquis Bank — 8\.10 CASC, 99\.55% pass, 1,992 ms p95](/api-directory/openbankingukproduction/vanquis-bank) - [Capital One — 8\.35 CASC, 99\.11% pass, 1,144 ms p95](/api-directory/openbankingukproduction/capital-one) - [Barclays Personal — 8\.80 CASC, 99\.89% pass, 664 ms p95](/api-directory/openbankingukproduction/barclays-personal) - [TSB — 8\.97 CASC, 99\.93% pass, 550 ms p95](/api-directory/openbankingukproduction/tsb) - [Virgin Money — 9\.44 CASC, 100\.00% pass, 681 ms p95](/api-directory/openbankingukproduction/virgin-money) - [OBIE Directory — 9\.17 CASC, 99\.99% pass, 1,989 ms p95](/api-directory/openbankingukproduction/obie-directory) - [Tide Platform Ltd — 9\.32 CASC, 100\.00% pass, 311 ms p95](/api-directory/openbankingukproduction/tide-platform-ltd) - [HSBC Bank \(Personal\) — 8\.88 CASC, 99\.95% pass, 778 ms p95](/api-directory/openbankingukproduction/hsbc-bank-personal) - [NewDay \- Amazon Mastercard — 9\.29 CASC, 100\.00% pass, 488 ms p95](/api-directory/openbankingukproduction/newday-amazon-mastercard) - [Cumberland Building Society — 8\.15 CASC, 99\.95% pass, 1,332 ms p95](/api-directory/openbankingukproduction/cumberland-building-society) - [HSBC Bank \(Business\) — 8\.90 CASC, 99\.98% pass, 784 ms p95](/api-directory/openbankingukproduction/hsbc-bank-business) - [Barclays Business — 8\.90 CASC, 99\.81% pass, 630 ms p95](/api-directory/openbankingukproduction/barclays-business) - [NewDay \- Aqua — 9\.21 CASC, 100\.00% pass, 518 ms p95](/api-directory/openbankingukproduction/newday-aqua) - [Starling Bank — 9\.18 CASC, 100\.00% pass, 248 ms p95](/api-directory/openbankingukproduction/starling-bank) - [Revolut — 8\.84 CASC, 100\.00% pass, 200 ms p95](/api-directory/openbankingukproduction/revolut) ## Key facts - 19 benchmark subjects are included in Open Banking UK Production\. - Average CASC score: 894\.63\. - Average median latency: 304\.79 ms\. - Benchmark subject type: banking\-api\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Open Banking UK Production - Benchmark Intelligence - Operational Intelligence - banking\-api ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/openbankingukproduction.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Bank of Ireland \(UK\) Plc Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/bank-of-ireland-uk-plc Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bank of Ireland \(UK\) Plc benchmark detail for api\.obapi\.bankofireland\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bank of Ireland \(UK\) Plc is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.62 CASC score, 99\.22% pass rate, 294 ms median latency, and 428 ms p95 latency\. ## Stats - 8\.62 CASC score - 99\.22% pass rate - 294 ms median latency - 428 ms p95 latency - degraded operational state ## Page sections ### Bank of Ireland \(UK\) Plc benchmark detail Category: Subject Bank of Ireland \(UK\) Plc is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\.obapi\.bankofireland\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.obapi\.bankofireland\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 12\.5 ms\. - TCP connection: 21\.75 ms\. - TLS handshake: 57 ms\. - Processing: 200\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/bank-of-ireland-uk-plc.json) - [Developer documentation](https://developer.bankofireland.com) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bank of Ireland \(UK\) Plc recorded 99\.22% pass rate in the latest verified snapshot\. - The p95 latency signal is 428 ms, with median latency at 294 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Bank of Ireland \(UK\) Plc domain: api\.obapi\.bankofireland\.com\. - Operational state: degraded\. - CASC score: 8\.62\. - Pass rate: 99\.22%\. - p95 latency: 428 ms\. - Developer documentation: https://developer\.bankofireland\.com\. ## Primary entities - APIContext - Bank of Ireland \(UK\) Plc - api\.obapi\.bankofireland\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/bank-of-ireland-uk-plc.json) - [Developer documentation](https://developer.bankofireland.com) --- # Barclays Business Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/barclays-business Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays Business benchmark detail for telesto\.api\.barclays, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays Business is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.90 CASC score, 99\.81% pass rate, 264 ms median latency, and 630 ms p95 latency\. ## Stats - 8\.90 CASC score - 99\.81% pass rate - 264 ms median latency - 630 ms p95 latency - stable operational state ## Page sections ### Barclays Business benchmark detail Category: Subject Barclays Business is measured as part of Open Banking UK Production\. This page summarizes operational signals for telesto\.api\.barclays, including quality, reliability, latency, and infrastructure context\. - Domain: telesto\.api\.barclays\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 39\.5 ms\. - TCP connection: 19\.5 ms\. - TLS handshake: 63\.25 ms\. - Processing: 124\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Barclays Bank Plc\.\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/barclays-business.json) - [Developer documentation](https://developer.barclays.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays Business recorded 99\.81% pass rate in the latest verified snapshot\. - The p95 latency signal is 630 ms, with median latency at 264 ms\. - Infrastructure fingerprinting identifies Barclays Bank Plc\. in the observed delivery path\. ## Key facts - Barclays Business domain: telesto\.api\.barclays\. - Operational state: stable\. - CASC score: 8\.90\. - Pass rate: 99\.81%\. - p95 latency: 630 ms\. - Developer documentation: https://developer\.barclays\.com/\. ## Primary entities - APIContext - Barclays Business - telesto\.api\.barclays - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/barclays-business.json) - [Developer documentation](https://developer.barclays.com/) --- # Barclays Personal Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/barclays-personal Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays Personal benchmark detail for telesto\.api\.barclays, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays Personal is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.80 CASC score, 99\.89% pass rate, 263 ms median latency, and 664 ms p95 latency\. ## Stats - 8\.80 CASC score - 99\.89% pass rate - 263 ms median latency - 664 ms p95 latency - stable operational state ## Page sections ### Barclays Personal benchmark detail Category: Subject Barclays Personal is measured as part of Open Banking UK Production\. This page summarizes operational signals for telesto\.api\.barclays, including quality, reliability, latency, and infrastructure context\. - Domain: telesto\.api\.barclays\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 41\.25 ms\. - TCP connection: 21\.5 ms\. - TLS handshake: 65\.25 ms\. - Processing: 124\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: Google Frontend\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/barclays-personal.json) - [Developer documentation](https://developer.barclays.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays Personal recorded 99\.89% pass rate in the latest verified snapshot\. - The p95 latency signal is 664 ms, with median latency at 263 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Barclays Personal domain: telesto\.api\.barclays\. - Operational state: stable\. - CASC score: 8\.80\. - Pass rate: 99\.89%\. - p95 latency: 664 ms\. - Developer documentation: https://developer\.barclays\.com/\. ## Primary entities - APIContext - Barclays Personal - telesto\.api\.barclays - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/barclays-personal.json) - [Developer documentation](https://developer.barclays.com/) --- # Capital One Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/capital-one Source: static Updated: 2026-10-19T15:15:15.051Z Description: Capital One benchmark detail for open\-banking\.capitalone\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Capital One is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.35 CASC score, 99\.11% pass rate, 270 ms median latency, and 1,144 ms p95 latency\. ## Stats - 8\.35 CASC score - 99\.11% pass rate - 270 ms median latency - 1,144 ms p95 latency - degraded operational state ## Page sections ### Capital One benchmark detail Category: Subject Capital One is measured as part of Open Banking UK Production\. This page summarizes operational signals for open\-banking\.capitalone\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: open\-banking\.capitalone\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 9 ms\. - TCP connection: 2\.25 ms\. - TLS handshake: 25\.75 ms\. - Processing: 184\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Akamai Technologies, Inc\.\. - Nameserver: Akamai Technologies, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/capital-one.json) - [Developer documentation](https://developer.capitalone.co.uk/api) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Capital One recorded 99\.11% pass rate in the latest verified snapshot\. - The p95 latency signal is 1144 ms, with median latency at 270 ms\. - Infrastructure fingerprinting identifies Akamai Technologies, Inc\. in the observed delivery path\. ## Key facts - Capital One domain: open\-banking\.capitalone\.co\.uk\. - Operational state: degraded\. - CASC score: 8\.35\. - Pass rate: 99\.11%\. - p95 latency: 1,144 ms\. - Developer documentation: https://developer\.capitalone\.co\.uk/api\. ## Primary entities - APIContext - Capital One - open\-banking\.capitalone\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/capital-one.json) - [Developer documentation](https://developer.capitalone.co.uk/api) --- # Cater Allen Private Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/cater-allen-private-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Cater Allen Private Bank benchmark detail for developer\.caterallen\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Cater Allen Private Bank is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.43 CASC score, 100\.00% pass rate, 301 ms median latency, and 624 ms p95 latency\. ## Stats - 9\.43 CASC score - 100\.00% pass rate - 301 ms median latency - 624 ms p95 latency - healthy operational state ## Page sections ### Cater Allen Private Bank benchmark detail Category: Subject Cater Allen Private Bank is measured as part of Open Banking UK Production\. This page summarizes operational signals for developer\.caterallen\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: developer\.caterallen\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 34 ms\. - TCP connection: 18\.75 ms\. - TLS handshake: 50\.75 ms\. - Processing: 174\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: Apache\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/cater-allen-private-bank.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Cater Allen Private Bank recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 624 ms, with median latency at 301 ms\. ## Key facts - Cater Allen Private Bank domain: developer\.caterallen\.co\.uk\. - Operational state: healthy\. - CASC score: 9\.43\. - Pass rate: 100\.00%\. - p95 latency: 624 ms\. ## Primary entities - APIContext - Cater Allen Private Bank - developer\.caterallen\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/cater-allen-private-bank.json) --- # Cumberland Building Society Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/cumberland-building-society Source: static Updated: 2026-10-19T15:15:15.051Z Description: Cumberland Building Society benchmark detail for tppopenbanking\.cumberland\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Cumberland Building Society is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.15 CASC score, 99\.95% pass rate, 628 ms median latency, and 1,332 ms p95 latency\. ## Stats - 8\.15 CASC score - 99\.95% pass rate - 628 ms median latency - 1,332 ms p95 latency - stable operational state ## Page sections ### Cumberland Building Society benchmark detail Category: Subject Cumberland Building Society is measured as part of Open Banking UK Production\. This page summarizes operational signals for tppopenbanking\.cumberland\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: tppopenbanking\.cumberland\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 3\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 27\.5 ms\. - TCP connection: 4\.25 ms\. - TLS handshake: 121\.25 ms\. - Processing: 418\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Incapsula Inc\. - Nameserver: Incapsula Inc\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/cumberland-building-society.json) - [Developer documentation](https://www.cumberland.co.uk/developers/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Cumberland Building Society recorded 99\.95% pass rate in the latest verified snapshot\. - The p95 latency signal is 1332 ms, with median latency at 628 ms\. - Infrastructure fingerprinting identifies Incapsula Inc in the observed delivery path\. ## Key facts - Cumberland Building Society domain: tppopenbanking\.cumberland\.co\.uk\. - Operational state: stable\. - CASC score: 8\.15\. - Pass rate: 99\.95%\. - p95 latency: 1,332 ms\. - Developer documentation: https://www\.cumberland\.co\.uk/developers/\. ## Primary entities - APIContext - Cumberland Building Society - tppopenbanking\.cumberland\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/cumberland-building-society.json) - [Developer documentation](https://www.cumberland.co.uk/developers/) --- # HSBC Bank \(Business\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/hsbc-bank-business Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC Bank \(Business\) benchmark detail for api\.ob\.business\.hsbc\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC Bank \(Business\) is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.90 CASC score, 99\.98% pass rate, 435 ms median latency, and 784 ms p95 latency\. ## Stats - 8\.90 CASC score - 99\.98% pass rate - 435 ms median latency - 784 ms p95 latency - healthy operational state ## Page sections ### HSBC Bank \(Business\) benchmark detail Category: Subject HSBC Bank \(Business\) is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\.ob\.business\.hsbc\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ob\.business\.hsbc\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 32\.75 ms\. - TCP connection: 3\.25 ms\. - TLS handshake: 15\.25 ms\. - Processing: 366\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/hsbc-bank-business.json) - [Developer documentation](https://develop.hsbc.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC Bank \(Business\) recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 784 ms, with median latency at 435 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - HSBC Bank \(Business\) domain: api\.ob\.business\.hsbc\.co\.uk\. - Operational state: healthy\. - CASC score: 8\.90\. - Pass rate: 99\.98%\. - p95 latency: 784 ms\. - Developer documentation: https://develop\.hsbc\.com/\. ## Primary entities - APIContext - HSBC Bank \(Business\) - api\.ob\.business\.hsbc\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/hsbc-bank-business.json) - [Developer documentation](https://develop.hsbc.com/) --- # HSBC Bank \(Personal\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/hsbc-bank-personal Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC Bank \(Personal\) benchmark detail for api\.ob\.hsbc\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC Bank \(Personal\) is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.88 CASC score, 99\.95% pass rate, 398 ms median latency, and 778 ms p95 latency\. ## Stats - 8\.88 CASC score - 99\.95% pass rate - 398 ms median latency - 778 ms p95 latency - healthy operational state ## Page sections ### HSBC Bank \(Personal\) benchmark detail Category: Subject HSBC Bank \(Personal\) is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\.ob\.hsbc\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ob\.hsbc\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 9\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 31 ms\. - TCP connection: 4 ms\. - TLS handshake: 14\.25 ms\. - Processing: 327\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/hsbc-bank-personal.json) - [Developer documentation](https://develop.hsbc.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC Bank \(Personal\) recorded 99\.95% pass rate in the latest verified snapshot\. - The p95 latency signal is 778 ms, with median latency at 398 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - HSBC Bank \(Personal\) domain: api\.ob\.hsbc\.co\.uk\. - Operational state: healthy\. - CASC score: 8\.88\. - Pass rate: 99\.95%\. - p95 latency: 778 ms\. - Developer documentation: https://develop\.hsbc\.com/\. ## Primary entities - APIContext - HSBC Bank \(Personal\) - api\.ob\.hsbc\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/hsbc-bank-personal.json) - [Developer documentation](https://develop.hsbc.com/) --- # Monzo Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/monzo-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Monzo Bank benchmark detail for openbanking\.monzo\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Monzo Bank is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.96 CASC score, 99\.99% pass rate, 244 ms median latency, and 424 ms p95 latency\. ## Stats - 8\.96 CASC score - 99\.99% pass rate - 244 ms median latency - 424 ms p95 latency - recovering operational state ## Page sections ### Monzo Bank benchmark detail Category: Subject Monzo Bank is measured as part of Open Banking UK Production\. This page summarizes operational signals for openbanking\.monzo\.com, including quality, reliability, latency, and infrastructure context\. - Domain: openbanking\.monzo\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 11\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 13\.5 ms\. - TCP connection: 24\.25 ms\. - TLS handshake: 28\.25 ms\. - Processing: 172 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/monzo-bank.json) - [Developer documentation](https://monzo.com/docs) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Monzo Bank recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 424 ms, with median latency at 244 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Monzo Bank domain: openbanking\.monzo\.com\. - Operational state: recovering\. - CASC score: 8\.96\. - Pass rate: 99\.99%\. - p95 latency: 424 ms\. - Developer documentation: https://monzo\.com/docs\. ## Primary entities - APIContext - Monzo Bank - openbanking\.monzo\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/monzo-bank.json) - [Developer documentation](https://monzo.com/docs) --- # NewDay \- Amazon Mastercard Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/newday-amazon-mastercard Source: static Updated: 2026-10-19T15:15:15.051Z Description: NewDay \- Amazon Mastercard benchmark detail for api\.newdaycards\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary NewDay \- Amazon Mastercard is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.29 CASC score, 100\.00% pass rate, 216 ms median latency, and 488 ms p95 latency\. ## Stats - 9\.29 CASC score - 100\.00% pass rate - 216 ms median latency - 488 ms p95 latency - healthy operational state ## Page sections ### NewDay \- Amazon Mastercard benchmark detail Category: Subject NewDay \- Amazon Mastercard is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\.newdaycards\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.newdaycards\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 33\.5 ms\. - TCP connection: 14 ms\. - TLS handshake: 35\.25 ms\. - Processing: 114 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Microsoft Corporation\. - Nameserver: Microsoft Corporation\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/newday-amazon-mastercard.json) - [Developer documentation](https://developer.newdaycards.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - NewDay \- Amazon Mastercard recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 488 ms, with median latency at 216 ms\. - Infrastructure fingerprinting identifies Microsoft Corporation in the observed delivery path\. ## Key facts - NewDay \- Amazon Mastercard domain: api\.newdaycards\.com\. - Operational state: healthy\. - CASC score: 9\.29\. - Pass rate: 100\.00%\. - p95 latency: 488 ms\. - Developer documentation: https://developer\.newdaycards\.com/\. ## Primary entities - APIContext - NewDay \- Amazon Mastercard - api\.newdaycards\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/newday-amazon-mastercard.json) - [Developer documentation](https://developer.newdaycards.com/) --- # NewDay \- Aqua Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/newday-aqua Source: static Updated: 2026-10-19T15:15:15.051Z Description: NewDay \- Aqua benchmark detail for api\.newdaycards\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary NewDay \- Aqua is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.21 CASC score, 100\.00% pass rate, 224 ms median latency, and 518 ms p95 latency\. ## Stats - 9\.21 CASC score - 100\.00% pass rate - 224 ms median latency - 518 ms p95 latency - healthy operational state ## Page sections ### NewDay \- Aqua benchmark detail Category: Subject NewDay \- Aqua is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\.newdaycards\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.newdaycards\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 34\.25 ms\. - TCP connection: 16\.5 ms\. - TLS handshake: 39\.75 ms\. - Processing: 111\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Microsoft Corporation\. - Nameserver: Microsoft Corporation\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/newday-aqua.json) - [Developer documentation](https://developer.newdaycards.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - NewDay \- Aqua recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 518 ms, with median latency at 224 ms\. - Infrastructure fingerprinting identifies Microsoft Corporation in the observed delivery path\. ## Key facts - NewDay \- Aqua domain: api\.newdaycards\.com\. - Operational state: healthy\. - CASC score: 9\.21\. - Pass rate: 100\.00%\. - p95 latency: 518 ms\. - Developer documentation: https://developer\.newdaycards\.com/\. ## Primary entities - APIContext - NewDay \- Aqua - api\.newdaycards\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/newday-aqua.json) - [Developer documentation](https://developer.newdaycards.com/) --- # OBIE Directory Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/obie-directory Source: static Updated: 2026-10-19T15:15:15.051Z Description: OBIE Directory benchmark detail for matls\-api\.openbanking\.org\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary OBIE Directory is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.17 CASC score, 99\.99% pass rate, 552 ms median latency, and 1,989 ms p95 latency\. ## Stats - 9\.17 CASC score - 99\.99% pass rate - 552 ms median latency - 1,989 ms p95 latency - healthy operational state ## Page sections ### OBIE Directory benchmark detail Category: Subject OBIE Directory is measured as part of Open Banking UK Production\. This page summarizes operational signals for matls\-api\.openbanking\.org\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: matls\-api\.openbanking\.org\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 18\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 12 ms\. - TCP connection: 21\.5 ms\. - TLS handshake: 46\.75 ms\. - Processing: 443\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: hidden\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/obie-directory.json) - [Developer documentation](https://standards.openbanking.org.uk/api-specifications/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - OBIE Directory recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 1989 ms, with median latency at 552 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - OBIE Directory domain: matls\-api\.openbanking\.org\.uk\. - Operational state: healthy\. - CASC score: 9\.17\. - Pass rate: 99\.99%\. - p95 latency: 1,989 ms\. - Developer documentation: https://standards\.openbanking\.org\.uk/api\-specifications/\. ## Primary entities - APIContext - OBIE Directory - matls\-api\.openbanking\.org\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/obie-directory.json) - [Developer documentation](https://standards.openbanking.org.uk/api-specifications/) --- # Revolut Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/revolut Source: static Updated: 2026-10-19T15:15:15.051Z Description: Revolut benchmark detail for oba\-auth\.revolut\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Revolut is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.84 CASC score, 100\.00% pass rate, 80 ms median latency, and 200 ms p95 latency\. ## Stats - 8\.84 CASC score - 100\.00% pass rate - 80 ms median latency - 200 ms p95 latency - healthy operational state ## Page sections ### Revolut benchmark detail Category: Subject Revolut is measured as part of Open Banking UK Production\. This page summarizes operational signals for oba\-auth\.revolut\.com, including quality, reliability, latency, and infrastructure context\. - Domain: oba\-auth\.revolut\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6\.75 ms\. - TCP connection: 3\.5 ms\. - TLS handshake: 27\.5 ms\. - Processing: 38\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/revolut.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Revolut recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 200 ms, with median latency at 80 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Revolut domain: oba\-auth\.revolut\.com\. - Operational state: healthy\. - CASC score: 8\.84\. - Pass rate: 100\.00%\. - p95 latency: 200 ms\. ## Primary entities - APIContext - Revolut - oba\-auth\.revolut\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/revolut.json) --- # Starling Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/starling-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Starling Bank benchmark detail for api\-openbanking\.starlingbank\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Starling Bank is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.18 CASC score, 100\.00% pass rate, 106 ms median latency, and 248 ms p95 latency\. ## Stats - 9\.18 CASC score - 100\.00% pass rate - 106 ms median latency - 248 ms p95 latency - healthy operational state ## Page sections ### Starling Bank benchmark detail Category: Subject Starling Bank is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\-openbanking\.starlingbank\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\-openbanking\.starlingbank\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 16\.25 ms\. - TCP connection: 24\.5 ms\. - TLS handshake: 28\.5 ms\. - Processing: 31\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/starling-bank.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Starling Bank recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 248 ms, with median latency at 106 ms\. ## Key facts - Starling Bank domain: api\-openbanking\.starlingbank\.com\. - Operational state: healthy\. - CASC score: 9\.18\. - Pass rate: 100\.00%\. - p95 latency: 248 ms\. ## Primary entities - APIContext - Starling Bank - api\-openbanking\.starlingbank\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/starling-bank.json) --- # Tide Platform Ltd Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/tide-platform-ltd Source: static Updated: 2026-10-19T15:15:15.051Z Description: Tide Platform Ltd benchmark detail for rs1\.openbanking\.api\.tide\.co, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Tide Platform Ltd is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.32 CASC score, 100\.00% pass rate, 142 ms median latency, and 311 ms p95 latency\. ## Stats - 9\.32 CASC score - 100\.00% pass rate - 142 ms median latency - 311 ms p95 latency - healthy operational state ## Page sections ### Tide Platform Ltd benchmark detail Category: Subject Tide Platform Ltd is measured as part of Open Banking UK Production\. This page summarizes operational signals for rs1\.openbanking\.api\.tide\.co, including quality, reliability, latency, and infrastructure context\. - Domain: rs1\.openbanking\.api\.tide\.co\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 18 ms\. - TCP connection: 15 ms\. - TLS handshake: 49\.75 ms\. - Processing: 50\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/tide-platform-ltd.json) - [Developer documentation](https://bitbucket.org/tideaccount/developer-portal/src/master/README.md) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Tide Platform Ltd recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 311 ms, with median latency at 142 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Tide Platform Ltd domain: rs1\.openbanking\.api\.tide\.co\. - Operational state: healthy\. - CASC score: 9\.32\. - Pass rate: 100\.00%\. - p95 latency: 311 ms\. - Developer documentation: https://bitbucket\.org/tideaccount/developer\-portal/src/master/README\.md\. ## Primary entities - APIContext - Tide Platform Ltd - rs1\.openbanking\.api\.tide\.co - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/tide-platform-ltd.json) - [Developer documentation](https://bitbucket.org/tideaccount/developer-portal/src/master/README.md) --- # TSB Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/tsb Source: static Updated: 2026-10-19T15:15:15.051Z Description: TSB benchmark detail for apis\.tsb\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary TSB is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.97 CASC score, 99\.93% pass rate, 355 ms median latency, and 550 ms p95 latency\. ## Stats - 8\.97 CASC score - 99\.93% pass rate - 355 ms median latency - 550 ms p95 latency - recovering operational state ## Page sections ### TSB benchmark detail Category: Subject TSB is measured as part of Open Banking UK Production\. This page summarizes operational signals for apis\.tsb\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: apis\.tsb\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 7\.25 ms\. - TCP connection: 22\.75 ms\. - TLS handshake: 49\.5 ms\. - Processing: 253\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: server\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/tsb.json) - [Developer documentation](https://apis.developer.tsb.co.uk) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - TSB recorded 99\.93% pass rate in the latest verified snapshot\. - The p95 latency signal is 550 ms, with median latency at 355 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - TSB domain: apis\.tsb\.co\.uk\. - Operational state: recovering\. - CASC score: 8\.97\. - Pass rate: 99\.93%\. - p95 latency: 550 ms\. - Developer documentation: https://apis\.developer\.tsb\.co\.uk\. ## Primary entities - APIContext - TSB - apis\.tsb\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/tsb.json) - [Developer documentation](https://apis.developer.tsb.co.uk) --- # Vanquis Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/vanquis-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Vanquis Bank benchmark detail for mtls\.data\.openbanking\.vanquis\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Vanquis Bank is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 8\.10 CASC score, 99\.55% pass rate, 538 ms median latency, and 1,992 ms p95 latency\. ## Stats - 8\.10 CASC score - 99\.55% pass rate - 538 ms median latency - 1,992 ms p95 latency - stable operational state ## Page sections ### Vanquis Bank benchmark detail Category: Subject Vanquis Bank is measured as part of Open Banking UK Production\. This page summarizes operational signals for mtls\.data\.openbanking\.vanquis\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: mtls\.data\.openbanking\.vanquis\.co\.uk\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10 ms\. - TCP connection: 16\.25 ms\. - TLS handshake: 34\.25 ms\. - Processing: 488 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: Google Frontend\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/vanquis-bank.json) - [Developer documentation](https://www.vanquis.co.uk/developer-portal) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Vanquis Bank recorded 99\.55% pass rate in the latest verified snapshot\. - The p95 latency signal is 1992 ms, with median latency at 538 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Vanquis Bank domain: mtls\.data\.openbanking\.vanquis\.co\.uk\. - Operational state: stable\. - CASC score: 8\.10\. - Pass rate: 99\.55%\. - p95 latency: 1,992 ms\. - Developer documentation: https://www\.vanquis\.co\.uk/developer\-portal\. ## Primary entities - APIContext - Vanquis Bank - mtls\.data\.openbanking\.vanquis\.co\.uk - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/vanquis-bank.json) - [Developer documentation](https://www.vanquis.co.uk/developer-portal) --- # Virgin Money Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/virgin-money Source: static Updated: 2026-10-19T15:15:15.051Z Description: Virgin Money benchmark detail for api\.openbanking\.virginmoney\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Virgin Money is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.44 CASC score, 100\.00% pass rate, 311 ms median latency, and 681 ms p95 latency\. ## Stats - 9\.44 CASC score - 100\.00% pass rate - 311 ms median latency - 681 ms p95 latency - healthy operational state ## Page sections ### Virgin Money benchmark detail Category: Subject Virgin Money is measured as part of Open Banking UK Production\. This page summarizes operational signals for api\.openbanking\.virginmoney\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.openbanking\.virginmoney\.com\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 70\.25 ms\. - TCP connection: 30\.5 ms\. - TLS handshake: 65\.25 ms\. - Processing: 167\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: Oracle Corporation\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/virgin-money.json) - [Developer documentation](https://developer.virginmoney.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Virgin Money recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 681 ms, with median latency at 311 ms\. ## Key facts - Virgin Money domain: api\.openbanking\.virginmoney\.com\. - Operational state: healthy\. - CASC score: 9\.44\. - Pass rate: 100\.00%\. - p95 latency: 681 ms\. - Developer documentation: https://developer\.virginmoney\.com/\. ## Primary entities - APIContext - Virgin Money - api\.openbanking\.virginmoney\.com - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/virgin-money.json) - [Developer documentation](https://developer.virginmoney.com/) --- # Zempler Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingukproduction/zempler-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Zempler Bank benchmark detail for matls\.api\.ob\.zempler\.tech, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Zempler Bank is a banking\-api benchmark subject in Open Banking UK Production\. Latest snapshot metrics include 9\.47 CASC score, 99\.96% pass rate, 170 ms median latency, and 669 ms p95 latency\. ## Stats - 9\.47 CASC score - 99\.96% pass rate - 170 ms median latency - 669 ms p95 latency - healthy operational state ## Page sections ### Zempler Bank benchmark detail Category: Subject Zempler Bank is measured as part of Open Banking UK Production\. This page summarizes operational signals for matls\.api\.ob\.zempler\.tech, including quality, reliability, latency, and infrastructure context\. - Domain: matls\.api\.ob\.zempler\.tech\. - Category: Open Banking UK Production\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 7\.25 ms\. - TCP connection: 15\.75 ms\. - TLS handshake: 42\.25 ms\. - Processing: 106\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: Cloudflare, Inc\.\. - Server: Microsoft\-IIS\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/zempler-bank.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Zempler Bank recorded 99\.96% pass rate in the latest verified snapshot\. - The p95 latency signal is 669 ms, with median latency at 170 ms\. ## Key facts - Zempler Bank domain: matls\.api\.ob\.zempler\.tech\. - Operational state: healthy\. - CASC score: 9\.47\. - Pass rate: 99\.96%\. - p95 latency: 669 ms\. ## Primary entities - APIContext - Zempler Bank - matls\.api\.ob\.zempler\.tech - Open Banking UK Production - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingukproduction/zempler-bank.json) --- # openbankingv4ukproduction Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 14 benchmark subjects in openbankingv4ukproduction, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 14 benchmark subjects in openbankingv4ukproduction, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 14 benchmark subjects - 9\.14 average CASC - 265\.36 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### openbankingv4ukproduction benchmark slice Category: Category Latest verified snapshot covers 14 benchmark subjects in openbankingv4ukproduction, with median latency signals and reliability measurements normalized for comparison\. - 14 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.88%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Allied Irish Bank V4 — 8\.97 CASC, 99\.99% pass, 514 ms p95](/api-directory/openbankingv4ukproduction/allied-irish-bank-v4) - [Ulster Bank V4 — 9\.46 CASC, 100\.00% pass, 599 ms p95](/api-directory/openbankingv4ukproduction/ulster-bank-v4) - [Santander V4 — 9\.68 CASC, 99\.92% pass, 235 ms p95](/api-directory/openbankingv4ukproduction/santander-v4) - [Zempler Bank V4 — 9\.64 CASC, 99\.98% pass, 673 ms p95](/api-directory/openbankingv4ukproduction/zempler-bank-v4) - [Natwest V4 — 9\.54 CASC, 100\.00% pass, 532 ms p95](/api-directory/openbankingv4ukproduction/natwest-v4) - [Barclays \(Personal\) V4 — 9\.24 CASC, 99\.90% pass, 494 ms p95](/api-directory/openbankingv4ukproduction/barclays-personal-v4) - [RBS V4 — 9\.50 CASC, 100\.00% pass, 564 ms p95](/api-directory/openbankingv4ukproduction/rbs-v4) - [Lloyds Bank V4 — 8\.38 CASC, 99\.53% pass, 647 ms p95](/api-directory/openbankingv4ukproduction/lloyds-bank-v4) - [HSBC Bank \(Personal\) V4 — 8\.93 CASC, 99\.94% pass, 819 ms p95](/api-directory/openbankingv4ukproduction/hsbc-bank-personal-v4) - [HSBC Bank \(Business\) V4 — 8\.89 CASC, 100\.00% pass, 1,026 ms p95](/api-directory/openbankingv4ukproduction/hsbc-bank-business-v4) - [Bank Of Scotland V4 — 8\.46 CASC, 99\.53% pass, 605 ms p95](/api-directory/openbankingv4ukproduction/bank-of-scotland-v4) - [Nationwide Building Society V4 — 9\.30 CASC, 99\.99% pass, 382 ms p95](/api-directory/openbankingv4ukproduction/nationwide-building-society-v4) - [Danske Bank V4 — 9\.58 CASC, 100\.00% pass, 409 ms p95](/api-directory/openbankingv4ukproduction/danske-bank-v4) - [Halifax V4 — 8\.36 CASC, 99\.52% pass, 604 ms p95](/api-directory/openbankingv4ukproduction/halifax-v4) ## Key facts - 14 benchmark subjects are included in openbankingv4ukproduction\. - Average CASC score: 913\.79\. - Average median latency: 265\.36 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - openbankingv4ukproduction - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/openbankingv4ukproduction.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Allied Irish Bank V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/allied-irish-bank-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Allied Irish Bank V4 benchmark detail for \{\{base\_domain\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Allied Irish Bank V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 8\.97 CASC score, 99\.99% pass rate, 320 ms median latency, and 514 ms p95 latency\. ## Stats - 8\.97 CASC score - 99\.99% pass rate - 320 ms median latency - 514 ms p95 latency - healthy operational state ## Page sections ### Allied Irish Bank V4 benchmark detail Category: Subject Allied Irish Bank V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_domain\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_domain\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 12\.75 ms\. - TCP connection: 23 ms\. - TLS handshake: 71\.75 ms\. - Processing: 205\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/allied-irish-bank-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Allied Irish Bank V4 recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 514 ms, with median latency at 320 ms\. ## Key facts - Allied Irish Bank V4 domain: \{\{base\_domain\}\}\. - Operational state: healthy\. - CASC score: 8\.97\. - Pass rate: 99\.99%\. - p95 latency: 514 ms\. ## Primary entities - APIContext - Allied Irish Bank V4 - \{\{base\_domain\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/allied-irish-bank-v4.json) --- # Bank Of Scotland V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/bank-of-scotland-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bank Of Scotland V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bank Of Scotland V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 8\.46 CASC score, 99\.53% pass rate, 285 ms median latency, and 605 ms p95 latency\. ## Stats - 8\.46 CASC score - 99\.53% pass rate - 285 ms median latency - 605 ms p95 latency - stable operational state ## Page sections ### Bank Of Scotland V4 benchmark detail Category: Subject Bank Of Scotland V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 30\.25 ms\. - TCP connection: 3 ms\. - TLS handshake: 13 ms\. - Processing: 228\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/bank-of-scotland-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bank Of Scotland V4 recorded 99\.53% pass rate in the latest verified snapshot\. - The p95 latency signal is 605 ms, with median latency at 285 ms\. ## Key facts - Bank Of Scotland V4 domain: \{\{base\_url\}\}\. - Operational state: stable\. - CASC score: 8\.46\. - Pass rate: 99\.53%\. - p95 latency: 605 ms\. ## Primary entities - APIContext - Bank Of Scotland V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/bank-of-scotland-v4.json) --- # Barclays \(Personal\) V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/barclays-personal-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays \(Personal\) V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays \(Personal\) V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.24 CASC score, 99\.90% pass rate, 236 ms median latency, and 494 ms p95 latency\. ## Stats - 9\.24 CASC score - 99\.90% pass rate - 236 ms median latency - 494 ms p95 latency - stable operational state ## Page sections ### Barclays \(Personal\) V4 benchmark detail Category: Subject Barclays \(Personal\) V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 33 ms\. - TCP connection: 19\.75 ms\. - TLS handshake: 60\.75 ms\. - Processing: 109\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/barclays-personal-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays \(Personal\) V4 recorded 99\.9% pass rate in the latest verified snapshot\. - The p95 latency signal is 494 ms, with median latency at 236 ms\. ## Key facts - Barclays \(Personal\) V4 domain: \{\{base\_url\}\}\. - Operational state: stable\. - CASC score: 9\.24\. - Pass rate: 99\.90%\. - p95 latency: 494 ms\. ## Primary entities - APIContext - Barclays \(Personal\) V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/barclays-personal-v4.json) --- # Danske Bank V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/danske-bank-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Danske Bank V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Danske Bank V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.58 CASC score, 100\.00% pass rate, 263 ms median latency, and 409 ms p95 latency\. ## Stats - 9\.58 CASC score - 100\.00% pass rate - 263 ms median latency - 409 ms p95 latency - healthy operational state ## Page sections ### Danske Bank V4 benchmark detail Category: Subject Danske Bank V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 6\.5 ms\. - TCP connection: 31\.25 ms\. - TLS handshake: 35\.75 ms\. - Processing: 182\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/danske-bank-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Danske Bank V4 recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 409 ms, with median latency at 263 ms\. ## Key facts - Danske Bank V4 domain: \{\{base\_url\}\}\. - Operational state: healthy\. - CASC score: 9\.58\. - Pass rate: 100\.00%\. - p95 latency: 409 ms\. ## Primary entities - APIContext - Danske Bank V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/danske-bank-v4.json) --- # Halifax V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/halifax-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Halifax V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Halifax V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 8\.36 CASC score, 99\.52% pass rate, 284 ms median latency, and 604 ms p95 latency\. ## Stats - 8\.36 CASC score - 99\.52% pass rate - 284 ms median latency - 604 ms p95 latency - stable operational state ## Page sections ### Halifax V4 benchmark detail Category: Subject Halifax V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 30\.75 ms\. - TCP connection: 3 ms\. - TLS handshake: 13\.25 ms\. - Processing: 227 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/halifax-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Halifax V4 recorded 99\.52% pass rate in the latest verified snapshot\. - The p95 latency signal is 604 ms, with median latency at 284 ms\. ## Key facts - Halifax V4 domain: \{\{base\_url\}\}\. - Operational state: stable\. - CASC score: 8\.36\. - Pass rate: 99\.52%\. - p95 latency: 604 ms\. ## Primary entities - APIContext - Halifax V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/halifax-v4.json) --- # HSBC Bank \(Business\) V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/hsbc-bank-business-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC Bank \(Business\) V4 benchmark detail for api\.ob\.business\.hsbc\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC Bank \(Business\) V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 8\.89 CASC score, 100\.00% pass rate, 369 ms median latency, and 1,026 ms p95 latency\. ## Stats - 8\.89 CASC score - 100\.00% pass rate - 369 ms median latency - 1,026 ms p95 latency - healthy operational state ## Page sections ### HSBC Bank \(Business\) V4 benchmark detail Category: Subject HSBC Bank \(Business\) V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for api\.ob\.business\.hsbc\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: api\.ob\.business\.hsbc\.co\.uk\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 34 ms\. - TCP connection: 3\.75 ms\. - TLS handshake: 15\.75 ms\. - Processing: 302\.5 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/hsbc-bank-business-v4.json) - [Developer documentation](https://develop.hsbc.com/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC Bank \(Business\) V4 recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1026 ms, with median latency at 369 ms\. ## Key facts - HSBC Bank \(Business\) V4 domain: api\.ob\.business\.hsbc\.co\.uk\. - Operational state: healthy\. - CASC score: 8\.89\. - Pass rate: 100\.00%\. - p95 latency: 1,026 ms\. - Developer documentation: https://develop\.hsbc\.com/\. ## Primary entities - APIContext - HSBC Bank \(Business\) V4 - api\.ob\.business\.hsbc\.co\.uk - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/hsbc-bank-business-v4.json) - [Developer documentation](https://develop.hsbc.com/) --- # HSBC Bank \(Personal\) V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/hsbc-bank-personal-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC Bank \(Personal\) V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC Bank \(Personal\) V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 8\.93 CASC score, 99\.94% pass rate, 311 ms median latency, and 819 ms p95 latency\. ## Stats - 8\.93 CASC score - 99\.94% pass rate - 311 ms median latency - 819 ms p95 latency - stable operational state ## Page sections ### HSBC Bank \(Personal\) V4 benchmark detail Category: Subject HSBC Bank \(Personal\) V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 32\.75 ms\. - TCP connection: 3\.5 ms\. - TLS handshake: 14\.25 ms\. - Processing: 253\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/hsbc-bank-personal-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC Bank \(Personal\) V4 recorded 99\.94% pass rate in the latest verified snapshot\. - The p95 latency signal is 819 ms, with median latency at 311 ms\. ## Key facts - HSBC Bank \(Personal\) V4 domain: \{\{base\_url\}\}\. - Operational state: stable\. - CASC score: 8\.93\. - Pass rate: 99\.94%\. - p95 latency: 819 ms\. ## Primary entities - APIContext - HSBC Bank \(Personal\) V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/hsbc-bank-personal-v4.json) --- # Lloyds Bank V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/lloyds-bank-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Lloyds Bank V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Lloyds Bank V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 8\.38 CASC score, 99\.53% pass rate, 290 ms median latency, and 647 ms p95 latency\. ## Stats - 8\.38 CASC score - 99\.53% pass rate - 290 ms median latency - 647 ms p95 latency - stable operational state ## Page sections ### Lloyds Bank V4 benchmark detail Category: Subject Lloyds Bank V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 33\.75 ms\. - TCP connection: 3 ms\. - TLS handshake: 13\.5 ms\. - Processing: 230 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/lloyds-bank-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Lloyds Bank V4 recorded 99\.53% pass rate in the latest verified snapshot\. - The p95 latency signal is 647 ms, with median latency at 290 ms\. ## Key facts - Lloyds Bank V4 domain: \{\{base\_url\}\}\. - Operational state: stable\. - CASC score: 8\.38\. - Pass rate: 99\.53%\. - p95 latency: 647 ms\. ## Primary entities - APIContext - Lloyds Bank V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/lloyds-bank-v4.json) --- # Nationwide Building Society V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/nationwide-building-society-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Nationwide Building Society V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Nationwide Building Society V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.30 CASC score, 99\.99% pass rate, 230 ms median latency, and 382 ms p95 latency\. ## Stats - 9\.30 CASC score - 99\.99% pass rate - 230 ms median latency - 382 ms p95 latency - healthy operational state ## Page sections ### Nationwide Building Society V4 benchmark detail Category: Subject Nationwide Building Society V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 4\.25 ms\. - TCP connection: 20 ms\. - TLS handshake: 44 ms\. - Processing: 150 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/nationwide-building-society-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Nationwide Building Society V4 recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 382 ms, with median latency at 230 ms\. ## Key facts - Nationwide Building Society V4 domain: \{\{base\_url\}\}\. - Operational state: healthy\. - CASC score: 9\.30\. - Pass rate: 99\.99%\. - p95 latency: 382 ms\. ## Primary entities - APIContext - Nationwide Building Society V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/nationwide-building-society-v4.json) --- # Natwest V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/natwest-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Natwest V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Natwest V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.54 CASC score, 100\.00% pass rate, 266 ms median latency, and 532 ms p95 latency\. ## Stats - 9\.54 CASC score - 100\.00% pass rate - 266 ms median latency - 532 ms p95 latency - healthy operational state ## Page sections ### Natwest V4 benchmark detail Category: Subject Natwest V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.5 ms\. - TCP connection: 12\.25 ms\. - TLS handshake: 45\.25 ms\. - Processing: 179\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/natwest-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Natwest V4 recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 532 ms, with median latency at 266 ms\. ## Key facts - Natwest V4 domain: \{\{base\_url\}\}\. - Operational state: healthy\. - CASC score: 9\.54\. - Pass rate: 100\.00%\. - p95 latency: 532 ms\. ## Primary entities - APIContext - Natwest V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/natwest-v4.json) --- # RBS V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/rbs-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: RBS V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary RBS V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.50 CASC score, 100\.00% pass rate, 276 ms median latency, and 564 ms p95 latency\. ## Stats - 9\.50 CASC score - 100\.00% pass rate - 276 ms median latency - 564 ms p95 latency - healthy operational state ## Page sections ### RBS V4 benchmark detail Category: Subject RBS V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.75 ms\. - TCP connection: 11\.75 ms\. - TLS handshake: 44\.25 ms\. - Processing: 187\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/rbs-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - RBS V4 recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 564 ms, with median latency at 276 ms\. ## Key facts - RBS V4 domain: \{\{base\_url\}\}\. - Operational state: healthy\. - CASC score: 9\.50\. - Pass rate: 100\.00%\. - p95 latency: 564 ms\. ## Primary entities - APIContext - RBS V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/rbs-v4.json) --- # Santander V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/santander-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Santander V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Santander V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.68 CASC score, 99\.92% pass rate, 122 ms median latency, and 235 ms p95 latency\. ## Stats - 9\.68 CASC score - 99\.92% pass rate - 122 ms median latency - 235 ms p95 latency - stable operational state ## Page sections ### Santander V4 benchmark detail Category: Subject Santander V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 8 ms\. - TCP connection: 19\.25 ms\. - TLS handshake: 20\.25 ms\. - Processing: 59\.25 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/santander-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Santander V4 recorded 99\.92% pass rate in the latest verified snapshot\. - The p95 latency signal is 235 ms, with median latency at 122 ms\. ## Key facts - Santander V4 domain: \{\{base\_url\}\}\. - Operational state: stable\. - CASC score: 9\.68\. - Pass rate: 99\.92%\. - p95 latency: 235 ms\. ## Primary entities - APIContext - Santander V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/santander-v4.json) --- # Ulster Bank V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/ulster-bank-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Ulster Bank V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Ulster Bank V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.46 CASC score, 100\.00% pass rate, 285 ms median latency, and 599 ms p95 latency\. ## Stats - 9\.46 CASC score - 100\.00% pass rate - 285 ms median latency - 599 ms p95 latency - healthy operational state ## Page sections ### Ulster Bank V4 benchmark detail Category: Subject Ulster Bank V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.75 ms\. - TCP connection: 12\.25 ms\. - TLS handshake: 44\.25 ms\. - Processing: 194 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/ulster-bank-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Ulster Bank V4 recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 599 ms, with median latency at 285 ms\. ## Key facts - Ulster Bank V4 domain: \{\{base\_url\}\}\. - Operational state: healthy\. - CASC score: 9\.46\. - Pass rate: 100\.00%\. - p95 latency: 599 ms\. ## Primary entities - APIContext - Ulster Bank V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/ulster-bank-v4.json) --- # Zempler Bank V4 Operational Intelligence Canonical URL: https://apicontext.com/api-directory/openbankingv4ukproduction/zempler-bank-v4 Source: static Updated: 2026-10-19T15:15:15.051Z Description: Zempler Bank V4 benchmark detail for \{\{base\_url\}\}, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Zempler Bank V4 is a api\-provider benchmark subject in openbankingv4ukproduction\. Latest snapshot metrics include 9\.64 CASC score, 99\.98% pass rate, 178 ms median latency, and 673 ms p95 latency\. ## Stats - 9\.64 CASC score - 99\.98% pass rate - 178 ms median latency - 673 ms p95 latency - healthy operational state ## Page sections ### Zempler Bank V4 benchmark detail Category: Subject Zempler Bank V4 is measured as part of openbankingv4ukproduction\. This page summarizes operational signals for \{\{base\_url\}\}, including quality, reliability, latency, and infrastructure context\. - Domain: \{\{base\_url\}\}\. - Category: openbankingv4ukproduction\. - Benchmark subject type: api\-provider\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.75 ms\. - TCP connection: 17\.25 ms\. - TLS handshake: 43\.75 ms\. - Processing: 107\.75 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/zempler-bank-v4.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Zempler Bank V4 recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 673 ms, with median latency at 178 ms\. ## Key facts - Zempler Bank V4 domain: \{\{base\_url\}\}\. - Operational state: healthy\. - CASC score: 9\.64\. - Pass rate: 99\.98%\. - p95 latency: 673 ms\. ## Primary entities - APIContext - Zempler Bank V4 - \{\{base\_url\}\} - openbankingv4ukproduction - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/openbankingv4ukproduction/zempler-bank-v4.json) --- # PSD2 Institutions Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/psd2institutions Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 2 benchmark subjects in PSD2 Institutions, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 2 benchmark subjects in PSD2 Institutions, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 2 benchmark subjects - 8\.60 average CASC - 820 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### PSD2 Institutions benchmark slice Category: Category Latest verified snapshot covers 2 benchmark subjects in PSD2 Institutions, with median latency signals and reliability measurements normalized for comparison\. - 2 subjects are normalized in this category\. - Benchmark subject type: banking\-api\. - Average pass rate: 100\.00%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Capital One US \(sandbox\) — 8\.96 CASC, 100\.00% pass, 1,559 ms p95](/api-directory/psd2institutions/capital-one-us-sandbox) - [ABN — 8\.23 CASC, 100\.00% pass, 3,285 ms p95](/api-directory/psd2institutions/abn) ## Key facts - 2 benchmark subjects are included in PSD2 Institutions\. - Average CASC score: 859\.5\. - Average median latency: 820 ms\. - Benchmark subject type: banking\-api\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - PSD2 Institutions - Benchmark Intelligence - Operational Intelligence - banking\-api ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/psd2institutions.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # ABN Operational Intelligence Canonical URL: https://apicontext.com/api-directory/psd2institutions/abn Source: static Updated: 2026-10-19T15:15:15.051Z Description: ABN benchmark detail for api\-sandbox\.abnamro\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary ABN is a banking\-api benchmark subject in PSD2 Institutions\. Latest snapshot metrics include 8\.23 CASC score, 100\.00% pass rate, 1,140 ms median latency, and 3,285 ms p95 latency\. ## Stats - 8\.23 CASC score - 100\.00% pass rate - 1,140 ms median latency - 3,285 ms p95 latency - stable operational state ## Page sections ### ABN benchmark detail Category: Subject ABN is measured as part of PSD2 Institutions\. This page summarizes operational signals for api\-sandbox\.abnamro\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\-sandbox\.abnamro\.com\. - Category: PSD2 Institutions\. - Benchmark subject type: banking\-api\. - Monitored count: 6\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 43\.45 ms\. - TCP connection: 7\.09 ms\. - TLS handshake: 31\.41 ms\. - Processing: 1,040\.27 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/psd2institutions/abn.json) - [Developer documentation](https://developer.abnamro.com/) - [OpenAPI specification](https://developer.abnamro.com/sites/default/files/tmCzak94.yaml) - [Postman collection](https://www.postman.com/api-evangelist/workspace/abn-amro/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - ABN recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 3285 ms, with median latency at 1140 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - ABN domain: api\-sandbox\.abnamro\.com\. - Operational state: stable\. - CASC score: 8\.23\. - Pass rate: 100\.00%\. - p95 latency: 3,285 ms\. - Developer documentation: https://developer\.abnamro\.com/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/abn\-amro/overview\. - OpenAPI specification: https://developer\.abnamro\.com/sites/default/files/tmCzak94\.yaml\. ## Primary entities - APIContext - ABN - api\-sandbox\.abnamro\.com - PSD2 Institutions - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/psd2institutions/abn.json) - [Developer documentation](https://developer.abnamro.com/) - [OpenAPI specification](https://developer.abnamro.com/sites/default/files/tmCzak94.yaml) --- # Capital One US \(sandbox\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/psd2institutions/capital-one-us-sandbox Source: static Updated: 2026-10-19T15:15:15.051Z Description: Capital One US \(sandbox\) benchmark detail for api\-sandbox\.capitalone\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Capital One US \(sandbox\) is a banking\-api benchmark subject in PSD2 Institutions\. Latest snapshot metrics include 8\.96 CASC score, 100\.00% pass rate, 500 ms median latency, and 1,559 ms p95 latency\. ## Stats - 8\.96 CASC score - 100\.00% pass rate - 500 ms median latency - 1,559 ms p95 latency - healthy operational state ## Page sections ### Capital One US \(sandbox\) benchmark detail Category: Subject Capital One US \(sandbox\) is measured as part of PSD2 Institutions\. This page summarizes operational signals for api\-sandbox\.capitalone\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\-sandbox\.capitalone\.com\. - Category: PSD2 Institutions\. - Benchmark subject type: banking\-api\. - Monitored count: 2\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 68\.19 ms\. - TCP connection: 117\.62 ms\. - TLS handshake: 120\.14 ms\. - Processing: 386\.71 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon\.com, Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/psd2institutions/capital-one-us-sandbox.json) - [Developer documentation](https://developer.capitalone.com/) - [Postman collection](https://www.postman.com/api-evangelist/workspace/capital-one-devexchange/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Capital One US \(sandbox\) recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1559 ms, with median latency at 500 ms\. - Infrastructure fingerprinting identifies Amazon\.com, Inc\. in the observed delivery path\. ## Key facts - Capital One US \(sandbox\) domain: api\-sandbox\.capitalone\.com\. - Operational state: healthy\. - CASC score: 8\.96\. - Pass rate: 100\.00%\. - p95 latency: 1,559 ms\. - Developer documentation: https://developer\.capitalone\.com/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/capital\-one\-devexchange/overview\. ## Primary entities - APIContext - Capital One US \(sandbox\) - api\-sandbox\.capitalone\.com - PSD2 Institutions - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/psd2institutions/capital-one-us-sandbox.json) - [Developer documentation](https://developer.capitalone.com/) --- # Search Platforms Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/search Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 2 benchmark subjects in Search Platforms, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 2 benchmark subjects in Search Platforms, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 2 benchmark subjects - 8\.85 average CASC - 264 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Search Platforms benchmark slice Category: Category Latest verified snapshot covers 2 benchmark subjects in Search Platforms, with median latency signals and reliability measurements normalized for comparison\. - 2 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.48%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [DuckDuckGo — 9\.04 CASC, 99\.10% pass, 442 ms p95](/api-directory/search/duckduckgo) - [Google \(Search\) — 8\.65 CASC, 99\.85% pass, 764 ms p95](/api-directory/search/google-search) ## Key facts - 2 benchmark subjects are included in Search Platforms\. - Average CASC score: 884\.5\. - Average median latency: 264 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Search Platforms - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/search.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # DuckDuckGo Operational Intelligence Canonical URL: https://apicontext.com/api-directory/search/duckduckgo Source: static Updated: 2026-10-19T15:15:15.051Z Description: DuckDuckGo benchmark detail for api\.duckduckgo\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary DuckDuckGo is a api\-provider benchmark subject in Search Platforms\. Latest snapshot metrics include 9\.04 CASC score, 99\.10% pass rate, 153 ms median latency, and 442 ms p95 latency\. ## Stats - 9\.04 CASC score - 99\.10% pass rate - 153 ms median latency - 442 ms p95 latency - degraded operational state ## Page sections ### DuckDuckGo benchmark detail Category: Subject DuckDuckGo is measured as part of Search Platforms\. This page summarizes operational signals for api\.duckduckgo\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.duckduckgo\.com\. - Category: Search Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 60\.05 ms\. - TCP connection: 18\.45 ms\. - TLS handshake: 19\.45 ms\. - Processing: 68\.8 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Microsoft Corporation\. - Nameserver: Microsoft Corporation\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/search/duckduckgo.json) - [Developer documentation](https://duckduckgo.com/api) - [OpenAPI specification](https://raw.githubusercontent.com/api-evangelist/duckduckgo/master/duckduckgo-instant-answer-api-openapi.json) - [Postman collection](https://www.postman.com/api-evangelist/workspace/duckduckgo/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - DuckDuckGo recorded 99\.1% pass rate in the latest verified snapshot\. - The p95 latency signal is 442 ms, with median latency at 153 ms\. - Infrastructure fingerprinting identifies Microsoft Corporation in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - DuckDuckGo domain: api\.duckduckgo\.com\. - Operational state: degraded\. - CASC score: 9\.04\. - Pass rate: 99\.10%\. - p95 latency: 442 ms\. - Developer documentation: https://duckduckgo\.com/api\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/duckduckgo/overview\. - OpenAPI specification: https://raw\.githubusercontent\.com/api\-evangelist/duckduckgo/master/duckduckgo\-instant\-answer\-api\-openapi\.json\. ## Primary entities - APIContext - DuckDuckGo - api\.duckduckgo\.com - Search Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/search/duckduckgo.json) - [Developer documentation](https://duckduckgo.com/api) - [OpenAPI specification](https://raw.githubusercontent.com/api-evangelist/duckduckgo/master/duckduckgo-instant-answer-api-openapi.json) --- # Google \(Search\) Operational Intelligence Canonical URL: https://apicontext.com/api-directory/search/google-search Source: static Updated: 2026-10-19T15:15:15.051Z Description: Google \(Search\) benchmark detail for www\.googleapis\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Google \(Search\) is a api\-provider benchmark subject in Search Platforms\. Latest snapshot metrics include 8\.65 CASC score, 99\.85% pass rate, 375 ms median latency, and 764 ms p95 latency\. ## Stats - 8\.65 CASC score - 99\.85% pass rate - 375 ms median latency - 764 ms p95 latency - stable operational state ## Page sections ### Google \(Search\) benchmark detail Category: Subject Google \(Search\) is measured as part of Search Platforms\. This page summarizes operational signals for www\.googleapis\.com, including quality, reliability, latency, and infrastructure context\. - Domain: www\.googleapis\.com\. - Category: Search Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 2\.55 ms\. - TCP connection: 3\.91 ms\. - TLS handshake: 50\.82 ms\. - Processing: 444\.45 ms\. - Download: 3\.73 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: ESF\. - [Subject JSON](/api-directory/data/latest/subjects/search/google-search.json) - [Developer documentation](https://developers.google.com/custom-search) - [Postman collection](https://www.postman.com/api-evangelist/workspace/google/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Google \(Search\) recorded 99\.85% pass rate in the latest verified snapshot\. - The p95 latency signal is 764 ms, with median latency at 375 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - Google \(Search\) domain: www\.googleapis\.com\. - Operational state: stable\. - CASC score: 8\.65\. - Pass rate: 99\.85%\. - p95 latency: 764 ms\. - Developer documentation: https://developers\.google\.com/custom\-search\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/google/overview\. ## Primary entities - APIContext - Google \(Search\) - www\.googleapis\.com - Search Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/search/google-search.json) - [Developer documentation](https://developers.google.com/custom-search) --- # Social Platforms Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/social Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 5 benchmark subjects in Social Platforms, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 5 benchmark subjects in Social Platforms, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 5 benchmark subjects - 9\.17 average CASC - 272\.2 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Social Platforms benchmark slice Category: Category Latest verified snapshot covers 5 benchmark subjects in Social Platforms, with median latency signals and reliability measurements normalized for comparison\. - 5 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.64%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Tumblr — 9\.01 CASC, 100\.00% pass, 754 ms p95](/api-directory/social/tumblr) - [Foursquare — 9\.11 CASC, 100\.00% pass, 1,211 ms p95](/api-directory/social/foursquare) - [Twitter — 9\.34 CASC, 100\.00% pass, 478 ms p95](/api-directory/social/twitter) - [Reddit — 9\.05 CASC, 100\.00% pass, 480 ms p95](/api-directory/social/reddit) - [Flickr — 9\.34 CASC, 98\.2% pass, 487 ms p95](/api-directory/social/flickr) ## Key facts - 5 benchmark subjects are included in Social Platforms\. - Average CASC score: 917\. - Average median latency: 272\.2 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Social Platforms - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/social.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Flickr Operational Intelligence Canonical URL: https://apicontext.com/api-directory/social/flickr Source: static Updated: 2026-10-19T15:15:15.051Z Description: Flickr benchmark detail for api\.flickr\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Flickr is a api\-provider benchmark subject in Social Platforms\. Latest snapshot metrics include 9\.34 CASC score, 98\.2% pass rate, 210 ms median latency, and 487 ms p95 latency\. ## Stats - 9\.34 CASC score - 98\.2% pass rate - 210 ms median latency - 487 ms p95 latency - degraded operational state ## Page sections ### Flickr benchmark detail Category: Subject Flickr is measured as part of Social Platforms\. This page summarizes operational signals for api\.flickr\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.flickr\.com\. - Category: Social Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 39\.24 ms\. - TCP connection: 4\.94 ms\. - TLS handshake: 7\.24 ms\. - Processing: 195\.94 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: amazon\_cloudfront\_cdn\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon\.com, Inc\.\. - Server: Apache\. - [Subject JSON](/api-directory/data/latest/subjects/social/flickr.json) - [Developer documentation](https://www.flickr.com/services/developer) - [OpenAPI specification](https://raw.githubusercontent.com/flickr/flickr-api-swagger/master/dist/schema.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Flickr recorded 98\.2% pass rate in the latest verified snapshot\. - The p95 latency signal is 487 ms, with median latency at 210 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Flickr domain: api\.flickr\.com\. - Operational state: degraded\. - CASC score: 9\.34\. - Pass rate: 98\.2%\. - p95 latency: 487 ms\. - Developer documentation: https://www\.flickr\.com/services/developer\. - OpenAPI specification: https://raw\.githubusercontent\.com/flickr/flickr\-api\-swagger/master/dist/schema\.json\. ## Primary entities - APIContext - Flickr - api\.flickr\.com - Social Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/social/flickr.json) - [Developer documentation](https://www.flickr.com/services/developer) - [OpenAPI specification](https://raw.githubusercontent.com/flickr/flickr-api-swagger/master/dist/schema.json) --- # Foursquare Operational Intelligence Canonical URL: https://apicontext.com/api-directory/social/foursquare Source: static Updated: 2026-10-19T15:15:15.051Z Description: Foursquare benchmark detail for api\.foursquare\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Foursquare is a api\-provider benchmark subject in Social Platforms\. Latest snapshot metrics include 9\.11 CASC score, 100\.00% pass rate, 393 ms median latency, and 1,211 ms p95 latency\. ## Stats - 9\.11 CASC score - 100\.00% pass rate - 393 ms median latency - 1,211 ms p95 latency - healthy operational state ## Page sections ### Foursquare benchmark detail Category: Subject Foursquare is measured as part of Social Platforms\. This page summarizes operational signals for api\.foursquare\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.foursquare\.com\. - Category: Social Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 46\.71 ms\. - TCP connection: 5\.41 ms\. - TLS handshake: 8\.24 ms\. - Processing: 560\.24 ms\. - Download: 0\.12 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Fastly, Inc\.\. - Nameserver: Fastly, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/social/foursquare.json) - [Developer documentation](https://developer.foursquare.com/) - [Postman collection](https://www.postman.com/foursquare-places-api/workspace/foursquare-s-public-workspace/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Foursquare recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 1211 ms, with median latency at 393 ms\. - Infrastructure fingerprinting identifies Fastly, Inc\. in the observed delivery path\. ## Key facts - Foursquare domain: api\.foursquare\.com\. - Operational state: healthy\. - CASC score: 9\.11\. - Pass rate: 100\.00%\. - p95 latency: 1,211 ms\. - Developer documentation: https://developer\.foursquare\.com/\. - Postman collection: https://www\.postman\.com/foursquare\-places\-api/workspace/foursquare\-s\-public\-workspace/overview\. ## Primary entities - APIContext - Foursquare - api\.foursquare\.com - Social Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/social/foursquare.json) - [Developer documentation](https://developer.foursquare.com/) --- # Reddit Operational Intelligence Canonical URL: https://apicontext.com/api-directory/social/reddit Source: static Updated: 2026-10-19T15:15:15.051Z Description: Reddit benchmark detail for oauth\.reddit\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Reddit is a api\-provider benchmark subject in Social Platforms\. Latest snapshot metrics include 9\.05 CASC score, 100\.00% pass rate, 243 ms median latency, and 480 ms p95 latency\. ## Stats - 9\.05 CASC score - 100\.00% pass rate - 243 ms median latency - 480 ms p95 latency - healthy operational state ## Page sections ### Reddit benchmark detail Category: Subject Reddit is measured as part of Social Platforms\. This page summarizes operational signals for oauth\.reddit\.com, including quality, reliability, latency, and infrastructure context\. - Domain: oauth\.reddit\.com\. - Category: Social Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10\.06 ms\. - TCP connection: 4\.35 ms\. - TLS handshake: 7 ms\. - Processing: 249\.76 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Fastly, Inc\.\. - Nameserver: Fastly, Inc\.\. - Server: snooserv\. - [Subject JSON](/api-directory/data/latest/subjects/social/reddit.json) - [Developer documentation](https://www.reddit.com/dev/api/) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Reddit recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 480 ms, with median latency at 243 ms\. - Infrastructure fingerprinting identifies Fastly, Inc\. in the observed delivery path\. ## Key facts - Reddit domain: oauth\.reddit\.com\. - Operational state: healthy\. - CASC score: 9\.05\. - Pass rate: 100\.00%\. - p95 latency: 480 ms\. - Developer documentation: https://www\.reddit\.com/dev/api/\. ## Primary entities - APIContext - Reddit - oauth\.reddit\.com - Social Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/social/reddit.json) - [Developer documentation](https://www.reddit.com/dev/api/) --- # Tumblr Operational Intelligence Canonical URL: https://apicontext.com/api-directory/social/tumblr Source: static Updated: 2026-10-19T15:15:15.051Z Description: Tumblr benchmark detail for api\.tumblr\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Tumblr is a api\-provider benchmark subject in Social Platforms\. Latest snapshot metrics include 9\.01 CASC score, 100\.00% pass rate, 234 ms median latency, and 754 ms p95 latency\. ## Stats - 9\.01 CASC score - 100\.00% pass rate - 234 ms median latency - 754 ms p95 latency - healthy operational state ## Page sections ### Tumblr benchmark detail Category: Subject Tumblr is measured as part of Social Platforms\. This page summarizes operational signals for api\.tumblr\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.tumblr\.com\. - Category: Social Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 16\.35 ms\. - TCP connection: 8\.65 ms\. - TLS handshake: 10\.24 ms\. - Processing: 263\.59 ms\. - Download: 1\.06 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Automattic, Inc\. - Nameserver: Automattic, Inc\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/social/tumblr.json) - [Developer documentation](https://www.tumblr.com/docs/en/api/v2) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Tumblr recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 754 ms, with median latency at 234 ms\. - Infrastructure fingerprinting identifies Automattic, Inc in the observed delivery path\. ## Key facts - Tumblr domain: api\.tumblr\.com\. - Operational state: healthy\. - CASC score: 9\.01\. - Pass rate: 100\.00%\. - p95 latency: 754 ms\. - Developer documentation: https://www\.tumblr\.com/docs/en/api/v2\. ## Primary entities - APIContext - Tumblr - api\.tumblr\.com - Social Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/social/tumblr.json) - [Developer documentation](https://www.tumblr.com/docs/en/api/v2) --- # Twitter Operational Intelligence Canonical URL: https://apicontext.com/api-directory/social/twitter Source: static Updated: 2026-10-19T15:15:15.051Z Description: Twitter benchmark detail for api\.twitter\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Twitter is a api\-provider benchmark subject in Social Platforms\. Latest snapshot metrics include 9\.34 CASC score, 100\.00% pass rate, 281 ms median latency, and 478 ms p95 latency\. ## Stats - 9\.34 CASC score - 100\.00% pass rate - 281 ms median latency - 478 ms p95 latency - recovering operational state ## Page sections ### Twitter benchmark detail Category: Subject Twitter is measured as part of Social Platforms\. This page summarizes operational signals for api\.twitter\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.twitter\.com\. - Category: Social Platforms\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 15\.47 ms\. - TCP connection: 6\.71 ms\. - TLS handshake: 10\.47 ms\. - Processing: 274\.53 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Twitter Inc\.\. - Nameserver: Twitter Inc\.\. - Server: tsa\_l\. - [Subject JSON](/api-directory/data/latest/subjects/social/twitter.json) - [Developer documentation](https://developer.twitter.com/en/docs) - [OpenAPI specification](https://api.twitter.com/2/openapi.json) - [Postman collection](https://www.postman.com/twitter/workspace/twitter-s-public-workspace/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Twitter recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 478 ms, with median latency at 281 ms\. - Infrastructure fingerprinting identifies Twitter Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Twitter domain: api\.twitter\.com\. - Operational state: recovering\. - CASC score: 9\.34\. - Pass rate: 100\.00%\. - p95 latency: 478 ms\. - Developer documentation: https://developer\.twitter\.com/en/docs\. - Postman collection: https://www\.postman\.com/twitter/workspace/twitter\-s\-public\-workspace/overview\. - OpenAPI specification: https://api\.twitter\.com/2/openapi\.json\. ## Primary entities - APIContext - Twitter - api\.twitter\.com - Social Platforms - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/social/twitter.json) - [Developer documentation](https://developer.twitter.com/en/docs) - [OpenAPI specification](https://api.twitter.com/2/openapi.json) --- # UK Banks Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 9 benchmark subjects in UK Banks, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 9 benchmark subjects in UK Banks, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 9 benchmark subjects - 8\.78 average CASC - 341\.67 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### UK Banks benchmark slice Category: Category Latest verified snapshot covers 9 benchmark subjects in UK Banks, with median latency signals and reliability measurements normalized for comparison\. - 9 subjects are normalized in this category\. - Benchmark subject type: banking\-api\. - Average pass rate: 99\.99%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Danske Bank — 9\.15 CASC, 100\.00% pass, 503 ms p95](/api-directory/ukbanks/danske-bank) - [Nationwide — 9\.41 CASC, 100\.00% pass, 394 ms p95](/api-directory/ukbanks/nationwide) - [NatWest Group — 9\.25 CASC, 100\.00% pass, 779 ms p95](/api-directory/ukbanks/natwest-group) - [Bank of Ireland — 9\.37 CASC, 100\.00% pass, 614 ms p95](/api-directory/ukbanks/bank-of-ireland) - [Santander — 9\.53 CASC, 100\.00% pass, 390 ms p95](/api-directory/ukbanks/santander) - [HSBC — 7\.23 CASC, 99\.96% pass, 2,206 ms p95](/api-directory/ukbanks/hsbc) - [Barclays — 7\.36 CASC, 99\.98% pass, 1,889 ms p95](/api-directory/ukbanks/barclays) - [Lloyds Group — 8\.38 CASC, 99\.95% pass, 888 ms p95](/api-directory/ukbanks/lloyds-group) - [Allied Irish Bank — 9\.36 CASC, 99\.99% pass, 453 ms p95](/api-directory/ukbanks/allied-irish-bank) ## Key facts - 9 benchmark subjects are included in UK Banks\. - Average CASC score: 878\.22\. - Average median latency: 341\.67 ms\. - Benchmark subject type: banking\-api\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - UK Banks - Benchmark Intelligence - Operational Intelligence - banking\-api ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/ukbanks.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Allied Irish Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/allied-irish-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Allied Irish Bank benchmark detail for openapi\.firsttrustbank\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Allied Irish Bank is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 9\.36 CASC score, 99\.99% pass rate, 237 ms median latency, and 453 ms p95 latency\. ## Stats - 9\.36 CASC score - 99\.99% pass rate - 237 ms median latency - 453 ms p95 latency - healthy operational state ## Page sections ### Allied Irish Bank benchmark detail Category: Subject Allied Irish Bank is measured as part of UK Banks\. This page summarizes operational signals for openapi\.firsttrustbank\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: openapi\.firsttrustbank\.co\.uk\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 10\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 32\.5 ms\. - TCP connection: 24\.5 ms\. - TLS handshake: 49\.25 ms\. - Processing: 110\.25 ms\. - Download: 15\.5 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/allied-irish-bank.json) - [Developer documentation](https://developer.firsttrustbank.co.uk/) - [Postman collection](https://www.postman.com/apievangelist/workspace/uk-public-banking/environment/35240-93009c96-ea74-4eea-aa37-ca7bedcb1c6d) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Allied Irish Bank recorded 99\.99% pass rate in the latest verified snapshot\. - The p95 latency signal is 453 ms, with median latency at 237 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Allied Irish Bank domain: openapi\.firsttrustbank\.co\.uk\. - Operational state: healthy\. - CASC score: 9\.36\. - Pass rate: 99\.99%\. - p95 latency: 453 ms\. - Developer documentation: https://developer\.firsttrustbank\.co\.uk/\. - Postman collection: https://www\.postman\.com/apievangelist/workspace/uk\-public\-banking/environment/35240\-93009c96\-ea74\-4eea\-aa37\-ca7bedcb1c6d\. ## Primary entities - APIContext - Allied Irish Bank - openapi\.firsttrustbank\.co\.uk - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/allied-irish-bank.json) - [Developer documentation](https://developer.firsttrustbank.co.uk/) --- # Bank of Ireland Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/bank-of-ireland Source: static Updated: 2026-10-19T15:15:15.051Z Description: Bank of Ireland benchmark detail for openapi\.bankofireland\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Bank of Ireland is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 9\.37 CASC score, 100\.00% pass rate, 310 ms median latency, and 614 ms p95 latency\. ## Stats - 9\.37 CASC score - 100\.00% pass rate - 310 ms median latency - 614 ms p95 latency - healthy operational state ## Page sections ### Bank of Ireland benchmark detail Category: Subject Bank of Ireland is measured as part of UK Banks\. This page summarizes operational signals for openapi\.bankofireland\.com, including quality, reliability, latency, and infrastructure context\. - Domain: openapi\.bankofireland\.com\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 8\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 54\.25 ms\. - TCP connection: 23\.75 ms\. - TLS handshake: 49\.5 ms\. - Processing: 88\.75 ms\. - Download: 72 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: NeuStar, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/bank-of-ireland.json) - [Developer documentation](https://developer.bankofireland.com) - [Postman collection](https://www.postman.com/api-evangelist/workspace/uk-public-banking/environment/35240-c8636894-7212-49c9-97bc-119c20002e0b) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Bank of Ireland recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 614 ms, with median latency at 310 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. ## Key facts - Bank of Ireland domain: openapi\.bankofireland\.com\. - Operational state: healthy\. - CASC score: 9\.37\. - Pass rate: 100\.00%\. - p95 latency: 614 ms\. - Developer documentation: https://developer\.bankofireland\.com\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/uk\-public\-banking/environment/35240\-c8636894\-7212\-49c9\-97bc\-119c20002e0b\. ## Primary entities - APIContext - Bank of Ireland - openapi\.bankofireland\.com - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/bank-of-ireland.json) - [Developer documentation](https://developer.bankofireland.com) --- # Barclays Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/barclays Source: static Updated: 2026-10-19T15:15:15.051Z Description: Barclays benchmark detail for atlas\.api\.barclays, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Barclays is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 7\.36 CASC score, 99\.98% pass rate, 850 ms median latency, and 1,889 ms p95 latency\. ## Stats - 7\.36 CASC score - 99\.98% pass rate - 850 ms median latency - 1,889 ms p95 latency - recovering operational state ## Page sections ### Barclays benchmark detail Category: Subject Barclays is measured as part of UK Banks\. This page summarizes operational signals for atlas\.api\.barclays, including quality, reliability, latency, and infrastructure context\. - Domain: atlas\.api\.barclays\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 8\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 39 ms\. - TCP connection: 2\.5 ms\. - TLS handshake: 449 ms\. - Processing: 315\.25 ms\. - Download: 1\.75 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Barclays Bank Plc\.\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/barclays.json) - [Developer documentation](https://developer.barclays.com/) - [Postman collection](https://www.postman.com/apievangelist/workspace/uk-public-banking/environment/35240-a61c3ef7-7014-4a58-b942-d60e53d5afe2) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Barclays recorded 99\.98% pass rate in the latest verified snapshot\. - The p95 latency signal is 1889 ms, with median latency at 850 ms\. - Infrastructure fingerprinting identifies Barclays Bank Plc\. in the observed delivery path\. ## Key facts - Barclays domain: atlas\.api\.barclays\. - Operational state: recovering\. - CASC score: 7\.36\. - Pass rate: 99\.98%\. - p95 latency: 1,889 ms\. - Developer documentation: https://developer\.barclays\.com/\. - Postman collection: https://www\.postman\.com/apievangelist/workspace/uk\-public\-banking/environment/35240\-a61c3ef7\-7014\-4a58\-b942\-d60e53d5afe2\. ## Primary entities - APIContext - Barclays - atlas\.api\.barclays - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/barclays.json) - [Developer documentation](https://developer.barclays.com/) --- # Danske Bank Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/danske-bank Source: static Updated: 2026-10-19T15:15:15.051Z Description: Danske Bank benchmark detail for obp\-data\.danskebank\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Danske Bank is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 9\.15 CASC score, 100\.00% pass rate, 225 ms median latency, and 503 ms p95 latency\. ## Stats - 9\.15 CASC score - 100\.00% pass rate - 225 ms median latency - 503 ms p95 latency - recovering operational state ## Page sections ### Danske Bank benchmark detail Category: Subject Danske Bank is measured as part of UK Banks\. This page summarizes operational signals for obp\-data\.danskebank\.com, including quality, reliability, latency, and infrastructure context\. - Domain: obp\-data\.danskebank\.com\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 7\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 10\.25 ms\. - TCP connection: 31\.5 ms\. - TLS handshake: 34 ms\. - Processing: 44\.5 ms\. - Download: 77 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: NeuStar, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/danske-bank.json) - [Developer documentation](https://developers.danskebank.com/api_products/danske_bank_apis) - [Postman collection](https://www.postman.com/apievangelist/workspace/uk-public-banking/environment/35240-337c6ef5-76c9-4d52-ad7b-041075dc4de5) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Danske Bank recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 503 ms, with median latency at 225 ms\. ## Key facts - Danske Bank domain: obp\-data\.danskebank\.com\. - Operational state: recovering\. - CASC score: 9\.15\. - Pass rate: 100\.00%\. - p95 latency: 503 ms\. - Developer documentation: https://developers\.danskebank\.com/api\_products/danske\_bank\_apis\. - Postman collection: https://www\.postman\.com/apievangelist/workspace/uk\-public\-banking/environment/35240\-337c6ef5\-76c9\-4d52\-ad7b\-041075dc4de5\. ## Primary entities - APIContext - Danske Bank - obp\-data\.danskebank\.com - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/danske-bank.json) - [Developer documentation](https://developers.danskebank.com/api_products/danske_bank_apis) --- # HSBC Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/hsbc Source: static Updated: 2026-10-19T15:15:15.051Z Description: HSBC benchmark detail for api\.hsbc\.com, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary HSBC is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 7\.23 CASC score, 99\.96% pass rate, 537 ms median latency, and 2,206 ms p95 latency\. ## Stats - 7\.23 CASC score - 99\.96% pass rate - 537 ms median latency - 2,206 ms p95 latency - stable operational state ## Page sections ### HSBC benchmark detail Category: Subject HSBC is measured as part of UK Banks\. This page summarizes operational signals for api\.hsbc\.com, including quality, reliability, latency, and infrastructure context\. - Domain: api\.hsbc\.com\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 8\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 79\.75 ms\. - TCP connection: 3\.5 ms\. - TLS handshake: 7\.75 ms\. - Processing: 361\.5 ms\. - Download: 25\.25 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: amazon\_cloudfront\_cdn\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/hsbc.json) - [Developer documentation](https://develop.hsbc.com/) - [OpenAPI specification](https://developer.hsbc.com/assets/swaggers/open-atm-locator-swagger.json) - [Postman collection](https://www.postman.com/api-evangelist/workspace/uk-public-banking/environment/35240-59754bcc-1b18-4e73-81e3-c1642b2ecd0c) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - HSBC recorded 99\.96% pass rate in the latest verified snapshot\. - The p95 latency signal is 2206 ms, with median latency at 537 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - HSBC domain: api\.hsbc\.com\. - Operational state: stable\. - CASC score: 7\.23\. - Pass rate: 99\.96%\. - p95 latency: 2,206 ms\. - Developer documentation: https://develop\.hsbc\.com/\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/uk\-public\-banking/environment/35240\-59754bcc\-1b18\-4e73\-81e3\-c1642b2ecd0c\. - OpenAPI specification: https://developer\.hsbc\.com/assets/swaggers/open\-atm\-locator\-swagger\.json\. ## Primary entities - APIContext - HSBC - api\.hsbc\.com - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/hsbc.json) - [Developer documentation](https://develop.hsbc.com/) - [OpenAPI specification](https://developer.hsbc.com/assets/swaggers/open-atm-locator-swagger.json) --- # Lloyds Group Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/lloyds-group Source: static Updated: 2026-10-19T15:15:15.051Z Description: Lloyds Group benchmark detail for api\.bankofscotland\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Lloyds Group is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 8\.38 CASC score, 99\.95% pass rate, 400 ms median latency, and 888 ms p95 latency\. ## Stats - 8\.38 CASC score - 99\.95% pass rate - 400 ms median latency - 888 ms p95 latency - recovering operational state ## Page sections ### Lloyds Group benchmark detail Category: Subject Lloyds Group is measured as part of UK Banks\. This page summarizes operational signals for api\.bankofscotland\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: api\.bankofscotland\.co\.uk\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 25\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 36\.75 ms\. - TCP connection: 3 ms\. - TLS handshake: 10\.5 ms\. - Processing: 301\.75 ms\. - Download: 12\.75 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Akamai Technologies, Inc\.\. - Nameserver: Akamai Technologies, Inc\.\. - Server: nginx\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/lloyds-group.json) - [Developer documentation](https://developer.lloydsbanking.com) - [Postman collection](https://www.postman.com/apievangelist/workspace/uk-public-banking/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Lloyds Group recorded 99\.95% pass rate in the latest verified snapshot\. - The p95 latency signal is 888 ms, with median latency at 400 ms\. - Infrastructure fingerprinting identifies Akamai Technologies, Inc\. in the observed delivery path\. ## Key facts - Lloyds Group domain: api\.bankofscotland\.co\.uk\. - Operational state: recovering\. - CASC score: 8\.38\. - Pass rate: 99\.95%\. - p95 latency: 888 ms\. - Developer documentation: https://developer\.lloydsbanking\.com\. - Postman collection: https://www\.postman\.com/apievangelist/workspace/uk\-public\-banking/overview\. ## Primary entities - APIContext - Lloyds Group - api\.bankofscotland\.co\.uk - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/lloyds-group.json) - [Developer documentation](https://developer.lloydsbanking.com) --- # Nationwide Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/nationwide Source: static Updated: 2026-10-19T15:15:15.051Z Description: Nationwide benchmark detail for openapi\.nationwide\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Nationwide is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 9\.41 CASC score, 100\.00% pass rate, 162 ms median latency, and 394 ms p95 latency\. ## Stats - 9\.41 CASC score - 100\.00% pass rate - 162 ms median latency - 394 ms p95 latency - healthy operational state ## Page sections ### Nationwide benchmark detail Category: Subject Nationwide is measured as part of UK Banks\. This page summarizes operational signals for openapi\.nationwide\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: openapi\.nationwide\.co\.uk\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 4\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 70 ms\. - TCP connection: 3\.25 ms\. - TLS handshake: 9 ms\. - Processing: 67\.75 ms\. - Download: 6 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: amazon\_cloudfront\_cdn\. - Hosting provider: Amazon Technologies Inc\.\. - Nameserver: Amazon Technologies Inc\.\. - Server: CloudFront\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/nationwide.json) - [Developer documentation](https://www.nationwidedeveloper.co.uk) - [OpenAPI specification](https://developer.nationwide.co.uk/sites/default/files/apidoc_specs/Utility_prd_r13_2.yaml) - [Postman collection](https://www.postman.com/api-evangelist/workspace/uk-public-banking/environment/35240-27c90b6a-a5c4-4cb6-b810-f4f89b14b471) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Nationwide recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 394 ms, with median latency at 162 ms\. - Infrastructure fingerprinting identifies Amazon Technologies Inc\. in the observed delivery path\. - Developer\-facing integration resources are available for this benchmark subject\. ## Key facts - Nationwide domain: openapi\.nationwide\.co\.uk\. - Operational state: healthy\. - CASC score: 9\.41\. - Pass rate: 100\.00%\. - p95 latency: 394 ms\. - Developer documentation: https://www\.nationwidedeveloper\.co\.uk\. - Postman collection: https://www\.postman\.com/api\-evangelist/workspace/uk\-public\-banking/environment/35240\-27c90b6a\-a5c4\-4cb6\-b810\-f4f89b14b471\. - OpenAPI specification: https://developer\.nationwide\.co\.uk/sites/default/files/apidoc\_specs/Utility\_prd\_r13\_2\.yaml\. ## Primary entities - APIContext - Nationwide - openapi\.nationwide\.co\.uk - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/nationwide.json) - [Developer documentation](https://www.nationwidedeveloper.co.uk) - [OpenAPI specification](https://developer.nationwide.co.uk/sites/default/files/apidoc_specs/Utility_prd_r13_2.yaml) --- # NatWest Group Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/natwest-group Source: static Updated: 2026-10-19T15:15:15.051Z Description: NatWest Group benchmark detail for openapi\.rbs\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary NatWest Group is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 9\.25 CASC score, 100\.00% pass rate, 299 ms median latency, and 779 ms p95 latency\. ## Stats - 9\.25 CASC score - 100\.00% pass rate - 299 ms median latency - 779 ms p95 latency - healthy operational state ## Page sections ### NatWest Group benchmark detail Category: Subject NatWest Group is measured as part of UK Banks\. This page summarizes operational signals for openapi\.rbs\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: openapi\.rbs\.co\.uk\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 23\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 28\.25 ms\. - TCP connection: 12\.75 ms\. - TLS handshake: 29\.25 ms\. - Processing: 186 ms\. - Download: 22\.75 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: Google LLC\. - Nameserver: Google LLC\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/natwest-group.json) - [Developer documentation](https://www.bankofapis.com) - [Postman collection](https://www.postman.com/apievangelist/workspace/uk-public-banking/environment/35240-3cd6effb-e600-467f-9ae1-f84053d6099a) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - NatWest Group recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 779 ms, with median latency at 299 ms\. - Infrastructure fingerprinting identifies Google LLC in the observed delivery path\. ## Key facts - NatWest Group domain: openapi\.rbs\.co\.uk\. - Operational state: healthy\. - CASC score: 9\.25\. - Pass rate: 100\.00%\. - p95 latency: 779 ms\. - Developer documentation: https://www\.bankofapis\.com\. - Postman collection: https://www\.postman\.com/apievangelist/workspace/uk\-public\-banking/environment/35240\-3cd6effb\-e600\-467f\-9ae1\-f84053d6099a\. ## Primary entities - APIContext - NatWest Group - openapi\.rbs\.co\.uk - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/natwest-group.json) - [Developer documentation](https://www.bankofapis.com) --- # Santander Operational Intelligence Canonical URL: https://apicontext.com/api-directory/ukbanks/santander Source: static Updated: 2026-10-19T15:15:15.051Z Description: Santander benchmark detail for openbanking\.santander\.co\.uk, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Santander is a banking\-api benchmark subject in UK Banks\. Latest snapshot metrics include 9\.53 CASC score, 100\.00% pass rate, 55 ms median latency, and 390 ms p95 latency\. ## Stats - 9\.53 CASC score - 100\.00% pass rate - 55 ms median latency - 390 ms p95 latency - healthy operational state ## Page sections ### Santander benchmark detail Category: Subject Santander is measured as part of UK Banks\. This page summarizes operational signals for openbanking\.santander\.co\.uk, including quality, reliability, latency, and infrastructure context\. - Domain: openbanking\.santander\.co\.uk\. - Category: UK Banks\. - Benchmark subject type: banking\-api\. - Monitored count: 8\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 13\.5 ms\. - TCP connection: 4\.5 ms\. - TLS handshake: 7 ms\. - Processing: 8\.75 ms\. - Download: 8\.25 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: NeuStar, Inc\.\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/santander.json) - [Developer documentation](https://developer.santander.co.uk) - [Postman collection](https://www.postman.com/apievangelist/workspace/uk-public-banking/environment/35240-f6ff0a13-a8cc-44bb-a201-9e58fe16abfa) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Santander recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 390 ms, with median latency at 55 ms\. ## Key facts - Santander domain: openbanking\.santander\.co\.uk\. - Operational state: healthy\. - CASC score: 9\.53\. - Pass rate: 100\.00%\. - p95 latency: 390 ms\. - Developer documentation: https://developer\.santander\.co\.uk\. - Postman collection: https://www\.postman\.com/apievangelist/workspace/uk\-public\-banking/environment/35240\-f6ff0a13\-a8cc\-44bb\-a201\-9e58fe16abfa\. ## Primary entities - APIContext - Santander - openbanking\.santander\.co\.uk - UK Banks - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/ukbanks/santander.json) - [Developer documentation](https://developer.santander.co.uk) --- # Weather Services Benchmark Intelligence Canonical URL: https://apicontext.com/api-directory/weather Source: static Updated: 2026-10-19T15:15:15.051Z Description: Latest verified snapshot covers 2 benchmark subjects in Weather Services, with median latency signals and reliability measurements normalized for comparison\. ## Summary Latest verified snapshot covers 2 benchmark subjects in Weather Services, with median latency signals and reliability measurements normalized for comparison\. ## Stats - 2 benchmark subjects - 8\.71 average CASC - 231\.5 ms average median latency - W2026\-10\-12 snapshot ## Page sections ### Weather Services benchmark slice Category: Category Latest verified snapshot covers 2 benchmark subjects in Weather Services, with median latency signals and reliability measurements normalized for comparison\. - 2 subjects are normalized in this category\. - Benchmark subject type: api\-provider\. - Average pass rate: 99\.85%\. - Latest snapshot: W2026\-10\-12\. ### Measured providers and services Category: Subjects Open a subject page for detailed operational intelligence including CASC score, pass rate, tail latency, regional signals, infrastructure metadata, and citation links\. - [Open Weather — 8\.74 CASC, 100\.00% pass, 422 ms p95](/api-directory/weather/open-weather) - [Pirate Weather — 8\.68 CASC, 99\.70% pass, 1,183 ms p95](/api-directory/weather/pirate-weather) ## Key facts - 2 benchmark subjects are included in Weather Services\. - Average CASC score: 871\. - Average median latency: 231\.5 ms\. - Benchmark subject type: api\-provider\. - Latest snapshot: W2026\-10\-12\. ## Primary entities - APIContext - Weather Services - Benchmark Intelligence - Operational Intelligence - api\-provider ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Category JSON](/api-directory/data/latest/categories/weather.json) - [Latest catalog](/api-directory/data/latest/catalog.json) - [Compare subjects](/api-directory/compare) --- # Open Weather Operational Intelligence Canonical URL: https://apicontext.com/api-directory/weather/open-weather Source: static Updated: 2026-10-19T15:15:15.051Z Description: Open Weather benchmark detail for api\.openweathermap\.org, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Open Weather is a api\-provider benchmark subject in Weather Services\. Latest snapshot metrics include 8\.74 CASC score, 100\.00% pass rate, 69 ms median latency, and 422 ms p95 latency\. ## Stats - 8\.74 CASC score - 100\.00% pass rate - 69 ms median latency - 422 ms p95 latency - healthy operational state ## Page sections ### Open Weather benchmark detail Category: Subject Open Weather is measured as part of Weather Services\. This page summarizes operational signals for api\.openweathermap\.org, including quality, reliability, latency, and infrastructure context\. - Domain: api\.openweathermap\.org\. - Category: Weather Services\. - Benchmark subject type: api\-provider\. - Monitored count: 2\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 5\.77 ms\. - TCP connection: 91\.82 ms\. - TLS handshake: 0 ms\. - Processing: 98\.27 ms\. - Download: 0 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: DigitalOcean, LLC\. - Nameserver: Amazon\.com, Inc\.\. - Server: openresty\. - [Subject JSON](/api-directory/data/latest/subjects/weather/open-weather.json) - [Developer documentation](https://openweathermap.org/api) - [Postman collection](https://www.postman.com/crimson-station-599498/workspace/openweather/overview) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Open Weather recorded 100% pass rate in the latest verified snapshot\. - The p95 latency signal is 422 ms, with median latency at 69 ms\. - Infrastructure fingerprinting identifies DigitalOcean, LLC in the observed delivery path\. ## Key facts - Open Weather domain: api\.openweathermap\.org\. - Operational state: healthy\. - CASC score: 8\.74\. - Pass rate: 100\.00%\. - p95 latency: 422 ms\. - Developer documentation: https://openweathermap\.org/api\. - Postman collection: https://www\.postman\.com/crimson\-station\-599498/workspace/openweather/overview\. ## Primary entities - APIContext - Open Weather - api\.openweathermap\.org - Weather Services - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/weather/open-weather.json) - [Developer documentation](https://openweathermap.org/api) --- # Pirate Weather Operational Intelligence Canonical URL: https://apicontext.com/api-directory/weather/pirate-weather Source: static Updated: 2026-10-19T15:15:15.051Z Description: Pirate Weather benchmark detail for api\.pirateweather\.net, including CASC score, latency anatomy, infrastructure fingerprinting, and developer resources\. ## Summary Pirate Weather is a api\-provider benchmark subject in Weather Services\. Latest snapshot metrics include 8\.68 CASC score, 99\.70% pass rate, 394 ms median latency, and 1,183 ms p95 latency\. ## Stats - 8\.68 CASC score - 99\.70% pass rate - 394 ms median latency - 1,183 ms p95 latency - stable operational state ## Page sections ### Pirate Weather benchmark detail Category: Subject Pirate Weather is measured as part of Weather Services\. This page summarizes operational signals for api\.pirateweather\.net, including quality, reliability, latency, and infrastructure context\. - Domain: api\.pirateweather\.net\. - Category: Weather Services\. - Benchmark subject type: api\-provider\. - Monitored count: 1\. - Latest snapshot: W2026\-10\-12\. ### Latency anatomy Category: Latency Latency anatomy breaks the request into network and processing phases so agents can reason about whether delay is likely DNS, connection, TLS, server processing, or transfer related\. - DNS: 95\.09 ms\. - TCP connection: 93\.18 ms\. - TLS handshake: 96\.09 ms\. - Processing: 302 ms\. - Download: 41\.64 ms\. ### Infrastructure fingerprint Category: Infrastructure Infrastructure fields identify the observable delivery layer for the benchmark subject where that data is available\. - CDN: not available\. - Hosting provider: not available\. - Nameserver: not available\. - Server: not available\. - [Subject JSON](/api-directory/data/latest/subjects/weather/pirate-weather.json) ### Benchmark interpretation Category: Interpretation Generated interpretation from the latest verified snapshot\. - Pirate Weather recorded 99\.7% pass rate in the latest verified snapshot\. - The p95 latency signal is 1183 ms, with median latency at 394 ms\. ## Key facts - Pirate Weather domain: api\.pirateweather\.net\. - Operational state: stable\. - CASC score: 8\.68\. - Pass rate: 99\.70%\. - p95 latency: 1,183 ms\. ## Primary entities - APIContext - Pirate Weather - api\.pirateweather\.net - Weather Services - Benchmark Intelligence - Infrastructure Intelligence ## Audience - API teams - SRE teams - researchers - AI retrieval systems ## Primary links - [Subject JSON](/api-directory/data/latest/subjects/weather/pirate-weather.json) --- # Knowledge Base Canonical URL: https://apicontext.com/api-knowledge-base Source: static Description: Everything you need to know about APIs and APIContext — how APIs work, why they matter, and how to test and monitor them\. ## Summary Everything you need to know about APIs and APIContext — how APIs work, why they matter, and how to test and monitor them\. ## Page sections ### Browse Knowledge Base Category: Catalog Everything you need to know about APIs and APIContext — how they work, why they matter, and how to test and monitor them\. - [API Testing: Frequently Asked Questions](/api-knowledge-base/api-testing) - [What Is An API?](/api-knowledge-base/what-is-an-api) - [RESTful APIs Explained](/api-knowledge-base/restful-apis) - [Cloud APIs](/api-knowledge-base/apis/cloud-api) - [API Examples](/api-knowledge-base/api-examples) - [REST API](/api-knowledge-base/rest-api) - [Bank APIs](/api-knowledge-base/apis/bank-api) - [Understanding the API Economy](/api-knowledge-base/apis) - [API Monitoring Basics](/api-knowledge-base/api-monitoring) - [API Tutorials](/api-knowledge-base/api-tutorials) - [Government APIs](/api-knowledge-base/apis/government-api) - [Open APIs](/api-knowledge-base/apis/open-api) ### Browse Understanding APIs Category: Foundations A guide to the API ecosystem, critical monitoring technologies, and how APIContext fits into your DevOps world\. - [API Gateway](/understanding-api/api-gateway) - [API Ratings](/understanding-api/api-ratings) - [API Monitoring For Dummies](/understanding-api/api-monitoring-for-dummies) - [Service Level Objectives](/understanding-api/service-level-objectives-and-slas) - [APIContext Global Coverage](/understanding-api/apimetrics-global-coverage) - [Advanced API Monitoring](/understanding-api/advanced-api-monitoring) - [Why API Monitoring – Problems](/understanding-api/why-api-monitoring-problems) - [KPIs for APIs – Key Performance Indicators](/understanding-api/api-kpis) - [CASC – Cloud API Service Consistency Score](/understanding-api/casc-score-cloud-api-service-consistency) - [SLA for APIs: Monitoring Your API SLA \(Service Level Agreement\)](/understanding-api/api-sla-management) ### Browse APIContext User Guide Category: Product Guides to APIContext features and services, including Open Banking monitoring, SLA tracking, and more\. - [API Monitoring Frequency – how much is too much?](/apicontext-user-guide/api-monitoring-frequency-how-much-is-too-much) - [Tutorial: Handling Microsoft Graph API Auth](/apicontext-user-guide/microsoft_graph_api_auth) - [Customer Case Studies](/apicontext-user-guide/customer-case-studies) - [APIContext Case Study Power Utility](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-power-utility) - [APIContext Case Study Government APIs](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-government-apis) - [Automated Postman Collection Monitoring](/apicontext-user-guide/automated-postman-collection-monitoring) - [Make an API Call](/apicontext-user-guide/make-an-api-call) - [APIContext AI\-Based Reporting and Analytics](/apicontext-user-guide/apicontext-ai-based-reporting-and-analytics) - [Easy DNS Monitoring with APIContext](/apicontext-user-guide/easy-dns-monitoring-with-apimetrics) - [Tutorial: Schedule API Calls](/apicontext-user-guide/tutorial-scheduling-api-calls) - [Types of API Calls](/apicontext-user-guide/types-api-calls) - [PSD2](/apicontext-user-guide/psd2) - [API Monitoring Features](/apicontext-user-guide/features-2) - [Who Uses APIContext](/apicontext-user-guide/who-uses-apimetrics) - [White Papers](/apicontext-user-guide/customer-case-studies/white-papers) ### Browse Free API Tools Category: Tools Free API tools and datasets from APIContext: performance dashboards, regional data, and reference test servers\. - [Cross Cloud API Latency Analysis](/apimetrics-free-api-tools-resources/cross-cloud-api-latency-analysis) - [HTTPbin Network](/apimetrics-free-api-tools-resources/free-test-api) - [US Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/us-government-api-rating-dashboard) - [UK Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/uk-government-api-rating-dashboard) - [Social Networking API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/social-networking-api-rating-dashboard) - [Search API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/search-api-rating-dashboard) - [PSD2 Sandbox API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/psd2-sandbox-api-rating-dashboard) - [Cryptocurrency Exchange API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/cryptocurrency-exchange-api-rating-dashboard) - [COVID19 API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/covid19-api-rating-dashboard) - [Corporate API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/corporate-api-rating-dashboard) - [CMA9 Open Data API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/cma9-open-data-api-rating-dashboard-2) - [API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards) ### Everything you needed to know about APIs and APIContext \(but were afraid to ask\) If you’re even marginally around the tech world, you’ve probably heard of APIs\. They’re an integral part of pretty much everything you do online, whether it’s on a computer or in an app\. So, it’s natural that you want to know more about them\. Our API Information Knowledge Base is designed to help guide you through\. For example – what the heck is an API? What kinds of API data are there? How can you test it before you go live, and how can you monitor an API to make sure it’s doing what you want it to do? And what is something called REST?\! Sounds like it’s slacking off\. So, you have questions\. And lucky for you, here at APIContext, we’ve got answers\. Answers to questions you were embarrassed to ask, and even some questions you didn’t know you needed to ask\. So without further ado, please check out our knowledge base, linked to the left\. And make sure to visit every once in a while, as we’ll be adding more so you can talk about APIs with confidence – no matter who you are\! Even if it’s your job to explain them to others, these articles might give you some help in doing so\. They’re written for people who are not experts\. And if you want to know about some specific we haven’t covered here, then just let us know – we’re here to help\. Happy reading\! ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Everything you needed to know about APIs and APIContext \(but were afraid to ask\) - Ready To Start Monitoring? - API Testing: Frequently Asked Questions - What Is An API? - RESTful APIs Explained - Cloud APIs - API Examples - REST API - Bank APIs - Understanding the API Economy - API Gateway - API Ratings - API Monitoring For Dummies - Service Level Objectives - APIContext Global Coverage - Advanced API Monitoring - Why API Monitoring – Problems - KPIs for APIs – Key Performance Indicators - API Monitoring Frequency – how much is too much? - Tutorial: Handling Microsoft Graph API Auth - Customer Case Studies - APIContext Case Study Power Utility - APIContext Case Study Government APIs - Automated Postman Collection Monitoring - Make an API Call - APIContext AI\-Based Reporting and Analytics - Cross Cloud API Latency Analysis - HTTPbin Network - US Government API Ratings Dashboards - UK Government API Ratings Dashboards - Social Networking API Ratings Dashboards - Search API Ratings Dashboards - PSD2 Sandbox API Ratings Dashboards - Cryptocurrency Exchange API Ratings Dashboards - Everything you needed to know about APIs and APIContext \(but were afraid to ask\) If you’re even marginally around the tech world, you’ve probably heard of APIs\. - They’re an integral part of pretty much everything you do online, whether it’s on a computer or in an app\. - So, it’s natural that you want to know more about them\. ## Primary entities - APIContext - API Knowledge Base - Knowledge Base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base) - [API Testing: Frequently Asked Questions](/api-knowledge-base/api-testing) - [What Is An API?](/api-knowledge-base/what-is-an-api) - [RESTful APIs Explained](/api-knowledge-base/restful-apis) - [Cloud APIs](/api-knowledge-base/apis/cloud-api) - [API Examples](/api-knowledge-base/api-examples) - [REST API](/api-knowledge-base/rest-api) - [API Gateway](/understanding-api/api-gateway) - [API Ratings](/understanding-api/api-ratings) - [API Monitoring For Dummies](/understanding-api/api-monitoring-for-dummies) - [Service Level Objectives](/understanding-api/service-level-objectives-and-slas) - [APIContext Global Coverage](/understanding-api/apimetrics-global-coverage) - [Advanced API Monitoring](/understanding-api/advanced-api-monitoring) - [API Monitoring Frequency – how much is too much?](/apicontext-user-guide/api-monitoring-frequency-how-much-is-too-much) - [Tutorial: Handling Microsoft Graph API Auth](/apicontext-user-guide/microsoft_graph_api_auth) - [Customer Case Studies](/apicontext-user-guide/customer-case-studies) - [APIContext Case Study Power Utility](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-power-utility) - [APIContext Case Study Government APIs](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-government-apis) - [Automated Postman Collection Monitoring](/apicontext-user-guide/automated-postman-collection-monitoring) - [Cross Cloud API Latency Analysis](/apimetrics-free-api-tools-resources/cross-cloud-api-latency-analysis) - [HTTPbin Network](/apimetrics-free-api-tools-resources/free-test-api) - [US Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/us-government-api-rating-dashboard) - [UK Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/uk-government-api-rating-dashboard) - [Social Networking API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/social-networking-api-rating-dashboard) - [Search API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/search-api-rating-dashboard) --- # API Performance Examples Canonical URL: https://apicontext.com/api-knowledge-base/api-examples Source: static Description: If some companies just made a little more effort and investment in their APIs, the results of these API examples would look very different\. ## Summary If some companies just made a little more effort and investment in their APIs, the results of these API examples would look very different\. ## Page sections ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - Every website in the world uses APIs\. - Some are far better than others\. - When your API isn’t doing its job correctly, users get a less than great experience\. ## Primary entities - APIContext - API Examples - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/api-examples) --- # API Monitoring Basics Canonical URL: https://apicontext.com/api-knowledge-base/api-monitoring Source: static Description: API monitoring looks at how users actually interact with your API, so you can build solutions that match real\-world usage\. ## Summary API monitoring looks at how users actually interact with your API, so you can build solutions that match real\-world usage\. ## Page sections ### Doing API Monitoring Right The best practices for API monitoring are going to vary by industry and can run into some problems internally – like, for example, what do you do if the internal risk teams don’t want you to monitor? \(We’ll come back to that in another article…\) However, there are some key principles we go by that we want to share here with some tips on doing it right, even if you don’t use APIContext\. ### Monitor 24/7 Services go down when you’re not looking, so having heartbeat monitoring is essential – 24/7 365 days a year, have all of your API endpoints exercised by an external call\. It doesn’t have to be high frequency, in fact we suggest to customers that anything from 5\-10 times an hour for functional testing and maybe only once per hour for security and OAuth monitoring is enough\. But they key thing is this – it needs to be a real call from somewhere outside your stack\. ### External NOT Internal It really doesn’t matter if your gateway is up, or your backend is running if an actual person calling the API is getting some kind of error, or, worse, can’t even get to the API itself\. So monitor externally, set up real API calls, using real security to real resources that run around the clock\. Also the whole world isn’t on AWS, so stop using products that think it is\. ### Cover Everything Do the little used things as well as the stuff that’s used all the time\. You never know when a resource has been turned off without somebody realizing it and you only find out when a customer tries to do something essential for them that they only do once a week\. An example from a customer – an expenses reporting API went down and they only realized when people filed their expenses on a Friday, of a holiday weekend\. ### HTTP Codes Are Not Magic HTTP 200 All Ok… right? Well, not so much – the dirty secret of the API industry is this\. HTTP codes lie\. HTTP 200 especially so\. Worse offenders are SOAP APIs pretending to be REST APIs where the error is buried in what looks like a pass\. This can be tricky and we’ll have a whole article on this, spotting the situation can take some work but it’s well worth it – look our for changes in the size of content returned by the APIs as a first clue – if you usually get 500kb back and occasionally it’s only 100kb or even 2\-3 bytes, then you’re possible getting an error or failure\. ### Did We Say That? A MUCH overlooked part of API monitoring is what exactly it is you’re monitoring\. As the story goes, you see somebody under a street light looking around, you offer help and they say they lost their car keys\. You start looking and say where did they last see them, and they say over in the woods\. When you stop and ask why they’re looking here, they say, “because the light is here…” – so, part of monitoring is monitoring the service you say you provide NOT what you know you deliver\. ### API Monitoring for Dummies Best Practice Top 10 We’d suggest the following are the absolute MINIMUM items to monitor on a regular basis AND have alerts set up to tell you when something goes wrong\. • Regular API monitoring heart beat checks from multiple locations • Set up assertion/condition checks on the returned content to validate that what you get back is what you expected and trigger warnings and alerts on those accordingly • Hit the production endpoints using the same security as your external users use • Look at the statistical spread of latency results not just the averages – what are your q95 and q99 values? • Have alerting set up for failures and issues • Double check what 4XX errors are telling you – a 4XX error often is ignored as a problem elsewhere in the stack, but with APIs while it might mean you’ve got your security wrong, it could indicated that something outside your control has been shut down – there can be a world of difference in the API space between a 401 – unauthorized and a 404 Not Found • Monitor that your API Security is doing what you think it is? Going back to 6, if you’re meant to return a 401 error if you hit the API with an invalid Scope or Token, do you? • Don’t worry, too much, about one off events, look at trends and groups of issues • SLOW isn’t always as bad as inconsistent – people can cope with slow, you can build it into your service – but if your service is inconsistent then that’s hard for you and end\-users • Look for odd geographical or cloud issues – if you’re on Azure but all your users are on AWS, don’t assume that Amazon and Microsoft are doing all the hard work for you on the networking side of things – look at those performance numbers and take steps to remedy what you see API monitoring is often used as a check box exercise to be able to say you do it, or it’s done in a perfunctory way\. It doesn’t have to be hard or as in depth as your test coverage but if you’re not monitoring the APIs you use or provide you are going to building up problems for your business and customers\. ### Here to help Never forget, we’re here to help – we’ve been involved in API monitoring and performance measurement since before people realized it was a problem and we have the best tools available to deliver the data you didn’t even know you needed\. ### API Monitoring See how APIContext monitors the APIs you rely on and provides peace of mind\. ### API Performance See what metrics you can identify with your APIs and learn how things work\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ### Take a Detailed Look Download a detailed introduction to APIContext and learn how we are bringing common standards to API monitoring with integrated monitoring, performance assurance and compliance analysis\! ## Key facts - Doing API Monitoring Right - Monitor 24/7 - External NOT Internal - Cover Everything - HTTP Codes Are Not Magic - Did We Say That? - API Monitoring for Dummies Best Practice Top 10 - Here to help - So why API Monitoring? - after all, you’ve coded your service, API, app or whatever and why do we need API monitoring for dummies? - It’s up and running\. ## Primary entities - APIContext - API Monitoring Basics - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/api-monitoring) --- # API Testing FAQs Canonical URL: https://apicontext.com/api-knowledge-base/api-testing Source: static Description: In API testing you test the various components of the API both directly and in action with the site itself\. ## Summary In API testing you test the various components of the API both directly and in action with the site itself\. ## Page sections ### API Testing: The Basics API testing is a broad topic and can include a variety of stages when you would test, functionality and components and metrics to track and a lot of different options on how that can impact your overall API Governance strategy\. Some of the testing areas include: • The core functionality of the API • Seeing how the API functions in a broader sense in the real world – i\.e\. outside in • How big a load the API can handle – stress testing and load testing • Runtime error tests – functional validation of the API • Performance tests – how well does it function speed wise • Security testing – are you likely to hit any BOLA or OWASP top 10 issues • Ongoing operational monitoring ### API Testing: The Basics API testing is a broad topic and can include a variety of stages when you would test, functionality and components and metrics to track and a lot of different options on how that can impact your overall API Governance strategy\. Some of the testing areas include: • The core functionality of the API • Seeing how the API functions in a broader sense in the real world – i\.e\. outside in • How big a load the API can handle – stress testing and load testing • Runtime error tests – functional validation of the API • Performance tests – how well does it function speed wise • Security testing – are you likely to hit any BOLA or OWASP top 10 issues • Ongoing operational monitoring ### What Is An API And How Is It Used? An API is a program or product that allows a website or app to communicate with the end user\. It does so in the background\. It takes a data request from the user, sends it to the site or app, grabs the data that it needs and returns it to the user\. It does all of this in the background and does not leave either the user or the website data exposed\. An API is like a waiter or waitress at a restaurant taking an order from a customer to the kitchen and coming back with food\. ### Types of Testing? That will depend on your needs, whether you are using a RESTful or SOAP API and your budget\. You should research the various API tools listed above and figure out which one will work best for you\. That said, why don’t you try us out and go straight from testing your APIs to monitoring them too? ### What to Test? For the most part, you test the same things for SOAP APIs as you do for RESTful ones\. The exceptions are SOAP APIs must test for WS compliance and interoperability\. ### What Tools Are Used For API Testing? API Testing can be done using various free and premium tools\. Here are some of the most popular: • APIContext • Postman • ChecklyHQ • HTTPie • Blazemeter • Smartbear ### How is testing different to monitoring? We’re glad you asked\. A test tells you everything was working on the day you took it\. It doesn’t tell you that all the bits stayed working, or work for your customers or a million other things\. That’s why monitoring after you’ve deployed is essential\. ### Make an API Call See how you can make an API call with APIContext and learn about what goes into it\. ### APIContext Testing See how APIContext can be used to test your critical APIs and identify issues\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Testing: The Basics - What Is An API And How Is It Used? - Types of Testing? - What to Test? - What Tools Are Used For API Testing? - How is testing different to monitoring? - Make an API Call - API Testing: The Basics API testing is a broad topic and can include a variety of stages when you would test, functionality and components and metrics to track and a lot of different options on how that can impact your overall API Governance strategy\. - Some of the testing areas include: • The core functionality of the API • Seeing how the API functions in a broader sense in the real world – i\.e\. - outside in • How big a load the API can handle – stress testing and load testing • Runtime error tests – functional validation of the API • Performance tests – how well does it function speed wise • Security testing – are you likely to hit any BOLA or OWASP top 10 issues • Ongoing operational monitoring API Testing: The Basics API testing is a broad topic and can include a variety of stages when you would test, functionality and components and metrics to track and a lot of different options on how that can impact your overall API Governance strategy\. ## Primary entities - APIContext - API Testing: Frequently Asked Questions - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/api-testing) --- # API Tutorials Canonical URL: https://apicontext.com/api-knowledge-base/api-tutorials Source: static Description: Creating and using APIs doesn’t have to be that hard\. We scoured the web and found some of the best API tutorials around that can help you get started\. ## Summary Creating and using APIs doesn’t have to be that hard\. We scoured the web and found some of the best API tutorials around that can help you get started\. ## Page sections ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - So, you’re a web developer\. - You want to create the best website or app possible for your company\. - You know that the way to do this is through APIs\. ## Primary entities - APIContext - API Tutorials - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/api-tutorials) --- # APIs: Understanding the API Economy Canonical URL: https://apicontext.com/api-knowledge-base/apis Source: static Description: APIs are an integral part of nearly everything you do online — on a computer or in an app\. Here's what you need to know\. ## Summary APIs are an integral part of nearly everything you do online — on a computer or in an app\. Here's what you need to know\. ## Page sections ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - APIs have grown exponentially over the last 10 years, from a virtually known technology a decade ago, to the core base of pretty much everything we do online and in places you’ve probably not even realized\. - We’re going to cover some of the sectors using APIs and how they’re using them\. - When you’re finished, check out the details of what we do for a sector that might impact your life or business in more detail to see how we can help directly\. ## Primary entities - APIContext - Understanding the API Economy - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/apis) --- # Bank APIs Canonical URL: https://apicontext.com/api-knowledge-base/apis/bank-api Source: static Description: They are the building blocks of any online transaction with the bank\. Let’s take a look at some common bank API issues\. ## Summary They are the building blocks of any online transaction with the bank\. Let’s take a look at some common bank API issues\. ## Page sections ### What Is A Bank API? The core problem with any banking site or app is that customers need to get information, and so does the bank\. But they only need a limited amount of information\. The bank doesn’t want too much data to go to the customer\. Neither does the customer want to overshare with the bank\. A bank API solves this problem\. It takes information from either the bank or the customer, transmits the data to the other party, and doesn’t access any other data on either end\. It doesn’t puncture either side’s security protocols\. This provides a perfect system for everyone involved and allows the business of the bank to operate without risk of intrusions\. When it comes to dealing with websites or apps for banks, understanding how their APIs work is crucial\. Banking APIs and open banking APIs are what make these apps run well, be able to communicate with each other and become secure\. They are the building blocks of any online transaction with the bank\. Let’s take a look at some common bank API issues\. ### What Does Open Banking Mean? Open banking is a system that uses APIs to allow customers and potential customers to access the data of financial institutions\. It means that larger banks are made to be competitive with smaller banks\. Open banking standards regulate how financial data should be shared and accessed\. More importantly, open banking requires banks have a system in place to notice unforeseen overdrafts and provide customers with a period of time to correct them without facing additional charges or fees\. In addition, open banking allows customers to see what impact a new debt would have on their lives\. It also allows banks to view a customer’s entire credit and income history so they can tailor debts to their needs\. Across the world, financial services regulators are waking up to the issues of Open Banking and providing significant monitoring and compliance requirements on banks, Third Party Payment processors \(TPPs\) and Account Information Service Providers \(AISPs\)\. These are regations like those created for PSD2\. ### What Is API In Trading? APIs are essential when it comes to trading nearly anything online\. Whether cash, stocks, bonds or whatever banking APIs are what get the job done\. They provide live streaming prices, trade execution, advanced order types and various related tasks on both sites and apps\. They operate in the background so you can’t see them but whenever you research or execute a trade they are there making it happen\. If you are developing a trading site or a site to advise traders you can find open APIs that you can insert into you code to make it happen smoothly and without any lag on the end for your customer\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What Is A Bank API? - What Does Open Banking Mean? - What Is API In Trading? - Ready To Start Monitoring? - When it comes to dealing with websites or apps for banks, understanding how bank APIs work is crucial\. - Bank APIs and open banking APIs are what make these apps run well, communicate with each other, and stay secure\. - They are the building blocks of any online transaction with the bank\. ## Primary entities - APIContext - Bank APIs - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/apis/bank-api) --- # Cloud APIs Canonical URL: https://apicontext.com/api-knowledge-base/apis/cloud-api Source: static Description: If your business uses the cloud, you'll need to work with cloud APIs\. Here's how to get your head around the concept\. ## Summary If your business uses the cloud, you'll need to work with cloud APIs\. Here's how to get your head around the concept\. ## Page sections ### What Is Meant By a Cloud API? A cloud API is a program that acts as a gateway to the cloud from your website or app\. In that sense it is the cornerstone or backbone of any public cloud based system\. It provides both the direct and indirect infrastructure to cloud users\. A cloud API will allocate computing, storage, and network resources for requested cloud applications\. It is the gateway to the cloud and from the cloud back to your website or app\. ### What Is The Role Of APIs In Cloud Computing? Like with normal APIs cloud APIs facilitate the back and forth sending of data\. They allow you to access the cloud and allow the cloud to send information back to you\. There are three primary ways in which they do this: • Infrastructure as a Service \(IaaS\): Infrastructure APIs provision raw computing and storage\. • Software as a Service \(SaaS\): Software or application APIs provision connectivity and interaction with a software suite\. • Platform as a Service \(PaaS\): Platform APIs provide backend architecture for building intensive and feature rich applications\. ### What Is The Use Of APIs In Cloud Services? As we mentioned earlier, APIs send information back and forth\. Think of being in a restaurant\. You don’t go directly to the kitchen\. Instead you place your order with a waiter or waitress\. The server is this analogy is the API\. He or she goes to the kitchen with your information and then brings back what you were looking for\. A cloud API is basically doing the same thing, but the cloud itself is the kitchen\. This may seem simple but accessing the cloud in the background is essential\. When a cloud API is used correctly, you don’t notice it\. It simply does its job\. In addition a cloud API only accesses the data it needs on both ends\. In other words, it doesn’t compromise the entire cloud\. It also does not compromise your users’ data\. It works to only access the data it needs to get the job done\. Photo courtesy of Sergio Russo ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What Is Meant By a Cloud API? - What Is The Role Of APIs In Cloud Computing? - What Is The Use Of APIs In Cloud Services? - Ready To Start Monitoring? - Cloud APIs have taken over the entire world, from controlling light bulbs, to even controlling your smart TV\. - But what is a Cloud API? - If your business wants to use the cloud in any way, you are going to have to work with cloud APIs\. ## Primary entities - APIContext - Cloud APIs - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/apis/cloud-api) --- # Government APIs Canonical URL: https://apicontext.com/api-knowledge-base/apis/government-api Source: static Description: What are we talking about when we discuss API data? When it comes to government APIs we are talking about publicly available information\. ## Summary What are we talking about when we discuss API data? When it comes to government APIs we are talking about publicly available information\. ## Page sections ### Data API Definition What are we talking about when we discuss API data? When it comes to government APIs we are talking about publicly available information\. This is nearly all data that is collected by the government\. Your tax dollars pay for it to be collected so you own it\. API data is simply that information on government servers that your website or app can access and then send out to your customers\. For example say you are running a license plate look up site\. The data would be that connected to the license plates that you can send to your customers\. ### Open Data API When you get the API from the government it may not be exactly what you need for your site or app\. That’s why it’s great that government APIs are open\. You can modify them yourself\. Or you can look online to see if someone else has already modified it for your needs\. Because APIs from the government are open, you can use and alter them as you like\. ### Free API The good news is that all government APIs will be free for you to use\. You just have to find the code online and plug it into your site or app\. Governments make their APIs free so that people use the right ones\. They don’t want false or misleading data getting out there\. Therefore they build free APIs put them online and let developers find them\. To start looking for free government APIs, begin here \. If you follow the links, you should be able to find the one that will work the best for your site or app\. All of the APIs you will find should be at no cost to you\. If you find a site that is trying to charge you for a government API walk away from that site\. They are ripping you off\. ### City Data API Cities are where you are probably going to really want government APIs\. Every city is going to collect and disseminate data in a different way\. Therefore you don’t want to have to write your own generic API and then modify it for every city\. Instead you want to get their own official API and incorporate it into your code\. This will also help when the city inevitably updates their method of giving out data\. Their own API will update itself withing your code\. Photo courtesy of justgrimes ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Data API Definition - Open Data API - Free API - City Data API - Ready To Start Monitoring? - As you build your website or app you may find the need to link to government resources online\. - You could want to help people register to vote, or to find information about parking services in a given town\. - Or, you may want to keep people up to date about what’s going on in a given courthouse\. ## Primary entities - APIContext - Government APIs - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/apis/government-api) --- # Open APIs Canonical URL: https://apicontext.com/api-knowledge-base/apis/open-api Source: static Description: Use Open API software instead of building from scratch — save time and money with tools others have already built\. ## Summary Use Open API software instead of building from scratch — save time and money with tools others have already built\. ## Page sections ### What Is Open API? Open API simply refers to API code that has already been written and is available for the public to use\. Developers of all sorts created them and put them on the web so people can put it directly into their code\. It carries no licenses or restrictions\. It is totally free for people to use when developing their sites or apps\. ### What Are Open API Specifications? The Open API specifications – formerly known as the Swagger Specifications – are a set of rules that define the API itself\. The specifications let users describe, produce, consume and visualize RESTful APIs\. In layman’s terms, the specifications tell you what to expect and how to use the API \. ### Open API List Searching for open APIs can be a challenge\. Luckily, there are sites that have curated general open APIs, and you can search them\. On these lists, all of the open APIs meet current specifications and can be used\. Probably the best list to start with is provided by Git Hub \. API List is another great resource\. ### What Is Swagger API Used For? Swagger is the term for the tools used to implement open APIs\. In other words they allow you to view, edit and put open APIs into your programming code\. Most Swagger tools are free for the public to use\. Some of them may cost a minor fee\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What Is Open API? - What Are Open API Specifications? - Open API List - What Is Swagger API Used For? - Ready To Start Monitoring? - Developing websites and apps these days means understanding how to use APIs\. - They send data from your customer to your site and then back again\. - APIs are the key to making websites and apps do what they are supposed to do\. ## Primary entities - APIContext - Open APIs - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/apis/open-api) --- # REST API Canonical URL: https://apicontext.com/api-knowledge-base/rest-api Source: static Description: What is a REST API, why you probably want it for your website, and how it lets your site talk to the outside world\. ## Summary What is a REST API, why you probably want it for your website, and how it lets your site talk to the outside world\. ## Page sections ### REST API Definition REST stands for Representational State Transfer \. That sounds complex, but it really isn’t\. An API is a product or program that sends information back and forth between a website or app and its user\. It does it in the background, where you don’t notice it working\. That said, just because you don’t see it, doesn’t make it any less mission crucial for your site\. A REST API generally uses HTTP to accomplish this mission\. While doing so, it breaks the request down into very small packets of information that are sent back and forth\. Because it is designed in HTTP, it can handle a large variety of data formats including XML, JSON, YAML and others\. This is an advantage over SOAP APIS, which can only handle XML data formats\. All requests sent through REST APIs are stateless\. That means they remember nothing from the exchange\. They simply get the data, send it back, and then forget about it\. This is helpful in making the transactions secure for your users\. This makes them ideal to use if you are doing anything involving the Cloud\. You simply send your request to the cloud, get the data you need and send it back\. It also allows the requests to scale up as much as they need to without becoming overloaded\. ### What Is The Difference Between A REST API And An API? A REST API is simply one of the many types of APIs out there\. All APIs send data back and forth\. A REST API is simply constructed to handle multiple formats of data\. It is not locked into XML as the only code it can handle\. REST APIs are more complex to design than other forms of APIs\. That said, they are considerably more robust and likely to be longer lasting\. In general if you are looking for an API for your website or app you probably want a RESTful one\. ### What Is A RESTful API? To put it simply, a RESTful API is simply one that uses the REST format to transfer data back and forth\. Because it’s not tied to resources or methods, it can handle many different types of requests and return multiple data formats\. This is clearly to your advantage\. Even if you are only requesting one type of data today, you have the availability to request different types of data in the future\. It’s this flexibility that will make REST APIs the future of the Internet\. Data request types are constantly changing\. RESTful APIs can adapt to that change fairly easily\. ### API Testing See how APIContext lets you test your APIs and identify problems and issues\. ### API Monitoring See how APIContext monitors the APIs you rely on and provides peace of mind\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - REST API Definition - What Is The Difference Between A REST API And An API? - What Is A RESTful API? - API Testing - API Monitoring - Ready To Start Monitoring? - If you have a website that interacts with customers, you’ll hear people talking about using REST APIs\. - Understanding what they are and why they are important is crucial to running your business correctly\. - In this article, we’re going to spend some time explaining exactly what a REST API is, why you probably want it for your website, and its ability to communicate with the outside world\. ## Primary entities - APIContext - REST API - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/rest-api) --- # RESTful APIs Explained Canonical URL: https://apicontext.com/api-knowledge-base/restful-apis Source: static Description: What is a REST or RESTful API? A plain\-English explanation for anyone who works with or manages web developers\. ## Summary What is a REST or RESTful API? A plain\-English explanation for anyone who works with or manages web developers\. ## Page sections ### What Are RESTful APIs? RESTful APIs are a type of API that breaks requests into small packets of information\. REST stands for Representational State Transfer\. They are typically written in HTTP\. The other type of API out there is a SOAP API\. The main difference between a RESTful API and a SOAP Api is that a SOAP API only deals with XML data\. A RESTful API can handle XML, JSON, YAML and other data formats\. That makes RESTful APIs much more adaptable than SOAP APIs\. The other important thing about RESTful APIs is that they are stateless\. This means that when send and receiving data they do not keep any of the information about either the user or the site they visited\. This makes using them as secure as possible\. The cloud is one of the main reasons to use a RESTful API\. You can send a data request to the cloud, have the cloud answer it back and no trace is left behind by the API\. The final important thing to know about RESTful APIs is that they are very scaleable\. You won’t risk overloading a system when you use them\. ### What Is The Difference Between A RESTful API And An API? A RESTful API is simply one type of API format that it out there\. Other API formats exist – particularly SOAP APIs\. An API is simply a program or product that sends information from a user to a website and then back again\. Think about going out to dinner\. There is you and the kitchen\. But you don’t go the kitchen to order\. Instead you place your order with the waiter or waitress who goes to the kitchen and then brings you your meal\. The waiter or waitress is the API in this scenario\. RESTful APIs take a good deal of work to be done correctly\. However their ability to handle all different types of data makes them considerably more robust than a SOAP API\. And it will allow them to grow in the future and deal with emerging data types\. New API formats are coming, especially those designed for streaming or asynchronous communications, but more on that another time\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What Are RESTful APIs? - What Is The Difference Between A RESTful API And An API? - Ready To Start Monitoring? - Figuring out what a REST or RESTful API is sounds difficult\. - But really, it’s not\. - If you are involved in web development – or if you are in charge of web developers – you’ll likely to hear people talk about REST APIs\. ## Primary entities - APIContext - RESTful APIs Explained - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/restful-apis) --- # What is an API? Canonical URL: https://apicontext.com/api-knowledge-base/what-is-an-api Source: static Description: New to APIs? Learn what an API is, how it works, and why it matters if you work in web development or programming\. ## Summary New to APIs? Learn what an API is, how it works, and why it matters if you work in web development or programming\. ## Page sections ### What is an API in Simple Terms? Here’s a metaphor for an API: When you go out to eat, you look at a menu and decide what you want\. But you don’t go to the kitchen yourself\. Instead, you ask a waiter or waitress\. He or she then goes to the kitchen, places your order, and brings it to your table\. In essence, the website you are visiting is the kitchen, you are the user, and the waiter or waitress is the API\. In real life, you can see how this works\. Imagine you want to go to a concert\. You go to the website and find the show you want to see\. When you place your order, an API will contact the bank and make sure your card is good\. It will then tell the website whether or not to honor your card\. Then if it’s a go, you’ll get your tickets\. You don’t notice the API; you just know you got your tickets\. The website doesn’t notice the API; it just knows that your card is good\. Like little ghosts in the background, APIs get the real work of websites done\. ### What is an API and How Does It Work? The most important thing to understand about an API is that it is discreet\. It takes a small bit of data from the initial user, but does not leave their computer or device exposed\. It then accesses a small bit of data from the website, but does not leave the website exposed\. It just takes what it needs, and then brings back what is required\. This makes APIs a safe and secure way to transmit data\. So much so that websites often treat them like products that they can sell or give away to developers to help make their own offerings better\! For example, say you wanted to offer a guide app to the most famous wine cellars in Paris\. You’d want to include directions from Google Maps in order to make the app as user friendly as possible\. Luckily, Google offers an API for Google Maps that allows you to embed it into your guide\. That way, you don’t have to make a complex program to access Google Maps\. You simply insert Google’s API into your code, and the link to and from Google Maps is there\. This is obviously good for you\. But it’s also good for Google, because it means when people access their maps they are doing so the right way\. And in the end, it’s good for your customers, because they end up with a working app\. The “productization” of APIs has made them have much stronger levels of discipline for security and governance than most programs\. That’s because you don’t want the processes working in the background to fail, driving every website that uses your apps to a halt\. In a nutshell, that’s what an API is\. It connects websites to consumers in an invisible, friendly way, and in general makes the internet run\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What is an API in Simple Terms? - What is an API and How Does It Work? - Ready To Start Monitoring? - Knowing what an API is and what it does is important\. - So in this article we are going to answer the question: “What is an API?” If you spend any time dealing with web development or programming, you are eventually going to hear the term API\. - To the uninitiated, it can seem to be quite a complex term\. ## Primary entities - APIContext - What Is An API? - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/api-knowledge-base/what-is-an-api) --- # Independent service\-level assurance for every API you depend on\. Canonical URL: https://apicontext.com/api-sla-and-slo-management Source: static Description: Set, measure, and report on SLOs and SLAs across your own APIs and third\-party suppliers\. Independent monitoring with detailed attribution shows the right team exactly what to fix\. ## Summary Independent service\-level assurance for every API you depend on\. Set, measure, and report on SLOs and SLAs across your own APIs and third\-party suppliers\. Independent monitoring with detailed attribution shows the right team exactly what to fix\. ## Stats - 30d rolling SLO windows - 1\.2M synthetic calls per SLO - 125\+ external monitoring locations - API supplier and internal targets ## Page sections ### Know whether service levels are being met before the contract is in dispute\. Category: Define · Measure · Prove APIContext runs production\-grade synthetic checks against the APIs and suppliers behind critical journeys, then rolls the evidence into targets, burn rates, attribution, reports, and alerts\. ### Setting SLOs is easy\. Knowing whether you are meeting them is the hard part\. Category: Set and test SLOs Define availability, latency, error\-rate, pass\-rate, and conformance objectives per route, region, supplier, or workflow\. APIContext continuously tests those targets from the places customers and partners actually use\. - 30\-day rolling windows per route, region, and supplier - Fast and slow burn\-rate alerts before budgets are exhausted - Configuration as code, reviewed alongside the APIs it covers ### Separate vendor, network, and application failures\. Category: Take the guesswork out When a critical journey slows down, APIContext shows whether the issue sits in your application, the network, a CDN, a supplier, or a chain of dependencies\. Teams get evidence instead of a long triage argument\. - Continuous testing across complicated multi\-supplier workflows - Payload, trace, latency, and status evidence attached to each issue - Ownership context for customer support, operations, and vendor managers ### Share service\-level evidence that holds up\. Category: Ready for external reporting Compliance officers need defensible numbers\. Customer support needs to know before customers call\. Vendor managers need breach evidence for credit claims and renewal conversations\. APIContext gives each team the same independent record\. - Status pages, stakeholder reports, and automated email summaries - Contractual SLA evidence for suppliers and customer\-facing services - Compliance\-ready dashboards for auditors, regulators, and leadership ### Everything you need in production\. Category: Key Features - Burn\-rate alerting: Fast and slow burn\-rate alerts based on service\-level budgets, not isolated blips\. - Independent measurement: External synthetic calls from global locations create numbers auditors, customers, and suppliers can trust\. - Multi\-supplier workflows: Trace service levels across chains of APIs and attribute degradation to the segment that caused it\. - Configuration as code: Keep SLO targets and thresholds versioned with the contracts and APIs they govern\. - SLA evidence: Generate defensible reports for customer commitments, supplier disputes, credit claims, and reviews\. - Service\-level trends: Track uptime, availability, latency, error rates, and pass rates against agreed objectives\. ### Independent SLO and SLA data flows into reporting, status, compliance, and incident tools - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Independent monitoring - Burn\-rate alerting - Vendor attribution - Regulator\-ready reports - Configuration as code - 30d rolling SLO windows - 1\.2M synthetic calls per SLO - 125\+ external monitoring locations - API supplier and internal targets - Burn\-rate alerting: Fast and slow burn\-rate alerts based on service\-level budgets, not isolated blips\. - Independent measurement: External synthetic calls from global locations create numbers auditors, customers, and suppliers can trust\. - Multi\-supplier workflows: Trace service levels across chains of APIs and attribute degradation to the segment that caused it\. - Configuration as code: Keep SLO targets and thresholds versioned with the contracts and APIs they govern\. - SLA evidence: Generate defensible reports for customer commitments, supplier disputes, credit claims, and reviews\. - Service\-level trends: Track uptime, availability, latency, error rates, and pass rates against agreed objectives\. ## Primary entities - APIContext - SLO & SLA Management - API monitoring - OpenTelemetry - Independent monitoring - Burn\-rate alerting - Vendor attribution - Regulator\-ready reports - Configuration as code ## Audience - API teams - SRE teams - platform teams ## Primary links - [Are your service levels holding up?](/contact) --- # APIContext User Guide Canonical URL: https://apicontext.com/apicontext-user-guide Source: static Description: APIContext user guides covering key features and services, including monitoring for Open Banking, SLA tracking, and more\. ## Summary APIContext user guides covering key features and services, including monitoring for Open Banking, SLA tracking, and more\. ## Page sections ### Browse APIContext User Guide Category: Product Guides to APIContext features and services, including Open Banking monitoring, SLA tracking, and more\. - [API Monitoring Frequency – how much is too much?](/apicontext-user-guide/api-monitoring-frequency-how-much-is-too-much) - [Tutorial: Handling Microsoft Graph API Auth](/apicontext-user-guide/microsoft_graph_api_auth) - [Customer Case Studies](/apicontext-user-guide/customer-case-studies) - [APIContext Case Study Power Utility](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-power-utility) - [APIContext Case Study Government APIs](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-government-apis) - [Automated Postman Collection Monitoring](/apicontext-user-guide/automated-postman-collection-monitoring) - [Make an API Call](/apicontext-user-guide/make-an-api-call) - [APIContext AI\-Based Reporting and Analytics](/apicontext-user-guide/apicontext-ai-based-reporting-and-analytics) - [Easy DNS Monitoring with APIContext](/apicontext-user-guide/easy-dns-monitoring-with-apimetrics) - [Tutorial: Schedule API Calls](/apicontext-user-guide/tutorial-scheduling-api-calls) - [Types of API Calls](/apicontext-user-guide/types-api-calls) - [PSD2](/apicontext-user-guide/psd2) - [API Monitoring Features](/apicontext-user-guide/features-2) - [Who Uses APIContext](/apicontext-user-guide/who-uses-apimetrics) - [White Papers](/apicontext-user-guide/customer-case-studies/white-papers) ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - API Monitoring Frequency – how much is too much? - Tutorial: Handling Microsoft Graph API Auth - Customer Case Studies - APIContext Case Study Power Utility - APIContext Case Study Government APIs - Automated Postman Collection Monitoring - Make an API Call - APIContext AI\-Based Reporting and Analytics - APIContext can meet your monitoring needs for your API stacks\. - These guides help outline some of the key features and services that we offer, including guides to how to use us for certain types of monitoring like Open Banking or SLA tracking\. - If you don’t find what you’re looking for, don’t hesitate to reach out to one of our experts\. ## Primary entities - APIContext - APIContext User Guides - APIContext User Guide - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide) - [API Monitoring Frequency – how much is too much?](/apicontext-user-guide/api-monitoring-frequency-how-much-is-too-much) - [Tutorial: Handling Microsoft Graph API Auth](/apicontext-user-guide/microsoft_graph_api_auth) - [Customer Case Studies](/apicontext-user-guide/customer-case-studies) - [APIContext Case Study Power Utility](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-power-utility) - [APIContext Case Study Government APIs](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-government-apis) - [Automated Postman Collection Monitoring](/apicontext-user-guide/automated-postman-collection-monitoring) --- # API Monitoring Frequency Canonical URL: https://apicontext.com/apicontext-user-guide/api-monitoring-frequency-how-much-is-too-much Source: static Description: How often should you monitor your APIs? APIContext offers options from once per second to longer intervals — here's how to choose\. ## Summary How often should you monitor your APIs? APIContext offers options from once per second to longer intervals — here's how to choose\. ## Page sections ### How much is too much? There are many schools of thought on the frequency you should monitor your APIs, but there’s no one specific answer to the question of what is the right API monitoring frequency\. APImetrics offers a wide range of options from essentially every second through to a single call a day\. That said, there are some general guides we can give to help with this\. ### What is a meaningful sample size? We’ve written at length about the perils of relying entirely on your existing log traffic – after all, it would be logical to think that all the traffic gives you what you need\. The challenge is that it doesn’t always work that way for a number of reasons: • If the call isn’t reaching your servers you’ll have no logs to look at • Logs won’t tell you about issues with a partner or users cloud services • You might have too much data to sort meaningfully for a low frequency event – the flipside of this is you might not store the logs long enough because storing all the logs in a meaningful way gets very spendy quickly • Existing services might ignore failure chains – say a database that technically isn’t in your API stack is taken down – it’s not uncommon for an engineering team to set their systems to ignore client errors With that in mind, we always recommend a series of sample calls from outside your stack to give you data that you can use as a control sample – after all, it’s what we do\. ### What are you trying to achieve? The rule of the thumb with API monitoring frequency is that the higher is better, but only up to a certain point\. Once a day is probably not enough because a lot can happen in a day and you can lose a lot of lot of money if something goes wrong and you don’t notice for the entire day\. Once a second is probably too fast because the signal will tend to be noisy and you can’t respond to things on a 1\-second timescale \(unless you are a high frequency trading bot\)\. Every 5 minutes is typically a good frequency\. This gives you good resolution of what has happened over a day and allows you to respond quickly in human timescale if something really has gone wrong\. ### Location Issues Depending on your authentication protocol and load balancing system you might also need to consider monitoring frequencies by region too\. If you are monitoring globally once a minute, so that over the course of a few hours you’ll have equal calls from different locations around the world, there could be significant gaps in coverage for regions\. So if you have a regional load balancer go down you could miss it\. In that situation, or where a particular authentication routes to a specific location, you might want to schedule more frequent monitoring but distributed by location, i\.e\., a call every 5 minutes per region\. ### So what frequency should I pick? It largely depends on your use patterns and what you want the monitoring to achieve but for most API based applications we usually believe 5\-10 times an hour per region you’re interested in will give you enough warning to fix something that could have negative impacts on users before they start to notice\. For security monitoring, where you’re more interested in negative issues, such as accessing a forbidden resource or verifying that Tokens refresh as expected you might only do that a couple of times an hour just to be sure\. ### Pulling API Monitoring Frequency Together You don’t need a massively high API monitoring frequency to generate useful data and give you insights into how things are working where your users are\. But you should focus on samples that give you meaningful performance data and the alerting you need to be responsive to outages before your users notice\. APIContext has a world beating scheduling engine designed to help you as you can learn in this helpful tutorial\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - How much is too much? - What is a meaningful sample size? - What are you trying to achieve? - Location Issues - So what frequency should I pick? - Pulling API Monitoring Frequency Together - Ready To Start Monitoring? - There are many schools of thought on the frequency you should monitor your APIs, but there’s no one specific answer to the question of what is the right API monitoring frequency\. - APImetrics offers a wide range of options from essentially every second through to a single call a day\. ## Primary entities - APIContext - API Monitoring Frequency – how much is too much? - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/api-monitoring-frequency-how-much-is-too-much) --- # APIContext AI Based Reporting and Analytics Canonical URL: https://apicontext.com/apicontext-user-guide/apicontext-ai-based-reporting-and-analytics Source: static Description: APIContext brings AI\-based reporting to API monitoring, answering the key questions behind your API performance metrics\. ## Summary APIContext brings AI\-based reporting to API monitoring, answering the key questions behind your API performance metrics\. ## Page sections ### AI\-Driven Insights At the heart of APIContext is the AI Based API Insights Report\. The analysis works from the calls you make and the training our system has gained from the billions of data points we’ve collected since we started monitoring APIs globally in 2016\. The data that goes into Insights is based on: • Pass Rates – as measured by the criteria you set in your API tests • Latency – the time it takes the API call to execute • Outlier rates – calls which the AI determines fall outside of your normal test criteria • Consistent response times – your API may be blisteringly fast, or snail\-like slow; do you have periods of time when it’s much slower than you expect? • Overall speed – we don’t look too hard at the speed, but we do keep an eye on a famous IT metric of about 450ms \(the speed IBM determined that a computer system had to respond before people noticed the lag\) These API metrics are pulled together in the CASC score, which tells you out of a perfect 10 if there are any problems with a specific API\. The clever thing with CASC is it allows us to compare different APIs, so you can see how they rate against each other or a competitor\. Regional metrics are generated so you can see Cloud, Location, and Regional API performance metrics at a glance to understand where there might be problems\. This provides insight to internal engineering AND external customer facing teams\. ### What API Insights Tell You With the AI Based API Insights report, you can learn which data centers and clouds are providing the worst service – a critical piece of data for informing third parties about their issues\. If you know, for example, that AWS Frankfurt is 2 seconds per transaction slower than Azure London, then you’re equipped to understand why people might be complaining about a specific location\. Likewise if you’re using containers, you might want to know where in the world and on which of the major clouds you get the best performance\. APIContext can do that and more\. We also provide API metrics benchmarking so we can easily show how your specific API ranks against groups of APIs, industries, and more\. ### Integrated Statistical Analysis Tools With APIContext, you don’t have to export your data into yet another product\. With our fully integrated statistical analysis system, you get all the data you need in our statistics views and reports – without having to sign up for, or pay for, another product\. Statistics analysis gives you data on the actual performance metrics for your APIs for as long as you’ve been a customer\. This includes: • A geographic mapping feature to show calls by call segment \(DNS, TCP, Processing Times\) and Cloud on an interactive world map view including percentile breakdowns • Pass/fail rates • Latency graphs for all call segments and also the ability to map different APIs together for direct comparison purposes – these can be saved for future reference • Heat maps to show when calls are slow either over an hourly/daily/weekly/monthly basis so you can visualize performance trends for the speed of your responses ### Reporting and Status Pages In addition to statistical analysis tools we provide a range of reporting and status page options – including the ability to download reports as a CSV file \. Reports show API pass rates either as a total or by call location, and break it down further by the data center that they were made from\. Data is also presented with 95th and 99th percentile analysis so you can see which APIs have long extreme times that can impact you\. Every report can also be automatically turned into a real\-time status page for direct embedding into a blog, operations center, or other similar reporting service for internal and external users\. ### Compliance and Governance Imagine being able to generate the reports your regulators need automatically – from real external performance data – just like users of your platform experience\. Imagine being able to bring that data to dispute resolution discussions with actual evidence that it isn’t your platform, or show where the weak links are in somebody else’s stack\. Well, imagine no more\. APIContext provides automatically generated regulator reports for the key regulated industries or we can customize the output of the product to generate exactly what you need when you need it\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - AI\-Driven Insights - What API Insights Tell You - Integrated Statistical Analysis Tools - Reporting and Status Pages - Compliance and Governance - Ready To Start Monitoring? - APIContext has spent years focused on the key questions about API performance and bringing AI based reporting to API monitoring in a single monitoring and reporting product\. - This is so you can identify what you need to know versus what might mislead you into thinking all is well, when, in fact, it isn’t\. - To achieve this, APIContext created a database of over a billion API calls, and 10 billion data points in over 30 TB of data \. ## Primary entities - APIContext - APIContext AI\-Based Reporting and Analytics - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/apicontext-ai-based-reporting-and-analytics) --- # Automated Postman Collection Monitoring Canonical URL: https://apicontext.com/apicontext-user-guide/automated-postman-collection-monitoring Source: static Description: APIContext partners with Postman for automated Postman collection monitoring using our global network of Cross\-Cloud agents\. ## Summary APIContext partners with Postman for automated Postman collection monitoring using our global network of Cross\-Cloud agents\. ## Page sections ### Seamless Postman Collection Monitoring with APIContext APIContext has partnered with our friends at Postman to take Postman collection monitoring to the next level, with a completely automated solution that lets you take full advantage of the APIContext global network of Cross\-Cloud agents and the ease of Postman’s collection management tools\. ### What does that mean? If you have a significant set of tests in Postman that you’ve been working with during development but want to move to a more robust system for monitoring your production setup, it can seem daunting to move the entire test configuration over to another product\. To simplify this, APIContext now offers two different approaches to having the best of both worlds\. Option 1 is to import your Postman collection using our importer and then set up the environment\. The upside here is you will be able to manage the collection within APIContext and have an easier time of the security handling\. The downside is there is a significant overhead in terms of time\. Option2, which we developed in conjunction with the team at Postman, is to sync the collection directly to Postman using the Postman API\. By syncing your Postman collection directly to APIContext, we can run your entire collection through the APIContext network and gather stats on the process with almost no work needed on your part\. If the collection runs in Postman, it will run in the same way through about 40 of our Azure, Google and AWS locations with no additional setup needed on your part\. READ HOW TO RUN A COLLECTION IN DETAIL ### Key Features With our integration to Postman you don’t have to worry about configuring anything in APIContext, BUT you will need to have a premium account in Postman for the collection to sync correctly as the process of running calls will use one of your Postman API call quota per sequence, plus whatever APIContext calls you use\. The key steps to the process are simple: • Enter your Postman API key into the APImetrics product \( read the full guide at Postman here \) • Select the collection you are planning to monitor • Confirm the environment details • Schedule the collection to run through our network of Newman based agents \(we currently have about 40 across AWS, Azure and Google data centers using our standard scheduling engine • Sit back and watch the results come in\. APIContext will also take the alerting cues from the configuration in your Postman Collection, which means that errors and issues will be picked up automatically and used in our insights engine\. To get the most out of our cross\-cloud functionality you will need to add the following to your Postman collection before you turn on monitoring: Connection: close This will close the current TCP connection and force our agents to do a complete new connect each time the API calls run\. This will give you the networking data which is critical to understanding how APIs perform globally and show you where there might be issues with your customer configurations or hosting choices\. ### Everything included You get access to all the reporting, alerting through our wide range of webhook integrations like Ops Genie, Pager Duty and all the automated insights that you would have from setting up inside APImetrics but you can control the experience inside your test setup directly from your Postman collection in Postman itself\. With APImetrics projects, you can also share these configurations with other members of the team, or share the results and output to non\-engineers without them having access to Postman itself\. Giving you confidence in your ability to share reporting without interfering in your test set up\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Seamless Postman Collection Monitoring with APIContext - What does that mean? - Key Features - Everything included - Ready To Start Monitoring? - Seamless Postman Collection Monitoring with APIContext APIContext has partnered with our friends at Postman to take Postman collection monitoring to the next level, with a completely automated solution that lets you take full advantage of the APIContext global network of Cross\-Cloud agents and the ease of Postman’s collection management tools\. - If you have a significant set of tests in Postman that you’ve been working with during development but want to move to a more robust system for monitoring your production setup, it can seem daunting to move the entire test configuration over to another product\. ## Primary entities - APIContext - Automated Postman Collection Monitoring - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/automated-postman-collection-monitoring) --- # Customer Case Studies Canonical URL: https://apicontext.com/apicontext-user-guide/customer-case-studies Source: static Description: yes ## Summary yes ## Page sections ### Read our customer case studies Learn more about our customer case studies, from government to banking – how to use APIContext and build value\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Read our customer case studies - Ready To Start Monitoring? - Read our customer case studies Learn more about our customer case studies, from government to banking – how to use APIContext and build value\. - Want to learn more? ## Primary entities - APIContext - Customer Case Studies - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/customer-case-studies) --- # APIContext Case Study Government APIs Canonical URL: https://apicontext.com/apicontext-user-guide/customer-case-studies/apimetrics-case-study-government-apis Source: static Description: How New Zealand's Ministry of Business, Innovation and Employment uses APIContext to monitor its critical government APIs\. ## Summary How New Zealand's Ministry of Business, Innovation and Employment uses APIContext to monitor its critical government APIs\. ## Page sections ### BACKGROUND The Ministry of Business, Innovation and Employment \(MBIE\) is the government’s lead business\-facing agency\. Its purpose is to grow the New Zealand economy to provide a better standard of living for all New Zealanders\. Some of MBIE’s main public\-facing operational responsibilities include: • Provide company registration, intellectual property and insolvency services Regulate the supply and use of radio spectrum, electricity and gas • Provide and enforce consumer, commercial and occupational regulatory frameworks • Deliver immigration services and policy • Lead the Government’s health and safety reform programme • Advise on and support employment relations and enforce minimum employment standards • Lead the Government Centre for Dispute Resolution MBIE and its preceding agencies have been providing public APIs since 2002\. It has recognised that APIs are an important method for delivering services and is increasing its efforts in supporting and promoting existing APIs, and providing new and improved APIs across a variety of business areas\. MBIE operates an outsourced ICT model and has a range of vendors responsible for API delivery\. There are various layers of monitoring and reporting available from these vendors, but it was felt that independent external monitoring would provide richer information on how its APIs perform from a customer perspective\. ### MBIE’S API MONITORING REQUIREMENTS MBIE needed external monitoring of some of its key APIs \(see www\.api\.business\.govt\.nz for a list of APIs provided by MBIE\)\. The key requirements were: • Ability to get notification of issues in production and test environments • Support for SOAP and REST APIs • Reporting on API performance • Ability to monitor from regional and international locations • Ability to have multiple users under one account ### USE OF APIContext MBIE evaluated several cloud services for API monitoring and found APIContext the best fit for these requirements\. During the initial trial period the APIContext team were very responsive to questions and proactively made contact with MBIE to provide assistance and training\. This, combined with their comprehensive documentation, helped ensure that the capabilities of the product were well understood and that monitoring was set up to provide maximum effectiveness\. MBIE currently has ten different API calls set up in APIContext to provide targeted testing of API platforms and key services\. Each API has at least three deployments to different international locations and hosts \(Google, AWS, Azure, and Softlayer\)\. The number of API calls will grow when a new MBIE API platform is launched in July 2016 and as more individual APIs are monitored for performance\. ### API Calls for Different API Types MBIE uses a number of legacy API technologies and is working on consolidating these to a single main API platform over time\. APIContext has the level of support needed to set up tests against MBIE’s SOAP and REST services, using different authentication schemes including basic authentication, OAuth1, OAuth2, and WS\-Security\. ### Outage Monitoring MBIE needs to know as early as possible when there are any outages with its API platforms and APIs, preferably before customers or vendors have to notify that there is a problem\. APIContext provides flexible deployment frequencies and alert settings on each API deployment, which allows MBIE to tailor the alerting for each scenario being monitored\. Higher priority APIs are set up with multiple deployments each running at a 10 or 15 minute frequency, with call times offset so that there is a call being made to the API every three to five minutes\. Alerts for these are sent to a specified email address when any failure is received\. Lower priority APIs or test environment versions of APIs are called at a lower frequency and alerts are set up to be sent only when multiple failures in a row are encountered\. Deployments are always set up to originate from different geographical locations and hosts to ensure that problems at the host side can be identified, while allowing monitoring to continue from other locations\. API calls are configured to test for particular response conditions to confirm whether the call was successful or not\. APIContext allows for various conditions to be tested, including HTTP status, header and body content, and response time and size\. These features allow MBIE to set up suitable business monitoring for outages without receiving many false positive alerts\. ### Performance Monitoring and Reporting MBIE includes API performance monitoring sections in internal reports for management\. The standard reports that are generated from APIContext are a suitable form to include without modification\. The reports and dashboards in APIContext provide a clear visual representation of API performance including pass rates, latency, and whether performance has improved or degraded between reporting periods\. The information in these reports and in the new Insights section is being used by MBIE to baseline performance of current APIs as a comparison for when the new API platform is introduced into production use\. This information will also be used to set performance SLAs with MBIE customers in future\. Current customer agreements are focussed around legal terms and conditions, with no detail of service availability and performance\. APIContext reporting will ensure that achievable targets are set and can be reported on\. The impact of a customer’s geographical location can be easily seen when looking at performance of MBIE APIs from regional locations in the Asia\-Pacific area compared to Europe and the United States\. The API Insights function visually shows that there is significant additional latency added for the more distant locations, which help with understanding customer issues with MBIE APIs\. APIContext also offers capabilities for information collation that MBIE intends to use in future after its new API platform is bedded in\. This includes the use of an API to retrieve performance data from MBIE’s API calls and webhooks for receiving data\. These features will allow improved ability to collate APIContext data for display and analysis alongside other MBIE system reporting\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - BACKGROUND - MBIE’S API MONITORING REQUIREMENTS - USE OF APIContext - API Calls for Different API Types - Outage Monitoring - Performance Monitoring and Reporting - Ready To Start Monitoring? - The government of New Zealand Ministry of Business Innovation and Enterprise uses APIContext to monitor their critical APIs\. - BACKGROUND The Ministry of Business, Innovation and Employment \(MBIE\) is the government’s lead business\-facing agency\. - Its purpose is to grow the New Zealand economy to provide a better standard of living for all New Zealanders\. ## Primary entities - APIContext - APIContext Case Study Government APIs - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-government-apis) --- # APIContext Case Study Power Utility Canonical URL: https://apicontext.com/apicontext-user-guide/customer-case-studies/apimetrics-case-study-power-utility Source: static Description: How First Utility \(now Shell Energy\) uses APIContext to increase API throughput without increasing infrastructure capacity\. ## Summary How First Utility \(now Shell Energy\) uses APIContext to increase API throughput without increasing infrastructure capacity\. ## Page sections ### First Utility \(Now Shell Energy\) uses APIContext to Increase Throughput Without Increasing Capacity First Utility is one of the UK’s largest and fastest growing independent energy providers\. Since beginning operations in 2009, the company has rapidly built a loyal following by offering homeowners innovative smart meters, website tools and mobile apps\. These products give customers the ability to reduce their gas and electric bills by helping them monitor and control energy usage\. In the UK’s deregulated market, giving First Utility customers real\-time insight into their short\- and long\-term energy consumption patterns is a competitive advantage\. Within just a few years, First Utility’s customer base has grown to more than 850,000, with more than a third using First Utility’s iOS and Android mobile apps\. “First Utility empowers customers by giving them access to information,” said Richard Marshall, principal technical operations engineer\. “We were one of the first companies to introduce smart meters, giving customers real\-time feedback and comparisons to help them understand their energy usage\. We stay ahead of our competition by introducing new features and ensuring that our website tools and mobile apps are the best they can be\. The more knowledge we can share with our customers, the more power they have at their disposal to control energy usage and ultimately save money\.” ### Limited visibility First Utility’s reliance on technology means that fast, dependable access to customer accounts via the website and mobile applications is central to the company’s success\. All of this functionality, including billing, is driven by just a handful of mission\-critical APIs\. Initially, the company’s TechOps team used a variety of tools to monitor the website internally and ensure that everything was running smoothly, but they realized over time that running tests internally did not give an accurate picture of real\-life usability from customers’ perspectives\. “Rather than an inside\-out view, we realized that we needed a specialized tool that could give us visibility into the performance of our site and apps in the same way that the rest of the internet sees us,” continued Marshall\. “It was really important for us to know when the site became unavailable for users, and to understand long\-term trends and any pinch points in the network\. The only way to accomplish these goals was to adopt a third party set of tools, and for that we chose APImetrics\.” ### Knowledge is Power First Utility uses a complicated OAuth authentication process for access to its services, so it initially struggled to find a compatible monitoring tool\. With its ability to handle most API security systems and renewals natively, APIContext enabled the TechOps team to easily configure customized dashboards specifically for their RESTful APIs\. APIContext also allows First Utility to start monitoring new API end\-points within minutes, and can generate useful latency charts and analytical summaries in a few simple keystrokes\. These features give First Utility a great deal of ongoing confidence that their web tools and mobile apps are working properly and providing a first class user experience to the company’s customers\. “For our particular implementation, we use APIContext as a reference tool to help establish performance baselines for our mobile apps and the First Utility website,” said Marshall\. “APIContext provides multiple monitoring sites globally\. That helps companies conduct realistic tests as close to their user base as possible\. In the case of First Utility, all of our customers are here in the UK, so we appreciate the fact that we can test Azure from Ireland, for example, or tap into Softlayer from London\. It’s a feature that most other API testing or monitoring tools simply don’t offer\.” ### More than a performance tool First Utility has approximately 1,000 employees, but within its lean 30\-man operations team there are only five people tasked with managing web tech support and issue resolution\. Having limited resources, the company naturally needs an efficient way to isolate, investigate and resolve website or application issues as quickly as possible\. Prior to implementing the APIContext tools in mid\-2015, First Utility began running into potential capacity problems\. Like most companies facing this common concern, the operations team considered several options including the installation of additional servers to boost performance\. However, once APIContext was implemented, the team discovered that the issue was not one of capacity, but rather of configuration\. By fixing the problem, they were able to improve throughput dramatically, helping user content load faster and effectively producing more bandwidth without adding more server capacity\. This not only saved the company considerable time and effort isolating the problem, it also allowed the team to optimize their existing Oracle resources and park additional infrastructure expenditure\. “Energy companies have complex back\-end systems, which become even more difficult to manage when they’re required to meet the needs of customers, suppliers and other stakeholders,” said Marshall\. “There’s no question that APIContext has allowed us to establish practical baselines and improve performance\. It opened a window to let us see what is really going on further down the line with our critical services, and points us in the right direction to take quick action before problems have a chance to impact customers\. Without these kind of outside\-in monitoring and diagnostic tools, enterprises cannot hope to adequately investigate or even avoid issues\.” ### The proof is in the pudding “Most of First Utility’s employees are also customers\. That gives us a really good incentive to make sure that the website and the apps are working,” concluded Marshall\. “Being consumers of our own service, we have a vested interest in ensuring that the site and the apps are reliable, responsive, and act exactly the way we anticipate them to\. So if they’re working well for us, we know they’re working well for our customers\. We’ve set ourselves a high bar, expecting the systems to work just as well as any other big sites in the industry\. With tools like the ones from APIContext, we’re certainly on the right track\.” ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - First Utility \(Now Shell Energy\) uses APIContext to Increase Throughput Without Increasing Capacity - Limited visibility - Knowledge is Power - More than a performance tool - The proof is in the pudding - Ready To Start Monitoring? - First Utility \(Now Shell Energy\) uses APIContext to Increase Throughput Without Increasing Capacity First Utility is one of the UK’s largest and fastest growing independent energy providers\. - Since beginning operations in 2009, the company has rapidly built a loyal following by offering homeowners innovative smart meters, website tools and mobile apps\. - These products give customers the ability to reduce their gas and electric bills by helping them monitor and control energy usage\. ## Primary entities - APIContext - APIContext Case Study Power Utility - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/customer-case-studies/apimetrics-case-study-power-utility) --- # White Papers Canonical URL: https://apicontext.com/apicontext-user-guide/customer-case-studies/white-papers Source: static Description: APImetrics Guides White Papers White Papers Our most recent paper ## Summary APImetrics Guides White Papers White Papers Our most recent paper ## Page sections ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - Want to learn more? - Sign up now and start using the product immediately\. ## Primary entities - APIContext - White Papers - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/customer-case-studies/white-papers) --- # Easy DNS Monitoring with APIContext Canonical URL: https://apicontext.com/apicontext-user-guide/easy-dns-monitoring-with-apimetrics Source: static Description: APIContext Guides easy DNS Monitoring ## Summary APIContext Guides easy DNS Monitoring ## Page sections ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - Want to learn more? - Sign up now and start using the product immediately\. ## Primary entities - APIContext - Easy DNS Monitoring with APIContext - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/easy-dns-monitoring-with-apimetrics) --- # API Monitoring Features Canonical URL: https://apicontext.com/apicontext-user-guide/features-2 Source: static Description: APIContext's API call monitoring features: reporting, alerting, analysis, and support for REST and other API call types\. ## Summary APIContext's API call monitoring features: reporting, alerting, analysis, and support for REST and other API call types\. ## Page sections ### Create and run real API calls\.Just like users and partners do\. • Set up and run REST & SOAP APIs • Import from OpenAPI, RAML, Postman or use our API • Create workflows of linked API calls to test scenarios • Detailed results \(DNS, TCP connect, handshake, processing, download time\) • Look for specific content returned, package sizes or specific response codes • Set timing\-based conditions and alerts ### Schedule calls globally\. Any public cloud location\. No configuration or setup\. • Deploy to any cloud location from AWS, Azure, Google, and Akamai • Pick from 125\+ locations around the world • Deploy on VMs inside your firewall • Deploy to micro\-controller devices like Raspberry Pis for IOT scenarios ### Clear dashboards\. Integrated reporting\. Insightful analysis\. • See all scheduled API calls at a single glance • Response times for the last day and over 2 weeks • Pass rates, latency and CASC scores • Detailed analysis of latency breakdown ### Alerts on the issues you need to know about\. • Email based messages • Webhook push notifications to common DevOps tools • Configurable webhook connection • Trigger alerts from any condition • Set reverse testing scenarios • Set thresholds before alerts are triggered ### Automated diagnosis\. Fully secure\. • AI & ML based analysis • Automated trend and issue analysis • Tools designed to accelerate problem and issue detection ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Create and run real API calls\.Just like users and partners do\. - Schedule calls globally\. Any public cloud location\. No configuration or setup\. - Clear dashboards\. Integrated reporting\. Insightful analysis\. - Alerts on the issues you need to know about\. - Automated diagnosis\. Fully secure\. - Ready To Start Monitoring? - Reporting, alerting, analysis and more\. - APIContext offers a complete suite for API call monitoring\. - Dive into our detailed features – but first, check out this summary of what you can do\. ## Primary entities - APIContext - API Monitoring Features - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/features-2) --- # Make an API Call Canonical URL: https://apicontext.com/apicontext-user-guide/make-an-api-call Source: static Description: Learn how to make your first API call with APIContext — it's as simple as typing a URL into a browser\. ## Summary Learn how to make your first API call with APIContext — it's as simple as typing a URL into a browser\. ## Page sections ### Step 1: Click on “Add API Call” In the side menu or at the top of the screen you’ll see “Add API Call” – just click on that and we’re off to the races\. This will bring up step 2, the call editing window\. ### Step 2: “Enter the URI” When the edit screen appears we’re going to want to enter the URI of the call we are going to be making\. We’re using the HTTPbin server as our test which gives us a bunch of fun features to play with, but for the first one we’re going to ask for the IP address of the agent that will make the API call\. Remember, these are REAL API calls from outside your firewall from real application servers in the cloud to your APIs\. If you’re not able to reach the API call then you won’t be able to get this working with your APIs yet\. But you shouldn’t go public without being 100% sure your APIs work flawlessly from outside the firewall\. We’ve give the call a name so we remember it and we’ve used the reference location of the APImetrics HTTPbin servers “http://google\.apimetrics\.xyz” after that just add “ip” and save the call\. You’re now ready to make an API call\. ### Step 3: “Run the API call” You’re now ready to run the API call – you can select “Run” and it will be sent to our default server in Iowa, or you can click the arrow and pick any of the 70\+ locations around the world we operate in\. For this test, we’re picking AWS Tokyo\. ### Step 4: Read the Result Assuming everything worked, you should now have a result screen to look at\. There are 4 key things here to see: • The response code and assertions set\. We got a HTTP 200 OK\! and we have the overall latency and the timing for the call\. • A breakdown of the timings of each step – DNS lookup, connect time, upload, processing and download which all come to 16ms • A graphical view of the breakdown • Benchmarking the steps of the call against other similar calls in our database – if it’s green, it’s good; yellow means the time taken puts the call in the 90th percentile of responses, i\.e\., the worst 10%; red means the worst 1% of all calls If you look further you’ll see the call made, the header received and the actual body\. APIContext will store these results for you for as long as you’re a customer so you will always have an audit trail of results\. ### Step 5: There is no step 5\! You’ve made a real, functional API call to the outside world, congratulations\! You might want to try with your own APIs or schedule this API and see how it performs\! ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Step 1: Click on “Add API Call” - Step 2: “Enter the URI” - Step 3: “Run the API call” - Step 4: Read the Result - Step 5: There is no step 5\! - Ready To Start Monitoring? - At a simple level, if you can type a URL into a browser, you can make an API call with APIContext\. - In fact, there’s a lot in common between what happens when you make an API call and when you go to a webpage – APIs are involved in both, as are the same protocols\. - But here, we’re going to walk through the basic steps here for making a call to one of our HTTPbin servers which will get the IP address of the place you’re making the call from\. ## Primary entities - APIContext - Make an API Call - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/make-an-api-call) --- # Handling Microsoft Graph API Auth Canonical URL: https://apicontext.com/apicontext-user-guide/microsoft_graph_api_auth Source: static Description: How to make secure, authenticated API calls to Microsoft Graph API endpoints — a common challenge even Microsoft users face\. ## Summary How to make secure, authenticated API calls to Microsoft Graph API endpoints — a common challenge even Microsoft users face\. ## Page sections ### making secure API calls to Microsoft Graph API Endpoints Microsoft Graph APIs are at the heart of everything Microsoft does but they’re not entirely straight forward to monitor or even call successfully – something even Microsoft can struggle with\. Fortunately, this is a relatively easy problem to solve\. ### Overview Microsoft Graph is an OAuth based service but has some additional layers which mean our Wizard doesn’t handle it directly ‘out of the box’ – instead we recommend a 2\-stage workflow with environment variables set for your organization or project: Workflow 1 will contain a single call which initiates the call to kick off the sign in process where you authenticate the service – this will uses unique GUIDs that are passed to Microsoft to be used in the generation of the tokens Workflow 2 – contains a single call which obtains the access token, the expires in timing and sets the refresh token The variables this process sets will be used in our security configuration to then handle ongoing authentication\. This will let you get an OAuth Token from Microsoft Graph, but we’ll need to add a final stage to handle a Refresh Token cleanly and securely so you don’t have to set it manually\. ### Basic Configuration for Microsoft Graph API Auth In the “Environment Variables” menu set the following variables: Client\_id – provided by your Microsoft application Client\_secret – all provided by Microsoft Graph API Auth Redirect\_uri – this is the callback setting to allow Microsoft to know what to do after sign in – this will be client\.apimetrics\.io/tokens/callback Scope – you’ll obtain this from Microsoft for the service you are authenticating the call to reach – more details can be found here: https://docs\.microsoft\.com/en\-us/azure/active\-directory/develop/v2\-permissions\-and\-consent Once they are set you need to create 3 API calls\. Call 1 – OAuth: Authorize – using the POST method you should enter something like this – note you don’t need to put a body for this URI The call here uses 2 system variables we generate for you as well as the environment variables we set first\. Finally, this call needs to know to open the browser and make the authenticate call, so in the META tab, you need to add the following: apimetrics:browser Now when you run the call it will trigger the web browser to open\. Call 2 – OAuth Access Token – to be triggered AFTER you’ve authenticated with your log in should look like this and when it’s setup, you should click on the CONDITIONS tab\. In the Conditions Tab you’ll need to set the variables we will be using for actual calls\. This will look something like this\. Call 3 – Refresh Token Auth This will be called to refresh the authentication once we have everything set up, so you don’t have to worry about going in every time a token expires\. Once this is done, we recommend creating 3 workflows – one for each of these API calls – and naming them something like: • Auth Step 1: \(scope reference\) Step 1 / 2 • Auth Step 2 \(scope reference\) Step 2 / 2 • OAuth: Refresh Token Next we set up the security setting and token we will use\. ### Configure Security Settings and Tokens We now need to set up a way to tell the APIs you create what Auth settings to use – you’ll have seen that already in the screen shots but now we set it up\. APIContext handles security separate to the API calls, so you can set up a type of authentication and a token and then you can apply that to lots of calls without having to create and edit the security for each different API call you monitor\. Go to Auth & Tokens in the side navigation menu\. Select ‘Create New Authentication’ – because the Microsoft Graph system is a little non\-standard for an OAuth service we’re going to select ‘Manual Auth’ Things to note: 1\) We do recommend adding the Endpoint domain that this auth will apply to – this will make it easier to track moving forward 2\) Authentication Type is Manual Setup – don’t use the OAuth options 3\) Select the OAuth: Refresh Token Workflow 4\) It’s worth filling in the meta data fields so you can easily find docs later 5\) Finally, under ‘Refresh Token Workflow’ select the Refresh Token Workflow you configured first Save the configuration\. We can now create our first token to use with this auth\. All the API will need is a header to be set with the following parameters: Authorization: Bearer \(token number\) Create the Token and give it a name, then select enter values manually and set a header with: Authorization with the parameter Bearer %%ACCESS\_TOKEN%% – which is the variable we set in the work flow we created\. ### Pulling It All Together Step 1 – Authenticate to service\. Run Workflow 1 / 2 and sign in to the service When you arrive back at the Callback screen, select Workflow 2 / 2 from the menu and run it\. You should now have valid tokens\! Now go to the API call and select ‘RUN NOW’ from the top left\. This should run and pass\. From now on we’ll handle things for you, whenever the Token expires, the Refresh Token workflow will be triggered in the background and will automatically update the tokens for you\. ### Run a Microsoft Graph API call Create an API call to your endpoint and select your Security Method and add the name of your auth settings and the token name to use\. Click Run Now to test – it should pass\. ### Start Monitoring your Microsoft Graph APIs Select Monitor and pick a schedule and off you go\! ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - making secure API calls to Microsoft Graph API Endpoints - Overview - Basic Configuration for Microsoft Graph API Auth - Configure Security Settings and Tokens - Pulling It All Together - Run a Microsoft Graph API call - Start Monitoring your Microsoft Graph APIs - Ready To Start Monitoring? - making secure API calls to Microsoft Graph API Endpoints Microsoft Graph APIs are at the heart of everything Microsoft does but they’re not entirely straight forward to monitor or even call successfully – something even Microsoft can struggle with\. - Fortunately, this is a relatively easy problem to solve\. - Overview Microsoft Graph is an OAuth based service but has some additional layers which mean our Wizard doesn’t handle it directly ‘out of the box’ – instead we recommend a 2\-stage workflow with environment variables set for your organization or project: Workflow 1 will contain a single call which initiates the call to kick off the sign in process where you authenticate the service – this will uses unique GUIDs that are passed to Microsoft to be used in the generation of the tokens Workflow 2 – contains a single call which obtains the access token, the expires in timing and sets the refresh token The variables this process sets will be used in our security configuration to then handle ongoing authentication\. ## Primary entities - APIContext - Tutorial: Handling Microsoft Graph API Auth - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/microsoft_graph_api_auth) --- # PSD2 Canonical URL: https://apicontext.com/apicontext-user-guide/psd2 Source: static Description: What is PSD2 \(Revised Payment Service Directive\) and what does it mean for banking and open banking APIs? ## Summary What is PSD2 \(Revised Payment Service Directive\) and what does it mean for banking and open banking APIs? ## Page sections ### What is PSD2\(and what does it have to do with APIs?\) A new European Union directive has come into force that will eventually change the way people bank as we know it\. It’s called PSD2 \(Revised Payment Service Directive\), and it will open up the way banks do business\. It will also create new companies for processing payments\. If you are in the banking or financial sector, it’s important to understand what PSD2 means for your industry, and how to react to it and become compliant with all of the regulations that encompass it\. ### The nuts and bolts of PSD2 PSD2 makes it mandatory for banks to open up their records to third\-party companies\. And in many companies – particularly the UK – they must do so in a standardized format\. This will allow third\-party companies to see an overall picture of a given person’s financial state\. As it is now, if you have two or three bank accounts, it can be nearly impossible for a third\-party company to see your full financial picture\. With the advent of PSD2, it will now become very easy for them to do so\. The method of making banking data open and transparent is achieved through the use of APIs\. This means that banks need to develop accurate, well\-functioning APIs in order to be compliant\. This will be a great benefit for people who bank in different countries\. For example, imagine you are from the UK but move to France\. Currently, France would have no information on your banking history\. This would make it very hard for them to determine whether or not they should grant you a loan – or even let you open a bank account at all\. With PSD2 in place, a French bank would be able to look at your file and see exactly what money choices you have made in the last couple of years\. This would give them the information they need to help them decide whether or not to provide you with a loan\. Of course, this also has the added benefit – for the bank – of making more careful and reasonable choices about who to make loans and other financial tools available\. SPEAK TO OUR TEAM ABOUT PSD2 COMPLIANCE MONITORING ### Cutting out the middleman Payments will also be radically simplified under PSD2\. Currently, when you try to buy something online, the information goes to a middleman, who then goes to Visa or MasterCard, who then sends the “yes” or “no” information back\. Having a standardized system in place will eliminate that middleman, and instead allow you to pay for the item directly from your bank account\. Banks, of course, will have to create APIs to make this possible\. That is expected to happen at some point in 2020\. ### Looking forward The biggest effect of PSD2 will be in the long term\. Internet\-only banks will be founded\. They will be able to use the open data to decide who to open a bank account for\. They will develop APIs in order to make all of their transactions open and apparent\. By not having to own commercial real estate in order to offer banking services, they will put a lot of pressure on traditional banks to find other ways to make profits\. This will be disruptive to the banking and financial sector as a whole\. ### The challenges of monitoring With 27\+ regional regulators all with different remits and the European Commission not setting any actual performance or quality bars PSD2 is also going to to present some interesting challenges for monitoring and API providers\. You can download our White Paper on this in our download zone – simply fill in the form on this page\. ### APIContext for Fintech Learn more about our offerings for banks, ASPs, TPP and other financial service providers ### Rankings for APIs Check out our financial services rankings for leading PSD2 APIS from the major vendors\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What is PSD2\(and what does it have to do with APIs?\) - The nuts and bolts of PSD2 - Cutting out the middleman - Looking forward - The challenges of monitoring - APIContext for Fintech - Rankings for APIs - Ready To Start Monitoring? - What is PSD2\(and what does it have to do with APIs?\) A new European Union directive has come into force that will eventually change the way people bank as we know it\. - It’s called PSD2 \(Revised Payment Service Directive\), and it will open up the way banks do business\. - It will also create new companies for processing payments\. ## Primary entities - APIContext - PSD2 - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/psd2) --- # Schedule API Calls Canonical URL: https://apicontext.com/apicontext-user-guide/tutorial-scheduling-api-calls Source: static Description: APIContext's scheduling system lets you set the frequency for repeated API calls, from once per second to longer intervals\. ## Summary APIContext's scheduling system lets you set the frequency for repeated API calls, from once per second to longer intervals\. ## Page sections ### Scheduling Main View Your available schedules are shown, an individual schedule or combinations of schedules can be applied to any individual API call or Workflow\. Calls are then randomly scheduled to run from remote locations at the frequency that you’ve requested\. This ensures that you don’t have multiple hits from the same location at the same time\. ### Create a Schedule To create a schedule, you need to decide 2 key factors: • The frequency you’re going to call the API at – this can be anything from 1 per second to 1 per day • The locations you want to call from Frequency is selected in the dropdown menu; 12 calls per hour means that your API Endpoint will be randomly called from one of our agents out in the public cloud 12 times each hour\. If, for example, you wanted to call your endpoints from every global location \(currently 125\+ locations\) every hour, you’d need a frequency of between 1 and 2 calls per minute\. Some accounts have some limitations on how frequently they can run calls – so please feel free to reach out if you have specific scheduling frequency questions\. You can then pick the locations you wish to call from\. You can do this by selecting a group: • Global regions or Worldwide • Individual Clouds i\.e\. ALL AWS, or ALL Azure • Finally, you can pick individual locations from the drop down\. ### Downtime As we realize you may, on occasion, need to take your APIs down, we’ve added in the ability to schedule downtime on API calls\. This can be used in two ways: • Schedule a maintenance outage • All for different call frequencies through the day For example: you want to monitor proactively during the work day where most of your customers are, but reduce the call frequency to maintain heartbeat monitoring over night – you’d create 2 schedules with different frequencies, one with a downtime set to outside of office hours and the other with a downtime set in office hours\. This would then give you a heartbeat test over night and normal testing during the day\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Scheduling Main View - Create a Schedule - Downtime - Ready To Start Monitoring? - Monitoring isn’t terribly useful if you have to individually run a call at a time, so we have a scheduling system to make repeated calls\. - With the APIContext scheduler you can: • Set the frequency you want to call your APIs at – this can be from once per second per location through to once a day • Select the locations you want to run from – this be refined to be a specific set of locations, or a region or a specific cloud • Set any downtime for periods you don’t want to have calls run during • Apply a schedule OR multiple schedules to API calls or Workflows and leave the rest to us This tutorial will walk through setting a schedule to test from every cloud location in Europe once every 5 minutes\. - Scheduling Main View Your available schedules are shown, an individual schedule or combinations of schedules can be applied to any individual API call or Workflow\. ## Primary entities - APIContext - Tutorial: Schedule API Calls - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/tutorial-scheduling-api-calls) --- # Types of API Calls Canonical URL: https://apicontext.com/apicontext-user-guide/types-api-calls Source: static Description: The common API call types APIContext supports for SOA, mobile app development, SaaS and similar systems that connect services\. ## Summary The common API call types APIContext supports for SOA, mobile app development, SaaS and similar systems that connect services\. ## Page sections ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - APIContext currently supports the following common types of API calls in use in Service Orientated Architectures \(SOA\), mobile application development, SaaS \(Software as a Service\) and similar systems\. - APIs allow different systems to communicate with each other\. - It lets a mobile app talk to a social network, or a payments service work the same way across the web, TV, mobile and other platforms\. ## Primary entities - APIContext - Types of API Calls - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/types-api-calls) --- # Who Uses APIContext? Canonical URL: https://apicontext.com/apicontext-user-guide/who-uses-apimetrics Source: static Description: Who uses APIContext? From the developers who build APIs to DevOps teams and the C\-suite — see who relies on our platform\. ## Summary Who uses APIContext? From the developers who build APIs to DevOps teams and the C\-suite — see who relies on our platform\. ## Page sections ### Developers Let’s start at the very beginning with the developers who build APIs\. Developers are often under pressure to get APIs out the door\. To do the key steps involved in testing their solution\. But sometimes, they don’t stop to think about how the API looks to the outside world\. APIContext is designed to test APIs from where your users are – where they are going to build their services and applications\. Without that understanding, you could be creating issues that will impact many different parts of the operation, all while thinking everything looks fine\. ### DevOps and API Platform Engineers They need to know that the APIs are functioning\. But they also have a lot of systems to look after\. And some of the ways APIs fail can be challenging to track down\. Some of the ways that APIs fail can hide from the traditional tools or systems used by DevOps teams\. An API can appear to be passing 100%, always returning pass codes\. Yet a failure can appear only to your end users\. This is extremely common in legacy systems involving chains of IT equipment of different ages\. Even then, there might be a problem somewhere in the networking stack\. An expired SSL certificate\. A misbehaving load balancer\. And your infrastructure won’t even see the inbound calls\. That’s why we had to build APIContext in the first place\. You can read a Case Study here from our client, NYLAS, about how they realized they needed to understand the external approach to maximize their performance and managed to increase their TLS speeds by 100%\. ### Customer Success Teams Stop us if you’ve heard this one: Customers are complaining about performance\. The DevOps teams are seeing no issues\. Who is right? Who can solve the disconnect? Customer success is often caught between engineering teams, who are not able to see the big picture, and customers who, clearly, believe they are always right\. With APIContext, you can see both sides of the equation\. It’s an accurate outside–in approach that see what the users are seeing\. We can even be configured to call your APIs from the same clouds your users are on\. You’ll quickly be able to see if the problem really is at your end, and take appropriate action without endless we said/they said fights\. ### Business Analysts How do you figure out what API data is telling you when so many groups might have a stake in the answer? There are a lot of parts to a successful API strategy: Understanding your critical SLAs\. Reporting accurately to customers and regulators\. Being confident that things are actually working\. With the growth of regulated Open Banking like the UK’s OB, our clients’ analyst teams are working flat\-out to report to regulators\. One client, a global Tier 1 bank, found that reporting to the UK FCA was taking most of the month to complete\. With APIContext, more than half the report was automatically generated out of the box on the first of the month and delivered directly to them\. We can automate huge parts of reporting – giving you peace of mind across your organization\. ### Regulators Sectors of the API economy are increasingly becoming regulated\. Complex and meaningful regulations have been set regarding how APIs should perform and what success looks like\. The challenge for global regulators is simple: how do you manage a system where both sides can prove compliance? Who provides the mechanism for dispute resolution? Currently, this relies on a degree of self\-reporting and reliance on all parties to offer reliable and accurate information\. Enter APIContext – an independent authority with no vested interest in the sector\. We can configure White Label portals and dashboards with detailed information\. All parties can use it as a dispute arbitration point\. In a recent example in the UK, one client was able to demonstrate to regulators that the problems stemmed from how a particular TPP had configured their integration – not from a problem with the bank’s APIs\. ### Sourcing Digital business is increasingly delivered via API, but how do you know what you are actually buying? Conversely, look at businesses like Google\. They have an SLA in place, but the onus is on the customer to demonstrate that the SLA was broken\. APIContext provides tools to identify and track the likely impact of poorly performing APIs\. We give sourcing departments the tools to monitor the SLAs critical to your business and potentially save money\! Read our series of articles on Service Level Management starting here\. ### C Suite Your business is digital\. You exist in an ecosystem of connected, open IT systems with new regulations\. You have competitors that you now need to work with\. How do you get the information on performance that you can trust? Do you have a way to get the data you need in clear, jargon\-free dashboards that will show you where you stand in the market and where work needs to be done? Don’t worry\. APIContext has your back\. Schedule some time with us and we can help\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Developers - DevOps and API Platform Engineers - Customer Success Teams - Business Analysts - Regulators - Sourcing - C Suite - Ready To Start Monitoring? - You might think that APIContext is \*just\* a technical product for a technical user base\. - Well, it can be\. - But we have users across all aspects of the digital business – from the developers who build APIs and the DevOps teams who manage them, up to the C suite\. ## Primary entities - APIContext - Who Uses APIContext - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apicontext-user-guide/who-uses-apimetrics) --- # Free API Tools Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources Source: static Description: Free API tools and datasets from APIContext, including performance dashboards, regional data, and reference servers to test against\. ## Summary Free API tools and datasets from APIContext, including performance dashboards, regional data, and reference servers to test against\. ## Page sections ### Browse Free API Tools Category: Tools Free API tools and datasets from APIContext: performance dashboards, regional data, and reference test servers\. - [Cross Cloud API Latency Analysis](/apimetrics-free-api-tools-resources/cross-cloud-api-latency-analysis) - [HTTPbin Network](/apimetrics-free-api-tools-resources/free-test-api) - [US Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/us-government-api-rating-dashboard) - [UK Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/uk-government-api-rating-dashboard) - [Social Networking API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/social-networking-api-rating-dashboard) - [Search API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/search-api-rating-dashboard) - [PSD2 Sandbox API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/psd2-sandbox-api-rating-dashboard) - [Cryptocurrency Exchange API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/cryptocurrency-exchange-api-rating-dashboard) - [COVID19 API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/covid19-api-rating-dashboard) - [Corporate API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/corporate-api-rating-dashboard) - [CMA9 Open Data API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/cma9-open-data-api-rating-dashboard-2) - [API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards) ### API Ratings Dashboards In addition to monitoring your critical APIs and providing you with insights into how they function, APIContext can provide detailed ratings, rankings and analysis on APIs you use, depend or are are interested in\. ### Cross Cloud API Latency Analysis The map shows relative performance of a standard, reference GET request made to servers running on all the Google locations and via the Google global load balancer\. ### HTTPbin Network APIContext provides a network of HTTPbin servers to use as free test API servers\. These can be called from a variety of locations to measure overall performance from many locations without any security or setup\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Ratings Dashboards - Cross Cloud API Latency Analysis - HTTPbin Network - Ready To Start Monitoring? - US Government API Ratings Dashboards - UK Government API Ratings Dashboards - Social Networking API Ratings Dashboards - Search API Ratings Dashboards - PSD2 Sandbox API Ratings Dashboards - Cryptocurrency Exchange API Ratings Dashboards - APIContext offers a free set of tools and datasets to help with decision making for your APIs – in addition to our Knowledge Base, we have dashboards of standard API performance and free regional data\. - We also provide a complete network of API reference servers to test against which provide insight into regional variance\. - API Ratings Dashboards In addition to monitoring your critical APIs and providing you with insights into how they function, APIContext can provide detailed ratings, rankings and analysis on APIs you use, depend or are are interested in\. ## Primary entities - APIContext - APIContext Resources - Free API Tools - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources) - [Cross Cloud API Latency Analysis](/apimetrics-free-api-tools-resources/cross-cloud-api-latency-analysis) - [HTTPbin Network](/apimetrics-free-api-tools-resources/free-test-api) - [US Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/us-government-api-rating-dashboard) - [UK Government API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/uk-government-api-rating-dashboard) - [Social Networking API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/social-networking-api-rating-dashboard) - [Search API Ratings Dashboards](/apimetrics-free-api-tools-resources/api-ratings-dashboards/search-api-rating-dashboard) --- # API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards Source: static Description: Free public API ratings, rankings and analysis from APIContext, covering the APIs you use, depend on, or are interested in\. ## Summary Free public API ratings, rankings and analysis from APIContext, covering the APIs you use, depend on, or are interested in\. ## Page sections ### Corporate IT APIs Top Corporate APIs from leading technology vendors ### PSD2 Fintech APIs PSD2 and Fintech APIs from top global providers ### UK CMA9 APIs Open Data, Open Banking APIs from the UK CMA9 Banks ### Search Comparisons of performance of the leading global search engines ### COVID\-19 Top APIs with the latest COVID19 data from around the world ### Social Networking Performance of leading social networking services ### Crypto Exchanges Rankings and performnce data on top cypto currency exchanges ### US Fed APIs Performance of leading USA Open Government APIs ### UK Gov APIs Key Open Data APIs from the UK government\. ### How we build our API Ranking Dashboards Our API rating dashboards are powered using the APIContext API Monitoring platform and we rank using our patented CASC scoring system that allows us to make like\-for\-like comparisons between different providers in a meaningful way\. We make standard calls to each of the APIs using our own credentials to handle the comparisons and make those calls from every public cloud data center\. ### Get Your own API Rating Dashboard If you’d like to discuss how you could have an API Rating Dashboard of your own, feel free to contact us and our team will assist you\. ## Key facts - Corporate IT APIs - PSD2 Fintech APIs - UK CMA9 APIs - Search - COVID\-19 - Social Networking - Crypto Exchanges - US Fed APIs - In addition to monitoring your critical APIs and providing insights into how they function, APIContext can provide detailed ratings, rankings and analysis on APIs you use, depend or are interested in\. - We host free public API reports and we have a variety of interesting datasets to explore that update on a weekly and monthly basis\. - Corporate IT APIs Top Corporate APIs from leading technology vendors PSD2 Fintech APIs PSD2 and Fintech APIs from top global providers UK CMA9 APIs Open Data, Open Banking APIs from the UK CMA9 Banks Search Comparisons of performance of the leading global search engines COVID\-19 Top APIs with the latest COVID19 data from around the world Social Networking Performance of leading social networking services Crypto Exchanges Rankings and performnce data on top cypto currency exchanges US Fed APIs Performance of leading USA Open Government APIs UK Gov APIs Key Open Data APIs from the UK government\. ## Primary entities - APIContext - API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards) --- # CMA9 Open Data API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/cma9-open-data-api-rating-dashboard-2 Source: static Description: APIContext tracks the CMA9 Open Data APIs mandated by the FCA for UK banks, covering products, branch locations and ATM data\. ## Summary APIContext tracks the CMA9 Open Data APIs mandated by the FCA for UK banks, covering products, branch locations and ATM data\. ## Page sections ### CMA9 Open Data API Rating Dashboard includes: • NatWest • Bank of Ireland • Lloyds Banking Group • HSBC • Nationwide • Danske • Santander • Barclays ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - CMA9 Open Data API Rating Dashboard includes: - Ready To Start Monitoring? - APIContext tracks the performance of the CMA9 Open Data API ratings that are mandated by the FCA for the leading UK banks to provide real data on products, branch locations and ATMs\. - We providing API Rating and Ranking data including overall quality, latency and up\-time\. - We also provide free, real\-time availability data\. ## Primary entities - APIContext - CMA9 Open Data API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/cma9-open-data-api-rating-dashboard-2) --- # Corporate API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/corporate-api-rating-dashboard Source: static Description: APIContext tracks the performance of hundreds of corporate APIs from Microsoft, Google, Salesforce and more, with free availability data\. ## Summary APIContext tracks the performance of hundreds of corporate APIs from Microsoft, Google, Salesforce and more, with free availability data\. ## Page sections ### Corporate API Rating Dashboard includes: • Microsoft • Google • Salesforce • Box • Mailchimp • Heroku • Dropbox • DocuSign • Zoom • Sendgrid • Cisco • PagerDuty • Github ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Corporate API Rating Dashboard includes: - Ready To Start Monitoring? - APIContext tracks the performance of hundreds of corporate APIs that developers and businesses rely on from data centers around the world\. - Providing API Rating and Ranking data including overall quality, latency and up\-time\. - We also provide free, real\-time availability data\. ## Primary entities - APIContext - Corporate API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/corporate-api-rating-dashboard) --- # COVID19 API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/covid19-api-rating-dashboard Source: static Description: APIContext tracks the performance of leading COVID\-19 APIs, including CDC data, with quality, latency and real\-time availability\. ## Summary APIContext tracks the performance of leading COVID\-19 APIs, including CDC data, with quality, latency and real\-time availability\. ## Page sections ### API Ratings: COVID19 APIs APIContext tracks the performance of leading COVID19 API ratings that people are relying on to track the pandemic\. Providing API Rating and Ranking data including overall quality, latency and up\-time\. We also provide free, real\-time availability data\. ### COVID19 API Rating Dashboard includes: • CDC • The COVID Tracking Project • COVID19\-India • New South Wales COVID19 • ECDC COVID Response • GSA COVID Response ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Ratings: COVID19 APIs - COVID19 API Rating Dashboard includes: - Ready To Start Monitoring? - API Ratings: COVID19 APIs APIContext tracks the performance of leading COVID19 API ratings that people are relying on to track the pandemic\. - Providing API Rating and Ranking data including overall quality, latency and up\-time\. - We also provide free, real\-time availability data\. ## Primary entities - APIContext - COVID19 API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/covid19-api-rating-dashboard) --- # Cryptocurrency Exchange API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/cryptocurrency-exchange-api-rating-dashboard Source: static Description: APIContext tracks the performance of major cryptocurrency exchange APIs, with quality, latency, uptime and availability data\. ## Summary APIContext tracks the performance of major cryptocurrency exchange APIs, with quality, latency, uptime and availability data\. ## Page sections ### API Ratings: Cryptocurrency Exchanges APIContext tracks the performance of a large number of cryptocurrency exchange API ratings that developers and traders rely on from data centers around the world\. Providing API Rating and Ranking data including overall quality, latency and up\-time\. We also provide free, real\-time availability data\. ### Cryptocurrency Exchange API Rating Dashboard includes: • OKEx • CryptoCompare • Coinpaprika • BitMEX • Poloniex • LAToken • Bancor Network • RadarRelay • Coinlore ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Ratings: Cryptocurrency Exchanges - Cryptocurrency Exchange API Rating Dashboard includes: - Ready To Start Monitoring? - API Ratings: Cryptocurrency Exchanges APIContext tracks the performance of a large number of cryptocurrency exchange API ratings that developers and traders rely on from data centers around the world\. - Providing API Rating and Ranking data including overall quality, latency and up\-time\. - We also provide free, real\-time availability data\. ## Primary entities - APIContext - Cryptocurrency Exchange API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/cryptocurrency-exchange-api-rating-dashboard) --- # PSD2 Sandbox API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/psd2-sandbox-api-rating-dashboard Source: static Description: APIContext tracks the performance of leading PSD2 Sandbox APIs used by open banking and fintech solutions, with free availability data\. ## Summary APIContext tracks the performance of leading PSD2 Sandbox APIs used by open banking and fintech solutions, with free availability data\. ## Page sections ### API Ratings: PSD2 Sandbox APIs APIContext tracks the performance of leading PSD2 Sandbox API ratings that are used by leading open banking and fintech solutions\. We provide API Rating and Ranking data including overall quality, latency and up\-time\. We also provide free, real\-time availability data\. ### PSD2 Sandbox API Rating Dashboard includes: • Capital One • Stripe • Railsbank • PayPal • Plaid • Open Bank Project • BBVA • Square ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Ratings: PSD2 Sandbox APIs - PSD2 Sandbox API Rating Dashboard includes: - Ready To Start Monitoring? - API Ratings: PSD2 Sandbox APIs APIContext tracks the performance of leading PSD2 Sandbox API ratings that are used by leading open banking and fintech solutions\. - We provide API Rating and Ranking data including overall quality, latency and up\-time\. - We also provide free, real\-time availability data\. ## Primary entities - APIContext - PSD2 Sandbox API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/psd2-sandbox-api-rating-dashboard) --- # Search API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/search-api-rating-dashboard Source: static Description: APIContext tracks the performance of leading Search APIs like Google, Bing and Foursquare — free reports on what works best\. ## Summary APIContext tracks the performance of leading Search APIs like Google, Bing and Foursquare — free reports on what works best\. ## Page sections ### API Ratings: Search APIs APIContext tracks the performance of leading Search API ratings that are used by hundreds of millions of people everyday\. Which should you use? Which work best? We have free reports with the answers\. ### Search API Rating Dashboard includes: • Google • Bing • Foursquare ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Ratings: Search APIs - Search API Rating Dashboard includes: - Ready To Start Monitoring? - API Ratings: Search APIs APIContext tracks the performance of leading Search API ratings that are used by hundreds of millions of people everyday\. - Which should you use? - Which work best? ## Primary entities - APIContext - Search API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/search-api-rating-dashboard) --- # Social Networking API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/social-networking-api-rating-dashboard Source: static Description: APIContext tracks the performance of leading Social Networking APIs used by hundreds of millions of people every day\. ## Summary APIContext tracks the performance of leading Social Networking APIs used by hundreds of millions of people every day\. ## Page sections ### API Ratings: Social Networking APIs APIContext tracks the performance of leading Social Networking API ratings that are used by hundreds of millions of people everyday\. Which should you use? Which work best – we have free reports with the answers\. ### Social Networking API Rating Dashboard includes: • Reddit • Facebook • Twitter • Etsy • Tumblr • LinkedIn • instagram • Foursquare ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Ratings: Social Networking APIs - Social Networking API Rating Dashboard includes: - Ready To Start Monitoring? - API Ratings: Social Networking APIs APIContext tracks the performance of leading Social Networking API ratings that are used by hundreds of millions of people everyday\. - Which should you use? - Which work best – we have free reports with the answers\. ## Primary entities - APIContext - Social Networking API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/social-networking-api-rating-dashboard) --- # UK Government API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/uk-government-api-rating-dashboard Source: static Description: APIContext tracks UK Government API performance, including GOV\.UK, Police\.uk, Met Office and NHS — free reports on what works best\. ## Summary APIContext tracks UK Government API performance, including GOV\.UK, Police\.uk, Met Office and NHS — free reports on what works best\. ## Page sections ### UK Government API Rating Dashboard includes: • GOV\.UK • Police\.uk • Met Office • NHS ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - UK Government API Rating Dashboard includes: - Ready To Start Monitoring? - APIContext tracks the performance of UK Government API ratings that are used by leading UK government departments\. - Which should you use? - Which work best? ## Primary entities - APIContext - UK Government API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/uk-government-api-rating-dashboard) --- # US Government API Ratings Dashboards Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/api-ratings-dashboards/us-government-api-rating-dashboard Source: static Description: APIContext tracks the performance, quality, latency and uptime of leading US government APIs, with free real\-time availability data\. ## Summary APIContext tracks the performance, quality, latency and uptime of leading US government APIs, with free real\-time availability data\. ## Page sections ### US Government API Rating Dashboard includes: • Department of Justice • FDA • Bureau of Labor & Statistics • Federal Aviation Administration • FCC • GSA • Dept of Energy • Dept of Veterans Affairs • FEC • Dept of Labor ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - US Government API Rating Dashboard includes: - Ready To Start Monitoring? - APIContext tracks the performance of of leading US government API ratings that developers and citizens rely on from data centers around the world\. - We provide API Rating and Ranking data including overall quality, latency and up\-time\. - We also provide free, real\-time availability data\. ## Primary entities - APIContext - US Government API Ratings Dashboards - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/api-ratings-dashboards/us-government-api-rating-dashboard) --- # Cross Cloud API Latency Analysis Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/cross-cloud-api-latency-analysis Source: static Description: APIContext's Google Cloud latency heat map shows GET request performance across Google locations, measured from AWS, Azure, and IBM\. ## Summary APIContext's Google Cloud latency heat map shows GET request performance across Google locations, measured from AWS, Azure, and IBM\. ## Page sections ### How we do it? APIContext has set up a network of HTTPbin servers which make reference calls from all our public locations hosted on AWS, Amazon, Google and IBM\. The calls themselves are either made in sequence from each data\-center to each end point or via the Google Global Load balancer\. ### What this means to you? With the basic chart you can see the impact of making a call from location X to cloud data center Y – either in terms of geography, usually the TCP connect time, or the location look up time\. ### Things to watch for Not all cloud services work well with all the others\. What works great on an all AWS setup can be poor if one of your partners works with Azure\. It’s important to understand these combinations and how they can impact customers and users when trouble shooting why you are missing problems other users are complaining about\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - How we do it? - What this means to you? - Things to watch for - Ready To Start Monitoring? - This APIContext API latency heat map shows relative performance of a standard, reference GET request made to servers running on all the Google locations and via the Google global load balancer\. - Calls are made from AWS, Azure, IBM and Google clouds, and data is stored for all steps of the API call process and the key percentiles under consideration\. ## Primary entities - APIContext - Cross Cloud API Latency Analysis - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/cross-cloud-api-latency-analysis) --- # HTTPbin Network Canonical URL: https://apicontext.com/apimetrics-free-api-tools-resources/free-test-api Source: static Description: APIContext's free HTTPbin test API servers let you measure performance from many locations with no security setup required\. ## Summary APIContext's free HTTPbin test API servers let you measure performance from many locations with no security setup required\. ## Page sections ### How HTTPbin works Measuring performance from different regions and different clouds is core to what we do and providing developers, managers and product owners with the tools needed to understand what the impact of different locations and clouds is critical\. To help people with this information we’ve set up a network of HTTPbin servers for developers to use to test against\. In each of the seven current Google Cloud regions, we have set up a small f1\-micro VM running the HTTPbin API service\. They are set up within a shared VPC network, which is fronted by the Google Cloud Load Balancer\. They also each have an external IP address allocated, so they may be accessed directly\. The external IPs for the Load Balancer and the VMs were assigned to DNS records for both apimetrics\.xyz and api\.expert – the diagram only shows the api\.expert domains, the naming pattern is the same for both\. We are using Google Cloud DNS for the nameservers, with the TTL of each record set to 24 hours to allow caching for a reasonable period of time\. ### How to use the free test API The easiest way to take advantage of the free test APIs is through a test account with APImetrics – when you create a first test we pre\-populate the form with a sample HTTPbin call – but you can just use the external IP and DNS names to hit them direct yourself\. ### Example data We use the data to generate our maps of Cloud Data Center Latency which can be seen here, which shows the differences in performance between different clouds and the Google network\. ### Testing Your Own APIs APIContext provides a complete set of test tools to test the performance and functionality of individual calls and workflows with a simple user interface that even lets you test locally through the browser\. Whatever your API testing needs, we have tools and services to help\. Create a free APIContext Trial Account – No Credit Card Needed to use our free test APIs ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - How HTTPbin works - How to use the free test API - Example data - Testing Your Own APIs - Ready To Start Monitoring? - APIContext provides a network of HTTPbin servers to use as free test API servers\. - These can be called from a variety of locations to measure overall performance from many locations without any security or setup\. - Create a free APIContext Trial Account – No Credit Card Needed to use our free test APIs How HTTPbin works Measuring performance from different regions and different clouds is core to what we do and providing developers, managers and product owners with the tools needed to understand what the impact of different locations and clouds is critical\. ## Primary entities - APIContext - HTTPbin Network - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/apimetrics-free-api-tools-resources/free-test-api) --- # Blog Canonical URL: https://apicontext.com/blog Source: static Description: Latest APIContext blog posts on API monitoring, reliability, open banking, and enterprise API strategy\. ## Summary The APIContext blog covers API monitoring, reliability, open banking, AI/MCP infrastructure, and enterprise API strategy, organized into topic categories\. ## Page sections ### Latest from APIContext Category: Blog & News The blog index lists the newest posts first and can be filtered by category using ?category=\. - [Announcements](/blog?category=announcements) - [API Updates](/blog?category=api-update) - [Ask the Experts](/blog?category=ask-the-experts) - [Case Studies](/blog?category=case-studies) - [Cloud](/blog?category=cloud) - [Enterprise IT](/blog?category=enterprise-it) - [Feature Updates](/blog?category=feature-updates) - [Fintech](/blog?category=fintech) - [News](/blog?category=news) - [Opinion](/blog?category=opinion) - [OWASP](/blog?category=owasp) - [Press Releases](/blog?category=press-release) - [Release Notes](/blog?category=release-notes) - [White Papers](/blog?category=white-papers) - [Automotive](/blog?category=automotive) - [Government](/blog?category=government) - [IoT](/blog?category=iot) - [Media](/blog?category=media) - [Retail](/blog?category=retail) - [Telco](/blog?category=telco) - [Travel](/blog?category=travel) - [Life Sciences](/blog?category=life-sciences) - [Utilities](/blog?category=utilities) ## Key facts - Announcements: Product launches, company milestones, and APIContext news\. - API Updates: Noteworthy changes and incidents across major public APIs\. - Ask the Experts: Interviews and Q&As with API practitioners and industry leaders\. - Case Studies: How enterprises use APIContext to improve API reliability and customer outcomes\. - Cloud: API performance across cloud providers, regions, and edge infrastructure\. - Enterprise IT: API reliability, governance, and observability for enterprise technology teams\. - Feature Updates: New features, improvements, and capabilities in the APIContext platform\. - Fintech: API reliability and conformance in financial services, open banking, and payments\. - News: Industry news and analysis relevant to API\-first teams\. - Opinion: Perspectives from the APIContext team on the state of APIs, standards, and monitoring\. - OWASP: API security analysis through the OWASP API Security Top 10 lens\. - Press Releases: Official announcements and press coverage\. - Release Notes: Technical changelogs and release details for the APIContext platform\. - White Papers: In\-depth research and technical analysis on API quality, monitoring, and conformance\. - Automotive: API reliability in connected vehicles and automotive platforms\. - Government: API standards, conformance, and monitoring in public sector contexts\. - IoT: API connectivity and reliability for Internet of Things ecosystems\. - Media: API performance and reliability in media and content delivery\. - Retail: API reliability and performance in retail and e\-commerce\. - Telco: API quality and monitoring in telecommunications networks\. - Travel: API performance in travel booking and hospitality platforms\. - Life Sciences: API reliability in scientific instruments, pharma, and life sciences platforms\. - Utilities: API reliability in energy, water, and utility sector platforms\. ## Primary entities - APIContext - API monitoring - blog - Announcements - API Updates - Ask the Experts - Case Studies - Cloud - Enterprise IT - Feature Updates - Fintech - News - Opinion - OWASP - Press Releases - Release Notes - White Papers - Automotive - Government - IoT - Media - Retail - Telco - Travel - Life Sciences - Utilities ## Audience - API teams - SRE teams - technology leaders ## Primary links - [Browse the blog](/blog) --- # Careers Canonical URL: https://apicontext.com/careers Source: static Description: Join APIContext and help teams make critical APIs more reliable, measurable, and trusted\. ## Summary APIContext is a small, focused team helping organizations collect independent evidence about API reliability, performance, quality, and trust\. ## Page sections ### Core values - Customer: Prioritizing customer needs and solving their problems effectively\. - Hope: Believing in the positive impact of our work on the world\. - Ownership: Taking responsibility and accountability for solving problems and delivering results\. - Integrity: Upholding our values with consistency and transparency\. - Contribution: Committing to impactful work and pulling our weight\. - Enjoyment: Finding joy in the journey and the work we do\. ## Key facts - APIContext monitors APIs from the outside in, across clouds and regions, using real calls and operational context\. - Customers use APIContext to understand service quality, compare providers, validate SLAs, catch drift, and prove what happened when an API experience breaks down\. - The team works across authentication, networking, observability, standards, customer workflows, and API reliability\. - Customer: Prioritizing customer needs and solving their problems effectively\. - Hope: Believing in the positive impact of our work on the world\. - Ownership: Taking responsibility and accountability for solving problems and delivering results\. - Integrity: Upholding our values with consistency and transparency\. - Contribution: Committing to impactful work and pulling our weight\. - Enjoyment: Finding joy in the journey and the work we do\. ## Primary entities - APIContext - API monitoring - API reliability - API careers ## Audience - job candidates - API engineers - SRE teams - product teams ## Primary links - [Talk to us](/contact) - [View open roles](https://www.linkedin.com/company/apicontext/jobs/) --- # APIContext \+ Akamai API Security Canonical URL: https://apicontext.com/compare/apicontext-and-akamai-api-security Source: static Description: Not an Akamai API Security alternative — APIContext feeds conformance signal into it and covers APIs traffic\-based discovery cannot see\. ## Summary Akamai API Security discovers and protects the APIs in your own traffic\. APIContext feeds conformance signal into it, and covers the APIs it structurally cannot see — the third\-party endpoints you consume\. Akamai API Security, built on the Noname Security platform Akamai acquired, discovers every API across your estate, scores its posture, tests it for vulnerabilities, and detects runtime threats\. It does that by observing traffic: mirrored flows, gateway and load balancer integrations, edge telemetry, and configuration\. That is the right way to secure what you publish, and it defines the boundary of what can be discovered — an API only becomes visible once its traffic crosses infrastructure you control\. APIContext works from the opposite direction, as a client, from 125\+ locations outside your estate\. Two things follow: APIContext conformance signal enriches the posture view, and the third\-party APIs your applications depend on become visible for the first time\. ## Page sections ### Which platform produces which signal Akamai API Security, built on the Noname Security platform Akamai acquired, discovers every API across your estate, scores its posture, tests it for vulnerabilities, and detects runtime threats\. It does that by observing traffic: mirrored flows, gateway and load balancer integrations, edge telemetry, and configuration\. That is the right way to secure what you publish, and it defines the boundary of what can be discovered — an API only becomes visible once its traffic crosses infrastructure you control\. APIContext works from the opposite direction, as a client, from 125\+ locations outside your estate\. Two things follow: APIContext conformance signal enriches the posture view, and the third\-party APIs your applications depend on become visible for the first time\. - Discovery method — APIContext: Active — calls the API as a client, from outside, on a schedule you set; Akamai API Security: Passive — observes traffic crossing infrastructure you control - APIs you publish — APIContext: Verified against their published contract from outside; Akamai API Security: Discovered, inventoried, posture\-scored, and protected - Third\-party APIs you consume — APIContext: Yes — monitored continuously, with SLA and conformance evidence; Akamai API Security: Not discoverable — their traffic never transits your estate\. APIContext supplies it - Shadow and zombie API discovery — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — core strength - Sensitive data classification — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — core strength - Runtime threat detection and blocking — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — core strength - Vulnerability and security testing — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — pre\-production and continuous testing - Contract and schema conformance — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Akamai API Security: Not collected — APIContext supplies it - Authentication chain verification — APIContext: Yes — executes full mTLS, FAPI 2\.0, PAR, DPoP, and JARM flows end to end; Akamai API Security: Observes and enforces auth policy on traffic it sees - Security header and TLS posture from outside — APIContext: Yes — measured per region and per hop on every check; Akamai API Security: Configuration and edge posture from inside - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response per hop; 30\+ data points per call; Akamai API Security: Not collected — APIContext supplies it - Works together — APIContext: Sends conformance events and evidence into security workflows; Akamai API Security: Correlates them with posture, discovery, and runtime findings ### What APIContext adds to Akamai API Security Passive discovery is the correct foundation for securing what you publish, and it has a hard edge: it can only see APIs whose traffic reaches your infrastructure\. APIContext adds two things — a class of API that is otherwise invisible, and a class of finding that traffic observation does not produce: - The third parties you consume\. Every payment provider, identity provider, KYC service, data vendor, and partner API your applications call is a dependency with a security posture you inherit and cannot inventory — its traffic never transits your estate, so nothing in your security tooling knows it exists\. APIContext monitors those endpoints continuously and gives you an inventory, conformance history, and SLA evidence for each\. - Contract drift as a security finding\. A response that silently starts returning an extra field, drops a security header, or stops matching its published schema is a posture change that no vulnerability scan and no traffic anomaly will flag\. APIContext validates every response against its OpenAPI and FAPI 2\.0 specification and reports the diff\. - Authentication verified by execution, not inspection\. APIContext performs complete mTLS handshakes and full FAPI 2\.0 flows — PAR, DPoP\-bound tokens, JARM validation — as a real client\. If a security control is misconfigured such that the flow no longer holds, that is discovered by an authorized check rather than by an attacker\. - Outside\-in TLS and header posture\. Certificate chains, cipher negotiation, and security headers measured from 125\+ locations, which is where regional edge misconfigurations actually show up\. ### What Akamai API Security does that APIContext doesn't APIContext is not a security product and does not pretend to be one\. Full\-estate API discovery including shadow and zombie endpoints, sensitive data classification, posture scoring, vulnerability and security testing, runtime threat detection, abuse and business\-logic attack detection, and enforcement at the edge are Akamai API Security's domain — and APIContext does none of them\. APIContext will never tell you that an endpoint is leaking PII, that a credential\-stuffing campaign is underway, or that an undocumented API is exposed\. It tells you whether the APIs you know about are behaving as specified, from outside, everywhere\. ### How teams run both Security teams use API Security as the authoritative inventory and enforcement layer for everything they publish, and APIContext for the two things sitting outside that boundary: continuous outside\-in verification of the critical published APIs, and the entire third\-party dependency surface\. In regulated environments the pairing has a compliance dimension too — API Security evidences that controls exist and are enforced, while APIContext evidences that they held, from named locations, on dated checks, which is the form auditors and regulators ask for\. Both are Akamai\-aligned: Akamai is an APIContext partner, and APIContext already runs checks from Akamai locations\. ### How to connect APIContext to Akamai API Security APIContext emits conformance events, evidence, and full payloads over webhook and as native OpenTelemetry, so signal can be routed into the security workflow and SIEM that API Security findings already flow through, and correlated on endpoint and timestamp\. Nothing is installed in your stack\. Start with the third\-party dependency list — it is usually the fastest thing to demonstrate, because most organisations cannot currently produce one — then add outside\-in verification on the published APIs that matter most\. Talk to us about the current Akamai integration path for your setup\. ## Key facts - APIContext is not a Akamai API Security competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Akamai API Security\. - Akamai API Security discovers and protects the APIs in your own traffic\. APIContext feeds conformance signal into it, and covers the APIs it structurally cannot see — the third\-party endpoints you consume\. - Akamai API Security, built on the Noname Security platform Akamai acquired, discovers every API across your estate, scores its posture, tests it for vulnerabilities, and detects runtime threats\. It does that by observing traffic: mirrored flows, gateway and load balancer integrations, edge telemetry, and configuration\. That is the right way to secure what you publish, and it defines the boundary of what can be discovered — an API only becomes visible once its traffic crosses infrastructure you control\. APIContext works from the opposite direction, as a client, from 125\+ locations outside your estate\. Two things follow: APIContext conformance signal enriches the posture view, and the third\-party APIs your applications depend on become visible for the first time\. - Discovery method — APIContext: Active — calls the API as a client, from outside, on a schedule you set; Akamai API Security: Passive — observes traffic crossing infrastructure you control - APIs you publish — APIContext: Verified against their published contract from outside; Akamai API Security: Discovered, inventoried, posture\-scored, and protected - Third\-party APIs you consume — APIContext: Yes — monitored continuously, with SLA and conformance evidence; Akamai API Security: Not discoverable — their traffic never transits your estate\. APIContext supplies it - Shadow and zombie API discovery — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — core strength - Sensitive data classification — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — core strength - Runtime threat detection and blocking — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — core strength - Vulnerability and security testing — APIContext: Not provided — API Security supplies it; Akamai API Security: Yes — pre\-production and continuous testing - Contract and schema conformance — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Akamai API Security: Not collected — APIContext supplies it - Authentication chain verification — APIContext: Yes — executes full mTLS, FAPI 2\.0, PAR, DPoP, and JARM flows end to end; Akamai API Security: Observes and enforces auth policy on traffic it sees - Security header and TLS posture from outside — APIContext: Yes — measured per region and per hop on every check; Akamai API Security: Configuration and edge posture from inside - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response per hop; 30\+ data points per call; Akamai API Security: Not collected — APIContext supplies it - Works together — APIContext: Sends conformance events and evidence into security workflows; Akamai API Security: Correlates them with posture, discovery, and runtime findings ## Primary entities - APIContext - Akamai API Security - APIContext \+ Akamai API Security integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext an API security product or an Akamai API Security competitor? No\. APIContext is an outside\-in API monitoring platform\. It performs no API discovery from traffic, no sensitive\-data classification, no vulnerability testing, no runtime threat detection, and no enforcement\. It complements API Security by verifying contract and authentication behavior from outside, and by covering third\-party APIs that traffic\-based discovery cannot see\. ### Why can't Akamai API Security see the third\-party APIs we consume? Because discovery works by observing traffic that crosses your infrastructure\. When your application calls a payment provider or identity provider, that API's behavior happens on someone else's infrastructure — there is no traffic to mirror, so there is nothing to discover\. APIContext calls those endpoints directly as a client and reports what they returned\. ### What kind of security\-relevant findings does APIContext produce? Schema and contract drift, disappeared or altered security headers, TLS and certificate problems observed per region, and failures in multi\-step authentication chains such as mTLS, FAPI 2\.0, PAR, DPoP, and JARM — all measured from outside your estate on every check\. --- # APIContext \+ Akamai TrafficPeak Canonical URL: https://apicontext.com/compare/apicontext-and-akamai-trafficpeak Source: static Description: Not a TrafficPeak alternative — a partner source\. Outside\-in API conformance and per\-hop timings land in the same Akamai lake as delivery data\. ## Summary TrafficPeak keeps petabytes of Akamai delivery data queryable for years\. APIContext adds the outside\-in API layer to the same lake — conformance verdicts, per\-hop timings, and full payloads\. TrafficPeak is Akamai's managed observability service: a hosted, high\-density telemetry lake that keeps delivery, edge, and log data queryable at petabyte scale and long retention\. Akamai is an APIContext partner and TrafficPeak is already an APIContext telemetry destination, so API monitoring results land in the same place as the CDN and delivery data they relate to\. That matters because most API incidents in an Akamai estate are joint problems — something at the edge, something in the origin, and a contract that stopped being honored somewhere in between\. ## Page sections ### Which platform produces which signal TrafficPeak is Akamai's managed observability service: a hosted, high\-density telemetry lake that keeps delivery, edge, and log data queryable at petabyte scale and long retention\. Akamai is an APIContext partner and TrafficPeak is already an APIContext telemetry destination, so API monitoring results land in the same place as the CDN and delivery data they relate to\. That matters because most API incidents in an Akamai estate are joint problems — something at the edge, something in the origin, and a contract that stopped being honored somewhere in between\. - Role in the pipeline — APIContext: Source — generates outside\-in API and network telemetry; Akamai TrafficPeak: Managed store and query layer — keeps it queryable at petabyte scale - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Akamai TrafficPeak: Akamai delivery, edge, and log data, plus whatever else you stream in - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Akamai TrafficPeak: Stores and indexes it alongside edge delivery records - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Akamai TrafficPeak: Not generated — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Akamai TrafficPeak: Not generated — APIContext supplies it - Monitoring from Akamai locations — APIContext: Yes — Akamai is one of the clouds APIContext runs checks from; Akamai TrafficPeak: Not applicable — TrafficPeak stores, it does not measure - Edge and CDN delivery data — APIContext: Not collected — Akamai supplies it; Akamai TrafficPeak: Yes — core strength - Managed ingest, retention, and query — APIContext: Operational retention windows; Akamai TrafficPeak: Yes — core strength, fully managed - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Akamai TrafficPeak: Stores the resulting history for as long as you need it - Works together — APIContext: Streams telemetry, events, and payloads to TrafficPeak; Akamai TrafficPeak: Ingests it as an existing APIContext destination ### What APIContext adds to TrafficPeak TrafficPeak already holds the richest possible record of what Akamai delivered\. What it does not hold is whether the API behind that delivery honored its contract\. APIContext supplies that layer: - The API contract next to the delivery record\. A 200 served fast from the edge and a response that no longer matches its OpenAPI spec are the same row in a delivery log and completely different events in a conformance check\. Both land in the same lake, on the same timestamp\. - Per\-hop timings from outside the edge\. DNS, TLS, connection, and transfer measured from 125\+ locations — including Akamai locations — so an origin problem, an edge configuration problem, and a routing problem are distinguishable rather than argued about\. - Third\-party APIs in the same view\. The partner and vendor APIs your application calls generate no Akamai delivery data at all, because they are not your traffic\. APIContext measures them and streams the results into the same lake\. ### What TrafficPeak does that APIContext doesn't Managed ingest, compression, indexing, and query across petabytes — plus the Akamai delivery, edge, and security data that only Akamai can produce — are TrafficPeak's domain, and APIContext does none of them\. The division is a question of time horizon and breadth\. APIContext answers "is this API honoring its contract right now, from everywhere?" TrafficPeak answers "what has happened across the whole estate, for as long as we need to be able to ask\." ### How teams run both Akamai customers usually arrive here already running TrafficPeak for delivery observability, and add APIContext to cover the API layer their edge data cannot describe\. The pairing is the same one behind the APIContext and Hydrolix story — TrafficPeak is built on Hydrolix — with Akamai running the ingest, retention, and query as a managed service rather than something your team operates\. - [APIContext and Hydrolix](/compare/apicontext-and-hydrolix) ### How to connect APIContext to TrafficPeak TrafficPeak is an existing APIContext telemetry destination, so this is a configuration step rather than an engineering project: point APIContext's exporter at your TrafficPeak instance and API telemetry, conformance events, and payloads begin landing alongside your delivery data\. Nothing is installed in your stack\. Most teams start with one API portfolio, confirm the records carry the tags they want to query on, then widen coverage\. ## Key facts - APIContext is not a Akamai TrafficPeak competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Akamai TrafficPeak\. - TrafficPeak keeps petabytes of Akamai delivery data queryable for years\. APIContext adds the outside\-in API layer to the same lake — conformance verdicts, per\-hop timings, and full payloads\. - TrafficPeak is Akamai's managed observability service: a hosted, high\-density telemetry lake that keeps delivery, edge, and log data queryable at petabyte scale and long retention\. Akamai is an APIContext partner and TrafficPeak is already an APIContext telemetry destination, so API monitoring results land in the same place as the CDN and delivery data they relate to\. That matters because most API incidents in an Akamai estate are joint problems — something at the edge, something in the origin, and a contract that stopped being honored somewhere in between\. - Role in the pipeline — APIContext: Source — generates outside\-in API and network telemetry; Akamai TrafficPeak: Managed store and query layer — keeps it queryable at petabyte scale - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Akamai TrafficPeak: Akamai delivery, edge, and log data, plus whatever else you stream in - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Akamai TrafficPeak: Stores and indexes it alongside edge delivery records - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Akamai TrafficPeak: Not generated — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Akamai TrafficPeak: Not generated — APIContext supplies it - Monitoring from Akamai locations — APIContext: Yes — Akamai is one of the clouds APIContext runs checks from; Akamai TrafficPeak: Not applicable — TrafficPeak stores, it does not measure - Edge and CDN delivery data — APIContext: Not collected — Akamai supplies it; Akamai TrafficPeak: Yes — core strength - Managed ingest, retention, and query — APIContext: Operational retention windows; Akamai TrafficPeak: Yes — core strength, fully managed - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Akamai TrafficPeak: Stores the resulting history for as long as you need it - Works together — APIContext: Streams telemetry, events, and payloads to TrafficPeak; Akamai TrafficPeak: Ingests it as an existing APIContext destination ## Primary entities - APIContext - Akamai TrafficPeak - APIContext \+ Akamai TrafficPeak integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a TrafficPeak competitor? No\. Akamai is an APIContext partner and TrafficPeak is an APIContext telemetry destination\. TrafficPeak stores and queries telemetry at scale; APIContext generates outside\-in API telemetry to put in it\. APIContext does not offer managed data lake storage\. ### How does this relate to APIContext and Hydrolix? TrafficPeak is built on Hydrolix and delivered by Akamai as a managed service\. The data model and the reason for pairing it with APIContext are the same; the difference is who operates it\. ### Can APIContext monitor from Akamai locations? Yes\. Akamai is one of the clouds APIContext runs checks from, alongside AWS, GCP, and Azure, plus private nodes inside your own network\. --- # APIContext \+ Apigee Canonical URL: https://apicontext.com/compare/apicontext-and-apigee Source: static Description: Not an Apigee alternative — Apigee manages and secures your APIs; APIContext verifies from outside that the published contract matches reality\. ## Summary Apigee manages, secures, and analyses the APIs you publish\. APIContext verifies from outside — from 125\+ locations — that the contract Apigee publishes is the one consumers actually receive\. Apigee is Google Cloud's API management platform: proxies, policies, security, quota and monetization, a developer portal, and analytics over the traffic it processes\. Its analytics are strong and bounded by the same thing every gateway's are — they describe requests that reached the proxy\. APIContext calls the same APIs as a client from outside Google Cloud entirely, executes full authentication chains, and validates each response against the OpenAPI specification Apigee publishes\. ## Page sections ### Which platform produces which signal Apigee is Google Cloud's API management platform: proxies, policies, security, quota and monetization, a developer portal, and analytics over the traffic it processes\. Its analytics are strong and bounded by the same thing every gateway's are — they describe requests that reached the proxy\. APIContext calls the same APIs as a client from outside Google Cloud entirely, executes full authentication chains, and validates each response against the OpenAPI specification Apigee publishes\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Apigee: At the gateway — traffic that reached Apigee and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Apigee: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Apigee: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Apigee: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Apigee: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Apigee: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Apigee: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Apigee: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Apigee: Analytics and reporting for traffic Apigee processed - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Apigee: Yes — core strength, via proxies, policies, and quotas - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Apigee: Yes — developer portal and API hub cataloguing - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Apigee: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Apigee publishes as its monitoring contract; Apigee: Publishes the spec, and exports its own telemetry alongside ### What APIContext adds to Apigee Apigee sees every request that reached it\. That is a complete record of one thing and no record at all of three others, each of which is where real API incidents tend to live: - Requests that never arrived\. A DNS record pointing at a decommissioned region, a certificate that stopped chaining on one edge node, a routing change at a transit provider — the gateway logs none of it, because the traffic never got there\. APIContext measures it from 125\+ locations and attributes the failure to the responsible hop\. - Responses that are wrong but successful\. Gateway analytics count status codes\. A 200 carrying a renamed field, a changed type, or a dropped security header breaks consumers immediately and looks perfectly healthy in a traffic dashboard\. APIContext validates every response against the published spec and reports the diff\. - The APIs you consume rather than publish\. Your gateway fronts what you expose\. It has nothing to say about the payment provider, identity provider, or partner API your services depend on — and those fail too\. APIContext monitors them continuously and produces SLA evidence you own\. - Coverage where no user has been yet\. Analytics can only describe endpoints somebody called\. Synthetic checks fire on every interval against every endpoint, including the ones with no traffic today and the auth chains nobody exercises until a partner tries at month end\. ### What Apigee does that APIContext doesn't Publishing and versioning APIs, authentication and authorization enforcement, rate limiting and quotas, request routing and transformation, developer onboarding, and the traffic analytics built on all of it are Apigee's domain — and APIContext does none of them\. APIContext sits entirely outside the request path: it enforces nothing, terminates nothing, and cannot change how a single production request is handled\. It is a client that calls your API the way your consumers do and reports what happened\. ### How teams run both Apigee remains the management and policy layer; APIContext becomes the independent consumer\-side check on what that layer actually delivers\. Teams running Apigee inside Google Cloud usually pair this with Cloud Monitoring, so proxy\-side analytics, project\-side service telemetry, and outside\-in conformance all reconcile in one place\. The value shows up most during proxy revision deployments and policy changes: both look correct in Apigee and can still change what a consumer receives, and APIContext names the operations and regions affected\. - [APIContext and Google Cloud Operations](/compare/apicontext-and-google-cloud-operations) ### How to connect APIContext to Apigee Export the OpenAPI spec from Apigee or your API hub and import it into APIContext; each operation becomes a monitored endpoint with its own assertions, authentication chain, and locations\. Nothing is installed in your stack and no proxy configuration changes\. Most teams start with one high\-value proxy — a login flow, a payments call, a partner\-facing endpoint — confirm the conformance results, then widen coverage\. ## Key facts - APIContext is not a Apigee competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Apigee\. - Apigee manages, secures, and analyses the APIs you publish\. APIContext verifies from outside — from 125\+ locations — that the contract Apigee publishes is the one consumers actually receive\. - Apigee is Google Cloud's API management platform: proxies, policies, security, quota and monetization, a developer portal, and analytics over the traffic it processes\. Its analytics are strong and bounded by the same thing every gateway's are — they describe requests that reached the proxy\. APIContext calls the same APIs as a client from outside Google Cloud entirely, executes full authentication chains, and validates each response against the OpenAPI specification Apigee publishes\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Apigee: At the gateway — traffic that reached Apigee and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Apigee: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Apigee: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Apigee: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Apigee: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Apigee: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Apigee: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Apigee: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Apigee: Analytics and reporting for traffic Apigee processed - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Apigee: Yes — core strength, via proxies, policies, and quotas - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Apigee: Yes — developer portal and API hub cataloguing - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Apigee: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Apigee publishes as its monitoring contract; Apigee: Publishes the spec, and exports its own telemetry alongside ## Primary entities - APIContext - Apigee - APIContext \+ Apigee integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Apigee competitor? No\. Apigee publishes, secures, and manages the APIs you expose; APIContext monitors API behavior from outside your infrastructure\. APIContext provides no gateway, no policy enforcement, no rate limiting, and no developer portal, and it sits outside the production request path entirely\. ### Apigee already has analytics\. Why add APIContext? Apigee Analytics measures traffic that reached the gateway\. It cannot see requests that failed before arriving — DNS, TLS, edge, and routing failures — cannot tell you whether a successful response still matches its published specification, and has no visibility into the third\-party APIs your services depend on\. APIContext covers all three\. ### Can APIContext use the OpenAPI spec we publish through Apigee? Yes\. Import the spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation, then validates live responses against that same contract on every check\. --- # APIContext \+ Amazon API Gateway Canonical URL: https://apicontext.com/compare/apicontext-and-aws-api-gateway Source: static Description: Not an API Gateway alternative — it secures your APIs inside AWS; APIContext reports what a client outside AWS receives, including DNS and TLS\. ## Summary API Gateway publishes and secures your APIs inside AWS\. APIContext reports what a client outside AWS actually received — including the DNS, TLS, and edge layers in front of the gateway\. Amazon API Gateway fronts your APIs inside AWS: stages and deployments, authorizers, usage plans and throttling, and CloudWatch metrics for the requests it served\. Everything it knows begins at the gateway\. APIContext calls the same APIs from outside AWS — from 125\+ locations across five clouds — executes full authentication chains, and validates each response against its OpenAPI specification, which means it also measures the DNS resolution, TLS negotiation, and CloudFront or custom\-domain layer sitting in front of the gateway\. ## Page sections ### Which platform produces which signal Amazon API Gateway fronts your APIs inside AWS: stages and deployments, authorizers, usage plans and throttling, and CloudWatch metrics for the requests it served\. Everything it knows begins at the gateway\. APIContext calls the same APIs from outside AWS — from 125\+ locations across five clouds — executes full authentication chains, and validates each response against its OpenAPI specification, which means it also measures the DNS resolution, TLS negotiation, and CloudFront or custom\-domain layer sitting in front of the gateway\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Amazon API Gateway: At the gateway — traffic that reached API Gateway and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Amazon API Gateway: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Amazon API Gateway: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Amazon API Gateway: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Amazon API Gateway: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Amazon API Gateway: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Amazon API Gateway: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Amazon API Gateway: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Amazon API Gateway: CloudWatch metrics and access logs for requests it served - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Amazon API Gateway: Yes — core strength, via authorizers, usage plans, and throttling - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Amazon API Gateway: Spec export and stage documentation - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Amazon API Gateway: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec API Gateway publishes as its monitoring contract; Amazon API Gateway: Publishes the spec, and exports its own telemetry alongside ### What APIContext adds to API Gateway API Gateway sees every request that reached it\. That is a complete record of one thing and no record at all of three others, each of which is where real API incidents tend to live: - Requests that never arrived\. A DNS record pointing at a decommissioned region, a certificate that stopped chaining on one edge node, a routing change at a transit provider — the gateway logs none of it, because the traffic never got there\. APIContext measures it from 125\+ locations and attributes the failure to the responsible hop\. - Responses that are wrong but successful\. Gateway analytics count status codes\. A 200 carrying a renamed field, a changed type, or a dropped security header breaks consumers immediately and looks perfectly healthy in a traffic dashboard\. APIContext validates every response against the published spec and reports the diff\. - The APIs you consume rather than publish\. Your gateway fronts what you expose\. It has nothing to say about the payment provider, identity provider, or partner API your services depend on — and those fail too\. APIContext monitors them continuously and produces SLA evidence you own\. - Coverage where no user has been yet\. Analytics can only describe endpoints somebody called\. Synthetic checks fire on every interval against every endpoint, including the ones with no traffic today and the auth chains nobody exercises until a partner tries at month end\. ### What API Gateway does that APIContext doesn't Publishing and versioning APIs, authentication and authorization enforcement, rate limiting and quotas, request routing and transformation, developer onboarding, and the traffic analytics built on all of it are API Gateway's domain — and APIContext does none of them\. APIContext sits entirely outside the request path: it enforces nothing, terminates nothing, and cannot change how a single production request is handled\. It is a client that calls your API the way your consumers do and reports what happened\. ### How teams run both API Gateway stays the publishing and enforcement layer, CloudWatch stays the AWS\-native control surface, and APIContext supplies the outside\-in view neither can produce\. The distinction matters most on custom domains and CloudFront distributions: a certificate, DNS, or edge configuration problem there produces no gateway log line and no CloudWatch metric, because the request never reached the gateway\. APIContext's results export into CloudWatch through the AWS Distro for OpenTelemetry, so they alarm alongside your native metrics\. - [APIContext and Amazon CloudWatch](/compare/apicontext-and-aws-cloudwatch) ### How to connect APIContext to Amazon API Gateway Export the OpenAPI spec from your API Gateway stage and import it into APIContext; each operation becomes a monitored endpoint with its own assertions, authentication chain, and locations\. Nothing is installed in your stack and no stage configuration changes\. Most teams start with one high\-value route — a login flow, a payments call, a partner\-facing endpoint — confirm the conformance results, then widen coverage and route the telemetry into CloudWatch\. ## Key facts - APIContext is not a Amazon API Gateway competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Amazon API Gateway\. - API Gateway publishes and secures your APIs inside AWS\. APIContext reports what a client outside AWS actually received — including the DNS, TLS, and edge layers in front of the gateway\. - Amazon API Gateway fronts your APIs inside AWS: stages and deployments, authorizers, usage plans and throttling, and CloudWatch metrics for the requests it served\. Everything it knows begins at the gateway\. APIContext calls the same APIs from outside AWS — from 125\+ locations across five clouds — executes full authentication chains, and validates each response against its OpenAPI specification, which means it also measures the DNS resolution, TLS negotiation, and CloudFront or custom\-domain layer sitting in front of the gateway\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Amazon API Gateway: At the gateway — traffic that reached API Gateway and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Amazon API Gateway: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Amazon API Gateway: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Amazon API Gateway: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Amazon API Gateway: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Amazon API Gateway: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Amazon API Gateway: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Amazon API Gateway: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Amazon API Gateway: CloudWatch metrics and access logs for requests it served - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Amazon API Gateway: Yes — core strength, via authorizers, usage plans, and throttling - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Amazon API Gateway: Spec export and stage documentation - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Amazon API Gateway: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec API Gateway publishes as its monitoring contract; Amazon API Gateway: Publishes the spec, and exports its own telemetry alongside ## Primary entities - APIContext - Amazon API Gateway - APIContext \+ Amazon API Gateway integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Amazon API Gateway competitor? No\. Amazon API Gateway publishes, secures, and manages the APIs you expose; APIContext monitors API behavior from outside your infrastructure\. APIContext provides no gateway, no policy enforcement, no rate limiting, and no developer portal, and it sits outside the production request path entirely\. ### Amazon API Gateway already has analytics\. Why add APIContext? CloudWatch metrics for API Gateway measures traffic that reached the gateway\. It cannot see requests that failed before arriving — DNS, TLS, edge, and routing failures — cannot tell you whether a successful response still matches its published specification, and has no visibility into the third\-party APIs your services depend on\. APIContext covers all three\. ### Can APIContext use the OpenAPI spec we publish through Amazon API Gateway? Yes\. Import the spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation, then validates live responses against that same contract on every check\. ### Does this overlap with CloudWatch Synthetics? Only loosely\. Canaries run from AWS regions and check availability and scripted flows\. APIContext runs from 125\+ locations across five clouds plus private nodes, validates responses against OpenAPI and FAPI 2\.0 specs, executes full mTLS and FAPI authentication chains, and produces CASC quality scores\. --- # APIContext \+ Amazon CloudWatch Canonical URL: https://apicontext.com/compare/apicontext-and-aws-cloudwatch Source: static Description: Not a CloudWatch alternative — a source\. CloudWatch reports what AWS resources emit; APIContext adds what clients outside AWS actually receive\. ## Summary CloudWatch reports what your AWS resources emit\. APIContext adds what customers and partners outside AWS actually receive — including the DNS, TLS, and edge layers in front of your account\. CloudWatch is the AWS\-native place metrics, logs, and alarms live: every service in your account reports into it, and your alarms and dashboards are built on it\. Every one of those signals originates inside your AWS boundary\. APIContext measures the same APIs from outside it — from 125\+ locations across AWS, GCP, Azure, and Akamai — and validates responses against their OpenAPI and FAPI 2\.0 specs\. Because APIContext emits native OpenTelemetry, those results can land in CloudWatch next to the resource metrics they explain\. ## Page sections ### Which platform produces which signal CloudWatch is the AWS\-native place metrics, logs, and alarms live: every service in your account reports into it, and your alarms and dashboards are built on it\. Every one of those signals originates inside your AWS boundary\. APIContext measures the same APIs from outside it — from 125\+ locations across AWS, GCP, Azure, and Akamai — and validates responses against their OpenAPI and FAPI 2\.0 specs\. Because APIContext emits native OpenTelemetry, those results can land in CloudWatch next to the resource metrics they explain\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Amazon CloudWatch: Inside your AWS account — what each service reports about itself - Scope — APIContext: Any API, on any cloud, including ones you do not own; Amazon CloudWatch: AWS services and anything you push via the CloudWatch APIs - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Amazon CloudWatch: Not collected — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Amazon CloudWatch: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Amazon CloudWatch: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Amazon CloudWatch: Not applicable — CloudWatch observes, it does not authenticate - Synthetic checks — APIContext: Yes — 125\+ locations across five clouds, plus private nodes; Amazon CloudWatch: CloudWatch Synthetics canaries, from AWS regions - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Amazon CloudWatch: Only what your own code chooses to log - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Amazon CloudWatch: Not collected — APIContext supplies it - AWS resource metrics and logs — APIContext: Not collected — CloudWatch supplies it; Amazon CloudWatch: Yes — core strength - Alarms, dashboards, and AWS\-native automation — APIContext: Alerts with schema diff and trace; Amazon CloudWatch: Yes — alarms wired into EventBridge, SNS, Auto Scaling, Lambda - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Amazon CloudWatch: Ingests them via the AWS Distro for OpenTelemetry ### What APIContext adds to CloudWatch CloudWatch is authoritative about your account and blind to everything in front of it\. A customer in Singapore resolving DNS to the wrong region, a certificate that stopped chaining correctly at the edge, a partner receiving a response your gateway logged as a 200 but which no longer matches its schema — none of that appears in a CloudWatch metric\. APIContext measures it and sends the results in: - Everything in front of the account\. DNS, TLS, connection, and transfer timings measured from outside AWS, attributed to the hop responsible — the layers CloudWatch has no visibility into by design\. - Contract correctness, not just status codes\. Live validation against OpenAPI specs, FAPI 2\.0 security requirements, and your own business rules, so a fast 200 carrying a malformed payload is reported as the failure it is\. - The APIs outside your account\. Third\-party and partner endpoints your workloads depend on emit nothing to CloudWatch\. APIContext measures them continuously and gives you SLA evidence you own\. ### What CloudWatch does that APIContext doesn't Resource metrics for every AWS service, log ingestion and Logs Insights, alarms wired into EventBridge, SNS, Auto Scaling, and Lambda, and the AWS\-native automation built on them are CloudWatch's domain — and APIContext does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint began returning a schema\-invalid response at 14:07 UTC from three regions\. CloudWatch shows the Lambda concurrency ceiling your account hit at 14:05\. Neither signal is worth much on its own\. ### How teams run both CloudWatch stays the AWS\-native control surface — alarms, dashboards, and automation — and APIContext becomes the external source feeding it\. Teams typically alarm on APIContext conformance and CASC signals the same way they alarm on native metrics, so an API contract failure triggers the same runbook as an infrastructure threshold\. APIContext also covers the ground CloudWatch Synthetics cannot: checks from outside AWS entirely, financial\-grade authentication chains, and live spec conformance\. ### How to connect APIContext to CloudWatch APIContext's OTLP exporter ships full payloads to an AWS Distro for OpenTelemetry collector, which writes metrics and logs into CloudWatch and traces into X\-Ray\. Conformance events can also be delivered by webhook into EventBridge or SNS for alarm and automation workflows\. Nothing is installed in your stack\. Most teams start with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the data lands in the right log group and namespace, then widen coverage endpoint by endpoint\. ## Key facts - APIContext is not a Amazon CloudWatch competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Amazon CloudWatch\. - CloudWatch reports what your AWS resources emit\. APIContext adds what customers and partners outside AWS actually receive — including the DNS, TLS, and edge layers in front of your account\. - CloudWatch is the AWS\-native place metrics, logs, and alarms live: every service in your account reports into it, and your alarms and dashboards are built on it\. Every one of those signals originates inside your AWS boundary\. APIContext measures the same APIs from outside it — from 125\+ locations across AWS, GCP, Azure, and Akamai — and validates responses against their OpenAPI and FAPI 2\.0 specs\. Because APIContext emits native OpenTelemetry, those results can land in CloudWatch next to the resource metrics they explain\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Amazon CloudWatch: Inside your AWS account — what each service reports about itself - Scope — APIContext: Any API, on any cloud, including ones you do not own; Amazon CloudWatch: AWS services and anything you push via the CloudWatch APIs - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Amazon CloudWatch: Not collected — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Amazon CloudWatch: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Amazon CloudWatch: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Amazon CloudWatch: Not applicable — CloudWatch observes, it does not authenticate - Synthetic checks — APIContext: Yes — 125\+ locations across five clouds, plus private nodes; Amazon CloudWatch: CloudWatch Synthetics canaries, from AWS regions - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Amazon CloudWatch: Only what your own code chooses to log - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Amazon CloudWatch: Not collected — APIContext supplies it - AWS resource metrics and logs — APIContext: Not collected — CloudWatch supplies it; Amazon CloudWatch: Yes — core strength - Alarms, dashboards, and AWS\-native automation — APIContext: Alerts with schema diff and trace; Amazon CloudWatch: Yes — alarms wired into EventBridge, SNS, Auto Scaling, Lambda - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Amazon CloudWatch: Ingests them via the AWS Distro for OpenTelemetry ## Primary entities - APIContext - Amazon CloudWatch - APIContext \+ Amazon CloudWatch integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a CloudWatch competitor? No\. CloudWatch is the AWS\-native metrics, logs, and alarms service; APIContext is an outside\-in API monitoring platform that generates telemetry for it\. APIContext does not collect AWS resource metrics or provide log storage\. ### Does APIContext replace CloudWatch Synthetics? CloudWatch Synthetics canaries run from AWS regions and check availability and scripted flows\. APIContext runs from 125\+ locations across five clouds plus private nodes, validates responses against OpenAPI and FAPI 2\.0 specs, executes full mTLS and FAPI authentication chains, and produces CASC quality scores — then sends the results into CloudWatch\. ### How does APIContext telemetry get into CloudWatch? Over OTLP into an AWS Distro for OpenTelemetry collector for metrics and logs, with traces to X\-Ray\. Conformance events can also arrive by webhook via EventBridge or SNS\. --- # APIContext \+ Azure Monitor Canonical URL: https://apicontext.com/compare/apicontext-and-azure-monitor Source: static Description: Not an Azure Monitor alternative — a source\. Azure Monitor reports from inside your estate; APIContext adds the outside\-in view of the same APIs\. ## Summary Azure Monitor and Application Insights report from inside your Azure estate\. APIContext adds the outside\-in measurement of the same APIs, plus the ones you only consume\. Azure Monitor is where Azure\-native telemetry converges: platform metrics, resource logs, Log Analytics workspaces, and Application Insights traces from applications you have instrumented\. All of it originates inside your subscription\. APIContext measures the same APIs from outside it — from 125\+ locations across AWS, GCP, Azure, and Akamai — and validates every response against its OpenAPI and FAPI 2\.0 specification\. Because APIContext emits native OpenTelemetry, those results land in Azure Monitor next to the resource and application telemetry they explain\. ## Page sections ### Which platform produces which signal Azure Monitor is where Azure\-native telemetry converges: platform metrics, resource logs, Log Analytics workspaces, and Application Insights traces from applications you have instrumented\. All of it originates inside your subscription\. APIContext measures the same APIs from outside it — from 125\+ locations across AWS, GCP, Azure, and Akamai — and validates every response against its OpenAPI and FAPI 2\.0 specification\. Because APIContext emits native OpenTelemetry, those results land in Azure Monitor next to the resource and application telemetry they explain\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Azure Monitor: Inside your Azure subscription — platform, resource, and instrumented application telemetry - Scope — APIContext: Any API, on any cloud, including ones you do not own; Azure Monitor: Azure resources and applications you instrument - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Azure Monitor: Not collected — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Azure Monitor: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Azure Monitor: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Azure Monitor: Not applicable — Azure Monitor observes, it does not authenticate - Availability testing — APIContext: Yes — 125\+ locations across five clouds, plus private nodes; Azure Monitor: Application Insights availability tests, from Azure locations - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Azure Monitor: Only what your own code chooses to log - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Azure Monitor: Not collected — APIContext supplies it - Azure resource and platform metrics — APIContext: Not collected — Azure Monitor supplies it; Azure Monitor: Yes — core strength - Log Analytics and KQL — APIContext: Operational dashboards and reports; Azure Monitor: Yes — core strength - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Azure Monitor: Ingests them through Azure Monitor's OpenTelemetry path ### What APIContext adds to Azure Monitor Application Insights tells you what your instrumented code did\. It cannot tell you what happened before the request reached your code, or what a caller you have no instrumentation over experienced\. APIContext measures both: - Everything in front of the subscription\. DNS resolution, TLS negotiation, connection setup, and transfer measured from outside Azure and attributed per hop, including the CDN or Front Door layer between your customer and your origin\. - Contract correctness, not just success rates\. Live validation against OpenAPI specs, FAPI 2\.0 security requirements, and your own business rules, so schema drift surfaces as an event in Log Analytics rather than as a support ticket\. - The APIs outside your estate\. Partner and vendor endpoints your workloads depend on emit nothing to Azure Monitor\. APIContext measures them continuously, giving you SLA evidence you hold yourself\. ### What Azure Monitor does that APIContext doesn't Platform and resource metrics across every Azure service, resource logs and Log Analytics with KQL, Application Insights code\-level traces and profiling, and the alert rules and action groups built on them are Azure Monitor's domain — and APIContext does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint began returning a schema\-invalid response at 14:07 UTC from three regions\. Azure Monitor shows the App Service deployment slot swap at 14:05\. Neither signal is worth much on its own\. ### How teams run both Azure Monitor stays the Azure\-native control surface — workbooks, alert rules, and action groups — and APIContext becomes the external source feeding it\. Teams typically alert on APIContext conformance and CASC signals the same way they alert on platform metrics, so an API contract failure runs the same escalation as a resource threshold\. APIContext also covers what Application Insights availability tests cannot: vantage points outside Azure, financial\-grade authentication chains, and live specification conformance\. ### How to connect APIContext to Azure Monitor APIContext's OTLP exporter ships full payloads into Azure Monitor through its OpenTelemetry ingestion path, using your Application Insights connection string — directly or via a collector, depending on how your workspace is organised\. Conformance events can also be delivered by webhook into action groups or Logic Apps\. Nothing is installed in your stack\. Most teams start with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the data lands in the right workspace, then widen coverage endpoint by endpoint\. ## Key facts - APIContext is not a Azure Monitor competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Azure Monitor\. - Azure Monitor and Application Insights report from inside your Azure estate\. APIContext adds the outside\-in measurement of the same APIs, plus the ones you only consume\. - Azure Monitor is where Azure\-native telemetry converges: platform metrics, resource logs, Log Analytics workspaces, and Application Insights traces from applications you have instrumented\. All of it originates inside your subscription\. APIContext measures the same APIs from outside it — from 125\+ locations across AWS, GCP, Azure, and Akamai — and validates every response against its OpenAPI and FAPI 2\.0 specification\. Because APIContext emits native OpenTelemetry, those results land in Azure Monitor next to the resource and application telemetry they explain\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Azure Monitor: Inside your Azure subscription — platform, resource, and instrumented application telemetry - Scope — APIContext: Any API, on any cloud, including ones you do not own; Azure Monitor: Azure resources and applications you instrument - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Azure Monitor: Not collected — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Azure Monitor: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Azure Monitor: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Azure Monitor: Not applicable — Azure Monitor observes, it does not authenticate - Availability testing — APIContext: Yes — 125\+ locations across five clouds, plus private nodes; Azure Monitor: Application Insights availability tests, from Azure locations - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Azure Monitor: Only what your own code chooses to log - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Azure Monitor: Not collected — APIContext supplies it - Azure resource and platform metrics — APIContext: Not collected — Azure Monitor supplies it; Azure Monitor: Yes — core strength - Log Analytics and KQL — APIContext: Operational dashboards and reports; Azure Monitor: Yes — core strength - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Azure Monitor: Ingests them through Azure Monitor's OpenTelemetry path ## Primary entities - APIContext - Azure Monitor - APIContext \+ Azure Monitor integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext an Azure Monitor competitor? No\. Azure Monitor is the Azure\-native telemetry, log analytics, and alerting service; APIContext is an outside\-in API monitoring platform that generates telemetry for it\. APIContext does not collect Azure resource metrics or provide log analytics\. ### Does APIContext replace Application Insights availability tests? Availability tests confirm an endpoint responds from Azure locations\. APIContext runs from 125\+ locations across five clouds plus private nodes, validates responses against OpenAPI and FAPI 2\.0 specs, executes full mTLS and FAPI authentication chains, and produces CASC quality scores — then sends the results into Azure Monitor\. ### How does APIContext telemetry get into Azure Monitor? Through Azure Monitor's OpenTelemetry ingestion, using an Application Insights connection string\. Conformance events can also arrive by webhook into action groups or Logic Apps\. --- # APIContext \+ BigPanda Canonical URL: https://apicontext.com/compare/apicontext-and-bigpanda Source: static Description: Not a BigPanda alternative — a signal source\. BigPanda correlates alerts into incidents; APIContext proves the customer\-facing contract broke\. ## Summary BigPanda collapses thousands of alerts into a handful of incidents\. APIContext supplies the signal that tells it which of those incidents actually reached a customer\. BigPanda is an AIOps correlation layer: it ingests alerts from every monitoring tool in a large estate, deduplicates and clusters them, and produces a small number of actionable incidents with probable root cause\. Its quality depends entirely on the diversity of what it ingests, and almost everything it ingests is internal — infrastructure, APM, network, and log alerts, all describing the estate to itself\. BigPanda is an APIContext partner destination, and what APIContext adds is the missing axis: an outside\-in signal saying whether the customer\-facing API contract is still being honored\. ## Page sections ### Which platform produces which signal BigPanda is an AIOps correlation layer: it ingests alerts from every monitoring tool in a large estate, deduplicates and clusters them, and produces a small number of actionable incidents with probable root cause\. Its quality depends entirely on the diversity of what it ingests, and almost everything it ingests is internal — infrastructure, APM, network, and log alerts, all describing the estate to itself\. BigPanda is an APIContext partner destination, and what APIContext adds is the missing axis: an outside\-in signal saying whether the customer\-facing API contract is still being honored\. - Role — APIContext: Detection — an independent, outside\-in signal; BigPanda: Correlation — collapses many signals into few incidents - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; BigPanda: Whatever your connected tools report, normalized into one model - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; BigPanda: Not collected — APIContext supplies it - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response per hop; 30\+ data points per call; BigPanda: Not collected — APIContext supplies it - Customer impact confirmation — APIContext: Yes — measured from the client's position, in each region; BigPanda: Inferred from correlated internal alerts - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; BigPanda: Only what a connected tool reports - Alert correlation and clustering — APIContext: Multi\-region confirmation before alerting; BigPanda: Yes — core strength, across every source - Probable root cause — APIContext: Attributes latency to the responsible network hop; BigPanda: Yes — across the correlated estate - Topology and change context — APIContext: Not provided — BigPanda supplies it; BigPanda: Yes — change and topology enrichment - Incident routing and ITSM handoff — APIContext: Not provided — BigPanda supplies it; BigPanda: Yes — core strength - Works together — APIContext: Sends conformance events as an alert source; BigPanda: Ingests them via its alerts REST API ### What APIContext adds to BigPanda Correlation engines have a structural blind spot: they can only relate the alerts they are given, and in most estates every one of those alerts is generated from inside\. That produces incidents that are internally coherent and silent on the question that matters — did a customer notice? APIContext supplies the independent axis: - Customer impact as a discrete signal\. An outside\-in conformance failure, reproduced from multiple regions, is direct evidence that consumers are affected — the enrichment that separates a real incident from a noisy cluster\. - Failures nothing internal reports\. Schema drift, a dropped security header, a broken FAPI or mTLS chain, or an edge misconfiguration generate no internal alert at all, so correlation never sees them\. - Third\-party degradation\. When a partner API fails, your estate reports symptoms — retries, queue depth, timeouts — and no cause\. An APIContext alert naming the vendor endpoint gives BigPanda the anchor to cluster those symptoms around\. ### What BigPanda does that APIContext doesn't Ingesting and normalizing alerts from every tool in the estate, deduplication and clustering, topology and change enrichment, probable root cause across correlated sources, incident routing, and ITSM handoff are BigPanda's domain — and APIContext does none of them\. APIContext produces one high\-quality signal about one thing\. BigPanda's job is to place that signal among thousands of others and decide what it means\. ### How teams run both APIContext is configured as an alert source in BigPanda with tags that match your existing enrichment model — service, portfolio, region — so conformance events cluster with the infrastructure and APM alerts describing the same moment\. The pattern operations teams value most is negative as well as positive: when a large internal alert storm arrives and APIContext conformance stays green from every region, that is strong evidence the customer\-facing path is intact and the incident can be de\-prioritized\. ### How to connect APIContext to BigPanda APIContext delivers conformance events to BigPanda's alerts REST API as an integration source, using an app key\. Nothing is installed in your stack\. Most teams start with one API portfolio, confirm events arrive with the tags their correlation rules expect, then widen coverage so every customer\-facing API contributes an outside\-in signal\. ## Key facts - APIContext is not a BigPanda competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into BigPanda\. - BigPanda collapses thousands of alerts into a handful of incidents\. APIContext supplies the signal that tells it which of those incidents actually reached a customer\. - BigPanda is an AIOps correlation layer: it ingests alerts from every monitoring tool in a large estate, deduplicates and clusters them, and produces a small number of actionable incidents with probable root cause\. Its quality depends entirely on the diversity of what it ingests, and almost everything it ingests is internal — infrastructure, APM, network, and log alerts, all describing the estate to itself\. BigPanda is an APIContext partner destination, and what APIContext adds is the missing axis: an outside\-in signal saying whether the customer\-facing API contract is still being honored\. - Role — APIContext: Detection — an independent, outside\-in signal; BigPanda: Correlation — collapses many signals into few incidents - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; BigPanda: Whatever your connected tools report, normalized into one model - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; BigPanda: Not collected — APIContext supplies it - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response per hop; 30\+ data points per call; BigPanda: Not collected — APIContext supplies it - Customer impact confirmation — APIContext: Yes — measured from the client's position, in each region; BigPanda: Inferred from correlated internal alerts - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; BigPanda: Only what a connected tool reports - Alert correlation and clustering — APIContext: Multi\-region confirmation before alerting; BigPanda: Yes — core strength, across every source - Probable root cause — APIContext: Attributes latency to the responsible network hop; BigPanda: Yes — across the correlated estate - Topology and change context — APIContext: Not provided — BigPanda supplies it; BigPanda: Yes — change and topology enrichment - Incident routing and ITSM handoff — APIContext: Not provided — BigPanda supplies it; BigPanda: Yes — core strength - Works together — APIContext: Sends conformance events as an alert source; BigPanda: Ingests them via its alerts REST API ## Primary entities - APIContext - BigPanda - APIContext \+ BigPanda integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a BigPanda competitor? No\. BigPanda is an AIOps event correlation platform; APIContext is an outside\-in API monitoring platform that supplies signal to it\. APIContext does not ingest third\-party alerts, correlate across an estate, or route incidents\. ### Won't this add more alerts to correlate? It adds a small number of high\-confidence ones\. APIContext confirms failures across multiple regions before alerting, and the signal is independent of your internal tooling — which is what makes it useful for confirming or ruling out customer impact rather than adding to the noise\. ### How does APIContext connect to BigPanda? Through BigPanda's alerts REST API using an app key, configured as an integration source with tags matching your enrichment model\. --- # APIContext \+ Catchpoint Canonical URL: https://apicontext.com/compare/apicontext-and-catchpoint Source: static Description: Not a Catchpoint replacement\. Catchpoint measures Internet delivery; APIContext measures whether your API delivers the contract it promised\. ## Summary Catchpoint measures whether the Internet is delivering your service; APIContext measures whether your API is delivering the contract it promised\. Catchpoint is an Internet Performance Monitoring platform: a very large global vantage network spanning backbone, last\-mile, wireless, and endpoint locations, with BGP, DNS, and traceroute visibility into the Internet between your service and the people using it\. APIContext monitors the API layer riding on top of that Internet — live conformance against OpenAPI and FAPI 2\.0 specs, complete financial\-grade authentication chains, payload\-level validation, and CASC quality scoring\. The two answer different questions about the same request, and both emit OpenTelemetry, so the answers can sit side by side in one backend\. ## Page sections ### Which platform produces which signal Catchpoint is an Internet Performance Monitoring platform: a very large global vantage network spanning backbone, last\-mile, wireless, and endpoint locations, with BGP, DNS, and traceroute visibility into the Internet between your service and the people using it\. APIContext monitors the API layer riding on top of that Internet — live conformance against OpenAPI and FAPI 2\.0 specs, complete financial\-grade authentication chains, payload\-level validation, and CASC quality scoring\. The two answer different questions about the same request, and both emit OpenTelemetry, so the answers can sit side by side in one backend\. - Primary layer — APIContext: The API contract — conformance, authentication, payload correctness; Catchpoint: The Internet — reachability, routing, and delivery performance - Vantage network — APIContext: 125\+ cloud nodes across AWS, GCP, Azure, and Akamai, plus private nodes in your own network; Catchpoint: Very large Internet\-scale network including backbone, last\-mile, wireless, and employee endpoints - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Catchpoint: Response assertions — APIContext supplies full conformance - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — full chains including PAR, PKCE, DPoP\-bound tokens, and JARM; Catchpoint: Standard auth in scripted tests — APIContext supplies financial\-grade chains - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Catchpoint: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Catchpoint: Not collected — APIContext supplies it - Open banking / FAPI compliance evidence — APIContext: Yes — native support for UK, EU, AU, and US frameworks; Catchpoint: Not collected — APIContext supplies it - BGP and route monitoring — APIContext: Not collected — Catchpoint supplies it; Catchpoint: Yes — core strength - Last\-mile, wireless, and ISP vantage — APIContext: Not collected — Catchpoint supplies it; Catchpoint: Yes — core strength - Employee endpoint experience — APIContext: Not collected — Catchpoint supplies it; Catchpoint: Yes — endpoint agents on user devices - Per\-hop network telemetry on API calls — APIContext: Yes — DNS, connection, TLS, transfer, and response; 30\+ data points per call; Catchpoint: Yes — traceroute and network\-layer diagnostics at Internet scale - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Catchpoint: Telemetry exports into the same observability backend ### What APIContext adds to Catchpoint Catchpoint tells you the request arrived, from where, how fast, and over which route\. APIContext tells you whether what came back was correct\. That distinction matters most on exactly the APIs where a 200 response proves nothing: - Contract conformance, not just availability\. Every response is validated live against its OpenAPI spec, its FAPI 2\.0 security requirements, and your own business rules — so a fast, reachable, schema\-invalid response is reported as the failure it is\. - Financial\-grade authentication chains\. Complete mTLS handshakes with client certificates and full FAPI 2\.0 flows including PAR, DPoP\-bound tokens, and JARM validation, executed end to end rather than stubbed\. - Agentic AI and MCP monitoring\. Continuous outside\-in testing of MCP servers, tool schema validation, session lifecycle verification, and per\-tool latency\. - Regulator\-ready evidence\. CASC quality scoring, conformance history, and per\-endpoint SLA reporting in the form compliance and governance teams have to file\. ### What Catchpoint does that APIContext doesn't Internet\-scale vantage breadth is Catchpoint's domain and APIContext does not attempt it: last\-mile ISP measurement, wireless and mobile carrier vantage, employee endpoint agents, BGP route monitoring, and Internet\-wide outage detection\. APIContext runs from 125\+ cloud nodes and private nodes, which is the right vantage for API and partner traffic, but it is not an Internet measurement network\. The division is easiest to see during an incident: Catchpoint shows a transit route change degrading delivery at 14:02\. APIContext shows the payments endpoint returning a schema\-invalid response at 14:07\. Those are two different failures, and each platform only sees one of them\. ### How teams run both Catchpoint watches the Internet between your service and your users; APIContext watches the contract at the end of that path, and produces the compliance evidence regulated teams need\. Both emit OpenTelemetry, so both land in the same observability backend — Datadog, Dynatrace, New Relic, Splunk, Grafana, or your own collector — and an on\-call engineer can tell a delivery problem apart from a contract problem in one view instead of two\. ### How to connect APIContext to Catchpoint There is no coupling to configure\. Each platform exports telemetry to a shared destination, and APIContext's OTLP exporter ships full payloads to whichever backend you already run\. Most teams correlate on endpoint and timestamp: Catchpoint supplies the delivery and routing context, APIContext supplies the conformance verdict and per\-hop timings for the same call\. ## Key facts - APIContext is not a Catchpoint competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Catchpoint\. - Catchpoint measures whether the Internet is delivering your service; APIContext measures whether your API is delivering the contract it promised\. - Catchpoint is an Internet Performance Monitoring platform: a very large global vantage network spanning backbone, last\-mile, wireless, and endpoint locations, with BGP, DNS, and traceroute visibility into the Internet between your service and the people using it\. APIContext monitors the API layer riding on top of that Internet — live conformance against OpenAPI and FAPI 2\.0 specs, complete financial\-grade authentication chains, payload\-level validation, and CASC quality scoring\. The two answer different questions about the same request, and both emit OpenTelemetry, so the answers can sit side by side in one backend\. - Primary layer — APIContext: The API contract — conformance, authentication, payload correctness; Catchpoint: The Internet — reachability, routing, and delivery performance - Vantage network — APIContext: 125\+ cloud nodes across AWS, GCP, Azure, and Akamai, plus private nodes in your own network; Catchpoint: Very large Internet\-scale network including backbone, last\-mile, wireless, and employee endpoints - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Catchpoint: Response assertions — APIContext supplies full conformance - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — full chains including PAR, PKCE, DPoP\-bound tokens, and JARM; Catchpoint: Standard auth in scripted tests — APIContext supplies financial\-grade chains - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Catchpoint: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Catchpoint: Not collected — APIContext supplies it - Open banking / FAPI compliance evidence — APIContext: Yes — native support for UK, EU, AU, and US frameworks; Catchpoint: Not collected — APIContext supplies it - BGP and route monitoring — APIContext: Not collected — Catchpoint supplies it; Catchpoint: Yes — core strength - Last\-mile, wireless, and ISP vantage — APIContext: Not collected — Catchpoint supplies it; Catchpoint: Yes — core strength - Employee endpoint experience — APIContext: Not collected — Catchpoint supplies it; Catchpoint: Yes — endpoint agents on user devices - Per\-hop network telemetry on API calls — APIContext: Yes — DNS, connection, TLS, transfer, and response; 30\+ data points per call; Catchpoint: Yes — traceroute and network\-layer diagnostics at Internet scale - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Catchpoint: Telemetry exports into the same observability backend ## Primary entities - APIContext - Catchpoint - APIContext \+ Catchpoint integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Are APIContext and Catchpoint competitors? No\. They monitor different layers\. Catchpoint measures Internet reachability, routing, and delivery from an Internet\-scale vantage network\. APIContext validates the API contract — conformance against OpenAPI and FAPI 2\.0 specs, financial\-grade authentication chains, payload correctness, and CASC quality scoring\. ### Can I run both without duplicating checks? Yes, and most teams do\. Catchpoint covers vantage breadth and network\-layer diagnostics; APIContext covers contract depth, authentication chains, and compliance evidence on the endpoints where correctness matters\. ### What can APIContext see that Catchpoint cannot? Whether a response actually conforms to its specification, whether a full FAPI 2\.0 or mTLS authentication chain completes correctly, whether an MCP server's tool schemas still match, and whether an endpoint meets the CASC quality and SLA thresholds you have committed to\. --- # APIContext \+ Datadog Canonical URL: https://apicontext.com/compare/apicontext-and-datadog Source: static Description: APIContext is not a Datadog competitor or replacement\. Its native integration streams outside\-in API conformance and per\-hop network telemetry into Datadog\. ## Summary A native Datadog integration adds outside\-in network and API\-conformance telemetry to the Datadog dashboards your team already runs\. Datadog is a full\-stack observability platform — APM, infrastructure, logs, and synthetics across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. The two are joined by a native Datadog integration, listed in the Datadog catalog, that ships two purpose\-built dashboards: one for governance teams tracking API conformance across a portfolio, and one for SRE teams handling API conformance events in Datadog's incident workflow\. APIContext does what Datadog cannot, and Datadog does what APIContext does not\. ## Page sections ### Which platform produces which signal Datadog is a full\-stack observability platform — APM, infrastructure, logs, and synthetics across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. The two are joined by a native Datadog integration, listed in the Datadog catalog, that ships two purpose\-built dashboards: one for governance teams tracking API conformance across a portfolio, and one for SRE teams handling API conformance events in Datadog's incident workflow\. APIContext does what Datadog cannot, and Datadog does what APIContext does not\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Datadog: Inside your infrastructure — what your code, hosts, and services are doing - Deployment — APIContext: None — fully external, 125\+ global nodes across AWS, GCP, Azure, and Akamai; Datadog: Datadog agents and SDKs in your stack, plus managed synthetics - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop from cloud node to origin; 30\+ data points per call; Datadog: Not collected outside\-in — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Datadog: Basic response assertions in synthetic monitors — APIContext supplies full conformance - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Datadog: Not collected — APIContext supplies it - OTEL signal per hop — APIContext: Yes — generated at every network layer from cloud node to origin; Datadog: Ingests OTLP and APIContext conformance events natively — APIContext is a source - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing and tool schema validation; Datadog: Not collected — APIContext supplies it - Multi\-step auth workflows — APIContext: Yes — FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Datadog: Scripted synthetics — APIContext adds financial\-grade auth chains - Open banking / FAPI compliance — APIContext: Yes — native support for UK, EU, AU, and US frameworks; Datadog: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Datadog: Limited to code paths you instrument - Log correlation — APIContext: Not collected — Datadog supplies it; Datadog: Yes — core strength - Infrastructure monitoring — APIContext: Not collected — Datadog supplies it; Datadog: Yes — core strength - Incident management — APIContext: Alerts with schema diff and trace; Datadog: Full incident management platform ### What APIContext adds to Datadog Datadog agents report from inside your processes and hosts\. That is their strength, and it is also where their horizon ends: an agent cannot measure the DNS resolution a customer's client performed, the TLS handshake negotiated at the edge, the CDN hop between customer and origin, or the latency a partner in São Paulo sees against an endpoint served from Frankfurt\. APIContext takes those measurements — 30\+ data points on every API call, broken out per hop, from 125\+ public locations plus private nodes inside your own network — and sends them into Datadog as native OTEL\. Three blind spots close at once: - Network telemetry Datadog agents do not generate\. Per\-hop DNS, TLS, connection, and transfer timings, attributed to the hop that caused the slowdown — so "the API is slow" becomes "TLS negotiation at the Sydney edge added 380 ms\." - API conformance evidence\. Live validation of responses against OpenAPI specs, FAPI 2\.0 security requirements, and custom business rules, so schema drift arrives in Datadog as an event rather than as a customer ticket\. - Coverage where no user has been yet\. Synthetic checks fire every interval from every region, including endpoints no real user touched today and third\-party APIs you depend on but cannot instrument\. ### What Datadog does that APIContext doesn't Log management and correlation, infrastructure and host monitoring, real user monitoring, code\-level transaction traces, database diagnostics, and full incident management are Datadog's domain — and APIContext deliberately does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint's response schema drifted at 14:07 UTC from three regions\. Datadog tells you the deploy that shipped at 14:05 is why\. Neither signal is worth much on its own\. ### How the integration works APIContext monitors your APIs for conformance with OpenAPI specifications and open standards including OAuth, OpenID Connect, FAPI, and FDX\. When a nonconformance is detected — a schema mismatch, an authentication failure, an unexpected response — APIContext sends a real\-time alert into Datadog as an event\. Install the APIContext integration from the Datadog Integrations page and click Connect Accounts to authorize; then in APIContext, open Alerts & Webhooks, create an alert, and select "Datadog \(Conformance Events\)" as its destination\. Failures are sent by default, and a toggle adds passing checks when you want the full record\. Two example dashboards are published with the integration: - A Governance dashboard — a portfolio\-level Conformance Summary across all monitored endpoints, for teams that report on API contract quality across a product suite\. - An SRE dashboard — API Conformance Events surfaced in Datadog's incident workflow, so on\-call engineers see contract violations alongside infrastructure alerts, logs, and traces from the same incident\. - [APIContext integration in the Datadog docs](https://docs.datadoghq.com/integrations/apicontext/) ### How teams run both Datadog stays the correlation and incident layer; APIContext becomes the outside\-in data source feeding it\. Teams running both use APIContext as the source of truth for external API quality — conformance, CASC scores, FAPI compliance, geographic availability — and Datadog to correlate that signal with a deployment, an error\-log spike, or a CDN configuration change happening at the same moment\. Datadog answers "why is something slow inside my stack?" APIContext answers "what does my API actually look like to the customer, the partner, and the regulator?" ## Key facts - APIContext is not a Datadog competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Datadog\. - A native Datadog integration adds outside\-in network and API\-conformance telemetry to the Datadog dashboards your team already runs\. - Datadog is a full\-stack observability platform — APM, infrastructure, logs, and synthetics across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. The two are joined by a native Datadog integration, listed in the Datadog catalog, that ships two purpose\-built dashboards: one for governance teams tracking API conformance across a portfolio, and one for SRE teams handling API conformance events in Datadog's incident workflow\. APIContext does what Datadog cannot, and Datadog does what APIContext does not\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Datadog: Inside your infrastructure — what your code, hosts, and services are doing - Deployment — APIContext: None — fully external, 125\+ global nodes across AWS, GCP, Azure, and Akamai; Datadog: Datadog agents and SDKs in your stack, plus managed synthetics - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop from cloud node to origin; 30\+ data points per call; Datadog: Not collected outside\-in — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Datadog: Basic response assertions in synthetic monitors — APIContext supplies full conformance - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Datadog: Not collected — APIContext supplies it - OTEL signal per hop — APIContext: Yes — generated at every network layer from cloud node to origin; Datadog: Ingests OTLP and APIContext conformance events natively — APIContext is a source - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing and tool schema validation; Datadog: Not collected — APIContext supplies it - Multi\-step auth workflows — APIContext: Yes — FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Datadog: Scripted synthetics — APIContext adds financial\-grade auth chains - Open banking / FAPI compliance — APIContext: Yes — native support for UK, EU, AU, and US frameworks; Datadog: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Datadog: Limited to code paths you instrument - Log correlation — APIContext: Not collected — Datadog supplies it; Datadog: Yes — core strength - Infrastructure monitoring — APIContext: Not collected — Datadog supplies it; Datadog: Yes — core strength - Incident management — APIContext: Alerts with schema diff and trace; Datadog: Full incident management platform ## Primary entities - APIContext - Datadog - APIContext \+ Datadog integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Datadog competitor? No\. APIContext is a native Datadog integration listed in the Datadog catalog\. It supplies outside\-in API conformance and per\-hop network telemetry to Datadog, and it does not provide infrastructure monitoring, log management, or incident response\. ### Does APIContext replace Datadog Synthetics? No\. Datadog Synthetics checks availability and basic assertions\. APIContext adds live OpenAPI and FAPI 2\.0 conformance validation, per\-hop network telemetry, financial\-grade authentication chains, and CASC quality scoring — then sends the results into Datadog\. ### How do I install the integration? Through the APIContext tile in the Datadog integrations catalog\. One authorization step provisions the Governance and SRE dashboards\. --- # APIContext \+ Dynatrace Canonical URL: https://apicontext.com/compare/apicontext-and-dynatrace Source: static Description: APIContext is not a Dynatrace competitor or replacement\. Its certified integration streams outside\-in API conformance and network telemetry into Dynatrace over OTLP\. ## Summary A certified Dynatrace integration and telemetry source: the outside\-in network and API\-conformance data OneAgent cannot collect, delivered into Dynatrace over OTLP\. Dynatrace is a full\-stack observability platform — OneAgent\-based APM, infrastructure, logs, RUM, and Davis AI root\-cause analysis across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. Because every APIContext check emits native OpenTelemetry, its results can land directly in Dynatrace as traces, metrics, and logs\. Dynatrace customers add APIContext to close the gaps OneAgent structurally cannot reach — network\-path telemetry, API contract conformance, and third\-party API behavior — and they see it all inside Dynatrace\. ## Page sections ### Which platform produces which signal Dynatrace is a full\-stack observability platform — OneAgent\-based APM, infrastructure, logs, RUM, and Davis AI root\-cause analysis across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. Because every APIContext check emits native OpenTelemetry, its results can land directly in Dynatrace as traces, metrics, and logs\. Dynatrace customers add APIContext to close the gaps OneAgent structurally cannot reach — network\-path telemetry, API contract conformance, and third\-party API behavior — and they see it all inside Dynatrace\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Dynatrace: Inside your infrastructure — what your code, hosts, and services are doing - Deployment — APIContext: None — fully external, nothing to install; Dynatrace: OneAgent on hosts and containers, plus ActiveGate - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Dynatrace: Not collected — OneAgent reports from inside the host\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Dynatrace: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Dynatrace: Not collected — APIContext supplies it - OTEL signal per hop — APIContext: Yes — generated at every network layer from cloud node to origin; Dynatrace: Ingests OTLP over gRPC and HTTP — APIContext is a source - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Dynatrace: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Dynatrace: Scripted HTTP monitors — APIContext adds financial\-grade auth chains - Open banking / FAPI 2\.0 — APIContext: Yes — native support for UK, EU, AU, and US frameworks; Dynatrace: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Dynatrace: Limited to code paths you instrument - AI root\-cause analysis — APIContext: Not provided — Dynatrace supplies it; Dynatrace: Yes — Davis AI across the instrumented estate - Log management and correlation — APIContext: Not collected — Dynatrace supplies it; Dynatrace: Yes — core strength - Infrastructure monitoring — APIContext: Not collected — Dynatrace supplies it; Dynatrace: Yes — core strength - Works together — APIContext: Exports traces, metrics, and logs to Dynatrace over OTLP; Dynatrace: Ingests APIContext telemetry as native OTEL ### What APIContext adds to Dynatrace OneAgent sees your estate from the inside, in extraordinary detail\. What it cannot see is the path between your customer and your origin: the DNS resolution a client performed, the TLS handshake negotiated at the edge, the CDN hop in between, and how all of it differs by region\. APIContext measures that path on every check — 30\+ data points per API call, broken out per hop, from 125\+ public locations plus private nodes inside your own network — and ships it into Dynatrace as native OTEL\. Three blind spots close at once: - Network telemetry OneAgent does not generate\. Per\-hop DNS, TLS, connection, and transfer timings, attributed to the hop that caused the slowdown rather than inferred from inside the host\. - API conformance evidence\. Live validation of responses against OpenAPI specs, FAPI 2\.0 security requirements, and custom business rules, so contract drift becomes a Dynatrace event with a diff attached\. - An external dimension for Davis\. Davis AI is only as complete as the signal it correlates\. Feeding it outside\-in measurements on endpoints no user touched today — and on third\-party APIs you cannot instrument — extends root\-cause analysis past the boundary of your own estate\. ### What Dynatrace does that APIContext doesn't Davis AI root\-cause analysis, log management and correlation, infrastructure and host monitoring, real user monitoring, code\-level transaction traces, and full incident workflows are Dynatrace's domain — and APIContext deliberately does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint's response schema drifted at 14:07 UTC from three regions\. Dynatrace tells you the deploy that shipped at 14:05 is why\. Neither signal is worth much on its own\. ### How teams run both Dynatrace stays the correlation, root\-cause, and incident layer; APIContext becomes the outside\-in data source feeding it\. Dynatrace answers "what in my estate caused this?" APIContext answers "what does my API actually look like to the customer, the partner, and the regulator?" Teams operating regulated APIs, open banking infrastructure, agentic AI services, or customer\-facing API products need both answers, and the second one cannot be produced from inside the stack at all\. ### How the integration works APIContext is listed as a certified integration in the Dynatrace Hub\. It monitors your APIs for conformance with OpenAPI specifications and open standards including OAuth, OpenID Connect, FAPI, and FDX, and when a nonconformance is detected — a schema mismatch, an authentication issue, an unexpected response — it sends a real\-time notification into Dynatrace\. The integration uses OpenTelemetry for transport: create a Dynatrace access token with the Ingest logs, Ingest metrics, and Ingest OpenTelemetry traces scopes, then point APIContext at your environment's OTLP endpoint\. Nothing is installed in your stack and nothing changes about your existing OneAgent deployment\. The result is centralized visibility into API health, early detection of API drift and misconfiguration, and noncompliance alerts routed to the right responders through the Dynatrace workflows you already run\. - [APIContext in the Dynatrace Hub](https://www.dynatrace.com/hub/detail/apicontext/) ### How teams get started Most teams begin with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the notifications and spans arrive in Dynatrace, then widen coverage endpoint by endpoint until every customer\-facing API contributes an outside\-in signal\. ## Key facts - APIContext is not a Dynatrace competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Dynatrace\. - A certified Dynatrace integration and telemetry source: the outside\-in network and API\-conformance data OneAgent cannot collect, delivered into Dynatrace over OTLP\. - Dynatrace is a full\-stack observability platform — OneAgent\-based APM, infrastructure, logs, RUM, and Davis AI root\-cause analysis across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. Because every APIContext check emits native OpenTelemetry, its results can land directly in Dynatrace as traces, metrics, and logs\. Dynatrace customers add APIContext to close the gaps OneAgent structurally cannot reach — network\-path telemetry, API contract conformance, and third\-party API behavior — and they see it all inside Dynatrace\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Dynatrace: Inside your infrastructure — what your code, hosts, and services are doing - Deployment — APIContext: None — fully external, nothing to install; Dynatrace: OneAgent on hosts and containers, plus ActiveGate - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Dynatrace: Not collected — OneAgent reports from inside the host\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Dynatrace: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Dynatrace: Not collected — APIContext supplies it - OTEL signal per hop — APIContext: Yes — generated at every network layer from cloud node to origin; Dynatrace: Ingests OTLP over gRPC and HTTP — APIContext is a source - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Dynatrace: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Dynatrace: Scripted HTTP monitors — APIContext adds financial\-grade auth chains - Open banking / FAPI 2\.0 — APIContext: Yes — native support for UK, EU, AU, and US frameworks; Dynatrace: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Dynatrace: Limited to code paths you instrument - AI root\-cause analysis — APIContext: Not provided — Dynatrace supplies it; Dynatrace: Yes — Davis AI across the instrumented estate - Log management and correlation — APIContext: Not collected — Dynatrace supplies it; Dynatrace: Yes — core strength - Infrastructure monitoring — APIContext: Not collected — Dynatrace supplies it; Dynatrace: Yes — core strength - Works together — APIContext: Exports traces, metrics, and logs to Dynatrace over OTLP; Dynatrace: Ingests APIContext telemetry as native OTEL ## Primary entities - APIContext - Dynatrace - APIContext \+ Dynatrace integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Dynatrace competitor? No\. APIContext is a certified Dynatrace integration and an outside\-in telemetry source\. It does not provide APM, infrastructure monitoring, log management, AI root\-cause analysis, or incident response, and it is not sold as a Dynatrace replacement\. ### Does APIContext replace Dynatrace Synthetic Monitoring? No\. Dynatrace synthetic monitors check availability and basic assertions from Dynatrace locations\. APIContext adds live OpenAPI and FAPI 2\.0 conformance validation, per\-hop network telemetry, financial\-grade authentication chains, and CASC quality scoring — then sends the results into Dynatrace\. ### How does APIContext telemetry get into Dynatrace? Over OpenTelemetry to your environment's OTLP endpoint, using a Dynatrace access token scoped for Ingest logs, Ingest metrics, and Ingest OpenTelemetry traces\. APIContext is a certified integration in the Dynatrace Hub, so no custom pipeline is required\. --- # APIContext \+ Google Cloud Operations Canonical URL: https://apicontext.com/compare/apicontext-and-google-cloud-operations Source: static Description: Not a Cloud Monitoring alternative — a source\. Google Cloud Operations reports from inside your projects; APIContext adds the outside\-in view\. ## Summary Cloud Monitoring, Cloud Logging, and Cloud Trace report from inside your Google Cloud projects\. APIContext adds the outside\-in measurement of the same APIs, plus the ones you only consume\. Google Cloud Operations — Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting — is where telemetry from your Google Cloud projects converges\. All of it originates inside those projects\. APIContext measures the same APIs from outside them, from 125\+ locations across AWS, GCP, Azure, and Akamai, and validates every response against its OpenAPI and FAPI 2\.0 specification\. Because APIContext emits native OpenTelemetry, those results land in Cloud Monitoring and Cloud Trace next to the service telemetry they explain\. ## Page sections ### Which platform produces which signal Google Cloud Operations — Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting — is where telemetry from your Google Cloud projects converges\. All of it originates inside those projects\. APIContext measures the same APIs from outside them, from 125\+ locations across AWS, GCP, Azure, and Akamai, and validates every response against its OpenAPI and FAPI 2\.0 specification\. Because APIContext emits native OpenTelemetry, those results land in Cloud Monitoring and Cloud Trace next to the service telemetry they explain\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Google Cloud Operations: Inside your Google Cloud projects — service, resource, and instrumented application telemetry - Scope — APIContext: Any API, on any cloud, including ones you do not own; Google Cloud Operations: Google Cloud services and applications you instrument - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Google Cloud Operations: Not collected — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Google Cloud Operations: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Google Cloud Operations: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Google Cloud Operations: Not applicable — Cloud Operations observes, it does not authenticate - Uptime checks — APIContext: Yes — 125\+ locations across five clouds, plus private nodes; Google Cloud Operations: Cloud Monitoring uptime checks, from Google locations - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Google Cloud Operations: Only what your own code chooses to log - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Google Cloud Operations: Not collected — APIContext supplies it - Google Cloud service metrics and logs — APIContext: Not collected — Cloud Operations supplies it; Google Cloud Operations: Yes — core strength - SLO monitoring and error budgets — APIContext: Native, per\-endpoint SLA and SLO reporting; Google Cloud Operations: Yes — service\-level objectives against ingested metrics - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Google Cloud Operations: Ingests them via the OpenTelemetry Collector's Google Cloud exporter ### What APIContext adds to Google Cloud Operations Cloud Monitoring is authoritative about your projects and silent about everything in front of them\. APIContext supplies the missing half: - Everything in front of the project\. DNS resolution, TLS negotiation, connection setup, and transfer measured from outside Google Cloud and attributed per hop — including the load balancer and CDN layer between your customer and your service\. - Contract correctness, not just service health\. Live validation against OpenAPI specs, FAPI 2\.0 security requirements, and your own business rules, so schema drift becomes a log entry you can alert on rather than a support ticket\. - The APIs outside your projects\. Partner and vendor endpoints your services depend on emit nothing to Cloud Logging\. APIContext measures them continuously and gives you SLA evidence you own\. ### What Google Cloud Operations does that APIContext doesn't Service and resource metrics across Google Cloud, Cloud Logging with log\-based metrics, Cloud Trace and Profiler, Error Reporting, and the alerting policies and SLO tooling built on them are Cloud Operations' domain — and APIContext does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint began returning a schema\-invalid response at 14:07 UTC from three regions\. Cloud Operations shows the Cloud Run revision that rolled out at 14:05\. Neither signal is worth much on its own\. ### How teams run both Cloud Operations stays the Google\-native control surface — dashboards, alerting policies, and SLOs — and APIContext becomes the external source feeding it\. Teams commonly build SLOs on APIContext conformance and CASC signals precisely because those signals reflect what customers received rather than what the service reported about itself\. APIContext also covers what uptime checks cannot: vantage points outside Google Cloud, financial\-grade authentication chains, and live specification conformance\. ### How to connect APIContext to Google Cloud Operations APIContext's OTLP exporter ships full payloads to an OpenTelemetry Collector running the Google Cloud exporter, which writes metrics into Cloud Monitoring, logs into Cloud Logging, and spans into Cloud Trace\. Conformance events can also be delivered by webhook into Pub/Sub for downstream automation\. Nothing is installed in your stack\. Most teams start with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the data lands in the right project, then widen coverage endpoint by endpoint\. ## Key facts - APIContext is not a Google Cloud Operations competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Google Cloud Operations\. - Cloud Monitoring, Cloud Logging, and Cloud Trace report from inside your Google Cloud projects\. APIContext adds the outside\-in measurement of the same APIs, plus the ones you only consume\. - Google Cloud Operations — Cloud Monitoring, Cloud Logging, Cloud Trace, and Error Reporting — is where telemetry from your Google Cloud projects converges\. All of it originates inside those projects\. APIContext measures the same APIs from outside them, from 125\+ locations across AWS, GCP, Azure, and Akamai, and validates every response against its OpenAPI and FAPI 2\.0 specification\. Because APIContext emits native OpenTelemetry, those results land in Cloud Monitoring and Cloud Trace next to the service telemetry they explain\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Google Cloud Operations: Inside your Google Cloud projects — service, resource, and instrumented application telemetry - Scope — APIContext: Any API, on any cloud, including ones you do not own; Google Cloud Operations: Google Cloud services and applications you instrument - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Google Cloud Operations: Not collected — APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Google Cloud Operations: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Google Cloud Operations: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Google Cloud Operations: Not applicable — Cloud Operations observes, it does not authenticate - Uptime checks — APIContext: Yes — 125\+ locations across five clouds, plus private nodes; Google Cloud Operations: Cloud Monitoring uptime checks, from Google locations - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Google Cloud Operations: Only what your own code chooses to log - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Google Cloud Operations: Not collected — APIContext supplies it - Google Cloud service metrics and logs — APIContext: Not collected — Cloud Operations supplies it; Google Cloud Operations: Yes — core strength - SLO monitoring and error budgets — APIContext: Native, per\-endpoint SLA and SLO reporting; Google Cloud Operations: Yes — service\-level objectives against ingested metrics - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; Google Cloud Operations: Ingests them via the OpenTelemetry Collector's Google Cloud exporter ## Primary entities - APIContext - Google Cloud Operations - APIContext \+ Google Cloud Operations integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Google Cloud Operations competitor? No\. Cloud Operations is Google Cloud's native metrics, logging, and tracing suite; APIContext is an outside\-in API monitoring platform that generates telemetry for it\. APIContext does not collect Google Cloud service metrics or provide log storage\. ### Does APIContext replace Cloud Monitoring uptime checks? Uptime checks confirm an endpoint responds from Google locations\. APIContext runs from 125\+ locations across five clouds plus private nodes, validates responses against OpenAPI and FAPI 2\.0 specs, executes full mTLS and FAPI authentication chains, and produces CASC quality scores — then sends the results into Cloud Monitoring\. ### How does APIContext telemetry get into Google Cloud Operations? Over OTLP to an OpenTelemetry Collector configured with the Google Cloud exporter, which routes metrics, logs, and traces to Cloud Monitoring, Cloud Logging, and Cloud Trace\. Conformance events can also arrive by webhook via Pub/Sub\. --- # APIContext \+ Hydrolix Canonical URL: https://apicontext.com/compare/apicontext-and-hydrolix Source: static Description: Not a Hydrolix alternative — a source\. APIContext generates high\-cardinality outside\-in API telemetry; Hydrolix keeps it queryable at petabyte scale\. ## Summary APIContext generates high\-cardinality API telemetry; Hydrolix stores and queries it at petabyte scale, for years, at a cost that makes long retention practical\. Hydrolix is a streaming data lake built for high\-cardinality, high\-volume telemetry: it keeps log and event data queryable for months or years at a cost profile conventional log platforms cannot match, and it is the engine behind Akamai TrafficPeak\. APIContext produces exactly that shape of data — 30\+ data points on every API call, broken out per hop, from 125\+ global locations, continuously, whether or not a real user is calling\. Sending APIContext telemetry to Hydrolix turns short\-lived monitoring results into a durable, queryable record of how every API has actually behaved\. ## Page sections ### Which platform produces which signal Hydrolix is a streaming data lake built for high\-cardinality, high\-volume telemetry: it keeps log and event data queryable for months or years at a cost profile conventional log platforms cannot match, and it is the engine behind Akamai TrafficPeak\. APIContext produces exactly that shape of data — 30\+ data points on every API call, broken out per hop, from 125\+ global locations, continuously, whether or not a real user is calling\. Sending APIContext telemetry to Hydrolix turns short\-lived monitoring results into a durable, queryable record of how every API has actually behaved\. - Role in the pipeline — APIContext: Source — generates outside\-in API and network telemetry; Hydrolix: Store and query engine — keeps that telemetry cheap, dense, and queryable - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Hydrolix: Vantage\-agnostic — stores whatever is streamed in - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Hydrolix: Stores and indexes it once APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Hydrolix: Not generated — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Hydrolix: Not generated — APIContext supplies it - Full request and response payloads — APIContext: Yes — captured on every check; Hydrolix: Stores them at high compression without re\-hydration - High\-cardinality query at scale — APIContext: Operational dashboards and reports; Hydrolix: Yes — core strength, across petabytes - Multi\-year retention economics — APIContext: Operational retention windows; Hydrolix: Yes — core strength - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Hydrolix: Stores the resulting history for as long as you need it - Continuous coverage regardless of traffic — APIContext: Yes — synthetic checks produce a complete series with no gaps; Hydrolix: Benefits from it — a dense, uniform dataset compresses and queries well - Works together — APIContext: Streams telemetry, events, and payloads to Hydrolix; Hydrolix: Ingests it via streaming HTTP ingest or an OpenTelemetry collector, including through Akamai TrafficPeak ### What APIContext adds to Hydrolix Hydrolix solves the economics of keeping telemetry; it does not generate any\. APIContext is built to generate the densest possible record of external API behavior, which is precisely the workload Hydrolix is designed for: - High\-cardinality outside\-in telemetry\. Per\-hop DNS, TLS, connection, and transfer timings, tagged by endpoint, region, cloud provider, and node — the cardinality that makes conventional log platforms expensive and Hydrolix efficient\. - Conformance verdicts with full payloads\. Every check validates the response against the spec and keeps the request and response, so the record is evidence rather than a summary metric\. - Continuous, gap\-free volume\. Synthetic checks do not depend on user traffic, so the series is uniform across every endpoint and region — including endpoints nobody called today and third\-party APIs you do not run\. ### What Hydrolix does that APIContext doesn't Compression, indexing, and sub\-second query across petabytes without re\-hydration, and the retention economics that make years of history affordable, are Hydrolix's domain — and APIContext does none of them\. The division is a question of time horizon\. APIContext answers "what is happening to this API right now, and does it still match its contract?" Hydrolix answers "what happened to every API, in every region, across the last three years?" That second question is the one that arrives as a regulator request, a partner SLA dispute, or a capacity argument, long after an operational retention window has closed\. ### How teams run both APIContext runs the checks and raises the alerts; Hydrolix becomes the long\-horizon archive that the same data flows into\. Teams in regulated industries use this pairing to hold years of dated conformance evidence at a cost that does not force a retention compromise\. Akamai customers often arrive at it from the other direction: TrafficPeak is built on Hydrolix and is already an APIContext destination, so the API telemetry lands in the same lake as their edge and delivery data\. ### How to connect APIContext to Hydrolix APIContext streams telemetry, conformance events, and full payloads into Hydrolix over its streaming HTTP ingest, or via an OpenTelemetry collector, or through Akamai TrafficPeak, which is built on Hydrolix\. Nothing is installed in your stack\. Most teams start by streaming one API portfolio, confirm the records land with the tags they want to query on, then widen coverage\. ## Key facts - APIContext is not a Hydrolix competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Hydrolix\. - APIContext generates high\-cardinality API telemetry; Hydrolix stores and queries it at petabyte scale, for years, at a cost that makes long retention practical\. - Hydrolix is a streaming data lake built for high\-cardinality, high\-volume telemetry: it keeps log and event data queryable for months or years at a cost profile conventional log platforms cannot match, and it is the engine behind Akamai TrafficPeak\. APIContext produces exactly that shape of data — 30\+ data points on every API call, broken out per hop, from 125\+ global locations, continuously, whether or not a real user is calling\. Sending APIContext telemetry to Hydrolix turns short\-lived monitoring results into a durable, queryable record of how every API has actually behaved\. - Role in the pipeline — APIContext: Source — generates outside\-in API and network telemetry; Hydrolix: Store and query engine — keeps that telemetry cheap, dense, and queryable - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Hydrolix: Vantage\-agnostic — stores whatever is streamed in - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Hydrolix: Stores and indexes it once APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Hydrolix: Not generated — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Hydrolix: Not generated — APIContext supplies it - Full request and response payloads — APIContext: Yes — captured on every check; Hydrolix: Stores them at high compression without re\-hydration - High\-cardinality query at scale — APIContext: Operational dashboards and reports; Hydrolix: Yes — core strength, across petabytes - Multi\-year retention economics — APIContext: Operational retention windows; Hydrolix: Yes — core strength - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Hydrolix: Stores the resulting history for as long as you need it - Continuous coverage regardless of traffic — APIContext: Yes — synthetic checks produce a complete series with no gaps; Hydrolix: Benefits from it — a dense, uniform dataset compresses and queries well - Works together — APIContext: Streams telemetry, events, and payloads to Hydrolix; Hydrolix: Ingests it via streaming HTTP ingest or an OpenTelemetry collector, including through Akamai TrafficPeak ## Primary entities - APIContext - Hydrolix - APIContext \+ Hydrolix integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Hydrolix competitor? No\. Hydrolix is a streaming data lake for high\-volume telemetry storage and query; APIContext is an outside\-in API monitoring platform that generates telemetry for it\. APIContext does not offer long\-term data lake storage, and Hydrolix does not generate API measurements\. ### Why send API monitoring data to Hydrolix at all? Because outside\-in API telemetry is high\-cardinality and continuous, and the questions asked of it often arrive years later — regulator requests, partner SLA disputes, long\-term quality trends\. Hydrolix keeps that history queryable at a cost that makes multi\-year retention practical\. ### Does this work through Akamai TrafficPeak? Yes\. TrafficPeak is built on Hydrolix and is already an APIContext telemetry destination, so Akamai customers can land API telemetry in the same lake as their edge and delivery data\. --- # APIContext \+ Kong Canonical URL: https://apicontext.com/compare/apicontext-and-kong Source: static Description: Not a Kong alternative — Kong enforces policy on APIs you publish; APIContext verifies from outside that what consumers receive matches\. ## Summary Kong enforces policy on the APIs you publish\. APIContext verifies from outside — from 125\+ locations — that what Kong publishes is what consumers actually receive\. Kong is the control plane for APIs you expose: routing, plugins, authentication, rate limiting, and a service catalog and developer portal in Konnect\. It is authoritative about every request that reached it and the policy applied to that request\. APIContext is the other half of the picture — a client outside your infrastructure that calls the same APIs from 125\+ locations, executes the full authentication chain, and validates each response against the OpenAPI specification Kong publishes\. Nothing about it touches the request path\. ## Page sections ### Which platform produces which signal Kong is the control plane for APIs you expose: routing, plugins, authentication, rate limiting, and a service catalog and developer portal in Konnect\. It is authoritative about every request that reached it and the policy applied to that request\. APIContext is the other half of the picture — a client outside your infrastructure that calls the same APIs from 125\+ locations, executes the full authentication chain, and validates each response against the OpenAPI specification Kong publishes\. Nothing about it touches the request path\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Kong: At the gateway — traffic that reached Kong and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Kong: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Kong: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Kong: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Kong: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Kong: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Kong: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Kong: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Kong: Traffic analytics and metrics for requests Kong served - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Kong: Yes — core strength, via routes, services, and plugins - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Kong: Yes — Konnect service catalog and developer portal - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Kong: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Kong publishes as its monitoring contract; Kong: Publishes the spec, and exports its own telemetry alongside ### What APIContext adds to Kong Kong sees every request that reached it\. That is a complete record of one thing and no record at all of three others, each of which is where real API incidents tend to live: - Requests that never arrived\. A DNS record pointing at a decommissioned region, a certificate that stopped chaining on one edge node, a routing change at a transit provider — the gateway logs none of it, because the traffic never got there\. APIContext measures it from 125\+ locations and attributes the failure to the responsible hop\. - Responses that are wrong but successful\. Gateway analytics count status codes\. A 200 carrying a renamed field, a changed type, or a dropped security header breaks consumers immediately and looks perfectly healthy in a traffic dashboard\. APIContext validates every response against the published spec and reports the diff\. - The APIs you consume rather than publish\. Your gateway fronts what you expose\. It has nothing to say about the payment provider, identity provider, or partner API your services depend on — and those fail too\. APIContext monitors them continuously and produces SLA evidence you own\. - Coverage where no user has been yet\. Analytics can only describe endpoints somebody called\. Synthetic checks fire on every interval against every endpoint, including the ones with no traffic today and the auth chains nobody exercises until a partner tries at month end\. ### What Kong does that APIContext doesn't Publishing and versioning APIs, authentication and authorization enforcement, rate limiting and quotas, request routing and transformation, developer onboarding, and the traffic analytics built on all of it are Kong's domain — and APIContext does none of them\. APIContext sits entirely outside the request path: it enforces nothing, terminates nothing, and cannot change how a single production request is handled\. It is a client that calls your API the way your consumers do and reports what happened\. ### How teams run both The pattern is a loop between the two\. Kong publishes the spec and enforces the policy; APIContext imports that spec and continuously proves it is being honored from the consumer's side, including through the plugin chain\. That is especially useful during change: a rate\-limit adjustment, an auth plugin upgrade, or a route migration all look correct in the control plane and can still break a consumer, and APIContext tells you which regions and which operations are affected before the support tickets do\. Kong's OpenTelemetry export and APIContext's OTLP export land in the same backend, so gateway\-side and consumer\-side views of the same request sit together\. ### How to connect APIContext to Kong Export the OpenAPI spec from Kong or Konnect and import it into APIContext; each operation becomes a monitored endpoint with its own assertions, authentication chain, and locations\. Nothing is installed in your stack and nothing changes in the gateway\. Most teams start with one high\-value route — a login flow, a payments call, a partner\-facing endpoint — confirm the conformance results, then widen coverage\. APIContext's OTLP exporter ships the results into whichever observability platform your Kong telemetry already goes to\. ## Key facts - APIContext is not a Kong competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Kong\. - Kong enforces policy on the APIs you publish\. APIContext verifies from outside — from 125\+ locations — that what Kong publishes is what consumers actually receive\. - Kong is the control plane for APIs you expose: routing, plugins, authentication, rate limiting, and a service catalog and developer portal in Konnect\. It is authoritative about every request that reached it and the policy applied to that request\. APIContext is the other half of the picture — a client outside your infrastructure that calls the same APIs from 125\+ locations, executes the full authentication chain, and validates each response against the OpenAPI specification Kong publishes\. Nothing about it touches the request path\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Kong: At the gateway — traffic that reached Kong and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Kong: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Kong: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Kong: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Kong: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Kong: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Kong: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Kong: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Kong: Traffic analytics and metrics for requests Kong served - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Kong: Yes — core strength, via routes, services, and plugins - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Kong: Yes — Konnect service catalog and developer portal - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Kong: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Kong publishes as its monitoring contract; Kong: Publishes the spec, and exports its own telemetry alongside ## Primary entities - APIContext - Kong - APIContext \+ Kong integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Kong competitor? No\. Kong publishes, secures, and manages the APIs you expose; APIContext monitors API behavior from outside your infrastructure\. APIContext provides no gateway, no policy enforcement, no rate limiting, and no developer portal, and it sits outside the production request path entirely\. ### Kong already has analytics\. Why add APIContext? Kong's analytics measures traffic that reached the gateway\. It cannot see requests that failed before arriving — DNS, TLS, edge, and routing failures — cannot tell you whether a successful response still matches its published specification, and has no visibility into the third\-party APIs your services depend on\. APIContext covers all three\. ### Can APIContext use the OpenAPI spec we publish through Kong? Yes\. Import the spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation, then validates live responses against that same contract on every check\. --- # APIContext \+ MuleSoft Canonical URL: https://apicontext.com/compare/apicontext-and-mulesoft Source: static Description: Not a MuleSoft alternative — Anypoint governs your integrations; APIContext verifies the contract from outside and monitors third\-party dependencies\. ## Summary Anypoint builds, publishes, and governs your integrations\. APIContext verifies the published contract from outside, and monitors the third\-party systems those integrations depend on\. MuleSoft Anypoint Platform builds and governs integrations: Mule applications, API Manager policies, Exchange for publishing and reuse, and monitoring over the applications it runs\. Integration platforms have a distinctive exposure — a Mule flow is usually only as reliable as the SaaS platforms, partner endpoints, and legacy systems it orchestrates, and Anypoint monitors the flow rather than those dependencies\. APIContext covers both sides: it verifies the APIs Anypoint publishes from outside, and monitors the third\-party systems the flows call\. ## Page sections ### Which platform produces which signal MuleSoft Anypoint Platform builds and governs integrations: Mule applications, API Manager policies, Exchange for publishing and reuse, and monitoring over the applications it runs\. Integration platforms have a distinctive exposure — a Mule flow is usually only as reliable as the SaaS platforms, partner endpoints, and legacy systems it orchestrates, and Anypoint monitors the flow rather than those dependencies\. APIContext covers both sides: it verifies the APIs Anypoint publishes from outside, and monitors the third\-party systems the flows call\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; MuleSoft: At the gateway — traffic that reached Anypoint and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; MuleSoft: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; MuleSoft: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; MuleSoft: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; MuleSoft: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; MuleSoft: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; MuleSoft: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; MuleSoft: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; MuleSoft: Monitoring and analytics for Mule applications and API traffic - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; MuleSoft: Yes — core strength, via API Manager policies and Mule flows - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; MuleSoft: Yes — Anypoint Exchange and developer portals - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; MuleSoft: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Anypoint publishes as its monitoring contract; MuleSoft: Publishes the spec, and exports its own telemetry alongside ### What APIContext adds to Anypoint Anypoint sees every request that reached it\. That is a complete record of one thing and no record at all of three others, each of which is where real API incidents tend to live: - Requests that never arrived\. A DNS record pointing at a decommissioned region, a certificate that stopped chaining on one edge node, a routing change at a transit provider — the gateway logs none of it, because the traffic never got there\. APIContext measures it from 125\+ locations and attributes the failure to the responsible hop\. - Responses that are wrong but successful\. Gateway analytics count status codes\. A 200 carrying a renamed field, a changed type, or a dropped security header breaks consumers immediately and looks perfectly healthy in a traffic dashboard\. APIContext validates every response against the published spec and reports the diff\. - The APIs you consume rather than publish\. Your gateway fronts what you expose\. It has nothing to say about the payment provider, identity provider, or partner API your services depend on — and those fail too\. APIContext monitors them continuously and produces SLA evidence you own\. - Coverage where no user has been yet\. Analytics can only describe endpoints somebody called\. Synthetic checks fire on every interval against every endpoint, including the ones with no traffic today and the auth chains nobody exercises until a partner tries at month end\. ### What Anypoint does that APIContext doesn't Publishing and versioning APIs, authentication and authorization enforcement, rate limiting and quotas, request routing and transformation, developer onboarding, and the traffic analytics built on all of it are Anypoint's domain — and APIContext does none of them\. APIContext sits entirely outside the request path: it enforces nothing, terminates nothing, and cannot change how a single production request is handled\. It is a client that calls your API the way your consumers do and reports what happened\. ### How teams run both Anypoint owns the integration logic and its governance; APIContext independently measures both ends of it\. The dependency case is usually the reason teams start: a Mule flow that orchestrates six SaaS APIs fails in ways Anypoint reports as a flow error with no attribution, and APIContext identifies which upstream provider degraded, in which region, and whether its response still matched its contract\. On the publishing side, APIContext imports the spec from Exchange and proves the API consumers call behaves as Exchange says it does\. ### How to connect APIContext to MuleSoft Export the OpenAPI or RAML\-derived spec from Anypoint Exchange and import it into APIContext; each operation becomes a monitored endpoint with its own assertions, authentication chain, and locations\. Then add the third\-party endpoints your flows depend on as monitors in their own right — this is usually the fastest source of value, because those dependencies are typically unmonitored\. Nothing is installed in your stack and no Mule application changes\. ## Key facts - APIContext is not a MuleSoft competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into MuleSoft\. - Anypoint builds, publishes, and governs your integrations\. APIContext verifies the published contract from outside, and monitors the third\-party systems those integrations depend on\. - MuleSoft Anypoint Platform builds and governs integrations: Mule applications, API Manager policies, Exchange for publishing and reuse, and monitoring over the applications it runs\. Integration platforms have a distinctive exposure — a Mule flow is usually only as reliable as the SaaS platforms, partner endpoints, and legacy systems it orchestrates, and Anypoint monitors the flow rather than those dependencies\. APIContext covers both sides: it verifies the APIs Anypoint publishes from outside, and monitors the third\-party systems the flows call\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; MuleSoft: At the gateway — traffic that reached Anypoint and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; MuleSoft: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; MuleSoft: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; MuleSoft: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; MuleSoft: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; MuleSoft: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; MuleSoft: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; MuleSoft: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; MuleSoft: Monitoring and analytics for Mule applications and API traffic - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; MuleSoft: Yes — core strength, via API Manager policies and Mule flows - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; MuleSoft: Yes — Anypoint Exchange and developer portals - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; MuleSoft: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Anypoint publishes as its monitoring contract; MuleSoft: Publishes the spec, and exports its own telemetry alongside ## Primary entities - APIContext - MuleSoft - APIContext \+ MuleSoft integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a MuleSoft competitor? No\. MuleSoft publishes, secures, and manages the APIs you expose; APIContext monitors API behavior from outside your infrastructure\. APIContext provides no gateway, no policy enforcement, no rate limiting, and no developer portal, and it sits outside the production request path entirely\. ### MuleSoft already has analytics\. Why add APIContext? Anypoint Monitoring measures traffic that reached the gateway\. It cannot see requests that failed before arriving — DNS, TLS, edge, and routing failures — cannot tell you whether a successful response still matches its published specification, and has no visibility into the third\-party APIs your services depend on\. APIContext covers all three\. ### Can APIContext use the OpenAPI spec we publish through MuleSoft? Yes\. Import the spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation, then validates live responses against that same contract on every check\. ### Can APIContext monitor the systems our Mule flows call? Yes, and it is often the highest\-value starting point\. Those SaaS, partner, and legacy endpoints sit outside Anypoint's visibility, so a flow failure caused by an upstream provider arrives without attribution\. APIContext monitors each dependency directly and reports which one degraded and whether its response still conformed\. --- # APIContext \+ New Relic Canonical URL: https://apicontext.com/compare/apicontext-and-new-relic Source: static Description: Not a New Relic alternative — a telemetry source for it\. Outside\-in API and network data streams into New Relic over OTLP, closing gaps APM cannot see\. ## Summary The outside\-in network and API telemetry New Relic's agents do not collect, streamed into New Relic over OTLP so it lands in the dashboards your team already uses\. New Relic is a full\-stack observability platform — APM, infrastructure, logs, browser, and synthetics across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. Because every APIContext check emits native OpenTelemetry, its results can land directly in New Relic as traces, metrics, and logs\. New Relic customers add APIContext to close the gaps agents structurally cannot reach — network\-path telemetry, API contract conformance, and third\-party API behavior — and they see it all inside New Relic\. ## Page sections ### Which platform produces which signal New Relic is a full\-stack observability platform — APM, infrastructure, logs, browser, and synthetics across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. Because every APIContext check emits native OpenTelemetry, its results can land directly in New Relic as traces, metrics, and logs\. New Relic customers add APIContext to close the gaps agents structurally cannot reach — network\-path telemetry, API contract conformance, and third\-party API behavior — and they see it all inside New Relic\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; New Relic: Inside your infrastructure — what your code, hosts, and services are doing - Deployment — APIContext: None — fully external, nothing to install; New Relic: New Relic agents and SDKs in your stack - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; New Relic: Not collected — agents report from inside the process, not the network path\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; New Relic: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; New Relic: Not collected — APIContext supplies it - OTEL signal per hop — APIContext: Yes — generated at every network layer from cloud node to origin; New Relic: Ingests OTLP over gRPC and HTTP — APIContext is a source - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; New Relic: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; New Relic: Scripted synthetics — APIContext adds financial\-grade auth chains - Open banking / FAPI 2\.0 — APIContext: Yes — native support for UK, EU, AU, and US frameworks; New Relic: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; New Relic: Limited to code paths you instrument - Private monitoring nodes — APIContext: Yes; New Relic: Yes — containerized private minions - Log correlation — APIContext: Not collected — New Relic supplies it; New Relic: Yes — core strength - Infrastructure monitoring — APIContext: Not collected — New Relic supplies it; New Relic: Yes — core strength - Config\-as\-code / CLI — APIContext: Yes; New Relic: Terraform provider, NerdGraph API - Works together — APIContext: Exports traces, metrics, and logs to New Relic over OTLP; New Relic: Ingests APIContext telemetry as native OTEL ### What APIContext adds to New Relic New Relic's agents report from inside your processes and hosts\. That is their strength, and it is also where their horizon ends: an agent cannot measure the DNS resolution a customer's client performed, the TLS handshake negotiated at the edge, the CDN hop between customer and origin, or the latency a partner in São Paulo sees against an endpoint served from Frankfurt\. APIContext takes those measurements — 30\+ data points on every API call, broken out by DNS, connection, TLS, transfer, and response, from 125\+ public locations across AWS, GCP, Azure, and Akamai plus private nodes inside your own network\. All of it exports to New Relic over OTLP, so it appears next to your existing APM data rather than in a second tool\. Three blind spots close at once: - Network telemetry New Relic does not generate\. Per\-hop DNS, TLS, connection, and transfer timings, attributed to the hop that caused the slowdown — so "the API is slow" becomes "TLS negotiation at the Sydney edge added 380 ms\." - API conformance evidence\. Live validation of responses against OpenAPI specs, FAPI 2\.0 security requirements, and custom business rules, so schema drift arrives in New Relic as an event rather than as a customer ticket\. - Coverage where no user has been yet\. Synthetic checks fire every interval from every region, including endpoints no real user touched today and third\-party APIs you depend on but cannot instrument\. ### What New Relic does that APIContext doesn't Log management and correlation, infrastructure and host monitoring, mobile and browser RUM, code\-level transaction traces, database and JVM diagnostics, and full incident management are New Relic's domain — and APIContext deliberately does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint's response schema drifted at 14:07 UTC from three regions\. New Relic tells you the deploy that shipped at 14:05 is why\. Neither signal is worth much on its own\. ### How teams run both New Relic stays the incident and correlation layer; APIContext becomes the outside\-in data source feeding it\. New Relic answers "why is something slow inside my stack?" APIContext answers "what does my API actually look like to the customer, the partner, and the regulator?" Teams operating regulated APIs, open banking infrastructure, agentic AI services, or customer\-facing API products need both answers, and the second one cannot be produced from inside the stack at all\. ### How to connect APIContext to New Relic APIContext's OTLP exporter ships full payloads to New Relic's OTLP endpoint using a New Relic ingest license key\. Nothing is installed in your stack and nothing changes about your existing New Relic agents\. Most teams start with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the spans arrive in New Relic, then widen coverage endpoint by endpoint\. ## Key facts - APIContext is not a New Relic competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into New Relic\. - The outside\-in network and API telemetry New Relic's agents do not collect, streamed into New Relic over OTLP so it lands in the dashboards your team already uses\. - New Relic is a full\-stack observability platform — APM, infrastructure, logs, browser, and synthetics across an environment you instrument\. APIContext runs entirely outside your infrastructure: no agents, no code changes, no instrumentation\. Because every APIContext check emits native OpenTelemetry, its results can land directly in New Relic as traces, metrics, and logs\. New Relic customers add APIContext to close the gaps agents structurally cannot reach — network\-path telemetry, API contract conformance, and third\-party API behavior — and they see it all inside New Relic\. - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; New Relic: Inside your infrastructure — what your code, hosts, and services are doing - Deployment — APIContext: None — fully external, nothing to install; New Relic: New Relic agents and SDKs in your stack - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; New Relic: Not collected — agents report from inside the process, not the network path\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; New Relic: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; New Relic: Not collected — APIContext supplies it - OTEL signal per hop — APIContext: Yes — generated at every network layer from cloud node to origin; New Relic: Ingests OTLP over gRPC and HTTP — APIContext is a source - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; New Relic: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; New Relic: Scripted synthetics — APIContext adds financial\-grade auth chains - Open banking / FAPI 2\.0 — APIContext: Yes — native support for UK, EU, AU, and US frameworks; New Relic: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; New Relic: Limited to code paths you instrument - Private monitoring nodes — APIContext: Yes; New Relic: Yes — containerized private minions - Log correlation — APIContext: Not collected — New Relic supplies it; New Relic: Yes — core strength - Infrastructure monitoring — APIContext: Not collected — New Relic supplies it; New Relic: Yes — core strength - Config\-as\-code / CLI — APIContext: Yes; New Relic: Terraform provider, NerdGraph API - Works together — APIContext: Exports traces, metrics, and logs to New Relic over OTLP; New Relic: Ingests APIContext telemetry as native OTEL ## Primary entities - APIContext - New Relic - APIContext \+ New Relic integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a New Relic competitor? No\. APIContext is an outside\-in API monitoring platform and a telemetry source for New Relic\. It does not provide APM, infrastructure monitoring, log management, or incident response, and it is not sold as a New Relic replacement\. New Relic customers add APIContext to obtain network\-path and API\-conformance telemetry that agent\-based instrumentation cannot produce\. ### Do I need to remove or reduce New Relic to use APIContext? No\. APIContext runs entirely outside your infrastructure and installs nothing in your stack\. It adds a signal to New Relic rather than replacing one\. ### How does APIContext telemetry get into New Relic? Over OTLP using a New Relic ingest license key\. APIContext emits native OpenTelemetry traces, metrics, and logs, so no custom pipeline is required\. ### What can APIContext see that New Relic cannot? Per\-hop network telemetry \(DNS, TLS, connection, transfer\) measured from outside your infrastructure; API contract conformance against OpenAPI and FAPI 2\.0 specs; geographic performance from 125\+ locations; the behavior of third\-party APIs you do not own; and MCP server behavior for agentic AI services\. ### What does New Relic do that APIContext cannot? Log correlation, infrastructure and host monitoring, code\-level transaction traces, mobile and browser RUM, and full incident management\. --- # APIContext \+ Opsgenie Canonical URL: https://apicontext.com/compare/apicontext-and-opsgenie Source: static Description: Not an Opsgenie alternative — a signal source\. Opsgenie routes and escalates; APIContext supplies pre\-qualified alerts with the schema diff\. ## Summary Opsgenie routes and escalates\. APIContext supplies alerts that arrive already qualified — an outside\-in contract failure with the offending payload, not a bare ping timeout\. Opsgenie is Atlassian's alerting and on\-call platform: routing rules, schedules, escalations, notification policies, and handoff into Jira for the work that follows\. Like any alerting layer, it is only as useful as the signals reaching it\. APIContext produces a signal most monitoring cannot: an outside\-in observation, from 125\+ global locations, that an API has stopped honoring its published contract — schema drift, a broken authentication chain, a security header that disappeared\. Routed into Opsgenie, that becomes an alert an engineer can act on immediately rather than one they have to reproduce first\. ## Page sections ### Which platform produces which signal Opsgenie is Atlassian's alerting and on\-call platform: routing rules, schedules, escalations, notification policies, and handoff into Jira for the work that follows\. Like any alerting layer, it is only as useful as the signals reaching it\. APIContext produces a signal most monitoring cannot: an outside\-in observation, from 125\+ global locations, that an API has stopped honoring its published contract — schema drift, a broken authentication chain, a security header that disappeared\. Routed into Opsgenie, that becomes an alert an engineer can act on immediately rather than one they have to reproduce first\. - Role — APIContext: Detection — decides that something is genuinely wrong; Opsgenie: Routing and escalation — decides who is notified and how - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Opsgenie: Not applicable — Opsgenie consumes alerts from any source - What triggers an alert — APIContext: Conformance failure, schema drift, auth chain break, CASC or SLA threshold, geographic degradation; Opsgenie: Whatever any connected tool sends - Alert content — APIContext: Schema diff, full request and response payload, per\-hop timings, affected regions; Opsgenie: Whatever the source provides, with your own routing tags applied - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Opsgenie: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — alerts on vendor APIs you do not own or instrument; Opsgenie: Only what a connected tool reports - Routing rules and notification policies — APIContext: Not provided — Opsgenie supplies it; Opsgenie: Yes — core strength - On\-call schedules and escalation — APIContext: Not provided — Opsgenie supplies it; Opsgenie: Yes — core strength - Alert deduplication and grouping — APIContext: Multi\-region confirmation before alerting; Opsgenie: Yes — core strength - Jira and Atlassian workflow handoff — APIContext: Conformance history and evidence for the ticket; Opsgenie: Yes — native to the Atlassian suite - Works together — APIContext: Sends alerts to Opsgenie on every plan tier; Opsgenie: Ingests them through its alert API integration key ### What APIContext adds to Opsgenie Opsgenie is good at getting the right alert to the right person\. It cannot make a weak alert stronger\. APIContext changes what is detectable in the first place: - Failures that return 200\. A fast response that no longer matches its OpenAPI spec breaks consumers immediately and is invisible to availability checks\. APIContext alerts on it, with the schema diff attached\. - Confirmation before escalation\. Checks run from 125\+ locations, so the alert can say "reproduced from Frankfurt, Sydney, and Virginia" instead of sending someone after one flaky probe\. - Third\-party APIs you cannot instrument\. When a partner or payment provider degrades, nothing in your own estate raises an alarm until customers do\. APIContext alerts directly\. - Auth chain breaks\. A FAPI 2\.0 or mTLS flow failing at the third step is an outage for regulated consumers and a silent non\-event for anything watching only the endpoint\. ### What Opsgenie does that APIContext doesn't Routing rules, on\-call schedules, escalation and notification policies, alert deduplication and grouping, and the handoff into Jira and the rest of the Atlassian suite are Opsgenie's domain — and APIContext does none of them\. APIContext raises an alert; it has no opinion about who is notified, in what order, over which channel, or what happens if nobody acknowledges\. ### How teams run both APIContext is configured as an alert source in Opsgenie, usually with tags that mirror API ownership so routing rules can send payments conformance failures to one team and partner API degradation to another\. Teams commonly escalate conformance failures and CASC or SLA breaches, and route lower\-severity signals to a non\-paging queue\. Because Opsgenie sits inside Atlassian, the evidence APIContext attaches — the diff, the payload, the affected regions — usually ends up on the Jira issue that follows, which is where it is most useful\. ### How to connect APIContext to Opsgenie Opsgenie is a built\-in APIContext alert destination on every plan tier\. Create an API integration in Opsgenie, add the integration key in APIContext's alerts configuration, and choose which conditions raise alerts\. Nothing is installed in your stack\. Most teams start with conformance failures on one critical endpoint chain, confirm the alerts arrive with payloads attached and route correctly, then widen coverage\. ## Key facts - APIContext is not a Opsgenie competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Opsgenie\. - Opsgenie routes and escalates\. APIContext supplies alerts that arrive already qualified — an outside\-in contract failure with the offending payload, not a bare ping timeout\. - Opsgenie is Atlassian's alerting and on\-call platform: routing rules, schedules, escalations, notification policies, and handoff into Jira for the work that follows\. Like any alerting layer, it is only as useful as the signals reaching it\. APIContext produces a signal most monitoring cannot: an outside\-in observation, from 125\+ global locations, that an API has stopped honoring its published contract — schema drift, a broken authentication chain, a security header that disappeared\. Routed into Opsgenie, that becomes an alert an engineer can act on immediately rather than one they have to reproduce first\. - Role — APIContext: Detection — decides that something is genuinely wrong; Opsgenie: Routing and escalation — decides who is notified and how - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Opsgenie: Not applicable — Opsgenie consumes alerts from any source - What triggers an alert — APIContext: Conformance failure, schema drift, auth chain break, CASC or SLA threshold, geographic degradation; Opsgenie: Whatever any connected tool sends - Alert content — APIContext: Schema diff, full request and response payload, per\-hop timings, affected regions; Opsgenie: Whatever the source provides, with your own routing tags applied - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Opsgenie: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — alerts on vendor APIs you do not own or instrument; Opsgenie: Only what a connected tool reports - Routing rules and notification policies — APIContext: Not provided — Opsgenie supplies it; Opsgenie: Yes — core strength - On\-call schedules and escalation — APIContext: Not provided — Opsgenie supplies it; Opsgenie: Yes — core strength - Alert deduplication and grouping — APIContext: Multi\-region confirmation before alerting; Opsgenie: Yes — core strength - Jira and Atlassian workflow handoff — APIContext: Conformance history and evidence for the ticket; Opsgenie: Yes — native to the Atlassian suite - Works together — APIContext: Sends alerts to Opsgenie on every plan tier; Opsgenie: Ingests them through its alert API integration key ## Primary entities - APIContext - Opsgenie - APIContext \+ Opsgenie integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext an Opsgenie competitor? No\. Opsgenie is an alerting and on\-call platform; APIContext is an outside\-in API monitoring platform that generates the alerts it routes\. APIContext does not provide routing rules, schedules, or escalation policies\. ### How is this different from alerting on a normal uptime check? An uptime check fires on timeouts and error codes\. APIContext also fires on responses that succeed but no longer match their specification, on broken multi\-step authentication chains, and on geographic degradation — and it confirms across regions before alerting\. ### How does APIContext connect to Opsgenie? Through Opsgenie's alert API using an integration key\. Opsgenie is a built\-in alert destination on every APIContext plan\. --- # APIContext \+ PagerDuty Canonical URL: https://apicontext.com/compare/apicontext-and-pagerduty Source: static Description: Not a PagerDuty alternative — a signal source\. PagerDuty decides who responds; APIContext decides if a contract failure is worth waking them\. ## Summary PagerDuty decides who wakes up\. APIContext decides what is worth waking them for — a contract failure observed from outside, with the offending payload and the schema diff attached\. PagerDuty is the on\-call layer: schedules, escalation policies, deduplication, mobile paging, and the incident lifecycle around them\. It does not generate signal; it routes and manages what it is given\. APIContext generates a specific and unusually high\-quality kind of signal — an outside\-in observation, from 125\+ global locations, that an API stopped honoring the contract it publishes\. Feeding one into the other means the pages your on\-call engineers get are qualified: not a ping timeout from a single region, but a schema violation reproduced from three, with the diff in the alert\. ## Page sections ### Which platform produces which signal PagerDuty is the on\-call layer: schedules, escalation policies, deduplication, mobile paging, and the incident lifecycle around them\. It does not generate signal; it routes and manages what it is given\. APIContext generates a specific and unusually high\-quality kind of signal — an outside\-in observation, from 125\+ global locations, that an API stopped honoring the contract it publishes\. Feeding one into the other means the pages your on\-call engineers get are qualified: not a ping timeout from a single region, but a schema violation reproduced from three, with the diff in the alert\. - Role — APIContext: Detection — decides that something is genuinely wrong; PagerDuty: Response — decides who is told, when, and what happens next - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; PagerDuty: Not applicable — PagerDuty consumes events from any source - What triggers an alert — APIContext: Conformance failure, schema drift, auth chain break, CASC or SLA threshold, geographic degradation; PagerDuty: Whatever any connected tool sends - Alert content — APIContext: Schema diff, full request and response payload, per\-hop timings, affected regions; PagerDuty: Whatever the source provides, normalized and deduplicated - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; PagerDuty: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — pages you on vendor APIs you do not own or instrument; PagerDuty: Only what a connected tool reports - On\-call schedules and escalation — APIContext: Not provided — PagerDuty supplies it; PagerDuty: Yes — core strength - Deduplication and noise suppression — APIContext: Multi\-region confirmation before alerting; PagerDuty: Yes — core strength, across every source - Incident lifecycle and postmortems — APIContext: Conformance history and evidence for the review; PagerDuty: Yes — core strength - Status pages and stakeholder comms — APIContext: Not provided — PagerDuty supplies it; PagerDuty: Yes - Works together — APIContext: Sends alerts to PagerDuty on every plan tier; PagerDuty: Ingests them through the Events API as a technical service ### What APIContext adds to PagerDuty The hardest problem in on\-call is not routing — PagerDuty solved that — it is signal quality\. Most API alerts that reach an on\-call engineer are availability pings: they fire on timeouts and 500s and stay silent on everything else\. APIContext changes what is detectable: - Failures that return 200\. A response that arrives quickly and no longer matches its OpenAPI spec is invisible to availability monitoring and breaks your consumers immediately\. APIContext pages on it, with the schema diff attached\. - Confirmation before escalation\. Checks run from 125\+ locations, so an alert can carry "reproduced from Frankfurt, Sydney, and Virginia" rather than sending someone to investigate one flaky probe\. - Third\-party APIs you cannot instrument\. When a payment provider or partner API degrades, nothing in your own stack raises an alarm until customers do\. APIContext pages your on\-call directly\. - Auth chain breaks\. A FAPI 2\.0 or mTLS flow that fails at the third step is a production outage for regulated consumers and a silent non\-event for anything watching only the endpoint\. ### What PagerDuty does that APIContext doesn't On\-call schedules, escalation policies, overrides, mobile paging, deduplication across every connected source, incident command, stakeholder communication, and postmortem workflow are PagerDuty's domain — and APIContext does none of them\. APIContext raises an alert; it has no opinion about who should be woken up at 03:00, in what order, or what happens if they do not acknowledge\. ### How teams run both APIContext is configured as a technical service in PagerDuty, usually split by API portfolio so escalation follows ownership: payments conformance failures page the payments team, partner API degradation pages the integrations team\. Teams typically route conformance failures and CASC or SLA breaches to paging, and everything else to a low\-urgency queue or chat\. The result is that API contract failures get the same treatment as infrastructure incidents, which is usually a change — they are frequently discovered by consumers first\. ### How to connect APIContext to PagerDuty PagerDuty is a built\-in APIContext alert destination on every plan tier\. Create a PagerDuty integration on the service you want paged, add the routing key in APIContext's alerts configuration, and choose which conditions escalate\. Nothing is installed in your stack\. Most teams start by paging on conformance failures for one critical endpoint chain, confirm the incidents arrive with the payload attached, then widen coverage\. ## Key facts - APIContext is not a PagerDuty competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into PagerDuty\. - PagerDuty decides who wakes up\. APIContext decides what is worth waking them for — a contract failure observed from outside, with the offending payload and the schema diff attached\. - PagerDuty is the on\-call layer: schedules, escalation policies, deduplication, mobile paging, and the incident lifecycle around them\. It does not generate signal; it routes and manages what it is given\. APIContext generates a specific and unusually high\-quality kind of signal — an outside\-in observation, from 125\+ global locations, that an API stopped honoring the contract it publishes\. Feeding one into the other means the pages your on\-call engineers get are qualified: not a ping timeout from a single region, but a schema violation reproduced from three, with the diff in the alert\. - Role — APIContext: Detection — decides that something is genuinely wrong; PagerDuty: Response — decides who is told, when, and what happens next - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; PagerDuty: Not applicable — PagerDuty consumes events from any source - What triggers an alert — APIContext: Conformance failure, schema drift, auth chain break, CASC or SLA threshold, geographic degradation; PagerDuty: Whatever any connected tool sends - Alert content — APIContext: Schema diff, full request and response payload, per\-hop timings, affected regions; PagerDuty: Whatever the source provides, normalized and deduplicated - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; PagerDuty: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — pages you on vendor APIs you do not own or instrument; PagerDuty: Only what a connected tool reports - On\-call schedules and escalation — APIContext: Not provided — PagerDuty supplies it; PagerDuty: Yes — core strength - Deduplication and noise suppression — APIContext: Multi\-region confirmation before alerting; PagerDuty: Yes — core strength, across every source - Incident lifecycle and postmortems — APIContext: Conformance history and evidence for the review; PagerDuty: Yes — core strength - Status pages and stakeholder comms — APIContext: Not provided — PagerDuty supplies it; PagerDuty: Yes - Works together — APIContext: Sends alerts to PagerDuty on every plan tier; PagerDuty: Ingests them through the Events API as a technical service ## Primary entities - APIContext - PagerDuty - APIContext \+ PagerDuty integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a PagerDuty competitor? No\. PagerDuty is an on\-call and incident response platform; APIContext is an outside\-in API monitoring platform that generates the alerts it routes\. APIContext does not provide on\-call schedules, escalation policies, or incident command\. ### Will this add noise to our on\-call rotation? It should reduce it\. APIContext confirms failures across multiple regions before alerting and sends the schema diff and payload with the alert, so an engineer can triage without reproducing the problem first\. Conditions are configurable per endpoint, so only what you consider page\-worthy escalates\. ### How does APIContext connect to PagerDuty? Through PagerDuty's Events API, using a routing key from the service you want paged\. PagerDuty is a built\-in alert destination on every APIContext plan\. --- # APIContext \+ Postman Canonical URL: https://apicontext.com/compare/apicontext-and-postman Source: static Description: Not a Postman alternative — the production half of the lifecycle\. Bring the OpenAPI spec from Postman and monitor it from 125\+ locations\. ## Summary Postman is where the API contract gets written; APIContext is where it gets verified, continuously, in production\. The same OpenAPI spec drives both\. Postman is an API design, documentation, and development\-testing platform — collaborative workspaces, mock servers, generated docs, and collection runs against an API you are still building\. APIContext runs entirely outside your infrastructure and picks up where that leaves off: continuous, multi\-location verification that the shipped API still matches the spec\. The handoff is literal — the OpenAPI spec you maintain in Postman becomes the contract APIContext validates on every check, and conformance results come back pointing at that spec\. Most APIContext customers use Postman\. ## Page sections ### Which tool covers which stage Postman is an API design, documentation, and development\-testing platform — collaborative workspaces, mock servers, generated docs, and collection runs against an API you are still building\. APIContext runs entirely outside your infrastructure and picks up where that leaves off: continuous, multi\-location verification that the shipped API still matches the spec\. The handoff is literal — the OpenAPI spec you maintain in Postman becomes the contract APIContext validates on every check, and conformance results come back pointing at that spec\. Most APIContext customers use Postman\. - Lifecycle stage — APIContext: Production — continuous verification after release; Postman: Design and build — contract definition, docs, and hands\-on testing - Monitoring locations — APIContext: 125\+ global nodes across AWS, GCP, Azure, and Akamai, plus private nodes; Postman: A small number of managed cloud regions - Network path telemetry — APIContext: Yes — DNS, TLS, connection, transfer, and response per hop; 30\+ data points per call; Postman: Not collected — APIContext supplies it - API conformance / schema diff — APIContext: Yes — live conformance against the spec on every check; Postman: Schema validation inside collection runs - CASC quality score — APIContext: Yes; Postman: Not collected — APIContext supplies it - OTEL per\-hop traces — APIContext: Yes — DNS, TLS, connection, transfer, response; Postman: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native; Postman: OAuth and token handling — APIContext adds financial\-grade auth chains - SLA/SLO reporting — APIContext: Native, per\-endpoint; Postman: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes; Postman: Not collected — APIContext supplies it - Open banking compliance — APIContext: Yes; Postman: Not collected — APIContext supplies it - Audit trail / compliance reporting — APIContext: Yes; Postman: Not collected — APIContext supplies it - Collaborative workspace, mocks, and docs — APIContext: Not provided — Postman supplies it; Postman: Yes — mock servers, docs generation, shared collections - Config\-as\-code / CLI — APIContext: Yes; Postman: Postman CLI \(newman\) - Works together — APIContext: Imports the OpenAPI spec Postman produces as its monitoring contract; Postman: Exports the OpenAPI spec APIContext monitors against ### What APIContext adds once the spec ships Postman's monitoring is a scheduler on top of its collection runner — it fires requests from a handful of cloud regions and reports pass or fail, which is the right shape for watching an API during development\. Production asks harder questions\. APIContext runs every check from 125\+ nodes across AWS, GCP, Azure, and Akamai; instruments the full request chain with OTEL spans covering DNS, TLS, connection, and transfer; and rolls results into conformance reports, CASC quality scores, and per\-endpoint SLA evidence\. For regulated APIs, agentic AI infrastructure, and multi\-step authenticated flows using mTLS, FAPI 2\.0, or DPoP, that is a different job from the one Postman set out to do\. ### What Postman does that APIContext doesn't Collaborative workspaces, mock servers, generated documentation, shared collections, and the hands\-on request\-tweaking loop every API developer lives in are Postman's domain, and APIContext builds none of them\. If the problem is getting a team to agree on a contract and exercise it while the API is still being built, that is Postman's job\. APIContext has nothing to offer before an API is deployed\. ### How teams run both The common pattern is a loop, not a choice\. Design and document the API in Postman\. Export the OpenAPI spec\. Import it into APIContext, which turns each operation into a continuously monitored contract across regions and auth flows\. When production drifts from the spec — a field type changes, a security header disappears, a partner\-facing endpoint slows in one region — APIContext reports the diff against that spec, and it goes back to the team maintaining the collection in Postman\. Postman defines the promise; APIContext proves it is still being kept\. ### How to connect APIContext to Postman Export the OpenAPI spec from Postman and import it into APIContext; each operation becomes a monitored endpoint with its own assertions, auth chain, and locations\. Nothing is installed in your stack\. Most teams start with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the conformance results, then widen coverage endpoint by endpoint\. APIContext's OTLP exporter then ships those results into whichever observability platform you already run\. ## Key facts - APIContext is not a Postman competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Postman\. - Postman is where the API contract gets written; APIContext is where it gets verified, continuously, in production\. The same OpenAPI spec drives both\. - Postman is an API design, documentation, and development\-testing platform — collaborative workspaces, mock servers, generated docs, and collection runs against an API you are still building\. APIContext runs entirely outside your infrastructure and picks up where that leaves off: continuous, multi\-location verification that the shipped API still matches the spec\. The handoff is literal — the OpenAPI spec you maintain in Postman becomes the contract APIContext validates on every check, and conformance results come back pointing at that spec\. Most APIContext customers use Postman\. - Lifecycle stage — APIContext: Production — continuous verification after release; Postman: Design and build — contract definition, docs, and hands\-on testing - Monitoring locations — APIContext: 125\+ global nodes across AWS, GCP, Azure, and Akamai, plus private nodes; Postman: A small number of managed cloud regions - Network path telemetry — APIContext: Yes — DNS, TLS, connection, transfer, and response per hop; 30\+ data points per call; Postman: Not collected — APIContext supplies it - API conformance / schema diff — APIContext: Yes — live conformance against the spec on every check; Postman: Schema validation inside collection runs - CASC quality score — APIContext: Yes; Postman: Not collected — APIContext supplies it - OTEL per\-hop traces — APIContext: Yes — DNS, TLS, connection, transfer, response; Postman: Not collected — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native; Postman: OAuth and token handling — APIContext adds financial\-grade auth chains - SLA/SLO reporting — APIContext: Native, per\-endpoint; Postman: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes; Postman: Not collected — APIContext supplies it - Open banking compliance — APIContext: Yes; Postman: Not collected — APIContext supplies it - Audit trail / compliance reporting — APIContext: Yes; Postman: Not collected — APIContext supplies it - Collaborative workspace, mocks, and docs — APIContext: Not provided — Postman supplies it; Postman: Yes — mock servers, docs generation, shared collections - Config\-as\-code / CLI — APIContext: Yes; Postman: Postman CLI \(newman\) - Works together — APIContext: Imports the OpenAPI spec Postman produces as its monitoring contract; Postman: Exports the OpenAPI spec APIContext monitors against ## Primary entities - APIContext - Postman - APIContext \+ Postman integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Postman competitor? No\. Postman is an API design, documentation, and development\-testing platform; APIContext is a production monitoring platform\. Most APIContext customers use Postman, and APIContext consumes the OpenAPI specs Postman produces\. ### Does APIContext replace Postman Monitors? For production monitoring, teams typically move to APIContext for geographic coverage, per\-hop OTEL telemetry, conformance validation, and SLA reporting — while continuing to use Postman for design, docs, and development testing\. ### Can I reuse my Postman work in APIContext? Yes\. Import the OpenAPI spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation\. --- # APIContext \+ ServiceNow Canonical URL: https://apicontext.com/compare/apicontext-and-servicenow Source: static Description: Not a ServiceNow alternative — an evidence source\. ServiceNow runs the incident record; APIContext supplies outside\-in proof of what the API did\. ## Summary ServiceNow runs the incident, change, and service record\. APIContext supplies the input those records usually lack — dated, outside\-in evidence of what an API actually did\. ServiceNow is where enterprise IT work is recorded and governed: incidents, changes, problems, the CMDB, service\-level management, and supplier records\. Its weakness has never been workflow; it is that the evidence attached to a record is usually whatever a human could find at the time\. APIContext produces exactly the evidence those records need — continuous, timestamped, outside\-in measurements of whether an API honored its published contract, taken from 125\+ global locations, on APIs you own and APIs you buy\. ## Page sections ### Which platform produces which signal ServiceNow is where enterprise IT work is recorded and governed: incidents, changes, problems, the CMDB, service\-level management, and supplier records\. Its weakness has never been workflow; it is that the evidence attached to a record is usually whatever a human could find at the time\. APIContext produces exactly the evidence those records need — continuous, timestamped, outside\-in measurements of whether an API honored its published contract, taken from 125\+ global locations, on APIs you own and APIs you buy\. - Role — APIContext: Evidence — measures what actually happened, continuously; ServiceNow: System of record and workflow — governs what is done about it - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; ServiceNow: Not applicable — ServiceNow records and orchestrates - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; ServiceNow: Not collected — APIContext supplies it - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response per hop; 30\+ data points per call; ServiceNow: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; ServiceNow: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — independent measurement of APIs your suppliers operate; ServiceNow: Supplier records, contracts, and manual attestations - Change validation evidence — APIContext: Conformance before and after, per region, on a timestamp; ServiceNow: Change request, approval, and implementation record - Incident and problem workflow — APIContext: Not provided — ServiceNow supplies it; ServiceNow: Yes — core strength - CMDB and service mapping — APIContext: Not provided — ServiceNow supplies it; ServiceNow: Yes — core strength - Service\-level management — APIContext: Native, per\-endpoint SLA and SLO measurement; ServiceNow: SLA definitions, breach tracking, and reporting workflow - Works together — APIContext: Sends conformance events and evidence by webhook; ServiceNow: Ingests them into Event Management or directly as records ### What APIContext adds to ServiceNow Three ServiceNow processes routinely run on assertions rather than measurements, and APIContext turns each of them into something evidence\-backed: - Incidents with proof attached\. Instead of "users report the payments API is failing," the record carries the schema diff, the payload, the affected regions, and the minute the contract broke\. - Change validation\. A change request closes on the implementer's word that nothing regressed\. APIContext supplies before\-and\-after conformance across every region, which either confirms that or does not\. - Supplier accountability\. When a vendor API breaches its SLA, the supplier record usually cites the vendor's own status page\. APIContext gives you independent measurement of an API you do not run, which is what makes a credit claim or a contract conversation possible\. ### What ServiceNow does that APIContext doesn't Incident, problem, and change workflow, approvals and CAB, the CMDB and service mapping, service\-level management, supplier and contract management, and the enterprise reporting built on all of it are ServiceNow's domain — and APIContext does none of them\. APIContext has no record model, no workflow engine, and no opinion about who approves what\. The division is clean: APIContext establishes what happened; ServiceNow governs the response and keeps the record\. ### How teams run both The common pattern is conformance events raising or enriching records automatically, with the API portfolio mapped to the services in the CMDB so an incident lands on the right service and assignment group\. Governance teams use the conformance history for periodic service reviews; procurement and vendor management teams use the third\-party measurements at renewal\. The most valuable single use is usually the least glamorous — attaching real evidence to change records, so the question "did that release break the contract?" has an answer\. ### How to connect APIContext to ServiceNow APIContext delivers conformance events by webhook, which can be received by ServiceNow's Event Management for incident creation and correlation, or written directly against the relevant table where Event Management is not deployed\. Nothing is installed in your stack\. Most teams start with one API portfolio mapped to one service, confirm records arrive with the evidence attached and route to the correct assignment group, then widen coverage\. ## Key facts - APIContext is not a ServiceNow competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into ServiceNow\. - ServiceNow runs the incident, change, and service record\. APIContext supplies the input those records usually lack — dated, outside\-in evidence of what an API actually did\. - ServiceNow is where enterprise IT work is recorded and governed: incidents, changes, problems, the CMDB, service\-level management, and supplier records\. Its weakness has never been workflow; it is that the evidence attached to a record is usually whatever a human could find at the time\. APIContext produces exactly the evidence those records need — continuous, timestamped, outside\-in measurements of whether an API honored its published contract, taken from 125\+ global locations, on APIs you own and APIs you buy\. - Role — APIContext: Evidence — measures what actually happened, continuously; ServiceNow: System of record and workflow — governs what is done about it - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; ServiceNow: Not applicable — ServiceNow records and orchestrates - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; ServiceNow: Not collected — APIContext supplies it - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response per hop; 30\+ data points per call; ServiceNow: Not collected — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; ServiceNow: Not collected — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — independent measurement of APIs your suppliers operate; ServiceNow: Supplier records, contracts, and manual attestations - Change validation evidence — APIContext: Conformance before and after, per region, on a timestamp; ServiceNow: Change request, approval, and implementation record - Incident and problem workflow — APIContext: Not provided — ServiceNow supplies it; ServiceNow: Yes — core strength - CMDB and service mapping — APIContext: Not provided — ServiceNow supplies it; ServiceNow: Yes — core strength - Service\-level management — APIContext: Native, per\-endpoint SLA and SLO measurement; ServiceNow: SLA definitions, breach tracking, and reporting workflow - Works together — APIContext: Sends conformance events and evidence by webhook; ServiceNow: Ingests them into Event Management or directly as records ## Primary entities - APIContext - ServiceNow - APIContext \+ ServiceNow integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a ServiceNow competitor? No\. ServiceNow is an ITSM and workflow platform; APIContext is an outside\-in API monitoring platform that supplies evidence into it\. APIContext provides no incident workflow, CMDB, change management, or approvals\. ### What does APIContext add that our existing monitoring does not? Independent, outside\-in measurement — including of APIs your suppliers operate, which internal monitoring cannot see\. That is what turns an SLA breach from an assertion into a documented claim\. ### How does APIContext connect to ServiceNow? By webhook into Event Management for incident creation and correlation, or directly against the relevant table\. Mapping API portfolios to CMDB services is what makes routing and reporting work\. --- # APIContext \+ Splunk Canonical URL: https://apicontext.com/compare/apicontext-and-splunk Source: static Description: Not a Splunk alternative — an OTLP source\. APIContext supplies outside\-in API conformance and network evidence your internal logs cannot contain\. ## Summary Splunk indexes and correlates the data your systems emit; APIContext produces data your systems cannot emit, because it is measured from outside them\. Splunk indexes, searches, and correlates machine data at scale — logs, metrics, traces, and security events across Splunk Enterprise, Splunk Cloud, and Splunk Observability Cloud\. Every one of those sources is something your own estate emitted\. APIContext produces the category Splunk has no other way to obtain: measurements taken from outside your infrastructure, from 125\+ global locations, against APIs you own and APIs you merely depend on\. Because every APIContext check emits native OpenTelemetry, those results land in Splunk alongside internal telemetry and become searchable with everything else\. ## Page sections ### Which platform produces which signal Splunk indexes, searches, and correlates machine data at scale — logs, metrics, traces, and security events across Splunk Enterprise, Splunk Cloud, and Splunk Observability Cloud\. Every one of those sources is something your own estate emitted\. APIContext produces the category Splunk has no other way to obtain: measurements taken from outside your infrastructure, from 125\+ global locations, against APIs you own and APIs you merely depend on\. Because every APIContext check emits native OpenTelemetry, those results land in Splunk alongside internal telemetry and become searchable with everything else\. - Role in the pipeline — APIContext: Source — generates telemetry that does not otherwise exist; Splunk: Destination — indexes, searches, and correlates telemetry from every source - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Splunk: Whatever your estate emits — logs, metrics, traces, security events - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Splunk: Indexes it once APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Splunk: Not generated — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Splunk: Not generated — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Splunk: Only what those endpoints happen to log on your side - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Splunk: Not generated — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Splunk: Not applicable — Splunk observes, it does not authenticate - Search and correlation at scale — APIContext: Not provided — Splunk supplies it; Splunk: Yes — core strength - SIEM and security analytics — APIContext: Not provided — Splunk supplies it; Splunk: Yes — core strength - Long\-term indexed retention — APIContext: Operational retention windows; Splunk: Yes — indexed retention and reporting across sources - Works together — APIContext: Exports traces, metrics, logs, and conformance events as native OTEL; Splunk: Ingests OTLP via the Splunk OpenTelemetry Collector and events via HTTP Event Collector ### What APIContext adds to Splunk A Splunk index is only as useful as the data reaching it, and there is a whole class of data your estate structurally cannot produce: what an API looks like from outside\. No application log records the DNS resolution a customer's client performed, the TLS handshake negotiated at the edge, or the fact that a partner in São Paulo has been getting schema\-invalid responses for twenty minutes\. APIContext generates that evidence continuously and ships it to Splunk as OTEL: - Per\-hop network telemetry\. DNS, TLS, connection, and transfer timings from 125\+ global locations plus private nodes, searchable next to your own logs for the same minute\. - Conformance verdicts with payloads\. Every check validates responses against OpenAPI specs, FAPI 2\.0 security requirements, and custom business rules — producing dated, queryable evidence for audits, disputes, and regulator requests\. - Third\-party API accountability\. Continuous measurement of the APIs you depend on but do not run, so an SLA claim against a vendor is backed by data in your own Splunk index rather than their status page\. ### What Splunk does that APIContext doesn't Indexing and search at scale, correlation across every data source, dashboards and alerting over the whole estate, SIEM and security analytics, and long\-term indexed retention are Splunk's domain — and APIContext does none of them\. The division is easiest to see during an incident: APIContext reports that a payments endpoint's response schema drifted at 14:07 UTC from three regions\. Splunk shows you the configuration change your own logs recorded at 14:05\. Neither signal is worth much on its own\. ### How teams run both Splunk stays the system of record and the search surface; APIContext becomes an external source feeding it\. Security and governance teams get something they usually lack — independent, outside\-in evidence of how an API behaved, held in the same platform as the internal record\. Splunk answers "what did my systems report?" APIContext answers "what did the outside world actually receive?" ### How to connect APIContext to Splunk APIContext's OTLP exporter ships full payloads to the Splunk distribution of the OpenTelemetry Collector, or directly to a Splunk Observability Cloud OTLP endpoint\. Conformance events can also be routed into Splunk Cloud or Splunk Enterprise over HTTP Event Collector for correlation with security and audit data\. Nothing is installed in your stack\. Most teams start with one high\-value chain — a login flow, a payments call, a partner webhook — confirm the events land in the right index, then widen coverage endpoint by endpoint\. ## Key facts - APIContext is not a Splunk competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Splunk\. - Splunk indexes and correlates the data your systems emit; APIContext produces data your systems cannot emit, because it is measured from outside them\. - Splunk indexes, searches, and correlates machine data at scale — logs, metrics, traces, and security events across Splunk Enterprise, Splunk Cloud, and Splunk Observability Cloud\. Every one of those sources is something your own estate emitted\. APIContext produces the category Splunk has no other way to obtain: measurements taken from outside your infrastructure, from 125\+ global locations, against APIs you own and APIs you merely depend on\. Because every APIContext check emits native OpenTelemetry, those results land in Splunk alongside internal telemetry and become searchable with everything else\. - Role in the pipeline — APIContext: Source — generates telemetry that does not otherwise exist; Splunk: Destination — indexes, searches, and correlates telemetry from every source - Vantage point — APIContext: Outside your infrastructure — what customers and partners actually experience; Splunk: Whatever your estate emits — logs, metrics, traces, security events - Network path telemetry — APIContext: Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30\+ data points per call; Splunk: Indexes it once APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; Splunk: Not generated — APIContext supplies it - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Splunk: Not generated — APIContext supplies it - Third\-party and partner APIs — APIContext: Yes — monitors endpoints you depend on but do not own or instrument; Splunk: Only what those endpoints happen to log on your side - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Splunk: Not generated — APIContext supplies it - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — native FAPI 2\.0, mTLS, DPoP, PAR, PKCE, and JARM; Splunk: Not applicable — Splunk observes, it does not authenticate - Search and correlation at scale — APIContext: Not provided — Splunk supplies it; Splunk: Yes — core strength - SIEM and security analytics — APIContext: Not provided — Splunk supplies it; Splunk: Yes — core strength - Long\-term indexed retention — APIContext: Operational retention windows; Splunk: Yes — indexed retention and reporting across sources - Works together — APIContext: Exports traces, metrics, logs, and conformance events as native OTEL; Splunk: Ingests OTLP via the Splunk OpenTelemetry Collector and events via HTTP Event Collector ## Primary entities - APIContext - Splunk - APIContext \+ Splunk integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Splunk competitor? No\. Splunk is a data platform for indexing, searching, and correlating machine data; APIContext is an outside\-in API monitoring platform that generates telemetry for it\. APIContext does not provide log indexing, search at scale, SIEM, or security analytics\. ### Does APIContext replace any part of Splunk? No\. It adds a source\. APIContext measures API behavior from outside your infrastructure, which is data no internal log or agent can produce, and sends the results into Splunk\. ### How does APIContext telemetry get into Splunk? Over OTLP to the Splunk OpenTelemetry Collector or Splunk Observability Cloud, and over HTTP Event Collector for conformance events destined for Splunk Cloud or Enterprise\. --- # APIContext \+ ThousandEyes Canonical URL: https://apicontext.com/compare/apicontext-and-thousandeyes Source: static Description: Not a ThousandEyes replacement\. ThousandEyes maps the network path; APIContext validates the API contract at the end of it\. ## Summary ThousandEyes maps the network path your traffic takes; APIContext validates the API contract waiting at the end of it\. ThousandEyes gives you hop\-by\-hop visibility into the networks between your users, your cloud providers, and your services: path visualization, BGP route monitoring, Internet and WAN outage detection, and endpoint agents on employee devices\. APIContext validates the API at the far end of that path — live conformance against OpenAPI and FAPI 2\.0 specs, complete authentication chains, payload\-level assertions, and CASC quality scoring from 125\+ global locations\. Neither substitutes for the other, and both emit OpenTelemetry, so their signals can be correlated in one backend\. ## Page sections ### Which platform produces which signal ThousandEyes gives you hop\-by\-hop visibility into the networks between your users, your cloud providers, and your services: path visualization, BGP route monitoring, Internet and WAN outage detection, and endpoint agents on employee devices\. APIContext validates the API at the far end of that path — live conformance against OpenAPI and FAPI 2\.0 specs, complete authentication chains, payload\-level assertions, and CASC quality scoring from 125\+ global locations\. Neither substitutes for the other, and both emit OpenTelemetry, so their signals can be correlated in one backend\. - Primary layer — APIContext: The API contract — conformance, authentication, payload correctness; ThousandEyes: The network path — Internet, WAN, and cloud connectivity between endpoints - Vantage network — APIContext: 125\+ cloud nodes across AWS, GCP, Azure, and Akamai, plus private nodes; ThousandEyes: Cloud, enterprise, and endpoint agents across Internet and WAN paths - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; ThousandEyes: HTTP server tests with response assertions — APIContext supplies full conformance - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — full chains including PAR, PKCE, DPoP\-bound tokens, and JARM; ThousandEyes: Standard auth in transaction tests — APIContext supplies financial\-grade chains - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; ThousandEyes: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; ThousandEyes: Not collected — APIContext supplies it - Open banking / FAPI compliance evidence — APIContext: Yes — native support for UK, EU, AU, and US frameworks; ThousandEyes: Not collected — APIContext supplies it - Hop\-by\-hop path visualization — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — core strength across ISP, WAN, and cloud networks - BGP and route monitoring — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — core strength - Internet and SaaS outage detection — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — Internet Insights across providers - Employee endpoint experience — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — endpoint agents on user devices - Per\-hop timings on API calls — APIContext: Yes — DNS, connection, TLS, transfer, and response; 30\+ data points per call; ThousandEyes: Yes — network\-layer path metrics - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; ThousandEyes: Telemetry exports into the same observability backend ### What APIContext adds to ThousandEyes ThousandEyes explains how traffic got there and what the network did to it\. APIContext explains whether the thing at the other end honored its contract\. On regulated and partner\-facing APIs, that second question is where the failures live: - Contract conformance, not just reachability\. Responses are validated live against their OpenAPI spec, FAPI 2\.0 security requirements, and your own business rules, so a reachable endpoint returning a malformed payload is caught as a failure\. - Financial\-grade authentication chains\. Complete mTLS handshakes with client certificates and full FAPI 2\.0 flows including PAR, DPoP\-bound tokens, and JARM validation, executed end to end\. - Agentic AI and MCP monitoring\. Continuous outside\-in testing of MCP servers, tool schema validation, session lifecycle verification, and per\-tool latency\. - Compliance evidence\. CASC quality scoring, conformance history, and per\-endpoint SLA reporting in the form governance and audit teams have to produce\. ### What ThousandEyes does that APIContext doesn't Hop\-by\-hop path visualization across ISP, WAN, and cloud networks, BGP route monitoring, Internet and SaaS outage detection, and endpoint agents on employee devices are ThousandEyes' domain — and APIContext does none of them\. The division is easiest to see during an incident: ThousandEyes shows that a transit provider re\-routed traffic at 14:02\. APIContext shows that the payments endpoint began returning a schema\-invalid response at 14:07\. One is a network event and one is a contract failure, and treating either as the other wastes the whole incident\. ### How teams run both ThousandEyes owns the network and connectivity picture; APIContext owns the API contract and the compliance record\. Network and platform teams use ThousandEyes to establish whether the path is healthy, then APIContext to establish whether the API is correct — which is the difference between escalating to a carrier and escalating to an API owner\. Both platforms export telemetry, so the two views can be correlated in Datadog, Dynatrace, New Relic, Splunk, Grafana, or your own collector\. ### How to connect APIContext to ThousandEyes There is no coupling to configure\. Each platform exports telemetry to a shared destination, and APIContext's OTLP exporter ships full payloads to whichever backend you already run\. Most teams correlate on endpoint and timestamp: ThousandEyes supplies the path and routing context, APIContext supplies the conformance verdict and per\-hop timings for the same call\. ## Key facts - APIContext is not a ThousandEyes competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into ThousandEyes\. - ThousandEyes maps the network path your traffic takes; APIContext validates the API contract waiting at the end of it\. - ThousandEyes gives you hop\-by\-hop visibility into the networks between your users, your cloud providers, and your services: path visualization, BGP route monitoring, Internet and WAN outage detection, and endpoint agents on employee devices\. APIContext validates the API at the far end of that path — live conformance against OpenAPI and FAPI 2\.0 specs, complete authentication chains, payload\-level assertions, and CASC quality scoring from 125\+ global locations\. Neither substitutes for the other, and both emit OpenTelemetry, so their signals can be correlated in one backend\. - Primary layer — APIContext: The API contract — conformance, authentication, payload correctness; ThousandEyes: The network path — Internet, WAN, and cloud connectivity between endpoints - Vantage network — APIContext: 125\+ cloud nodes across AWS, GCP, Azure, and Akamai, plus private nodes; ThousandEyes: Cloud, enterprise, and endpoint agents across Internet and WAN paths - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every check; ThousandEyes: HTTP server tests with response assertions — APIContext supplies full conformance - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — full chains including PAR, PKCE, DPoP\-bound tokens, and JARM; ThousandEyes: Standard auth in transaction tests — APIContext supplies financial\-grade chains - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; ThousandEyes: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; ThousandEyes: Not collected — APIContext supplies it - Open banking / FAPI compliance evidence — APIContext: Yes — native support for UK, EU, AU, and US frameworks; ThousandEyes: Not collected — APIContext supplies it - Hop\-by\-hop path visualization — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — core strength across ISP, WAN, and cloud networks - BGP and route monitoring — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — core strength - Internet and SaaS outage detection — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — Internet Insights across providers - Employee endpoint experience — APIContext: Not collected — ThousandEyes supplies it; ThousandEyes: Yes — endpoint agents on user devices - Per\-hop timings on API calls — APIContext: Yes — DNS, connection, TLS, transfer, and response; 30\+ data points per call; ThousandEyes: Yes — network\-layer path metrics - Works together — APIContext: Exports traces, metrics, and logs as native OTEL; ThousandEyes: Telemetry exports into the same observability backend ## Primary entities - APIContext - ThousandEyes - APIContext \+ ThousandEyes integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Are APIContext and ThousandEyes competitors? No\. ThousandEyes monitors network and Internet paths — routing, connectivity, and delivery between locations\. APIContext validates the API contract at the end of the path: conformance against OpenAPI and FAPI 2\.0 specs, authentication chains, payload correctness, and CASC quality scoring\. ### ThousandEyes has HTTP and API tests\. Why add APIContext? ThousandEyes HTTP tests confirm an endpoint responds and how the network behaved getting there\. APIContext validates that the response conforms to its specification, that multi\-step FAPI 2\.0 or mTLS authentication completes correctly, and that the endpoint meets the quality and SLA thresholds you have committed to — then produces the evidence to prove it\. ### How do the two datasets come together? Both platforms export telemetry into a shared observability backend, where they correlate on endpoint and timestamp\. APIContext ships native OpenTelemetry over OTLP\. --- # APIContext \+ TIBCO Canonical URL: https://apicontext.com/compare/apicontext-and-tibco Source: static Description: Not a TIBCO alternative — TIBCO governs APIs and integrations; APIContext verifies the contract from outside and monitors dependent systems\. ## Summary TIBCO governs and publishes your APIs and integrations\. APIContext verifies the published contract from outside, and monitors the systems those integrations depend on\. TIBCO's API management and integration stack publishes and governs APIs across estates that are usually long\-lived and heterogeneous — mainframe and packaged systems alongside modern services, with partner traffic on top\. That profile creates two blind spots at once: the gateway sees only what reached it, and the integration layer depends on backend and partner systems it does not monitor\. APIContext calls the published APIs from outside, from 125\+ locations, validates every response against its specification, and monitors the third\-party endpoints the integrations rely on\. ## Page sections ### Which platform produces which signal TIBCO's API management and integration stack publishes and governs APIs across estates that are usually long\-lived and heterogeneous — mainframe and packaged systems alongside modern services, with partner traffic on top\. That profile creates two blind spots at once: the gateway sees only what reached it, and the integration layer depends on backend and partner systems it does not monitor\. APIContext calls the published APIs from outside, from 125\+ locations, validates every response against its specification, and monitors the third\-party endpoints the integrations rely on\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; TIBCO: At the gateway — traffic that reached TIBCO and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; TIBCO: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; TIBCO: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; TIBCO: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; TIBCO: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; TIBCO: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; TIBCO: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; TIBCO: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; TIBCO: Analytics and reporting for traffic it processed - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; TIBCO: Yes — core strength, via API management policies and integration flows - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; TIBCO: Yes — developer portal and API packaging - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; TIBCO: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec TIBCO publishes as its monitoring contract; TIBCO: Publishes the spec, and exports its own telemetry alongside ### What APIContext adds to TIBCO TIBCO sees every request that reached it\. That is a complete record of one thing and no record at all of three others, each of which is where real API incidents tend to live: - Requests that never arrived\. A DNS record pointing at a decommissioned region, a certificate that stopped chaining on one edge node, a routing change at a transit provider — the gateway logs none of it, because the traffic never got there\. APIContext measures it from 125\+ locations and attributes the failure to the responsible hop\. - Responses that are wrong but successful\. Gateway analytics count status codes\. A 200 carrying a renamed field, a changed type, or a dropped security header breaks consumers immediately and looks perfectly healthy in a traffic dashboard\. APIContext validates every response against the published spec and reports the diff\. - The APIs you consume rather than publish\. Your gateway fronts what you expose\. It has nothing to say about the payment provider, identity provider, or partner API your services depend on — and those fail too\. APIContext monitors them continuously and produces SLA evidence you own\. - Coverage where no user has been yet\. Analytics can only describe endpoints somebody called\. Synthetic checks fire on every interval against every endpoint, including the ones with no traffic today and the auth chains nobody exercises until a partner tries at month end\. ### What TIBCO does that APIContext doesn't Publishing and versioning APIs, authentication and authorization enforcement, rate limiting and quotas, request routing and transformation, developer onboarding, and the traffic analytics built on all of it are TIBCO's domain — and APIContext does none of them\. APIContext sits entirely outside the request path: it enforces nothing, terminates nothing, and cannot change how a single production request is handled\. It is a client that calls your API the way your consumers do and reports what happened\. ### How teams run both TIBCO keeps the governance, packaging, and integration logic; APIContext measures the result from the consumer's position and monitors the dependencies underneath it\. In estates with significant legacy behind the gateway, the pairing tends to earn its place by settling attribution arguments: when a partner reports intermittent failures, APIContext shows whether the contract broke, in which regions, and at which hop, rather than leaving the integration team and the platform team to negotiate over gateway logs\. ### How to connect APIContext to TIBCO Export the OpenAPI spec for the APIs you publish through TIBCO and import it into APIContext; each operation becomes a monitored endpoint with its own assertions, authentication chain, and locations\. Then add the partner and backend endpoints your integrations depend on as monitors in their own right\. Nothing is installed in your stack and no integration flow changes\. ## Key facts - APIContext is not a TIBCO competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into TIBCO\. - TIBCO governs and publishes your APIs and integrations\. APIContext verifies the published contract from outside, and monitors the systems those integrations depend on\. - TIBCO's API management and integration stack publishes and governs APIs across estates that are usually long\-lived and heterogeneous — mainframe and packaged systems alongside modern services, with partner traffic on top\. That profile creates two blind spots at once: the gateway sees only what reached it, and the integration layer depends on backend and partner systems it does not monitor\. APIContext calls the published APIs from outside, from 125\+ locations, validates every response against its specification, and monitors the third\-party endpoints the integrations rely on\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; TIBCO: At the gateway — traffic that reached TIBCO and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; TIBCO: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; TIBCO: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; TIBCO: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; TIBCO: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; TIBCO: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; TIBCO: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; TIBCO: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; TIBCO: Analytics and reporting for traffic it processed - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; TIBCO: Yes — core strength, via API management policies and integration flows - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; TIBCO: Yes — developer portal and API packaging - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; TIBCO: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec TIBCO publishes as its monitoring contract; TIBCO: Publishes the spec, and exports its own telemetry alongside ## Primary entities - APIContext - TIBCO - APIContext \+ TIBCO integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a TIBCO competitor? No\. TIBCO publishes, secures, and manages the APIs you expose; APIContext monitors API behavior from outside your infrastructure\. APIContext provides no gateway, no policy enforcement, no rate limiting, and no developer portal, and it sits outside the production request path entirely\. ### TIBCO already has analytics\. Why add APIContext? TIBCO's API analytics measures traffic that reached the gateway\. It cannot see requests that failed before arriving — DNS, TLS, edge, and routing failures — cannot tell you whether a successful response still matches its published specification, and has no visibility into the third\-party APIs your services depend on\. APIContext covers all three\. ### Can APIContext use the OpenAPI spec we publish through TIBCO? Yes\. Import the spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation, then validates live responses against that same contract on every check\. --- # APIContext \+ Zuplo Canonical URL: https://apicontext.com/compare/apicontext-and-zuplo Source: static Description: Not a Zuplo alternative — Zuplo deploys APIs to the edge from an OpenAPI spec; APIContext monitors the spec from 125\+ locations for drift\. ## Summary Zuplo deploys your API to the edge from an OpenAPI spec\. APIContext monitors that same spec from 125\+ locations and reports the moment live behavior diverges from it\. Zuplo is a programmable, OpenAPI\-first gateway deployed to the edge: policies as code, a generated developer portal, and configuration that lives in your repository alongside the spec\. That makes the pairing with APIContext unusually direct — the spec is already the source of truth on both sides\. Zuplo enforces it at the edge; APIContext verifies from outside, as a client, that what the edge returns still matches it\. ## Page sections ### Which platform produces which signal Zuplo is a programmable, OpenAPI\-first gateway deployed to the edge: policies as code, a generated developer portal, and configuration that lives in your repository alongside the spec\. That makes the pairing with APIContext unusually direct — the spec is already the source of truth on both sides\. Zuplo enforces it at the edge; APIContext verifies from outside, as a client, that what the edge returns still matches it\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Zuplo: At the gateway — traffic that reached Zuplo and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Zuplo: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Zuplo: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Zuplo: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Zuplo: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Zuplo: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Zuplo: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Zuplo: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Zuplo: Analytics and logs for requests it served - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Zuplo: Yes — core strength, as programmable policies deployed to the edge - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Zuplo: Yes — generated developer portal from the OpenAPI spec - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Zuplo: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Zuplo publishes as its monitoring contract; Zuplo: Publishes the spec, and exports its own telemetry alongside ### What APIContext adds to Zuplo Zuplo sees every request that reached it\. That is a complete record of one thing and no record at all of three others, each of which is where real API incidents tend to live: - Requests that never arrived\. A DNS record pointing at a decommissioned region, a certificate that stopped chaining on one edge node, a routing change at a transit provider — the gateway logs none of it, because the traffic never got there\. APIContext measures it from 125\+ locations and attributes the failure to the responsible hop\. - Responses that are wrong but successful\. Gateway analytics count status codes\. A 200 carrying a renamed field, a changed type, or a dropped security header breaks consumers immediately and looks perfectly healthy in a traffic dashboard\. APIContext validates every response against the published spec and reports the diff\. - The APIs you consume rather than publish\. Your gateway fronts what you expose\. It has nothing to say about the payment provider, identity provider, or partner API your services depend on — and those fail too\. APIContext monitors them continuously and produces SLA evidence you own\. - Coverage where no user has been yet\. Analytics can only describe endpoints somebody called\. Synthetic checks fire on every interval against every endpoint, including the ones with no traffic today and the auth chains nobody exercises until a partner tries at month end\. ### What Zuplo does that APIContext doesn't Publishing and versioning APIs, authentication and authorization enforcement, rate limiting and quotas, request routing and transformation, developer onboarding, and the traffic analytics built on all of it are Zuplo's domain — and APIContext does none of them\. APIContext sits entirely outside the request path: it enforces nothing, terminates nothing, and cannot change how a single production request is handled\. It is a client that calls your API the way your consumers do and reports what happened\. ### How teams run both Because both sides are spec\-driven, the workflow fits naturally into CI: the OpenAPI document that configures Zuplo is the same one that defines what APIContext asserts, so a spec change and its monitoring update move together instead of drifting\. Edge deployment makes the outside\-in view more valuable rather than less — with policy running at many locations, a regression that only affects some of them is entirely plausible, and only a check running from many locations will find it\. ### How to connect APIContext to Zuplo Point APIContext at the same OpenAPI spec that drives your Zuplo configuration; each operation becomes a monitored endpoint with its own assertions, authentication chain, and locations\. Nothing is installed in your stack and no gateway configuration changes\. Most teams wire it into the same pipeline that deploys Zuplo, so monitoring coverage follows the spec automatically, then export the results over OTLP into whichever observability platform they already run\. ## Key facts - APIContext is not a Zuplo competitor, alternative, or replacement — the two are complementary, and APIContext exports its telemetry into Zuplo\. - Zuplo deploys your API to the edge from an OpenAPI spec\. APIContext monitors that same spec from 125\+ locations and reports the moment live behavior diverges from it\. - Zuplo is a programmable, OpenAPI\-first gateway deployed to the edge: policies as code, a generated developer portal, and configuration that lives in your repository alongside the spec\. That makes the pairing with APIContext unusually direct — the spec is already the source of truth on both sides\. Zuplo enforces it at the edge; APIContext verifies from outside, as a client, that what the edge returns still matches it\. - Vantage point — APIContext: Outside your infrastructure — what a client actually receives; Zuplo: At the gateway — traffic that reached Zuplo and the policy applied to it - Failures in front of the gateway — APIContext: Yes — DNS, TLS, connection, CDN, and routing failures measured per hop from 125\+ locations; Zuplo: Not visible — a request that never arrives is not logged\. APIContext supplies it - API conformance testing — APIContext: Yes — live OpenAPI, FAPI 2\.0, and custom schema validation on every response; Zuplo: Request validation against the spec at the boundary — APIContext verifies the live response - Third\-party APIs you consume — APIContext: Yes — monitors endpoints you depend on but do not publish or front; Zuplo: Out of scope — the gateway fronts what you publish - Multi\-step auth \(FAPI, mTLS, DPoP\) — APIContext: Yes — executes full FAPI 2\.0, mTLS, PAR, DPoP, PKCE, and JARM flows as a real client; Zuplo: Enforces auth policy on inbound requests — APIContext proves the whole chain still completes - CASC quality score — APIContext: Yes — composite score across latency, availability, geography, and conformance; Zuplo: Not collected — APIContext supplies it - MCP / agentic AI monitoring — APIContext: Yes — native MCP session testing, tool schema validation, per\-tool latency; Zuplo: Not collected — APIContext supplies it - Geographic performance — APIContext: Yes — per region, per cloud, from 125\+ locations plus private nodes; Zuplo: Latency as measured at the gateway's own location - Traffic analytics — APIContext: Synthetic checks — constant volume, complete coverage, no dependence on user traffic; Zuplo: Analytics and logs for requests it served - Policy enforcement, rate limiting, and routing — APIContext: Not provided — the gateway supplies it; Zuplo: Yes — core strength, as programmable policies deployed to the edge - Developer portal and spec publishing — APIContext: Not provided — the gateway supplies it; Zuplo: Yes — generated developer portal from the OpenAPI spec - SLA/SLO evidence — APIContext: Native, per\-endpoint, measured from the consumer's position; Zuplo: Usage and error rates for traffic the gateway served - Works together — APIContext: Imports the OpenAPI spec Zuplo publishes as its monitoring contract; Zuplo: Publishes the spec, and exports its own telemetry alongside ## Primary entities - APIContext - Zuplo - APIContext \+ Zuplo integration - complementary API monitoring ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) ## FAQs ### Is APIContext a Zuplo competitor? No\. Zuplo publishes, secures, and manages the APIs you expose; APIContext monitors API behavior from outside your infrastructure\. APIContext provides no gateway, no policy enforcement, no rate limiting, and no developer portal, and it sits outside the production request path entirely\. ### Zuplo already has analytics\. Why add APIContext? Zuplo's analytics measures traffic that reached the gateway\. It cannot see requests that failed before arriving — DNS, TLS, edge, and routing failures — cannot tell you whether a successful response still matches its published specification, and has no visibility into the third\-party APIs your services depend on\. APIContext covers all three\. ### Can APIContext use the OpenAPI spec we publish through Zuplo? Yes\. Import the spec and APIContext generates monitored endpoints from it, with assertions and authentication configured per operation, then validates live responses against that same contract on every check\. --- # APIContext vs\. Checkly Canonical URL: https://apicontext.com/compare/apicontext-vs-checkly Source: static Description: The most trusted banks, fintechs, and regulated enterprises run on APIContext — and it works just as well for less complex use cases\. ## Summary Checkly is a well\-regarded developer\-friendly synthetic monitoring platform for browser and API checks\. APIContext is a synthetic monitoring platform with significantly deeper coverage of API conformance, financial\-grade authentication, AI infrastructure monitoring, and enterprise compliance\. The most trusted regulated industries in the world — global banks, open banking implementations, government APIs, and AI infrastructure operators — run on APIContext\. That means it works exceptionally well across a wider range of use cases, including simpler ones\. ## Page sections ### Comparison Checkly is a well\-regarded developer\-friendly synthetic monitoring platform for browser and API checks\. APIContext is a synthetic monitoring platform with significantly deeper coverage of API conformance, financial\-grade authentication, AI infrastructure monitoring, and enterprise compliance\. The most trusted regulated industries in the world — global banks, open banking implementations, government APIs, and AI infrastructure operators — run on APIContext\. That means it works exceptionally well across a wider range of use cases, including simpler ones\. - Global nodes — APIContext: 125\+ across AWS, GCP, Azure, Akamai; Checkly: ~20 managed locations - Private / on\-premise nodes — APIContext: Yes; Checkly: Yes \(Checkly private locations\) - CASC quality score — APIContext: Yes; Checkly: No - API conformance / schema validation — APIContext: Yes — OpenAPI, FAPI, custom schemas; Checkly: Basic response assertions - OTEL native per\-hop instrumentation — APIContext: Yes — DNS, TLS, connection, transfer; Checkly: OTEL export available - mTLS client certificate authentication — APIContext: Yes — native support; Checkly: Not supported - FAPI 2\.0 / financial\-grade API security — APIContext: Yes — native support; Checkly: Not supported - MCP / agentic AI monitoring — APIContext: Yes — native MCP session and tool validation; Checkly: No - Multi\-step workflows with state — APIContext: Yes — preserves tokens across FAPI\-level auth chains; Checkly: Yes — OAuth and token refresh, not mTLS/FAPI - SLA/SLO management — APIContext: Native, per\-endpoint; Checkly: Via third\-party integrations - CLI / config\-as\-code — APIContext: Yes; Checkly: Yes — Checkly CLI is a strength - Browser monitoring — APIContext: Yes; Checkly: Yes — strong \(Playwright\) - Enterprise compliance reporting — APIContext: Yes; Checkly: Limited ### Where APIContext leads The most significant capability gap is in authentication depth and API intelligence\. Checkly supports basic authentication methods — API keys, environment variables, custom headers, and OAuth token flows\. APIContext goes further: it executes complete mTLS handshakes with client certificates, runs full FAPI 2\.0 flows including Pushed Authorization Requests \(PAR\), DPoP\-bound tokens, and JARM response validation\. These are not edge cases — they are the authentication requirements for open banking APIs, regulated financial services, and government APIs in the UK, EU, Australia, and the US\. APIContext's CASC score, schema conformance engine, and MCP monitoring for AI infrastructure \(tool schema validation, session lifecycle testing, per\-tool latency\) have no equivalent in Checkly\. ### Where Checkly is strong Checkly's developer experience is a genuine strength\. Its CLI, Playwright integration for browser checks, and monitoring\-as\-code workflow are clean and well\-documented\. For teams whose monitoring needs center on browser automation and basic API health checks, Checkly offers a straightforward setup\. The two tools can also coexist: some teams use Checkly for frontend browser flows while using APIContext for API conformance, financial\-grade authentication, and AI infrastructure monitoring\. ### The right tool for any environment If you're building in a regulated industry, operating open banking infrastructure, deploying MCP servers for AI agents, or managing APIs where mTLS and FAPI compliance matter, APIContext provides coverage Checkly is not designed to offer\. And because the world's most demanding API environments run on APIContext, the platform is equally capable for teams with simpler requirements — the depth is there when you need it, invisible when you don't\. ## Key facts - Checkly is a well\-regarded developer\-friendly synthetic monitoring platform for browser and API checks\. APIContext is a synthetic monitoring platform with significantly deeper coverage of API conformance, financial\-grade authentication, AI infrastructure monitoring, and enterprise compliance\. The most trusted regulated industries in the world — global banks, open banking implementations, government APIs, and AI infrastructure operators — run on APIContext\. That means it works exceptionally well across a wider range of use cases, including simpler ones\. - Global nodes — APIContext: 125\+ across AWS, GCP, Azure, Akamai; Checkly: ~20 managed locations - Private / on\-premise nodes — APIContext: Yes; Checkly: Yes \(Checkly private locations\) - CASC quality score — APIContext: Yes; Checkly: No - API conformance / schema validation — APIContext: Yes — OpenAPI, FAPI, custom schemas; Checkly: Basic response assertions - OTEL native per\-hop instrumentation — APIContext: Yes — DNS, TLS, connection, transfer; Checkly: OTEL export available - mTLS client certificate authentication — APIContext: Yes — native support; Checkly: Not supported - FAPI 2\.0 / financial\-grade API security — APIContext: Yes — native support; Checkly: Not supported - MCP / agentic AI monitoring — APIContext: Yes — native MCP session and tool validation; Checkly: No - Multi\-step workflows with state — APIContext: Yes — preserves tokens across FAPI\-level auth chains; Checkly: Yes — OAuth and token refresh, not mTLS/FAPI - SLA/SLO management — APIContext: Native, per\-endpoint; Checkly: Via third\-party integrations - CLI / config\-as\-code — APIContext: Yes; Checkly: Yes — Checkly CLI is a strength - Browser monitoring — APIContext: Yes; Checkly: Yes — strong \(Playwright\) - Enterprise compliance reporting — APIContext: Yes; Checkly: Limited ## Primary entities - APIContext - Checkly - API monitoring comparison ## Audience - API teams - SRE teams - technology leaders - procurement teams ## Primary links - [Contact APIContext](/contact) --- # Contact Canonical URL: https://apicontext.com/contact Source: static Description: Get in touch with the APIContext team\. Learn how we bring best practices and open standards to monitoring digital resilience\. ## Summary Get in touch\. Learn how we bring best practices and open standards to monitoring digital resilience\. ## Page sections ### Get in touch Category: Contact Learn how we bring best practices and open standards to monitoring digital resilience\. - [Support questions](http://apicontext.com/support) ### Trusted by teams running critical API programs RingCentral, Signify, Zempler Bank, DTN, MBIE, Akamai, SoftBank, Idera, First Tech Fed, InComm ## Key facts - Learn how we bring best practices and open standards to monitoring digital resilience\. - Trusted by teams running critical API programs: RingCentral, Signify, Zempler Bank, DTN, MBIE, Akamai, SoftBank, Idera, First Tech Fed, InComm ## Primary entities - APIContext - contact - sales - support ## Audience - prospective customers - API teams ## Primary links - [Support questions](http://apicontext.com/support) --- # AI Monitoring Canonical URL: https://apicontext.com/features/ai-monitoring Source: static Description: From MCP servers to inference providers, APIContext monitors the full AI stack — so you can see which providers are performing, catch schema drift before agents fail, and align every model with the right resilience and data protection boundary\. ## Summary Monitor every layer of your AI infrastructure\. From MCP servers to inference providers, APIContext monitors the full AI stack — so you can see which providers are performing, catch schema drift before agents fail, and align every model with the right resilience and data protection boundary\. ## Stats - Global monitoring locations across the globe - 24/7 continuous AI infrastructure monitoring - OTEL native spans on every call - <5m to start monitoring your AI stack ## Page sections ### Every tool call\. Every inference request\. Verified outside\-in\. Category: End\-to\-End AI Infrastructure Monitoring APIContext monitors both MCP server tool calls and inference provider APIs — validating schema, latency, availability, and contract correctness at every layer of your AI stack\. ### Know which AI providers are actually performing\. Category: Inference provider monitoring APIContext monitors inference provider APIs — OpenAI, Anthropic, Azure OpenAI, Google Gemini, and others — from the same global locations as your users\. See latency, availability, and throughput side by side so you route to the provider that earns it\. - Latency and availability across major inference providers - Mean, p90, p95 or p99 latency per AI model - Instant alerts when a provider degrades ### Simulate how a real AI client calls your tools\. Category: Full payloads APIContext runs full MCP sessions with realistic argument distributions\. This is not a synthetic ping against a health check\. See how your MCP servers work in production\. - Replay captured sessions from real agents - Fuzz tool arguments within schema bounds - Verify tools/list stability across deploys ### Match each AI provider to your product needs\. Category: Provider alignment Not every workload has the same availability requirement or data sensitivity\. APIContext gives you the performance evidence to route high\-stakes workloads to proven providers, keep sensitive prompts within compliant boundaries, and test failover paths before you need them\. - SLO verification per provider and model - Data residency and boundary checks - Failover readiness testing across provider pairs ### Connect MCP servers, endpoints, and APIs end\-to\-end\. Category: Works across multi\-step journeys Connect synthetic journeys across internal and external MCP servers, HTTP endpoints, third parties, and APIs to verify end\-to\-end resilience\. - Monitor both internal and external MCP servers in one flow - OAuth 2\.1, PAT, mTLS, signed HMAC - Run from global nodes or VPC collectors ### Everything you need in production\. Category: Key Features - Safety checks: Flag tools that are unexpected and resources that are out of specification\. - Latency SLOs: Separate SLOs for tools/list, individual tool calls, and inference provider endpoints — p50, p95, and p99\. - Instant alerting: Ping Slack, PagerDuty, Incident\.io, ServiceNow, and more when contracts break or providers degrade\. - Per\-tool uptime: Tool\-level availability rather than just server\-level availability\. - Provider comparison: Side\-by\-side latency and availability across inference providers — so you always know who's performing\. - OTEL native: Every MCP call and inference request emits OpenTelemetry spans — route signal to any compatible backend\. ### Signal ships OTEL\-native into every tool your SRE team already uses - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - MCP server monitoring - Inference provider APIs - Tool contract checks - Multi\-step workflows - Global monitoring locations across the globe - 24/7 continuous AI infrastructure monitoring - OTEL native spans on every call - <5m to start monitoring your AI stack - Safety checks: Flag tools that are unexpected and resources that are out of specification\. - Latency SLOs: Separate SLOs for tools/list, individual tool calls, and inference provider endpoints — p50, p95, and p99\. - Instant alerting: Ping Slack, PagerDuty, Incident\.io, ServiceNow, and more when contracts break or providers degrade\. - Per\-tool uptime: Tool\-level availability rather than just server\-level availability\. - Provider comparison: Side\-by\-side latency and availability across inference providers — so you always know who's performing\. - OTEL native: Every MCP call and inference request emits OpenTelemetry spans — route signal to any compatible backend\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - MCP server monitoring - Inference provider APIs - Tool contract checks - Multi\-step workflows ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start monitoring your AI infrastructure in 3 minutes\.](/contact) ## FAQs ### What is MCP monitoring? MCP monitoring is the continuous outside\-in verification of MCP servers — the tool\-serving endpoints that AI agents call to perform actions\. It involves running synthetic MCP sessions from external locations, exercising initialization, tool discovery, and real tool calls, then validating response schema, latency, and semantic correctness of each result\. ### Why do MCP servers need external monitoring? MCP servers are called by AI models rather than human developers, which means failures are harder to detect through normal operational channels\. A tool that returns a malformed schema or drifts its response format can silently degrade agent behavior — causing incorrect actions or task failures — without triggering conventional alerts\. Continuous external monitoring provides the same reliability guarantees for AI tool infrastructure that SREs expect for production APIs\. ### What does APIContext check on each MCP tool call? For each monitored MCP tool, APIContext verifies the server responds correctly to initialize and tools/list; declared tool schema matches actual response; tool call results match expected schemas and value ranges; latency is within acceptable bounds; and OTEL spans are generated at every step\. Schema drift is flagged with a before/after diff\. ### Does monitoring an MCP server require changes to the server itself? No\. APIContext operates as an external MCP client — no code changes to your MCP server are required\. You provide the server endpoint and authentication credentials; APIContext handles the MCP session lifecycle, tool enumeration, and continuous check execution from global locations\. ### What is AI inference provider monitoring? Inference provider monitoring tracks the latency, availability, and API contract health of the LLM providers your applications call — including OpenAI, Anthropic, Azure OpenAI, Google Gemini, and others\. APIContext runs synthetic inference requests from global locations and surfaces latency \(mean, p90, p95 or p99\), uptime, and schema conformance so you know which providers are performing and can route workloads accordingly\. ### How does APIContext help teams choose between inference providers? APIContext gives you independent, continuous measurement of every provider's performance — not marketing claims or infrequent benchmarks\. You can set SLOs per provider and model, receive alerts when a provider degrades, verify that data stays within required geographic or compliance boundaries, and test failover paths so your applications switch cleanly when a primary provider slips\. --- # Alerting Canonical URL: https://apicontext.com/features/alerting Source: static Description: Get real\-time notifications any time APIContext sees an issue with your applications or service APIs, with thresholds and channels tailored to the teams that need to respond\. ## Summary Know about API issues the moment they happen\. Get real\-time notifications any time APIContext sees an issue with your applications or service APIs, with thresholds and channels tailored to the teams that need to respond\. ## Stats - real\-time notifications for API issues - dozens preconfigured alert triggers - OTEL delivery into observability tools - multi channel escalation paths ## Page sections ### You cannot fix what you do not know about\. Category: Real\-time notifications APIContext detects API health and performance issues, then sends the right context to incident management, application monitoring, data platforms, or any service that supports OpenTelemetry\. ### Notify teams as soon as API behavior changes\. Category: Real\-time notifications Send alerts to incident management tools like ServiceNow, PagerDuty, and BigPanda; application monitoring tools like Datadog, Dynatrace, and New Relic; data platforms like Splunk, Databricks, and Snowflake; or OTEL\-compatible services\. - Alert on health and performance issues immediately - Route to incident, APM, data, and OTEL tools - Include API result context teams can act on ### Tune alerts to the issue, not just the endpoint\. Category: Customizable thresholds Define performance, availability, conformance, response\-code, and other thresholds\. Use preconfigured triggers for latency, uptime, response codes, and more\. - Latency, uptime, response\-code, and conformance triggers - Different thresholds for different teams and services - Reduce noise by tailoring severity and conditions ### Make sure the right team gets the right alert\. Category: Multi\-channel delivery Set multiple thresholds and channels, build escalation paths, and add redundant alerts so issues are visible and accountable\. - Multiple channels and escalation paths - Redundant notifications for critical APIs - Team\-specific routing for accountability ### Everything you need in production\. Category: Key Features - Incident tools: Send API issues to ServiceNow, PagerDuty, BigPanda, and other incident workflows\. - APM integrations: Route health and performance signal into Datadog, Dynatrace, New Relic, and related tools\. - Data platforms: Move alerts and events into Splunk, Databricks, Snowflake, or data pipelines\. - Threshold logic: Use latency, uptime, response code, conformance, and custom triggers\. - Escalation paths: Make accountability explicit with redundant alerts and severity\-based routing\. - OTEL delivery: Deliver alert events to any OpenTelemetry\-compatible system\. ### Alerting routes API issues into incident, APM, data, and OpenTelemetry workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Real\-time alerts - Custom thresholds - Multi\-channel delivery - Escalation paths - OTEL\-ready - real\-time notifications for API issues - dozens preconfigured alert triggers - OTEL delivery into observability tools - multi channel escalation paths - Incident tools: Send API issues to ServiceNow, PagerDuty, BigPanda, and other incident workflows\. - APM integrations: Route health and performance signal into Datadog, Dynatrace, New Relic, and related tools\. - Data platforms: Move alerts and events into Splunk, Databricks, Snowflake, or data pipelines\. - Threshold logic: Use latency, uptime, response code, conformance, and custom triggers\. - Escalation paths: Make accountability explicit with redundant alerts and severity\-based routing\. - OTEL delivery: Deliver alert events to any OpenTelemetry\-compatible system\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Real\-time alerts - Custom thresholds - Multi\-channel delivery - Escalation paths - OTEL\-ready ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start alerting before users notice\.](/contact) --- # API Conformance Canonical URL: https://apicontext.com/features/api-conformance Source: static Description: Compare production and pre\-production APIs against your own schemas, OpenAPI specifications, and open standards so compliance can be proven internally and externally\. ## Summary Demonstrate API compliance continuously\. Compare production and pre\-production APIs against your own schemas, OpenAPI specifications, and open standards so compliance can be proven internally and externally\. ## Stats - OpenAPI schema conformance checks - FAPI open\-standard gap analysis - 24/7 continuous drift monitoring - 100% call\-level audit history ## Page sections ### Real API calls\. Real workflows\. Real results\. Category: Compliance from real traffic shape APIContext builds sequenced workflows that replicate user scenarios, then shows how dependencies, security requirements, reliability, and response details affect compliance\. ### Compare live APIs against the contract they promised\. Category: Verify API compliance Run conformance checks against OpenAPI specifications in production or pre\-production\. Ongoing analysis alerts teams as soon as a deviation against spec is published\. - Compare requests and responses to OpenAPI specs - Validate production and pre\-production environments - Alert immediately when an endpoint drifts from contract ### Show compliance across schema, security, and reliability\. Category: Security and performance posture Schemas capture important requirements, but regulators and internal teams also care about uptime, availability, response time, auth posture, and reliability reporting\. - Consolidated security and performance reporting - Track uptime, availability, and response\-time mandates - Demonstrate posture in one auditable tool ### Compliance at launch is not enough\. Category: Guard against API drift Engineers keep iterating, and small changes accumulate\. Continuous conformance checks catch drift, preserve audit trails, and route remediation tasks to the teams that can fix them\. - Continuous drift detection across releases - Flag and mark individual compliance issues - Send remediation tasks into existing workflows ### Everything you need in production\. Category: Key Features - OpenAPI conformance: Measure whether live APIs match their published schemas and expected behavior\. - Security by design: Track auth, schema, and policy requirements as part of the same conformance posture\. - Performance evidence: Report reliability metrics such as uptime, availability, latency, and response time alongside compliance\. - Workflow validation: Sequence calls to reproduce real user scenarios and dependency chains\. - Audit trails: Review the details of every API call and preserve evidence for internal or external stakeholders\. - Remediation handoff: Send issues and tasks to existing systems and teams for resolution\. ### Conformance evidence flows into security, compliance, DevOps, and reporting workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - OpenAPI checks - API posture - Drift detection - Audit trails - Remediation workflows - OpenAPI schema conformance checks - FAPI open\-standard gap analysis - 24/7 continuous drift monitoring - 100% call\-level audit history - OpenAPI conformance: Measure whether live APIs match their published schemas and expected behavior\. - Security by design: Track auth, schema, and policy requirements as part of the same conformance posture\. - Performance evidence: Report reliability metrics such as uptime, availability, latency, and response time alongside compliance\. - Workflow validation: Sequence calls to reproduce real user scenarios and dependency chains\. - Audit trails: Review the details of every API call and preserve evidence for internal or external stakeholders\. - Remediation handoff: Send issues and tasks to existing systems and teams for resolution\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - OpenAPI checks - API posture - Drift detection - Audit trails - Remediation workflows ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start proving API conformance continuously\.](/contact) ## FAQs ### What is API conformance testing? API conformance testing verifies that a live API's behavior — response schemas, status codes, headers, and error formats — matches its declared specification, such as an OpenAPI document\. It is a complement to API contract testing, but more expansive: it tests not only the technical contract but also the business rules that need to be enforced by the API in context\. An API can be available and returning 200 status while still failing conformance — returning incorrect field types, omitting required headers, or violating documented business logic\. ### How does APIContext detect conformance failures? APIContext compares live API responses against an OpenAPI specification or custom schema on every synthetic check\. When a response deviates — a field type changes, a required property is missing, or a security header is dropped — the platform flags the drift with a diff view showing exactly what changed\. Checks also validate against regulatory security profiles including FAPI 2\.0 for financial APIs\. ### What standards does APIContext support for conformance? APIContext supports OpenAPI 3\.x, custom JSON schemas, and financial\-grade security standards including FAPI 1\.0 Baseline, FAPI 1\.0 Advanced, FAPI 2\.0, and many more\. This covers security and payload requirements applicable to open banking APIs under UK, EU, Australian, and US regulatory frameworks\. ### Can conformance testing run against pre\-production environments? Yes\. APIContext runs conformance checks against production and staging endpoints simultaneously, making it possible to catch regressions before they are promoted to production\. Teams can enforce a never\-ship\-a\-breaking\-change policy by gating deployments on conformance pass rates\. --- # API Monitoring Canonical URL: https://apicontext.com/features/api-monitoring Source: static Description: Continuously test public APIs, internal services, applications, and critical workflows so you can identify problems before customers notice\. ## Summary Monitor all your APIs, all the time\. Continuously test public APIs, internal services, applications, and critical workflows so you can identify problems before customers notice\. ## Stats - 125\+ worldwide monitoring locations - 1m uptime checks available - REST SOAP, GraphQL, and workflows - OTEL webhook and alert integrations ## Page sections ### From one URL to continuous production assurance\. Category: Setup · Monitor · Report Configure API workflows manually, from curl, from Postman Collections, or from OpenAPI specs\. Then schedule checks, capture traces, and alert the right tools when behavior changes\. ### Setting up an API monitor is as simple as entering a URL\. Category: Set up API calls easily Enter a URL, make any HTTP call, test it in the browser, or import existing definitions\. APIContext supports individual calls, sequences, variables, OAuth2, and advanced authentication scenarios\. - Configure manually, from curl, Postman, or OpenAPI - Test calls in the browser before scheduling - Build multi\-step workflows with variables and assertions ### Monitor from the places your users actually are\. Category: Global reach, inside and out Run checks from 125\+ data centers across major cloud providers including AWS, Azure, Google, and Akamai, and add private nodes for APIs behind your firewall\. - 125\+ public monitoring locations - China regions available on request - Cloud\-provider and geography\-aware checks - Private nodes for protected internal APIs ### Verify the APIs that matter most\. Category: Secure calls and conformance Use full OAuth handling, JWTs, mTLS, FAPI validation, and conformance checks against OpenAPI specs, security standards, service objectives, and performance metrics\. - OAuth, JWT, mTLS, and FAPI validation - OpenAPI and security\-standard conformance - Alerts through webhooks, OpenTelemetry, and incident tools ### Everything you need in production\. Category: Key Features - Continuous testing: Run checks all the time against public APIs, internal services, applications, and critical workflows\. - Import existing work: Start from curl, Postman Collections, OpenAPI specs, or manual request configuration\. - Functional workflows: Chain calls with variables, assertions, external dependencies, and auth steps\. - Global monitoring: Monitor simultaneously from 125\+ locations across major cloud providers\. - Secure synthetics: Validate secure APIs with OAuth, JWT, mTLS, FAPI, and token refresh handling\. - Integrated alerts: Send actionable alerts through webhooks, OpenTelemetry, and preconfigured integrations\. ### API monitoring results flow into incident, observability, reporting, and stakeholder workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Setup - Monitor - Report - 125\+ locations - Secure synthetics - 125\+ worldwide monitoring locations - 1m uptime checks available - REST SOAP, GraphQL, and workflows - OTEL webhook and alert integrations - Continuous testing: Run checks all the time against public APIs, internal services, applications, and critical workflows\. - Import existing work: Start from curl, Postman Collections, OpenAPI specs, or manual request configuration\. - Functional workflows: Chain calls with variables, assertions, external dependencies, and auth steps\. - Global monitoring: Monitor simultaneously from 125\+ locations across major cloud providers\. - Secure synthetics: Validate secure APIs with OAuth, JWT, mTLS, FAPI, and token refresh handling\. - Integrated alerts: Send actionable alerts through webhooks, OpenTelemetry, and preconfigured integrations\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Setup - Monitor - Report - 125\+ locations - Secure synthetics ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start monitoring before customers notice\.](/contact) ## FAQs ### What is synthetic API monitoring? Synthetic API monitoring involves sending scripted API requests from external locations on a continuous schedule, independent of real user traffic\. It provides consistent baseline measurements of API availability, latency, and correctness regardless of traffic volume\. Because checks originate outside your infrastructure, they reflect the experience of external callers — including partners, customers, and automated systems — rather than internal system health\. ### How is synthetic monitoring different from APM? APM instruments code inside your stack and measures internal system behavior; it sees the world from inside your infrastructure\. Synthetic monitoring connects from outside as your customers do, continuously running scripted checks whether or not real traffic is present\. This makes it the most reliable source of SLA\-grade availability data and the earliest detection method for edge\-layer failures and geographic performance degradation\. ### How many monitoring locations does APIContext use? APIContext runs synthetic checks from 125\+ nodes across AWS, Google Cloud, Azure, and Akamai networks\. Checks can be scoped globally, regionally, or to a specific subset of locations to mirror the geography of your actual user base or partner network\. ### Can APIContext monitor APIs from inside China? Yes\. APIContext can run tests from 13 regions in China: 12 in mainland China plus Hong Kong\. China monitoring is included in every APIContext plan at no additional cost, and it is available on request\. To turn it on, send a support request through the APIContext support page; after that you configure your China monitors yourself through the UI, API or CLI\. ### Can synthetic monitoring test APIs that require authentication? Yes\. APIContext supports OAuth 2\.0, OIDC, mTLS, DPoP, PKCE, PAR, FAPI 2\.0, and many more\. Multi\-step monitors preserve tokens and session state across dependent requests, enabling end\-to\-end verification of authenticated workflows rather than just unauthenticated health checks\. --- # Reporting & Analysis Canonical URL: https://apicontext.com/features/api-reporting-analysis Source: static Description: Identify API issues quickly, explain what changed, and keep engineers, product teams, executives, and regulators working from the same trusted data\. ## Summary Turn every API call into board\-ready signal\. Identify API issues quickly, explain what changed, and keep engineers, product teams, executives, and regulators working from the same trusted data\. ## Stats - p99 latency percentiles, along with p90, p95 and mean - 100% raw result and trace access - OTEL portable telemetry - 24/7 continuous compliance reporting ## Page sections ### From slow calls to service\-level trends\. Explained in context\. Category: A view for every stakeholder APIContext connects real synthetic call results, trace timing, conformance outcomes, and alert history into reporting that works for front\-line engineers and the board room\. And the light data volume means you can keep your synthetic history forever in your system of record\. ### Understand the metrics behind resilience\. Category: KPIs that matter Track performance, uptime, latency, p95, p99, conformance, spec violations, and more from the same consistent calls in every region\. In the monitor statistics view, choose mean, p90, p95 or p99 latency\. Reports can also be shared as an embeddable public status frame\. - Performance, uptime, and latency reporting - Conformance and specification violation trends - Shared source of truth for engineering and leadership - [Public status reports](https://docs.apicontext.com/guides/analytics/public-status-reports) ### See whether you are meeting your SLOs at a glance\. Category: Service level trends Compare time periods, detect downtime patterns, and correlate deployments with service\-impacting events so teams can explain what changed\. - Availability and downtime comparisons - Latency trends by mean, p90, p95 or p99 - Deployment markers for production changes ### Break every API call into the steps that created delay\. Category: Latency reporting Generate latency reports for DNS, handshake, connect, processing, transfer, and validation\. Compare results across location, cloud, and network path\. - DNS, TLS, connect, processing, and transfer timings - Location and cloud comparisons - Bottleneck detection from real\-world calls ### Everything you need in production\. Category: Key Features - Real API calls: Report on GET, PUT, POST, DELETE, and any HTTP request type from real synthetic checks\. - Validate responses: Set conditions, override expected return codes, and track variables across tests and environments\. - Alerting from data: Configure alerts from different sources, events, regions, and API call outcomes\. - Automated reports: Generate compliance, resilience, and stakeholder reports without manual spreadsheet work\. - Independent reporting: Use trusted metrics from an outside\-in source with real\-world network data\. - Full data access: Send result, trace, and analytics telemetry to the platform of your choice with OpenTelemetry out of the box\. ### Export reporting data into observability, BI, incident, and stakeholder workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - KPI dashboards - Latency waterfalls - Automated reports - p99 latency percentiles, along with p90, p95 and mean - 100% raw result and trace access - OTEL portable telemetry - 24/7 continuous compliance reporting - Real API calls: Report on GET, PUT, POST, DELETE, and any HTTP request type from real synthetic checks\. - Validate responses: Set conditions, override expected return codes, and track variables across tests and environments\. - Alerting from data: Configure alerts from different sources, events, regions, and API call outcomes\. - Automated reports: Generate compliance, resilience, and stakeholder reports without manual spreadsheet work\. - Independent reporting: Use trusted metrics from an outside\-in source with real\-world network data\. - Full data access: Send result, trace, and analytics telemetry to the platform of your choice with OpenTelemetry out of the box\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - KPI dashboards - Latency waterfalls - Automated reports ## Audience - API teams - SRE teams - platform teams ## Primary links - [Give every team the same API truth\.](/contact) --- # API Security Canonical URL: https://apicontext.com/features/api-security Source: static Description: Security is not a one\-time design check\. APIContext runs real calls against production security flows to verify OAuth, FAPI, JWT, MTLS, scopes, tokens, and protected resources\. ## Summary Runtime security validation for production APIs\. Security is not a one\-time design check\. APIContext runs real calls against production security flows to verify OAuth, FAPI, JWT, MTLS, scopes, tokens, and protected resources\. ## Stats - 24/7 security flow checks - FAPI runtime validation - JWT signing support - audit security evidence ## Page sections ### Make real functional security calls from outside your stack\. Category: Secured Verify authentication, authorization, and secure API behavior the way customers and partners experience it in production\. - Positive and negative security checks - OAuth, FAPI, JWT, and MTLS support - Encrypted key and certificate handling ### Shift security assurance into production runtime\. Category: Runtime metrics Traditional shift\-left checks are essential, but API teams also need production assurance that security functions continue to work\. - Token refresh and scope behavior checks - Protected\-resource verification - Production alerting for unexpected exposure ### Generate evidence for risk and compliance teams\. Category: Auditability Create audit traces that prove security controls are functioning for internal assessors, external stakeholders, and regulators\. - External end\-to\-end monitoring from the regions and cloud data centers stakeholders use - Accurate 24/7 data based on production scenarios customers depend on - SLO, SLA, security, and quality reporting that different teams can trust - Integrations with observability, incident, reporting, and DevOps workflows ## Key facts - Shift\-right security - OAuth and FAPI - JWT and MTLS - Audit traces - Production validation - 24/7 security flow checks - FAPI runtime validation - JWT signing support - audit security evidence - Make real functional security calls from outside your stack\.: Verify authentication, authorization, and secure API behavior the way customers and partners experience it in production\. - Shift security assurance into production runtime\.: Traditional shift\-left checks are essential, but API teams also need production assurance that security functions continue to work\. - Generate evidence for risk and compliance teams\.: Create audit traces that prove security controls are functioning for internal assessors, external stakeholders, and regulators\. - APIContext helped us increase visibility of our APIs performance and significantly improved awareness\. ## Testimonial > APIContext helped us increase visibility of our APIs performance and significantly improved awareness\. — Val Novikov, CTO, Fispan ## Primary entities - APIContext - Solutions - API monitoring - Shift\-right security - OAuth and FAPI - JWT and MTLS - Audit traces - Production validation ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Right\-shift API security monitoring\.](/contact) --- # API SLA and SLO Management Canonical URL: https://apicontext.com/features/api-sla-and-slo-management Source: static Description: Set, measure, and report on SLOs and SLAs across your own APIs and third\-party suppliers\. Independent monitoring with detailed attribution shows the right team exactly what to fix\. ## Summary Independent service\-level assurance for every API you depend on\. Set, measure, and report on SLOs and SLAs across your own APIs and third\-party suppliers\. Independent monitoring with detailed attribution shows the right team exactly what to fix\. ## Stats - 30d rolling SLO windows - 1\.2M synthetic calls per SLO - 125\+ external monitoring locations - API supplier and internal targets ## Page sections ### Know whether service levels are being met before the contract is in dispute\. Category: Define · Measure · Prove APIContext runs production\-grade synthetic checks against the APIs and suppliers behind critical journeys, then rolls the evidence into targets, burn rates, attribution, reports, and alerts\. ### Setting SLOs is easy\. Knowing whether you are meeting them is the hard part\. Category: Set and test SLOs Define availability, latency, error\-rate, pass\-rate, and conformance objectives per route, region, supplier, or workflow\. APIContext continuously tests those targets from the places customers and partners actually use\. - 30\-day rolling windows per route, region, and supplier - Fast and slow burn\-rate alerts before budgets are exhausted - Configuration as code, reviewed alongside the APIs it covers ### Separate vendor, network, and application failures\. Category: Take the guesswork out When a critical journey slows down, APIContext shows whether the issue sits in your application, the network, a CDN, a supplier, or a chain of dependencies\. Teams get evidence instead of a long triage argument\. - Continuous testing across complicated multi\-supplier workflows - Payload, trace, latency, and status evidence attached to each issue - Ownership context for customer support, operations, and vendor managers ### Share service\-level evidence that holds up\. Category: Ready for external reporting Compliance officers need defensible numbers\. Customer support needs to know before customers call\. Vendor managers need breach evidence for credit claims and renewal conversations\. APIContext gives each team the same independent record\. - Status pages, stakeholder reports, and automated email summaries - Contractual SLA evidence for suppliers and customer\-facing services - Compliance\-ready dashboards for auditors, regulators, and leadership ### Everything you need in production\. Category: Key Features - Burn\-rate alerting: Fast and slow burn\-rate alerts based on service\-level budgets, not isolated blips\. - Independent measurement: External synthetic calls from global locations create numbers auditors, customers, and suppliers can trust\. - Multi\-supplier workflows: Trace service levels across chains of APIs and attribute degradation to the segment that caused it\. - Configuration as code: Keep SLO targets and thresholds versioned with the contracts and APIs they govern\. - SLA evidence: Generate defensible reports for customer commitments, supplier disputes, credit claims, and reviews\. - Service\-level trends: Track uptime, availability, latency, error rates, and pass rates against agreed objectives\. ### Independent SLO and SLA data flows into reporting, status, compliance, and incident tools - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Independent monitoring - Burn\-rate alerting - Vendor attribution - Regulator\-ready reports - Configuration as code - 30d rolling SLO windows - 1\.2M synthetic calls per SLO - 125\+ external monitoring locations - API supplier and internal targets - Burn\-rate alerting: Fast and slow burn\-rate alerts based on service\-level budgets, not isolated blips\. - Independent measurement: External synthetic calls from global locations create numbers auditors, customers, and suppliers can trust\. - Multi\-supplier workflows: Trace service levels across chains of APIs and attribute degradation to the segment that caused it\. - Configuration as code: Keep SLO targets and thresholds versioned with the contracts and APIs they govern\. - SLA evidence: Generate defensible reports for customer commitments, supplier disputes, credit claims, and reviews\. - Service\-level trends: Track uptime, availability, latency, error rates, and pass rates against agreed objectives\. ## Primary entities - APIContext - SLO & SLA Management - API monitoring - OpenTelemetry - Independent monitoring - Burn\-rate alerting - Vendor attribution - Regulator\-ready reports - Configuration as code ## Audience - API teams - SRE teams - platform teams ## Primary links - [Are your service levels holding up?](/contact) --- # Build to Specifications Canonical URL: https://apicontext.com/features/build-to-specifications Source: static Description: Bridge the gap between your API’s intended functionality and real\-world behavior by continuously comparing production endpoints with their OpenAPI Specification definitions\. ## Summary Keep production APIs aligned with their OpenAPI specs\. Bridge the gap between your API’s intended functionality and real\-world behavior by continuously comparing production endpoints with their OpenAPI Specification definitions\. ## Stats - OAS production endpoint comparisons - 24/7 continuous conformance checks - full request and response validation - teams remediation routed by owner ## Page sections ### Catch contract drift every time code reaches production\. Category: Automated comparisons APIContext compares live endpoints to their architected OpenAPI specification and alerts teams to discrepancies in request format, response shape, status code, auth, and more\. ### Continuously compare production APIs to OpenAPI\. Category: Automated comparisons Every time teams push new code, APIContext can run conformance checks and alert on changes against the architected specification\. - Compare live endpoints to OAS definitions - Run checks continuously after production changes - Alert when behavior diverges from the spec ### Validate every part of the API contract\. Category: Granular validation Check request and response formats, HTTP status codes, authentication requirements, response definitions, and more so teams can see exactly what changed\. - Request and response format validation - HTTP status code and auth requirement checks - Detailed response\-definition comparison ### Turn variances into accountable remediation\. Category: Manage errors easily Variances are highlighted for review\. Alert or promote issues to the right teams so stakeholders understand tradeoffs, risks, and ownership\. - Highlight variances for quick review - Promote issues to remediation workflows - Align stakeholders around risk and ownership ### Everything you need in production\. Category: Key Features - Protect data and users: Use OpenAPI specifications as guardrails for production API behavior\. - Production reality: Compare intended functionality against how live endpoints actually respond\. - Spec\-driven checks: Use OpenAPI definitions to drive repeatable validation\. - Variance review: See discrepancies clearly, with the context needed for review\. - Change alerts: Notify teams when new production code changes behavior against the spec\. - Stakeholder alignment: Bring application owners, architects, and business teams together around the same evidence\. ### Specification drift evidence routes into engineering, architecture, and remediation workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - OpenAPI comparison - Production checks - Granular validation - Variance review - Remediation routing - OAS production endpoint comparisons - 24/7 continuous conformance checks - full request and response validation - teams remediation routed by owner - Protect data and users: Use OpenAPI specifications as guardrails for production API behavior\. - Production reality: Compare intended functionality against how live endpoints actually respond\. - Spec\-driven checks: Use OpenAPI definitions to drive repeatable validation\. - Variance review: See discrepancies clearly, with the context needed for review\. - Change alerts: Notify teams when new production code changes behavior against the spec\. - Stakeholder alignment: Bring application owners, architects, and business teams together around the same evidence\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - OpenAPI comparison - Production checks - Granular validation - Variance review - Remediation routing ## Audience - API teams - SRE teams - platform teams ## Primary links - [Build and run APIs to specification\.](/contact) --- # Business Rules Canonical URL: https://apicontext.com/features/business-rules Source: static Description: Your APIs need to deliver the correct data in every scenario\. Catch misconfigurations and align applications with internal and external business rules so your API stays the source of truth\. ## Summary Make sure your APIs return the right answer\. Your APIs need to deliver the correct data in every scenario\. Catch misconfigurations and align applications with internal and external business rules so your API stays the source of truth\. ## Stats - 0 pricing errors tolerated - 100% scenario\-level rule coverage - minutes to triage a variance - teams alerted by ownership ## Page sections ### Validate business logic, not just status codes\. Category: Rules that match your business APIContext checks whether APIs return the right information for real scenarios: pricing, eligibility, compliance, routing, regional behavior, and other rules unique to your business\. ### Define the rules your APIs must always follow\. Category: Unique to your business Every business has its own policies, products, prices, regulatory requirements, and edge cases\. Business rule checks make sure APIs deliver the right information, not merely a successful response\. - Validate pricing, eligibility, and policy outcomes - Catch business logic violations before customers do - Align API behavior with internal and external rules ### Turn every variance into a fast triage decision\. Category: Fix misconfigurations easily When APIContext finds a variance, teams can review the evidence, decide whether to update the API, change the application, or revise the rule, then get the right owner involved\. - Review detailed conformance evidence - Classify API, application, or rule changes - Route the work to the team that owns the fix ### Alert the right team to conformance issues \- not SRE Category: Right alert, right team Business rule conformance issues are not generic application monitoring noise\. Deliver alerts at the right cadence to compliance, architecture, product, or engineering teams\. - Alert by rule ownership and severity - Control cadence so teams are not overwhelmed - Separate compliance issues from infrastructure incidents ### Everything you need in production\. Category: Key Features - Custom rule checks: Assert outcomes that match your pricing, product, compliance, and policy requirements\. - Scenario coverage: Run checks across the edge cases where business logic failures usually hide\. - Detailed evidence: Review request, response, assertion, and variance details before choosing the fix\. - Ownership routing: Send API, application, and rule issues to the teams that actually own them\. - Targeted alerts: Notify compliance and architecture teams without flooding application monitoring queues\. - Rule audit trail: Keep a history of failures, accepted variances, and remediation decisions\. ### Business\-rule evidence routes cleanly into compliance, product, architecture, and engineering workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Custom rules - Scenario checks - Compliance workflows - 0 pricing errors tolerated - 100% scenario\-level rule coverage - minutes to triage a variance - teams alerted by ownership - Custom rule checks: Assert outcomes that match your pricing, product, compliance, and policy requirements\. - Scenario coverage: Run checks across the edge cases where business logic failures usually hide\. - Detailed evidence: Review request, response, assertion, and variance details before choosing the fix\. - Ownership routing: Send API, application, and rule issues to the teams that actually own them\. - Targeted alerts: Notify compliance and architecture teams without flooding application monitoring queues\. - Rule audit trail: Keep a history of failures, accepted variances, and remediation decisions\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Custom rules - Scenario checks - Compliance workflows ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start validating the answers your APIs provide\.](/contact) --- # CLI Canonical URL: https://apicontext.com/features/cli Source: static Description: Update monitoring, manage users, build API call workflows, and keep applications monitored as fast as your team can type\. ## Summary Manage your monitoring as code\. Update monitoring, manage users, build API call workflows, and keep applications monitored as fast as your team can type\. ## Stats - CLI direct project control - 0 call limits for complex workflows - brew Homebrew, winget, or release binaries - RBAC user and role operations ## Page sections ### Keep active projects in sync from your terminal\. Category: Build and monitor with the same tools The APIContext CLI gives developers a direct connection to API monitoring, so local changes can be pushed into active projects without leaving the development workflow\. ### Build and update API monitoring from the CLI\. Category: Developer\-native monitoring Install with Homebrew \(brew install apimetrics/tap/apimetrics\), winget \(winget install APIContext\.APImetricsCLI\), or a GitHub release binary for macOS, Linux, and Windows\. Manage schedules, API call structures, projects, and alerting directly through the command line or with your favorite AI agent harness\. - Install with Homebrew, winget, or a release binary - Make updates locally - Push changes into active projects ### Keep multi\-call journeys updated easily\. Category: Advanced workflows Critical application workflows often take 3 to 10 API calls\. Use call\-builder and workflow operations from the CLI to keep monitoring aligned with the journeys your users depend on\. - Build multi\-call workflows - Manage API call sequences - Keep critical journeys synchronized ### Manage projects, users, and access from one place\. Category: Project controls Manage user access, role management, view/edit operations, new projects, and existing projects with granular controls\. For CI and other headless runs, sign in with a service account \(\-\-service\-account or APIMETRICS\_SERVICE\_ACCOUNT\) and name the project with \-\-project\-id\. - Manage users and roles - Deploy and update projects - Analyze workflow issues and root causes ### Everything you need in production\. Category: Key Features - Monitoring as code: Build and update API monitoring with developer tooling\. - Workflow operations: Create and manage multi\-step API workflows directly from the terminal\. - Alerting controls: Manage alerting configuration alongside API call structures and schedules\. - Access management: Control users, roles, and permissions through CLI operations\. - Fast updates: Push local monitoring changes into active projects quickly\. - AI agent skills: Run apimetrics skills install \-\-claude\-skills to add eight operational skills to Claude Code, or use \-\-claude\-code or \-\-codex\. Other agents can read the AGENTS\.md file\. ### CLI workflows fit into developer terminals, project automation, and operational control loops - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - apimetrics CLI - Homebrew, winget, or release binaries - AI agent skills - Service accounts for CI - Project controls - CLI direct project control - 0 call limits for complex workflows - brew Homebrew, winget, or release binaries - RBAC user and role operations - Monitoring as code: Build and update API monitoring with developer tooling\. - Workflow operations: Create and manage multi\-step API workflows directly from the terminal\. - Alerting controls: Manage alerting configuration alongside API call structures and schedules\. - Access management: Control users, roles, and permissions through CLI operations\. - Fast updates: Push local monitoring changes into active projects quickly\. - AI agent skills: Run apimetrics skills install \-\-claude\-skills to add eight operational skills to Claude Code, or use \-\-claude\-code or \-\-codex\. Other agents can read the AGENTS\.md file\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - apimetrics CLI - Homebrew, winget, or release binaries - AI agent skills - Service accounts for CI - Project controls ## Audience - API teams - SRE teams - platform teams ## Primary links - [Manage API monitoring from the terminal\.](/contact) --- # Configuration as Code Canonical URL: https://apicontext.com/features/configuration-as-code Source: static Description: Define, manage, version, and update API monitoring configurations as part of your development workflow, using files your teams can review and change together\. ## Summary Maintain monitoring in human\-readable YAML or JSON\. Define, manage, version, and update API monitoring configurations as part of your development workflow, using files your teams can review and change together\. ## Stats - Git ready for version control - YAML human\-readable monitoring - CI/CD toolchain friendly - full program configuration ## Page sections ### Change monitoring with every API change\. Category: Make monitoring part of development Configuration as Code lets developers edit application monitoring as part of normal development, keeping checks, schedules, workflows, and alerting aligned with production APIs\. ### Write monitoring in YAML or JSON\. Category: Human\-readable config Simplify API monitoring and resilience by letting developers define, manage, and update project configurations in files that are easy to read and review\. - Define monitoring as YAML or JSON - Keep configuration readable - Review monitoring changes like code ### Track, roll back, and collaborate on monitoring changes\. Category: Version control Configuration is ready for Git or any version control system, enabling change tracking, rollbacks, collaborative updates, and repeatable project management\. - Track monitoring changes in Git - Roll back when needed - Collaborate across development teams ### Manage calls, workflows, schedules, alerts, projects, and users\. Category: Full monitoring program Update API call configuration, workflows, schedules, alerting thresholds, projects, and users from a consistent configuration model\. - Update API calls and workflows - Manage schedules and alert thresholds - Configure projects and users ### Everything you need in production\. Category: Key Features - Developer workflow: Bring monitoring into the same process as API development\. - Readable files: Use YAML or JSON that teams can inspect and review\. - Project\-wide config: Cover API calls, workflows, schedules, alerting, projects, and users\. - Consistency: Keep monitoring consistent across environments and teams\. - CI/CD friendly: Integrate monitoring changes into existing toolchains\. - Change visibility: Track rollbacks, reviews, and collaborative updates in version control\. ### Configuration as Code fits Git, CI/CD, project automation, and developer review workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - YAML - JSON - Version control - CI/CD - Project export - Git ready for version control - YAML human\-readable monitoring - CI/CD toolchain friendly - full program configuration - Developer workflow: Bring monitoring into the same process as API development\. - Readable files: Use YAML or JSON that teams can inspect and review\. - Project\-wide config: Cover API calls, workflows, schedules, alerting, projects, and users\. - Consistency: Keep monitoring consistent across environments and teams\. - CI/CD friendly: Integrate monitoring changes into existing toolchains\. - Change visibility: Track rollbacks, reviews, and collaborative updates in version control\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - YAML - JSON - Version control - CI/CD - Project export ## Audience - API teams - SRE teams - platform teams ## Primary links - [Put API monitoring under version control\.](/contact) --- # Network Monitoring Canonical URL: https://apicontext.com/features/network-monitoring Source: static Description: Track performance across major cloud providers, public locations, and private nodes so teams can spot DNS, handshake, CDN, and hosting issues from the places users and partners actually operate\. ## Summary See every cloud, region, and network path before customers notice an issue\. Track performance across major cloud providers, public locations, and private nodes so teams can spot DNS, handshake, CDN, and hosting issues from the places users and partners actually operate\. ## Stats - 125\+ public monitoring locations - 5\+ major cloud providers covered - 30\+ data points per network call - 24/7 network path checks ## Page sections ### Monitor from the locations your users depend on\. Category: Global nodes Run API and network checks from public cloud data centers around the world, from private networks, and from your own VMs to understand where latency, DNS, handshakes, CDN handoffs, or hosting choices are changing the customer experience\. ### Monitor from the cloud data centers partners and users use\. Category: Cross\-cloud visibility Run checks across major public cloud providers around the world, including China\. Then compare performance by region, provider, and path\. - Public locations across major cloud providers - Regional and provider\-level performance comparison - Fast setup for endpoints and OpenAPI imports ### Deploy private nodes behind the firewall\. Category: Inside your network Measure internal network performance and monitor private services without exposing sensitive systems to public networks\. - Outbound\-only private node monitoring - Internal API and service checks - Deploy on cloud, hybrid, on\-prem, or your own VMs ### Find DNS, handshake, CDN, and routing issues quickly\. Category: Network diagnostics Break down each API call into the network timings teams need to isolate misconfigurations, provider issues, and regional bottlenecks\. - DNS, connection, TLS, and transfer timing - CDN and service\-provider handoff evidence - Benchmark against peer services and regions ### Everything you need in production\. Category: Key Features - Public coverage: Monitor from public locations on the cloud and data centers your stakeholders use\. - Private nodes: Run the same network checks inside private environments and behind firewalls\. - Cloud comparison: Compare providers, regions, and hosting locations with the same checks\. - Detailed timings: Inspect DNS, handshake, connection, CDN, and API response behavior\. - Fast issue isolation: See whether the problem is your API, a network path, or a broader provider issue\. - Actionable alerts: Route network and API issues to the teams that own response\. ### Network telemetry supports public cloud, private nodes, dashboards, and alerting workflows - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - 125\+ public locations - Private nodes - Cloud provider views - 125\+ public monitoring locations - 5\+ major cloud providers covered - 30\+ data points per network call - 24/7 network path checks - Public coverage: Monitor from public locations on the cloud and data centers your stakeholders use\. - Private nodes: Run the same network checks inside private environments and behind firewalls\. - Cloud comparison: Compare providers, regions, and hosting locations with the same checks\. - Detailed timings: Inspect DNS, handshake, connection, CDN, and API response behavior\. - Fast issue isolation: See whether the problem is your API, a network path, or a broader provider issue\. - Actionable alerts: Route network and API issues to the teams that own response\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - 125\+ public locations - Private nodes - Cloud provider views ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start monitoring the network paths your APIs rely on\.](/contact) --- # Private Nodes Canonical URL: https://apicontext.com/features/private-nodes Source: static Description: Deploy lightweight APIContext nodes behind your firewall to test internal APIs, private services, and employee\-facing workflows without exposing sensitive systems to the public internet\. ## Summary Monitor APIs and apps inside your network\. Deploy lightweight APIContext nodes behind your firewall to test internal APIs, private services, and employee\-facing workflows without exposing sensitive systems to the public internet\. ## Stats - <5m to deploy the first node - 0 inbound firewall rules required - VPC cloud, hybrid, or on\-prem - OTEL traces from inside the boundary ## Page sections ### Run outside\-in checks from inside your own infrastructure\. Category: Inside the boundary Private nodes execute the same synthetic journeys as cloud nodes, but originate from your network so internal APIs, staging environments, and restricted applications can be tested safely\. ### Drop a lightweight runner into any private environment\. Category: Container\-native deployment Run nodes as Docker containers, scheduled jobs, or service workloads in your VPC, data center, Kubernetes cluster, or secure network segment\. - Docker\-first deployment - Kubernetes and VM friendly - Outbound connection to APIContext - No public exposure of internal endpoints ### Test business\-critical APIs customers and employees depend on\. Category: Behind\-firewall monitoring Validate private applications, partner integrations, internal APIs, and remote employee workflows from the places where they actually run\. - Internal API availability - Employee workflow checks - Partner and branch\-office perspectives - Private DNS and network path validation ### Keep sensitive calls and credentials under your control\. Category: Data control Nodes run inside your infrastructure using your enterprise credentials, secrets, and network policies\. APIContext receives telemetry, not unrestricted access to your private services\. - Use your identity and secret stores - Control who calls which services - Keep request paths inside your boundary - Send clean OTEL signal to your observability stack ### Everything you need in production\. Category: Key Features - Outbound\-only: Nodes connect out to APIContext, so private services do not need inbound public access\. - Credential control: Use your own enterprise auth, vault, and network policy for private checks\. - Hybrid coverage: Combine public cloud nodes with private nodes for a complete customer\-to\-origin picture\. - Internal synthetics: Run the same API, browser, and workflow checks against internal\-only systems\. - Topology\-aware: Separate cloud, edge, origin, and private\-network failures in a single journey\. - OTEL\-native: Forward traces, logs, metrics, and events from private runs to your existing tools\. ### Private\-node telemetry flows into the same tools your teams already use - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Docker deploy - Outbound\-only - Private APIs - Internal workflows - Enterprise credentials - <5m to deploy the first node - 0 inbound firewall rules required - VPC cloud, hybrid, or on\-prem - OTEL traces from inside the boundary - Outbound\-only: Nodes connect out to APIContext, so private services do not need inbound public access\. - Credential control: Use your own enterprise auth, vault, and network policy for private checks\. - Hybrid coverage: Combine public cloud nodes with private nodes for a complete customer\-to\-origin picture\. - Internal synthetics: Run the same API, browser, and workflow checks against internal\-only systems\. - Topology\-aware: Separate cloud, edge, origin, and private\-network failures in a single journey\. - OTEL\-native: Forward traces, logs, metrics, and events from private runs to your existing tools\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Docker deploy - Outbound\-only - Private APIs - Internal workflows - Enterprise credentials ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start monitoring behind the firewall\.](/contact) --- # Website Monitoring Canonical URL: https://apicontext.com/features/website-monitoring Source: static Description: Real\-browser monitors test your website from locations across the globe in Chromium, Firefox, and WebKit \(Safari\)\. Each run loads the page, measures how it renders, and checks the result, so you are the first to know when a third\-party script takes down checkout or a page goes blank\. ## Summary Know the moment your website breaks for a real customer\. Real\-browser monitors test your website from locations across the globe in Chromium, Firefox, and WebKit \(Safari\)\. Each run loads the page, measures how it renders, and checks the result, so you are the first to know when a third\-party script takes down checkout or a page goes blank\. ## Stats - Global monitoring locations across the globe - 24/7 continuous website monitoring - 3 engines: Chromium, Firefox, WebKit - CWV Core Web Vitals tracked ## Page sections ### Every request\. Every render\. Captured as OTEL\. Category: See one run A website check is not a black box\. Every span, from first\-mile DNS to edge TLS, origin backend, and client render, is a verifiable hop\. ### Set up fast\. Start from a URL\. Category: Minutes to live monitors Start from a URL and ship monitors in minutes, not a long scripting project\. Choose the browser and viewport, set your performance budgets, and schedule the check alongside your API monitors and workflows\. - Add a URL, set assertions and budgets, and schedule without scripts - Fail a run on a non\-2xx response, a console error, or a blown LCP, CLS, or FCP budget - Schedule it with your API monitors and workflows - Private nodes for WAF\-protected and pre\-production environments ### Field\-grade vitals from every region, continuously\. Category: Core Web Vitals LCP, TTFB, and FCP are tracked on every run, per region\. Know when your site or a third party you rely on impacts your website performance\. - Key AEO / GEO / SEO metrics tracked continuously - Alert on any change that falls out of expected ranges - Share results across your existing tooling to correlate environment changes ### Route the right context to the right team, fast\. Category: From alert to root cause When something breaks, get alerted immediately via webhooks, OpenTelemetry, or your existing observability toolchain, with a context\-rich payload and full page\-level waterfall to investigate\. - Webhook and OTEL\-compatible alert delivery - Full page\-level waterfall for investigation - Route to the right team with specific incident context - Share reports with stakeholders seamlessly ### Everything you need in production\. Category: Key Features - Core Web Vitals: Track LCP, TTFB, and other key metrics on every run, per region\. - Global coverage: Test from locations across the globe, on the networks your customers use\. - Private nodes: Run the same browser monitors inside your network against staging or WAF\-protected apps\. - Page\-level waterfalls: Full waterfall and OTEL trace on every run, ready for your APM\. - Console errors: Fail a run on any JavaScript console error, so a broken script never goes unnoticed\. - Smart alerts: Alert on consecutive failures from multiple regions, not noisy single\-run flakes\. ### Stream website monitoring results into your APM, SIEM, or data lake - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Chromium, Firefox & WebKit - Core Web Vitals - Visual regression - HAR capture - OTEL traces - Global monitoring locations across the globe - 24/7 continuous website monitoring - 3 engines: Chromium, Firefox, WebKit - CWV Core Web Vitals tracked - Core Web Vitals: Track LCP, TTFB, and other key metrics on every run, per region\. - Global coverage: Test from locations across the globe, on the networks your customers use\. - Private nodes: Run the same browser monitors inside your network against staging or WAF\-protected apps\. - Page\-level waterfalls: Full waterfall and OTEL trace on every run, ready for your APM\. - Console errors: Fail a run on any JavaScript console error, so a broken script never goes unnoticed\. - Smart alerts: Alert on consecutive failures from multiple regions, not noisy single\-run flakes\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Chromium, Firefox & WebKit - Core Web Vitals - Visual regression - HAR capture - OTEL traces ## Audience - API teams - SRE teams - platform teams ## Primary links - [Get your first website monitor running today\.](/contact) --- # Workflows and Traces \(feature\) Canonical URL: https://apicontext.com/features/workflows-and-traces Source: static Description: Traverse AI infrastructure, browsers, and APIs with reusable workflows, then record the full details of every step for review, investigation, and OpenTelemetry export\. ## Summary Build reusable workflows for high\-value journeys\. Traverse AI infrastructure, browsers, and APIs with reusable workflows, then record the full details of every step for review, investigation, and OpenTelemetry export\. ## Stats - 3 surfaces: AI, browser, API - 100% step\-level trace detail - OTEL review or export - 24/7 synthetic journey monitoring ## Page sections ### From authentication to downstream API dependencies\. Captured as a trace\. Category: Every event in the journey APIContext records the full journey, including each call, transition, dependency, and result, so teams can investigate failures without storing every packet of production traffic\. ### Build complex journeys across the systems users rely on\. Category: Advanced workflows Complex authentication and authorization flows? AI requests that call APIs? Browser interactions with API dependencies? Any journey that matters to you is one APIContext can verify\. - Reusable workflow steps across APIs, browsers, and AI infrastructure - Complex auth, authorization, and dependency handling - High\-value journey validation from the outside in ### See the entire path each workflow took\. Category: Full call details Every call APIContext makes is fully documented, including the route, timings, result details, and step outcomes, so teams have the information they need to investigate\. - Trace every step and segment of a workflow - Capture result details for each call - Filter the journey to find the broken dependency quickly ### Keep focused traces without drowning in traffic data\. Category: Only store what you need Storing all API traffic can be prohibitively expensive\. APIContext stores the traces for the synthetic calls it makes, reducing trace volume while preserving the journeys that matter\. - Store traces for monitored synthetic journeys - Reduce noisy production trace volume - Review or export focused evidence through OpenTelemetry ### Everything you need in production\. Category: Key Features - Reusable workflows: Build once, then reuse journey steps for critical production checks\. - AI infrastructure: Validate workflows that move between AI requests, tools, and APIs\. - Browser dependencies: Connect browser interactions with the API calls they depend on\. - Full trace detail: Capture every step, path, timing, and result for investigation\. - OTEL export: Review traces in APIContext or export them to your existing observability stack\. - Focused storage: Keep high\-value synthetic traces without storing every production call\. ### Workflow traces export cleanly into OpenTelemetry, APM, incident, and engineering review tools - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Reusable journeys - Full call traces - AI \+ browser \+ API steps - OTEL export - Focused trace storage - 3 surfaces: AI, browser, API - 100% step\-level trace detail - OTEL review or export - 24/7 synthetic journey monitoring - Reusable workflows: Build once, then reuse journey steps for critical production checks\. - AI infrastructure: Validate workflows that move between AI requests, tools, and APIs\. - Browser dependencies: Connect browser interactions with the API calls they depend on\. - Full trace detail: Capture every step, path, timing, and result for investigation\. - OTEL export: Review traces in APIContext or export them to your existing observability stack\. - Focused storage: Keep high\-value synthetic traces without storing every production call\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Reusable journeys - Full call traces - AI \+ browser \+ API steps - OTEL export - Focused trace storage ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start tracing the journeys that matter most\.](/contact) --- # API Monitoring Glossary Canonical URL: https://apicontext.com/glossary Source: static Description: Definitions of key terms in API monitoring, observability, and API quality — including synthetic monitoring, CASC score, FAPI 2\.0, OpenTelemetry, and more\. ## Summary Definitions of key terms in API monitoring, observability, and API quality\. ## Page sections ### Agentic AI Monitoring Continuous verification that the APIs and services consumed by autonomous AI agents — MCP servers, tool endpoints, vector databases, orchestration APIs — are behaving correctly and within their declared contracts\. Unlike traditional API monitoring, agentic AI monitoring must account for semantic correctness \(does the tool return what the model expects?\), schema drift \(has the response format changed without a version bump?\), and multi\-step workflow integrity\. As AI agents increasingly run autonomously in production, reliability and contract integrity of the underlying API layer becomes a critical operational concern\. ### API Availability The proportion of monitoring checks over a time period in which an API endpoint responds successfully — typically defined as returning an expected HTTP status code within an acceptable latency window\. Usually expressed as a percentage \(e\.g\. 99\.9%\)\. Availability measured from a single location may overstate actual quality: an endpoint reachable from a US data center may be unavailable or severely degraded for users in Southeast Asia\. Multi\-location availability across geographic nodes provides a more accurate picture of real\-world reliability\. ### API Conformance The degree to which an API's live production behavior matches its stated specification — typically an OpenAPI document — and any applicable standards and business rules\. API conformance is a complement to API contract testing, but more expansive: it tests not only the technical contract but also the business rules that need to be enforced by the API in context\. A conformant API returns the documented status codes, headers, response schemas, and error formats in all tested scenarios\. Continuous conformance testing catches schema drift and behavioral regression that availability monitoring misses\. ### API Latency The elapsed time between a client sending a request and receiving the complete response, measured from the client's perspective\. Reported at multiple percentiles — p50 \(median\), p95, and p99 — because averages obscure long\-tail degradation affecting a significant proportion of users\. Composed of DNS lookup, TCP connection, TLS negotiation, server processing, and data transfer\. External synthetic monitoring measures full client\-perceived latency including network transit and edge processing that internal APM cannot observe\. ### CASC Score A composite API quality metric developed by APIContext that combines latency percentiles \(p50–p99\), availability, geographic consistency across monitoring locations, and conformance pass rate into a single number on a 0–10 scale\. A CASC score above 9 indicates healthy performance; below 6 indicates a quality problem requiring immediate attention\. Designed to make API quality understandable and comparable across endpoints, providers, and time periods without requiring deep technical knowledge to interpret\. ### FAPI 2\.0 An OpenID Foundation security profile specifying minimum security requirements for APIs in financial and high\-value contexts, building on OAuth 2\.0 and OpenID Connect\. Mandates Pushed Authorization Requests \(PAR\), DPoP sender\-constrained access tokens, PKCE, JARM response mode, and mTLS or private\_key\_jwt client authentication\. Referenced by or incorporated into the UK Open Banking Standard, Brazil's Open Finance framework, Australia's Consumer Data Right, and the US CFPB 1033 rule\. Testing FAPI 2\.0 conformance requires executing complete authentication flows with real credentials, not just checking endpoint availability\. ### mTLS A variant of TLS in which both client and server present certificates to authenticate each other before establishing a connection, as opposed to standard TLS where only the server is authenticated\. Used in API contexts where strong client identity is required — open banking \(TPPs presenting qualified certificates to bank APIs\) or service\-to\-service communication within zero\-trust networks\. Monitoring APIs that require mTLS requires the monitoring client to manage valid certificates and present them correctly on every check\. ### Multi\-Step Workflow Testing A form of synthetic monitoring in which a sequence of dependent API calls is executed as a single test scenario, preserving state — tokens, session identifiers, response data — across steps\. Tests complete user journeys, for example: authenticate → retrieve account list → fetch transactions → initiate payment\. Necessary for detecting integration failures that per\-endpoint checks miss, and for validating APIs that require prior authentication before the target endpoint is reachable\. ### Open Banking A regulatory and industry framework requiring banks and financial institutions to share customer financial data with authorized Third Party Providers via standardized APIs, with customer consent\. Major implementations include the UK Open Banking Standard, Australia's Consumer Data Right \(CDR\), Brazil's Open Finance, and the US CFPB 1033 rule\. Open banking APIs typically require FAPI\-compliant security, machine\-readable specifications, and demonstrable availability and performance standards\. ### OpenTelemetry \(OTEL\) An open\-source observability framework \(CNCF project\) that standardizes the collection of traces, metrics, and logs across distributed systems using a vendor\-neutral wire format and SDK\. In API monitoring, OTEL traces instrument each hop in a request path — DNS resolution, TLS handshake, connection, request transmission, response — providing precise latency attribution\. APIContext generates OTEL\-compatible spans at every stage of the synthetic request chain, making external API observations correlatable with internal APM data in Datadog, Splunk, or Dynatrace\. ### Test node A geographically distributed network location from which monitoring checks are executed\. Typically deployed in major cloud regions \(AWS, GCP, Azure\) and network exchange points to represent real\-world client location diversity\. Running checks from multiple nodes simultaneously allows monitoring platforms to distinguish between global outages and regional performance degradation, and to detect CDN or edge\-layer failures invisible to single\-location checks\. APIContext operates 125\+ nodes worldwide\. ### Private Node A monitoring probe deployed inside a customer's own infrastructure — on\-premise, private cloud, or corporate network — rather than in a public cloud node\. Allows organizations to monitor internal APIs not exposed to the public internet, verify API behavior from inside a firewall or VPN, and test from network positions reflecting specific partner or internal consumer access patterns\. Common in financial services and enterprise IT where sensitive APIs are not internet\-accessible\. ### SLA \(Service Level Agreement\) A contractual commitment between a service provider and a customer defining minimum acceptable service levels, typically expressed as percentage uptime or maximum response time over a measurement period\. Failure to meet SLAs can trigger credits, penalties, or termination rights\. Measuring SLA compliance requires an agreed\-upon methodology, which is why third\-party synthetic monitoring from external locations is commonly used as the reference measurement rather than internal system metrics\. ### SLO \(Service Level Objective\) An internal target for service reliability or performance, typically more stringent than the SLA, used to drive engineering priorities before a contractual threshold is breached\. Commonly expressed as an error budget — the permissible number of failures within a time window\. Unlike SLAs, SLOs are not contractual; they enable teams to manage reliability proactively\. Well\-defined SLOs per API endpoint allow teams to triage incidents by business impact\. ### Synthetic API Monitoring The practice of sending scripted, simulated API requests to production endpoints on a continuous schedule from external locations, without relying on real user traffic\. Provides consistent baseline measurements of API availability, latency, and correctness regardless of traffic volume\. Particularly valuable for catching regressions before they affect customers, verifying geographic consistency, and producing SLA\-grade compliance evidence\. The term "synthetic" refers to the fact that traffic is artificially generated rather than observed from actual users\. ## Key facts - Agentic AI Monitoring: Continuous verification that the APIs and services consumed by autonomous AI agents — MCP servers, tool endpoints, vector databases, orchestration APIs — are behaving correctly and within their declared contracts\. Unlike traditional API monitoring, agentic AI monitoring must account for semantic correctness \(does the tool return what the model expects?\), schema drift \(has the response format changed without a version bump?\), and multi\-step workflow integrity\. As AI agents increasingly run autonomously in production, reliability and contract integrity of the underlying API layer becomes a critical operational concern\. - API Availability: The proportion of monitoring checks over a time period in which an API endpoint responds successfully — typically defined as returning an expected HTTP status code within an acceptable latency window\. Usually expressed as a percentage \(e\.g\. 99\.9%\)\. Availability measured from a single location may overstate actual quality: an endpoint reachable from a US data center may be unavailable or severely degraded for users in Southeast Asia\. Multi\-location availability across geographic nodes provides a more accurate picture of real\-world reliability\. - API Conformance: The degree to which an API's live production behavior matches its stated specification — typically an OpenAPI document — and any applicable standards and business rules\. API conformance is a complement to API contract testing, but more expansive: it tests not only the technical contract but also the business rules that need to be enforced by the API in context\. A conformant API returns the documented status codes, headers, response schemas, and error formats in all tested scenarios\. Continuous conformance testing catches schema drift and behavioral regression that availability monitoring misses\. - API Latency: The elapsed time between a client sending a request and receiving the complete response, measured from the client's perspective\. Reported at multiple percentiles — p50 \(median\), p95, and p99 — because averages obscure long\-tail degradation affecting a significant proportion of users\. Composed of DNS lookup, TCP connection, TLS negotiation, server processing, and data transfer\. External synthetic monitoring measures full client\-perceived latency including network transit and edge processing that internal APM cannot observe\. - CASC Score: A composite API quality metric developed by APIContext that combines latency percentiles \(p50–p99\), availability, geographic consistency across monitoring locations, and conformance pass rate into a single number on a 0–10 scale\. A CASC score above 9 indicates healthy performance; below 6 indicates a quality problem requiring immediate attention\. Designed to make API quality understandable and comparable across endpoints, providers, and time periods without requiring deep technical knowledge to interpret\. - FAPI 2\.0: An OpenID Foundation security profile specifying minimum security requirements for APIs in financial and high\-value contexts, building on OAuth 2\.0 and OpenID Connect\. Mandates Pushed Authorization Requests \(PAR\), DPoP sender\-constrained access tokens, PKCE, JARM response mode, and mTLS or private\_key\_jwt client authentication\. Referenced by or incorporated into the UK Open Banking Standard, Brazil's Open Finance framework, Australia's Consumer Data Right, and the US CFPB 1033 rule\. Testing FAPI 2\.0 conformance requires executing complete authentication flows with real credentials, not just checking endpoint availability\. - mTLS: A variant of TLS in which both client and server present certificates to authenticate each other before establishing a connection, as opposed to standard TLS where only the server is authenticated\. Used in API contexts where strong client identity is required — open banking \(TPPs presenting qualified certificates to bank APIs\) or service\-to\-service communication within zero\-trust networks\. Monitoring APIs that require mTLS requires the monitoring client to manage valid certificates and present them correctly on every check\. - Multi\-Step Workflow Testing: A form of synthetic monitoring in which a sequence of dependent API calls is executed as a single test scenario, preserving state — tokens, session identifiers, response data — across steps\. Tests complete user journeys, for example: authenticate → retrieve account list → fetch transactions → initiate payment\. Necessary for detecting integration failures that per\-endpoint checks miss, and for validating APIs that require prior authentication before the target endpoint is reachable\. - Open Banking: A regulatory and industry framework requiring banks and financial institutions to share customer financial data with authorized Third Party Providers via standardized APIs, with customer consent\. Major implementations include the UK Open Banking Standard, Australia's Consumer Data Right \(CDR\), Brazil's Open Finance, and the US CFPB 1033 rule\. Open banking APIs typically require FAPI\-compliant security, machine\-readable specifications, and demonstrable availability and performance standards\. - OpenTelemetry \(OTEL\): An open\-source observability framework \(CNCF project\) that standardizes the collection of traces, metrics, and logs across distributed systems using a vendor\-neutral wire format and SDK\. In API monitoring, OTEL traces instrument each hop in a request path — DNS resolution, TLS handshake, connection, request transmission, response — providing precise latency attribution\. APIContext generates OTEL\-compatible spans at every stage of the synthetic request chain, making external API observations correlatable with internal APM data in Datadog, Splunk, or Dynatrace\. - Test node: A geographically distributed network location from which monitoring checks are executed\. Typically deployed in major cloud regions \(AWS, GCP, Azure\) and network exchange points to represent real\-world client location diversity\. Running checks from multiple nodes simultaneously allows monitoring platforms to distinguish between global outages and regional performance degradation, and to detect CDN or edge\-layer failures invisible to single\-location checks\. APIContext operates 125\+ nodes worldwide\. - Private Node: A monitoring probe deployed inside a customer's own infrastructure — on\-premise, private cloud, or corporate network — rather than in a public cloud node\. Allows organizations to monitor internal APIs not exposed to the public internet, verify API behavior from inside a firewall or VPN, and test from network positions reflecting specific partner or internal consumer access patterns\. Common in financial services and enterprise IT where sensitive APIs are not internet\-accessible\. - SLA \(Service Level Agreement\): A contractual commitment between a service provider and a customer defining minimum acceptable service levels, typically expressed as percentage uptime or maximum response time over a measurement period\. Failure to meet SLAs can trigger credits, penalties, or termination rights\. Measuring SLA compliance requires an agreed\-upon methodology, which is why third\-party synthetic monitoring from external locations is commonly used as the reference measurement rather than internal system metrics\. - SLO \(Service Level Objective\): An internal target for service reliability or performance, typically more stringent than the SLA, used to drive engineering priorities before a contractual threshold is breached\. Commonly expressed as an error budget — the permissible number of failures within a time window\. Unlike SLAs, SLOs are not contractual; they enable teams to manage reliability proactively\. Well\-defined SLOs per API endpoint allow teams to triage incidents by business impact\. - Synthetic API Monitoring: The practice of sending scripted, simulated API requests to production endpoints on a continuous schedule from external locations, without relying on real user traffic\. Provides consistent baseline measurements of API availability, latency, and correctness regardless of traffic volume\. Particularly valuable for catching regressions before they affect customers, verifying geographic consistency, and producing SLA\-grade compliance evidence\. The term "synthetic" refers to the fact that traffic is artificially generated rather than observed from actual users\. ## Primary entities - APIContext - API monitoring glossary - Agentic AI Monitoring - API Availability - API Conformance - API Latency - CASC Score - FAPI 2\.0 - mTLS - Multi\-Step Workflow Testing - Open Banking - OpenTelemetry \(OTEL\) - Test node - Private Node - SLA \(Service Level Agreement\) - SLO \(Service Level Objective\) - Synthetic API Monitoring ## Audience - API teams - SRE teams - technology leaders ## Primary links - [API Monitoring Glossary](/glossary) --- # Japan Canonical URL: https://apicontext.com/japan Source: static Description: 合成モニタリングによる監視、測定、そして軽減策によって、すべてのアプリケーション接続の耐障害性とデジタルコンピューティングチェーンの信頼性を確保します。APIの適合性、ウェブページの速度、MCPサーバーの信頼性を追跡します。 ## Summary APIContext provides Japanese enterprises with end\-to\-end visibility, proactive risk measures, and comprehensive monitoring capabilities for their APIs\. ## Page sections ### Overview APIContext provides Japanese enterprises with end\-to\-end visibility, proactive risk measures, and comprehensive monitoring capabilities for their APIs\. - APIContext monitors API compliance, web page speed, and MCP server reliability\. - Supports Japanese enterprises with local payment and billing through Meristem Inc\. - Covers Banking & Finance, Enterprise IT, IoT, Government, and Partners & Developers industries\. - [Try APIContext](https://client.apimetrics.io/) - [Contact Meristem Inc\.](/japan) ## Key facts - APIContext monitors API compliance, web page speed, and MCP server reliability\. - Supports Japanese enterprises with local payment and billing through Meristem Inc\. - Covers Banking & Finance, Enterprise IT, IoT, Government, and Partners & Developers industries\. ## Primary entities - APIContext - API monitoring Japan - API conformance - Meristem Inc\. ## Audience - Japanese enterprises - API teams - SRE teams - technology leaders ## Primary links - [Try APIContext](https://client.apimetrics.io/) - [Contact Meristem Inc\.](/japan) --- # Pricing Canonical URL: https://apicontext.com/pricing Source: static Description: Every plan includes synthetic monitoring, OTEL export, and 100\+ global regions\. Scale up only when you need more journeys, longer retention, or stricter security\. ## Summary Pay for the proof\. Not the platform sprawl\. Every plan includes synthetic monitoring, OTEL export, and 100\+ global regions\. Scale up only when you need more journeys, longer retention, or stricter security\. ## Page sections ### Starter For solo developers and small projects getting their first journeys live\. From $29/mo billed annually \($33/mo billed monthly\)\. - 1 project · up to 5 collaborators - 30,000 synthetic API calls / mo - 3 endpoints · 5\-min uptime checks - 3 months data retention - SLA / SLO \+ base security validation - 14 global regions - OTEL export · APM forwarding - Email support ### Team For teams that need richer monitoring and broader contract coverage\. From $99/mo billed annually \($114/mo billed monthly\)\. - Everything in Starter, plus… - Unlimited projects · 20 collaborators - 100,000 synthetic API calls / mo - 10 endpoints · 5\-min uptime checks - 6 months data retention - Schema, OAS, OAuth conformance - OAS & Postman inventory imports ### Pro For groups running multiple critical APIs and customer journeys at scale\. From $499/mo billed annually \($574/mo billed monthly\)\. - Everything in Team, plus… - Unlimited projects · unlimited collaborators - 500,000 synthetic API calls / mo - 40 endpoints · 3\-min uptime checks - 12 months data retention - FAPI, FDX, FHIR conformance - 4\-hour support response ### Enterprise For API\-first organizations and global enterprises\. From $1249/mo billed annually \($1436/mo billed monthly\)\. - Everything in Pro, plus… - Unlimited projects · collaborators - 1,000,000 synthetic API calls / mo - 100 endpoints · 60\-second checks - 36 months data retention - Enterprise SSO available as paid add\-on - mTLS · FIPS 140 HSM · IP allowlisting - Dedicated CSM · 99\.99% SLA ### Try it free\. 10,000 tests every month\. Category: Free tier · forever API, MCP, and HTTP tests only — no simulated browser journeys\. Includes OTEL export\. Perfect for hobby projects, evaluation, or proof of concept\. No card required, no expiry\. ### Account - Projects \(Logical workspaces\): 1 / Unlimited / 10 / Unlimited - Collaborators: 5 / 20 / Unlimited / Unlimited - Social SSO \(Google, Microsoft, GitHub, LinkedIn\): Yes / Yes / Yes / Yes - SAML SSO \($3,000 one\-time configuration \+ $500/mo license\): No / No / No / Add\-on - SCIM provisioning \(Available with Enterprise SSO add\-on\): No / No / No / Add\-on - Audit logs: No / No / 90 days / Unlimited ### Validation & Conformance - API inventory: Yes / Yes / Yes / Yes - SLA / SLO validation: Yes / Yes / Yes / Yes - Base security profile: Yes / Yes / Yes / Yes - Schema validation: No / Yes / Yes / Yes - Standards conformance \(OAuth, OAS, FAPI, FDX, FHIR\): No / OAuth, OAS / OAuth, FAPI, FDX, FHIR / OAuth, FAPI, FDX, FHIR - Custom assertions: No / Yes / Yes / Yes ### Uptime monitoring - Endpoints: 3 / 10 / 40 / 100 - Check interval: 5 min / 5 min / 3 min / 60 sec - Regions: 14 / 14 / 14 / 14 - Cloud test origin: Single cloud / Single cloud / Single cloud / Single cloud - Retry on failure: Yes / Yes / Yes / Yes - API key auth: Yes / Yes / Yes / Yes ### Synthetic API calls - Monthly synthetics: 30,000 / 100,000 / 500,000 / 1,000,000 - Endpoints: Unlimited / Unlimited / Unlimited / Unlimited - Regions: 100 / 100 / 100 / 100 - Cloud test origin \(AWS, Akamai, GCP, Azure\): Multicloud / Multicloud / Multicloud / Multicloud - OAS & Postman import: Yes / Yes / Yes / Yes - Custom requests \(Headers, body, workflows\): Yes / Yes / Yes / Yes - Workflow chaining: No / Yes / Yes / Yes - Variable storage: No / Yes / Yes / Yes ### Browser monitoring - Browser journeys: No / 5 / 25 / Unlimited - Chromium, Firefox and WebKit \(Safari\): No / Yes / Yes / Yes - Core Web Vitals: No / Yes / Yes / Yes - Visual regression: No / No / Yes / Yes - HAR \+ trace export: No / Yes / Yes / Yes ### MCP monitoring - MCP servers: No / 1 / 5 / Unlimited - Tool\-call validation: No / Yes / Yes / Yes - Session replay: No / No / Yes / Yes - Contract drift detection: No / No / Yes / Yes ### Telemetry & integrations - OTLP export \(gRPC \+ HTTP\): No / Yes / Yes / Yes - Datadog / New Relic / Honeycomb: No / Yes / Yes / Yes - PagerDuty / Opsgenie / Slack: Yes / Yes / Yes / Yes - Webhooks: Yes / Yes / Yes / Yes - Private nodes \(Run in your VPC\): No / No / Add\-on / Yes ### Support & assurance - Email support: Yes / Yes / Yes / Yes - Response SLA: Best effort / 24 h / 4 h / 1 h - Dedicated CSM: No / No / No / Yes - Uptime SLA: — / 99\.9% / 99\.95% / 99\.99% - Custom contracts & invoicing: No / No / No / Yes ### Add\-ons - Extra synthetic calls \($0\.0008 per call\): Volume\-priced\. Auto\-bills above plan included usage\. - Enterprise SSO \($3,000 setup \+ $500 / mo\): SAML single sign\-on configuration and monthly license\. - Private nodes \($199 / node / mo\): Run journeys inside your VPC against staging or internal APIs\. Add\-on for Pro; included in Enterprise\. - Extended retention \($99 / mo per \+12 months\): Hold journey traces and waterfalls longer for compliance\. - Dedicated nodes \(Custom\): Reserved capacity in a geo of your choosing for predictable load\. - Premium support \($1,499 / mo\): 1\-hour response · architecture reviews · onboarding assistance\. - On\-call rotation \($299 / mo\): Direct alerts to PagerDuty / Opsgenie · escalation policies\. ## Key facts - Starter: For solo developers and small projects getting their first journeys live\. From $29/mo billed annually \($33/mo billed monthly\)\. - Team: For teams that need richer monitoring and broader contract coverage\. From $99/mo billed annually \($114/mo billed monthly\)\. - Pro: For groups running multiple critical APIs and customer journeys at scale\. From $499/mo billed annually \($574/mo billed monthly\)\. - Enterprise: For API\-first organizations and global enterprises\. From $1249/mo billed annually \($1436/mo billed monthly\)\. - API, MCP, and HTTP tests only — no simulated browser journeys\. Includes OTEL export\. Perfect for hobby projects, evaluation, or proof of concept\. No card required, no expiry\. - Extra synthetic calls \($0\.0008 per call\): Volume\-priced\. Auto\-bills above plan included usage\. - Enterprise SSO \($3,000 setup \+ $500 / mo\): SAML single sign\-on configuration and monthly license\. - Private nodes \($199 / node / mo\): Run journeys inside your VPC against staging or internal APIs\. Add\-on for Pro; included in Enterprise\. - Extended retention \($99 / mo per \+12 months\): Hold journey traces and waterfalls longer for compliance\. - Dedicated nodes \(Custom\): Reserved capacity in a geo of your choosing for predictable load\. - Premium support \($1,499 / mo\): 1\-hour response · architecture reviews · onboarding assistance\. - On\-call rotation \($299 / mo\): Direct alerts to PagerDuty / Opsgenie · escalation policies\. - SOC 2: Self\-attested controls - GDPR \+ DPA: EU \+ UK \+ US data residency - 99\.99% SLA: On Enterprise plan ## Primary entities - APIContext - API monitoring pricing - synthetic API calls - enterprise pricing ## Audience - API teams - SRE teams - procurement teams ## Primary links - [Start free](https://client.apimetrics.io/register) - [Contact us](/contact) --- # Privacy Policy Canonical URL: https://apicontext.com/privacy Source: static Description: How APIContext collects, uses, and protects your personal data\. ## Summary This Privacy Policy explains how we collect, use, and safeguard your information when you use our website and services\. ## Page sections ### Privacy Policy Category: Last updated: October 2026 This Privacy Policy \(“Privacy Policy”\) applies to websites owned or operated by APIContext, Inc\., including apicontext\.com and API\.expert \(collectively, the “Site”\), and to the Service as defined in the applicable APIContext Subscription Agreement or Subscription Agreement for Akamai Subscribers \(the “Subscription Agreement”\)\. Together, the Site and Service are referred to as the “APIContext Properties\.” This Privacy Policy governs data collection and usage related to the APIContext Properties\. BY USING THE APICONTEXT PROPERTIES, YOU CONSENT TO THIS PRIVACY POLICY AND AGREE TO ITS TERMS\. THIS PRIVACY POLICY IS INCORPORATED INTO THE SUBSCRIPTION AGREEMENT IF YOU ORDER SERVICES UNDER THE SUBSCRIPTION AGREEMENT AND THE APICONTEXT WEBSITE TERMS OF SERVICE AT https://apicontext\.com/tos \. COLLECTION OF YOUR PERSONAL INFORMATION APIContext may collect personally identifiable information, such as your e\-mail address, name, home or work address, telephone number, and company name \(“Personal Information”\)\. APIContext may also collect anonymous information, which is not unique to you when not combined with Personal Information, such as your postal code, age, gender, preferences, interests and APIContext Properties settings \(“Non\-Personal Information”\) \(collectively, Personal Information and Non\-Personal Information is “Information”\)\. APIContext reserves the right to delete any Information at any time, without notice to you\. Information about your computer hardware and software also may be automatically collected by APIContext\. This Information can include your IP address, browser type, domain names, access times, and referring website addresses\. This Information is used by APIContext for the operation of the APIContext Properties, to maintain quality of the APIContext Properties, and to provide general statistics regarding use of the APIContext Properties\. 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CONTACT INFORMATION APIContext welcomes your comments regarding this Privacy Policy\. Please contact APIContext at support@apicontext\.com if you have any questions\. ## Key facts - This Privacy Policy explains how we collect, use, and safeguard your information when you use our website and services\. ## Primary entities - APIContext - Privacy Policy ## Audience - customers - legal teams - procurement teams ## Primary links - [Contact APIContext](/contact) --- # Product Overview Canonical URL: https://apicontext.com/product-overview Source: static Description: Measure performance, ensure conformance, and understand your critical apps and services from the places your users, partners, and regulators actually depend on them\. ## Summary Advanced monitoring and resilience for the real world\. Measure performance, ensure conformance, and understand your critical apps and services from the places your users, partners, and regulators actually depend on them\. ## Stats - 125\+ global nodes - audit\-ready evidence for regulators, on demand - OTEL native alerting and telemetry export - 24/7 synthetic production verification ## Page sections ### Continuously test everything your customers depend on\. Category: Monitor all your applications APIContext actively makes real, valid calls into your applications on a continuous schedule from 125\+ global locations — not passively listening to existing traffic\. That covers REST and GraphQL APIs, web pages and user journeys in real browsers, MCP servers and AI tool workflows, and the third\-party services your applications depend on\. - APIs, web journeys, and AI infrastructure monitored continuously - Real browser checks for pages, load times, and user flows - MCP server and agentic AI workflow verification ### Verify service levels independently\. Category: Manage SLAs & SLOs Simple uptime metrics do not explain how your apps and services perform for real users\. APIContext gives teams independent evidence of latency, availability, conformance, and network behavior — so you can manage SLOs, SLAs, suppliers, and third parties with data everyone can trust\. - Independent SLO and SLA verification for apps and services - Latency trends by mean, p90, p95 or p99 - Alert routing into DevOps tools, APMs, and OTEL pipelines ### Send complete signal anywhere\. Category: Integrated alerting Connect APIContext to observability platforms, incident tools, and internal systems through OpenTelemetry, secure webhooks, and APIs — with full request, response, result, and trace context available\. - OpenTelemetry\-compatible traces, metrics, logs, and events - Secure webhooks and APIs for automation - Full call history including network and server components ### HTTP API call manager Manage REST, SOAP, and GraphQL calls, multi\-step sequences, and advanced authentication flows in one place\. ### HTTP endpoint monitor Monitor web pages, login flows, and critical user journeys in real browsers from locations around the world\. Catch broken elements and slow load times before users do\. ### AI infrastructure monitoring Continuously test MCP servers and AI tool workflows\. Verify that tool invocations return the right responses, meet latency budgets, and stay within your expected toolset\. ### Conformance monitoring Measure OpenAPI conformance, gap against standards like FAPI, and report on SLO conformance\. ### Integrated reporting Analyze mean and p90, p95 or p99 latency, full call history, outages, dependencies, and network paths\. ### Enterprise ready Support role\-based access, organization and project\-level controls, and single sign\-on\. ## Key facts - 125\+ global nodes - SLO verification - OpenTelemetry - audit\-ready evidence for regulators, on demand - OTEL native alerting and telemetry export - 24/7 synthetic production verification - Continuously test everything your customers depend on\.: APIContext actively makes real, valid calls into your applications on a continuous schedule from 125\+ global locations — not passively listening to existing traffic\. That covers REST and GraphQL APIs, web pages and user journeys in real browsers, MCP servers and AI tool workflows, and the third\-party services your applications depend on\. - Verify service levels independently\.: Simple uptime metrics do not explain how your apps and services perform for real users\. APIContext gives teams independent evidence of latency, availability, conformance, and network behavior — so you can manage SLOs, SLAs, suppliers, and third parties with data everyone can trust\. - Send complete signal anywhere\.: Connect APIContext to observability platforms, incident tools, and internal systems through OpenTelemetry, secure webhooks, and APIs — with full request, response, result, and trace context available\. - HTTP API call manager: Manage REST, SOAP, and GraphQL calls, multi\-step sequences, and advanced authentication flows in one place\. - HTTP endpoint monitor: Monitor web pages, login flows, and critical user journeys in real browsers from locations around the world\. Catch broken elements and slow load times before users do\. - AI infrastructure monitoring: Continuously test MCP servers and AI tool workflows\. Verify that tool invocations return the right responses, meet latency budgets, and stay within your expected toolset\. - Conformance monitoring: Measure OpenAPI conformance, gap against standards like FAPI, and report on SLO conformance\. - Integrated reporting: Analyze mean and p90, p95 or p99 latency, full call history, outages, dependencies, and network paths\. - Enterprise ready: Support role\-based access, organization and project\-level controls, and single sign\-on\. ## Primary entities - APIContext - API monitoring - SLO verification - OpenTelemetry - API conformance ## Audience - API teams - SRE teams - regulated API programs ## Primary links - [Lower your mean time to issue identification\.](/contact) --- # Resources \(alias\) Canonical URL: https://apicontext.com/resources Source: static Description: Explore CMS\-published reports, case studies, ebooks, and technical resources for API reliability, resilience, and service quality\. ## Summary Explore APIContext reports, case studies, ebooks, and technical resources for API reliability, resilience, and service quality\. ## Page sections ### Overview Explore APIContext reports, case studies, ebooks, and technical resources for API reliability, resilience, and service quality\. - Resources are grouped from the same CMS catalog as the public resources library\. - Resource categories include reports, case studies, ebooks, guides, and technical materials\. - Resource pages help teams understand API monitoring, conformance, resilience, and service quality\. - [API Knowledge Base](/api-knowledge-base) - [Understanding APIs](/understanding-api) ## Key facts - Resources are grouped from the same CMS catalog as the public resources library\. - Resource categories include reports, case studies, ebooks, guides, and technical materials\. - Resource pages help teams understand API monitoring, conformance, resilience, and service quality\. ## Primary entities - APIContext - API resources - API monitoring - API resilience ## Audience - API teams - SRE teams - platform teams - technology leaders ## Primary links - [API Knowledge Base](/api-knowledge-base) - [Understanding APIs](/understanding-api) --- # 5 Lessons From 3 Years of Open Banking Canonical URL: https://apicontext.com/resources/5-lessons-learned-from-3-years-of-open-banking Source: static Description: Download APIContext's white paper on five lessons from three years of Open Banking API monitoring — what works, what doesn't, and what the data shows\. ## Summary 5 Lessons Learned From 3 Years of Open Banking\. Hard\-won lessons from three years of monitoring Open Banking APIs at scale\.\. Download APIContext's white paper on five lessons from three years of Open Banking API monitoring — what works, what doesn't, and what the data shows\. ## Page sections ### Hard\-won lessons from three years of monitoring Open Banking APIs at scale\. Category: White paper Three years of continuous Open Banking API monitoring has produced a body of evidence about the patterns, problems, and progress of regulated API implementation across UK financial institutions\. This white paper synthesises that experience into five durable lessons — observations about where Open Banking succeeds and fails, the quality patterns that recur across institutions, and what the data says about the future of regulated API programmes\. Use it as a practical reference for teams building, managing, or governing Open Banking infrastructure\. - The five most durable lessons from three years of Open Banking monitoring - Quality patterns that recur across institutions regardless of technology stack - Where the data shows the most progress and the most persistent problems - What the evidence suggests for the next phase of Open Banking development ## Key facts - Three years of continuous Open Banking API monitoring has produced a body of evidence about the patterns, problems, and progress of regulated API implementation across UK financial institutions\. - This white paper synthesises that experience into five durable lessons — observations about where Open Banking succeeds and fails, the quality patterns that recur across institutions, and what the data says about the future of regulated API programmes\. - Use it as a practical reference for teams building, managing, or governing Open Banking infrastructure\. - The five most durable lessons from three years of Open Banking monitoring - Quality patterns that recur across institutions regardless of technology stack - Where the data shows the most progress and the most persistent problems - What the evidence suggests for the next phase of Open Banking development ## Primary entities - APIContext - White paper - 5 Lessons Learned From 3 Years of Open Banking - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the white paper](/resources/5-lessons-learned-from-3-years-of-open-banking) --- # 6 Benefits of API Monitoring Canonical URL: https://apicontext.com/resources/6-benefits-of-api-monitoring Source: static Description: API monitoring delivers more than just uptime alerts\. Download this APIContext infographic on the six core benefits of active API monitoring\. ## Summary 6 Benefits Of API Monitoring\. Teams that invest in active API monitoring consistently see benefits beyond basic uptime awareness — including faster incident response, better SLA evidence, improved consumer experience, and stronger governance\. ## Page sections ### 6 Benefits Of API Monitoring Teams that invest in active API monitoring consistently see benefits beyond basic uptime awareness — including faster incident response, better SLA evidence, improved consumer experience, and stronger governance\. This infographic summarises the six most impactful benefits of API monitoring, giving teams a clear framework for making the case for investment and measuring its value\. ## Key facts - Teams that invest in active API monitoring consistently see benefits beyond basic uptime awareness — including faster incident response, better SLA evidence, improved consumer experience, and stronger governance\. - This infographic summarises the six most impactful benefits of API monitoring, giving teams a clear framework for making the case for investment and measuring its value\. ## Primary entities - APIContext - Infographic - 6 Benefits Of API Monitoring - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/6%20Benefits%20of%20API%20Monitoring.pdf) - [Request a demo](/contact) --- # 6 Guidelines for Building and Using APIs Canonical URL: https://apicontext.com/resources/6-guidelines-for-building-and-using-apis Source: static Description: Download the APIContext infographic on 6 guidelines for building and using APIs\. Practical principles for teams designing and consuming APIs at scale\. ## Summary 6 Guidelines For Building And Using APIs\. Good API design and usage practices compound over time\. This infographic distils six core guidelines that help teams build APIs that are reliable, discoverable, and easy to consume\. ## Page sections ### 6 Guidelines For Building And Using APIs Good API design and usage practices compound over time\. This infographic distils six core guidelines that help teams build APIs that are reliable, discoverable, and easy to consume\. Download the PDF or view the infographic below\. ## Key facts - Good API design and usage practices compound over time\. This infographic distils six core guidelines that help teams build APIs that are reliable, discoverable, and easy to consume\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - 6 Guidelines For Building And Using APIs - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/Guidelines%20for%20building%20and%20using%20APIs.pdf) - [Request a demo](/contact) --- # 7 API Factors That Could Ruin Your Performance Canonical URL: https://apicontext.com/resources/7-api-factors-that-could-ruin-your-performance Source: static Description: Seven common API factors that degrade performance — and what to do about them\. Download this APIContext infographic\. ## Summary 7 API Factors That Could Ruin Your Performance\. API performance problems rarely come from a single cause\. This infographic identifies seven recurring factors that degrade API performance in production — from inefficient authentication flows to third\-party dependency latency and poor caching strategy\. ## Page sections ### 7 API Factors That Could Ruin Your Performance API performance problems rarely come from a single cause\. This infographic identifies seven recurring factors that degrade API performance in production — from inefficient authentication flows to third\-party dependency latency and poor caching strategy\. Download the PDF or view the infographic below\. ## Key facts - API performance problems rarely come from a single cause\. This infographic identifies seven recurring factors that degrade API performance in production — from inefficient authentication flows to third\-party dependency latency and poor caching strategy\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - 7 API Factors That Could Ruin Your Performance - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/7%20API%20Factors%20That%20Could%20ruin%20your%20api%20performance.pdf) - [Request a demo](/contact) --- # API Authentication in Context Canonical URL: https://apicontext.com/resources/api-authentication-in-context-spinning-off-a-bunch-of-devs-to-go-waste-their-time Source: static Description: Authentication problems waste developer time and break integrations\. Watch this APIContext video on the real cost of poorly designed API authentication\. ## Summary API authentication in context: Spinning off a bunch of devs to go waste their time\. Authentication is one of the most common sources of friction for developers integrating with APIs\. Token expiry, OAuth edge cases, certificate handling, and inconsistent error responses all contribute to integration time that should not be necessary\. ## Page sections ### API authentication in context: Spinning off a bunch of devs to go waste their time Authentication is one of the most common sources of friction for developers integrating with APIs\. Token expiry, OAuth edge cases, certificate handling, and inconsistent error responses all contribute to integration time that should not be necessary\. This video uses real examples to illustrate how authentication problems compound across integrations, why they are so costly to debug, and what better API design and monitoring can do to reduce the waste\. ## Key facts - Authentication is one of the most common sources of friction for developers integrating with APIs\. Token expiry, OAuth edge cases, certificate handling, and inconsistent error responses all contribute to integration time that should not be necessary\. - This video uses real examples to illustrate how authentication problems compound across integrations, why they are so costly to debug, and what better API design and monitoring can do to reduce the waste\. ## Primary entities - APIContext - Video - API authentication in context: Spinning off a bunch of devs to go waste their time - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # API Authentication: Unhappy Paths Canonical URL: https://apicontext.com/resources/api-authentication-unhappy-paths Source: static Description: Most authentication testing covers the happy path\. The unhappy paths are where integrations break in production\. Watch this APIContext video\. ## Summary API Authentication: Unhappy paths\. Authentication testing usually focuses on the happy path: valid credentials, expected flows, successful responses\. But production environments surface the unhappy paths — expired tokens, invalid grants, certificate mismatches, and edge cases that were never tested\. ## Page sections ### API Authentication: Unhappy paths Authentication testing usually focuses on the happy path: valid credentials, expected flows, successful responses\. But production environments surface the unhappy paths — expired tokens, invalid grants, certificate mismatches, and edge cases that were never tested\. This video explores the authentication failure modes that matter most in production, how they manifest for consumers, and how active monitoring helps teams catch auth problems before they escalate into incidents\. ## Key facts - Authentication testing usually focuses on the happy path: valid credentials, expected flows, successful responses\. But production environments surface the unhappy paths — expired tokens, invalid grants, certificate mismatches, and edge cases that were never tested\. - This video explores the authentication failure modes that matter most in production, how they manifest for consumers, and how active monitoring helps teams catch auth problems before they escalate into incidents\. ## Primary entities - APIContext - Video - API Authentication: Unhappy paths - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # API Drift White Paper Canonical URL: https://apicontext.com/resources/api-drift-white-paper Source: static Description: Download the API Drift white paper and learn how production APIs move away from contracts, expectations, and customer experience\. ## Summary API Drift White Paper\. Understand how APIs change in production, and what teams can do about it\.\. Download the API Drift white paper and learn how production APIs move away from contracts, expectations, and customer experience\. ## Page sections ### Understand how APIs change in production, and what teams can do about it\. Category: White paper API drift happens when live API behavior moves away from the contract, the documentation, or the experience customers were promised\. This guide explains why drift is hard to catch with static checks alone, how it shows up in production, and why active monitoring is essential for teams managing critical APIs\. Use it to sharpen reliability, governance, and change\-management conversations across engineering, product, and customer\-facing teams\. - Where API drift comes from and why it is rarely a single\-team problem - How drift affects API consumers, agents, partners, and regulated workflows - What active monitoring can detect that contract reviews miss - How to build better feedback loops between API owners and operations teams ## Key facts - API drift happens when live API behavior moves away from the contract, the documentation, or the experience customers were promised\. - This guide explains why drift is hard to catch with static checks alone, how it shows up in production, and why active monitoring is essential for teams managing critical APIs\. - Use it to sharpen reliability, governance, and change\-management conversations across engineering, product, and customer\-facing teams\. - Where API drift comes from and why it is rarely a single\-team problem - How drift affects API consumers, agents, partners, and regulated workflows - What active monitoring can detect that contract reviews miss - How to build better feedback loops between API owners and operations teams ## Primary entities - APIContext - White paper - API Drift White Paper - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the white paper](/resources/api-drift-white-paper) --- # API Economy by the Numbers 2022 Canonical URL: https://apicontext.com/resources/api-economy-by-the-numbers-2022 Source: static Description: Download APIContext's data\-driven infographic on the API economy in 2022 — scale, growth, quality, and what the numbers mean\. ## Summary API Economy by the Numbers\. A data\-driven look at the scale and quality of the API economy\.\. Download APIContext's data\-driven infographic on the API economy in 2022 — scale, growth, quality, and what the numbers mean\. ## Page sections ### A data\-driven look at the scale and quality of the API economy\. Category: Infographic The API economy has grown from a technical conversation to a strategic business priority\. The numbers tell a story about scale, growth, and the quality challenges that come with rapid expansion\. This infographic presents key data points about the API economy — the scale of API usage, growth trends, and what the numbers reveal about the quality imperative for organisations that depend on APIs\. Complete the form to download the full infographic\. - The scale and growth trajectory of the API economy - What the data reveals about API quality across the ecosystem - Why API reliability has become a strategic business concern - How the numbers translate into investment priorities for API teams ## Key facts - The API economy has grown from a technical conversation to a strategic business priority\. The numbers tell a story about scale, growth, and the quality challenges that come with rapid expansion\. - This infographic presents key data points about the API economy — the scale of API usage, growth trends, and what the numbers reveal about the quality imperative for organisations that depend on APIs\. - Complete the form to download the full infographic\. - The scale and growth trajectory of the API economy - What the data reveals about API quality across the ecosystem - Why API reliability has become a strategic business concern - How the numbers translate into investment priorities for API teams ## Primary entities - APIContext - Infographic - API Economy by the Numbers - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the infographic](/resources/api-economy-by-the-numbers-2022) --- # API Lifecycle Canonical URL: https://apicontext.com/resources/api-lifecycle Source: static Description: Download the APIContext infographic on the API lifecycle — from design and build through deployment, management, and retirement\. ## Summary API Lifecycle\. Managing APIs well requires understanding the full lifecycle: from initial design through development, testing, deployment, versioning, and eventual retirement\. Each stage has distinct quality and governance requirements\. ## Page sections ### API Lifecycle Managing APIs well requires understanding the full lifecycle: from initial design through development, testing, deployment, versioning, and eventual retirement\. Each stage has distinct quality and governance requirements\. This infographic maps the API lifecycle stages and the key activities at each, providing a reference framework for teams building or improving their API programmes\. ## Key facts - Managing APIs well requires understanding the full lifecycle: from initial design through development, testing, deployment, versioning, and eventual retirement\. Each stage has distinct quality and governance requirements\. - This infographic maps the API lifecycle stages and the key activities at each, providing a reference framework for teams building or improving their API programmes\. ## Primary entities - APIContext - Infographic - API Lifecycle - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/API%20Lifcycle.pdf) - [Request a demo](/contact) --- # API Monitoring and Governance in Production Runtime Canonical URL: https://apicontext.com/resources/api-monitoring-and-governance-in-your-production-runtime-environment Source: static Description: Production runtime is where API governance becomes real\. Watch this APIContext video on monitoring and governance in live environments\. ## Summary API Monitoring and Governance in your Production Runtime Environment\. API governance frameworks are often designed at the design and development stage, but the production runtime environment is where governance either holds or breaks down\. Real traffic, real dependencies, and real failures test policies that looked solid in theory\. ## Page sections ### API Monitoring and Governance in your Production Runtime Environment API governance frameworks are often designed at the design and development stage, but the production runtime environment is where governance either holds or breaks down\. Real traffic, real dependencies, and real failures test policies that looked solid in theory\. This video covers what monitoring and governance look like in production — how to connect runtime behaviour back to governance policies, and what teams need to see in order to maintain meaningful control over their live API estate\. ## Key facts - API governance frameworks are often designed at the design and development stage, but the production runtime environment is where governance either holds or breaks down\. Real traffic, real dependencies, and real failures test policies that looked solid in theory\. - This video covers what monitoring and governance look like in production — how to connect runtime behaviour back to governance policies, and what teams need to see in order to maintain meaningful control over their live API estate\. ## Primary entities - APIContext - Video - API Monitoring and Governance in your Production Runtime Environment - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Enterprise API Readiness in the Era of Agentic AI Canonical URL: https://apicontext.com/resources/api-readiness-for-agentic-ai-white-paper Source: static Updated: 2025-06-10 Description: Full white paper: 75% of tested APIs have a nonconformant endpoint\. Learn how API drift, MCP servers, and OAuth 2\.1 affect AI agent readiness\. ## Summary Enterprise API Readiness in the Era of Agentic AI\. Autonomous agents are already calling your APIs\. This report is the full technical guide to making those APIs safe, legible, and durable for them\. ## Stats - 75% had at least one nonconformant endpoint - 25% matched their spec on no endpoint at all - 89% of specs were more than six months stale ## Page sections ### Executive Summary As generative AI systems evolve into autonomous assistants, they stress APIs in new ways\. This report examines how enterprise APIs can achieve “AI agent readiness\.” Autonomous agents can orchestrate dozens of parallel API calls in seconds, adapt in real time, and lack the contextual intuition of human developers\. This shift exposes gaps in API documentation, drift in specifications, and insufficient safety guardrails, all of which can lead to unpredictable failures, security risks, and degraded system reliability\. By hardening API contracts, embracing agent\-oriented design patterns, and instituting robust orchestration and governance, organizations can welcome autonomous clients—unlocking powerful AI\-driven automation while safeguarding performance, security, and user trust\. To address these challenges, enterprises must rethink both their API contracts and infrastructure\. Key recommendations include: - Specification Discipline: Embed OpenAPI updates into the development workflow, enforce schema validation, and surface machine\-readable constraints and examples\. - Agent Gateway Adoption: Deploy Model Context Protocol \(MCP\) servers to abstract underlying APIs, enforce policies, manage OAuth 2\.1 flows with PKCE, and forward authenticated user identity\. - Agent\-Aware Controls: Implement nuanced rate limiting, concurrency caps, dynamic throttling, and tiered quotas to differentiate AI traffic from human usage\. - Observability & Resilience: Enhance logging, monitoring, caching, and retry mechanisms to detect and recover from agent misbehavior without manual intervention\. - “Your APIs are about to become your AI advantage\. They’re how your business becomes accessible to AI\.” — Erik Wilde, API Strategist ### AI Integration Checklist This checklist can serve as a starting point to ensure your API and environment are ready for autonomous agents\. Following it helps maintain reliability and trust as you expand into AI\-driven integrations\. - Spec accuracy verified \(no drift; test cases automated\)\. - OpenAPI spec updated to include examples and clarify tricky parts\. - Common agent tasks documented with high\-level actions or workflows\. - Rate limits reviewed for agent usage; policies in place for spikes\. - Sensitive operations flagged and special scope requirements defined\. - Audit logging enabled for all agent actions\. - Critic model or rule\-based secondary checks implemented for critical API calls\. - Sandbox and test suites created for agent developers\. - Emergency disable or alert mechanism deployed if agent behavior goes off\-course\. ### Introduction Traditional API strategies assume human\-paced usage, from web or mobile apps, with relatively linear request patterns\. Agentic AI breaks those assumptions\. An AI agent might chain together dozens of API calls in seconds, execute parallel requests, and adapt its behavior in real\-time\. It may also inadvertently exploit gaps in API definitions or error handling in ways human users wouldn’t\. Ensuring API readiness for agentic AI means rethinking API documentation, usage policies like rate limiting, authentication flows, and safety guardrails\. ### API Documentation Becomes Urgent APIs are contracts\. In the human\-driven era, breaking that contract \(or letting it decay\) mainly resulted in frustrated developers or broken integrations that would get manually fixed\. In the agent\-driven era, the stakes are higher: an AI agent might not have the intuition or context a human developer does when an API behaves inconsistently\. Agents might misinterpret a poorly documented response, or persist in calling an outdated endpoint unless explicitly corrected\. API drift – the divergence of an API’s actual behavior from its documented specification – thus becomes a serious friction point for agentic automation\. When we recently reviewed the landscape of API documentation and drift, the results were surprising: 75% of APIs we tested had at least one nonconformant endpoint, and 25% had documentation so out\-of\-sync that none of the tested endpoints matched the spec\. Moreover, 89% of the specs hadn’t been updated in six months\. The industry is simply not set up to make AI agents successful in accessing APIs\. Allowing an AI agent to consume an out\-of\-date OpenAPI spec will lead it astray in numerous ways such as calling deprecated endpoints, sending wrong parameter formats, or expecting data that never comes\. Many APIs drift because teams often treat their OpenAPI spec as an optional add\-on rather than the definitive contract\. Without a clear owner for the spec, updates easily fall through the cracks: hand\-edited docs are prone to omissions, internal\-only specs may be generated once and then neglected, and simple governance gaps mean revisions get postponed in favor of shipping code changes\. On top of this, philosophical and versioning misalignments deepen the problem\. Teams that view “the code as truth” defer spec updates until “later”—too late for real\-time AI agents—while specs published at launch frequently fail to keep pace with incremental API improvements, leaving documentation that no longer matches implemented behavior\. This kind of inconsistency simplifies work for API developers, but makes it much more difficult to troubleshoot problematic behavior and violates the principle of least surprise\. An AI agent expecting a well\-formed success response might be confused by a 200 status containing an error\. Here are some real\-world examples: - The spec says a field returns a string, but the actual response is an empty string or null, which wasn’t accounted for\. - An enum in the spec doesn’t list an “empty” state that the API uses in practice\. - An endpoint returns HTTP 200 with an error in the payload instead of an HTTP 4xx code\. ### Impacts of drift on AI agents The solution to eliminating API drift is to make sure that OpenAPI Definitions are accurate, complete, and easily accessible to the AI\. This enables AI agents to interface with your API reliably\. If your API always behaves as documented, an agent can be trained or instructed to use it with far fewer hiccups\. As an added bonus it ensures smoother integration for human developers\. - Predictable patterns vs\. guesswork: Agents rely on patterns\. If the documentation says “field X will always be present,” the agent might take that for granted when parsing a response\. If in reality the field is sometimes missing, a human developer might notice and add a null check – an agent might not, leading to failure or misunderstanding\. - Error handling: Agents don’t \(yet\) have the judgment of an experienced engineer to realize “Ah, the API returned a 200 but there’s an error message, I should handle that as an error\.” Unless explicitly trained or told, they might assume 200 means success\. Conversely, if an API deviates by using a 404 in some non\-standard way not reflected in the spec, the agent might treat it as a fatal error and stop, whereas a human might realize it’s benign\. - Tool learning: Some frameworks let you feed an OpenAPI spec to an LLM so it can formulate correct API calls \(this is a common approach in making LLM “plugins” or tools\)\. If the spec is wrong, the LLM will produce wrong calls\. It might persist, try to correct itself from the error message \(if any\), or hallucinate alternative parameters – none of which is reliable\. - Maintenance at scale: In a world where dozens of AI agents could be interacting with dozens of APIs, manual patching of each agent to accommodate drift is not feasible\. We need the contract itself to be dependable, so that we can automate agent interactions confidently\. - “Agentic AI puts a spotlight on a persistent problem: APIs built without fundamental security\. It’s rarely about tools — it’s a broken delivery process\.” — Ikenna Nwaiwu, API Governance Consultant ### Orchestration Evolves Yet Again As more AI agents come online, AI teams are working to orchestrate and streamline requests to downstream APIs\. One of the key enablers is a new open standard called the Model Context Protocol \(MCP\)\. But while MCP unlocks scale for agent developers, it creates new complexity and operational strain for downstream applications used by these autonomous agents\. ### What Is MCP and Why Does It Matter? The Model Context Protocol \(MCP\) is an open standard that allows AI agents to use tools—like APIs, databases, and SaaS applications—through a standardized interface\. This allows application owners to control usage, reduce API support costs, and protect the application from AI abuse\. ### In MCP’s architecture Think of MCP as a sort of “USB plug for AI agents”—a universal port for APIs and tools\. Instead of every agent framework defining its own plugins, MCP lets anyone implement a server once and make their app compatible with any agent that speaks MCP\. At first glance, it might seem like standing up an MCP server should be the responsibility of the AI team—after all, they’re the ones building the agent\. But in practice, many application owners are the ones building and publishing their own MCP server templates\. Why? Because the MCP server is where the definitions are set for how AI agents interact with your API\. By building the MCP server, application owners maintain control over how their systems are used by autonomous agents\. They get to enforce safe defaults, provide guardrails, and prevent agents from misusing or overloading your application\. An MCP server reference implementation is like a new SDK or client library—except instead of helping human developers integrate, it helps AI agents use your app safely and correctly\. There are some clear challenges to building an MCP server that is truly enterprise\-grade, including managing authentication; and abstracting and validating API calls\. The MCP server acts as a translation and enforcement layer\. It decides: - MCP Host: is the AI agent or orchestrator\. - MCP Client: is the connector module inside the agent\. - MCP Server: is the adapter that wraps around your API and exposes it to AI agents\. - “MCP doesn’t replace APIs — it exponentially multiplies API consumption and attack surfaces\.” — Sudeep Goswami, CEO, Traefik Labs - Which actions are exposed \(e\.g\., let users create new records, but don’t let them delete records\) - How inputs are validated - What rate limits apply - Which scopes are required - How underlying APIs are versioned or abstracted ### Authentication becomes more complex once more The MCP standard requires OAuth 2\.1 for authentication and authorization, which is not required for most API access today\. Agents must obtain PKCE\-protected tokens via a standard redirect/consent exchange\. The flow resembles a three\-legged OAuth flow, except that the agent is a new intermediary\. The MCP spec essentially requires the MCP server to implement an OAuth 2\.1 Authorization Server or delegate to one\. In fact, a controversial part of the spec is that it treats the MCP server as both a resource server and an authorization server\. This dual role adds significant complexity to the server design\. Of course, at this point, the human has not made any claim to the application\. The human user authorizes the MCP, and the MCP interacts with the downstream application API\. This creates a black box for the application\. In order for the application to know which human user is making the request, the MCP server must forward identity claims in the form structured metadata or \(preferably\) as signed JWTs\. In addition, applications should be prepared to manage access for abusive or problematic behavior with granularity\. If an AI agent is causing issues, blocking the agent entirely will impact all the human users on the other end of the transaction\. The solution is to require per\-user tokens rather than blanket agent tokens, or implement scoped API keys that bind to both the AI agent and the human user\. Finally, in regulated industries or other use cases where it’s imperative to know which specific users did specific actions, MCP clients should be required to include user attribution metadata \(e\.g\., x\-user\-id, x\-original\-auth\-sub\) and to log this metadata downstream\. The API should not accept ambiguous requests for sensitive operations without those details\. ### Abstracting and Validating API Calls Another function of MCP servers is translating agent intents into actual API calls safely\. An AI agent issues a request to the MCP server\. The MCP server then calls the underlying tool’s API and returns the result \(or error\) back to the agent in a standardized JSON structure\. Response handling and error abstraction: Similarly, the MCP server should normalize responses and errors from the underlying API into the MCP’s standard format\. If the tool API returns a 404 Not Found, the MCP server might translate that into an MCP error object indicating the action failed because an item was not found\. This is crucial for agent reasoning: the agent only understands what the MCP protocol conveys\. A poorly implemented MCP server might pass raw error messages that confuse the agent’s language model\. A well\-implemented one will catch exceptions and convert them to informative, structured errors or messages the agent can parse or even reason about\. By logging these, if an agent misbehaves \(e\.g\., spams an API with many calls or uses an API in an unintended way\), engineers can trace the sequence of events\. It also aids in error recovery: if an agent consistently fails on a certain action due to an unhandled edge case, the MCP logs will show that pattern, and developers can improve either the agent’s prompt or the MCP server’s handling\. All of this new infrastructure needs to be coordinated with the API itself\. If the MCP server has rate limiting capabilities to a certain threshold, the API needs to allow for a different rate limiting level\. Access controls and payload responses need to align\. And for most teams, the API itself will need hardening\. A key change: agent identity needs to be auditable\. Not just what was done, but who authorized it, which AI did it, and on what scope\. If your logging doesn’t yet include that level of granularity, start there\. For this to work reliably, several things need to be in place: Observability and logging: The orchestration role of the MCP server makes it the ideal vantage point for monitoring agent\-tool interactions\. For enterprises deploying AI agents, observability is paramount – you need to track what the agent is doing for both debugging and auditing\. MCP servers should implement robust logging of: Resilience and error recovery: Agents operate continuously and without direct supervision, so MCP servers should incorporate resilience patterns: Agents are often headless, so user login steps may occur in a companion UI or delegated flow\. You need to ensure your auth flows can: - Action templating: The MCP server defines a set of actions or tools it exposes\. Each action has a template for the API call\(s\) it performs\. The MCP server manages the configuration of these mappings\. Some MCP servers may even allow dynamic discovery of actions via a manifest\. - Input validation: Before calling the real API, the MCP server should validate the parameters an agent provided\. Since the agent is generating these from possibly natural language reasoning, there’s room for error\. This prevents the tool API from receiving a bad payload which could cause unintended effects if not properly sanitized\. It also provides immediate feedback to the agent which can then correct its usage\. - Schema enforcement: The MCP specification itself likely defines a schema for each message, built on JSON\-RPC 2\.0\. An MCP server should reject malformed requests at the protocol layer\. Additionally, the semantics of each action are defined by the server – e\.g\., which params, what they mean, what result to expect\. - Tool abstraction layer: A key benefit of MCP is that it decouples the agent from the specifics of each API, which requires ongoing maintenance\. If the underlying API changes \(new version, different parameters\), the MCP server must adapt its implementation while keeping the agent\-facing action consistent\. - “MCP and A2A are rewriting the rules of computing\. They turn rigid tools into a collaborative orchestra\.” — Liat Ben\-Zur, Author of “Rewrite the Rules: How to Lead, Influence, and Thrive in an AI Era” - “The idea of the MCP is to standardize… but deviation and new standards tend to crop up quickly\.” — Kristopher Sandoval, Technical Evangelist - Each action request from an agent \(timestamp, requesting agent identity, action name, parameters\)\. - Outgoing API calls to the third\-party service \(endpoint, maybe sanitized payload, response status/time\)\. - Responses or errors returned to the agent\. - Authorization events \(token issued, refreshed, revoked\)\. - Rate limiting and backpressure: If an agent goes into a tight loop and bombards the MCP server with requests, the server should detect this \(e\.g\., too many calls in a short time\) and throttle or even temporarily block to protect the backend API from overload\. Unlike human users, an AI might inadvertently DoS an API if something goes wrong in its logic\. - Caching responses: For read\-heavy tools, caching can both improve performance and mitigate unnecessary load\. If an agent asks for the same info repeatedly due to lack of memory on the agent’s part, the MCP server can cache recent results for a short period\. - Retry logic: Tools might fail due to transient issues \(network hiccup, rate limit, etc\.\)\. An MCP server can implement retries or circuit breakers for certain errors, increasing the robustness of the agent’s experience\. For example, if a payment API returns a 500 error, the server might wait a second and retry internally, instead of immediately propagating the failure to the agent\. - Fallbacks: In some cases, the MCP server might even have fallback behaviors\. If one data source is down, can it use an alternative? This is advanced usage, but not inconceivable for critical applications \(imagine an agent that needs stock prices – if Yahoo Finance API is down, the MCP server could try an alternate source\)\. - Support asynchronous user consent and token exchange - Distinguish AI agents from human users - Enforce rate limits and scope boundaries accordingly - “With great interoperability comes great responsibility\. MCP introduces powerful capabilities, but also complex new risks across infrastructure, observability, compliance, and external interactions\.” — Katharina Koerner, AI Governance ### AI Usage Patterns – Rethinking Rate Limits Rate limiting in the agentic context must move from blunt instruments like “X calls per second” to more nuanced controls that consider the nature of the caller and the context of calls\. Differentiating AI agents from human users allows APIs to enforce custom rate limits, rein in potentially misuse, while still enabling scalable use by agents\. Traditional API rate limiting strategies were designed with humans in mind, and tight rate limits made sense\. AI agents, however, have no natural throttle\. They can hammer an API with requests as fast as the network and computing allow, especially if stuck in a loop or working on a large task\. Additionally, multiple AI agents can coordinate or inadvertently swarm an API in parallel\. This necessitates a re\-examination of rate limiting models to be more agent\-aware\. AI agents use APIs differently, including: As a result, API owners need to adjust their policies to differentiate between human and AI consumers and apply appropriate controls\. Controls do not necessarily need to be stricter, but instead more granular\. Here are some considerations: - Concurrency: An AI agent might decide to fork into subtasks and do 10 things at once\. For instance, a multi\-agent system might spawn 5 agents, each calling an API concurrently\. To the API, that might look like one user suddenly doing 5x normal traffic simultaneously\. - Volume over time: An agent could make a steady stream of requests with no breaks\. Quotas may be set at the organization level, but a single agent could use the entire quota if not checked\. - Access patterns: AI agents may have repetitive patterns \(e\.g\., polling every minute, or iterating through a list of items rapidly\), which can trigger rate limits that look for too many similar calls\. Or an AI might burst irregularly – nothing for an hour, then 200 calls in a minute if a condition triggers it to act\. - Unpredictability: Humans follow workflows that were designed by the app maker, so the sequence of API calls is somewhat predictable\. Agents generate their own sequences\. They might hit endpoints in orders or frequencies an API provider didn’t anticipate\. For example, a human rarely requests the same record 50 times in a row, but an agent might if its loop fails to store the result\. - Tiered rate limits: Offer an “AI integration” tier with higher per\-second limits but perhaps lower burst allowances or stricter behavior monitoring\. Or conversely, limit AI agents to a lower rate unless they have proven need and reliability\. - Concurrency limits per token: Ensure that any single agent identity can only have N outstanding requests at once\. If an agent tries to exceed that, return errors or queue them\. This prevents runaway parallelism\. - Dynamic adjustment: Intelligent throttling where the system monitors usage patterns and if an agent starts hitting error responses \(like many 429s or 5xx\), it automatically slows down further requests from that agent to prevent things from worsening\. Similarly, if an agent has been well\-behaved, the system can allow a temporary burst beyond documented limits to accommodate an occasional spike\. - Separate quotas for read vs write: This ensures the agent can fetch data freely but cannot overwhelm with modifications\. - Safety valve limits: A “circuit breaker” that trips if any single client makes an absurd number of requests in a short time\. This prevents bugs in agents from causing sustained harm\. - Identification and analytics: If AI agents identify themselves, API providers can analyze their usage separate from human traffic and align behavior\-based quotas, and access tiers\. - “Any urgency you feel in this moment is intentionally manufactured to get you to expose your raw database and other digital resources you have already defined as APIs\.” — Kin Lane, API Evangelist ### Preparing Your APIs for Agentic AI: Recommendations So, what should API owners do today to future\-proof their APIs for the rising tide of AI agents? Below are technically grounded recommendations at different levels \(specification, infrastructure, security\) to ensure your APIs are ready for autonomous clients\. - “We’re essentially revisiting the desktop software security model, which means we need to rebuild trust mechanisms for this new context\.” — Kevin Swiber, API Strategist ### Strengthen and Leverage API Specifications - Keep your OpenAPI definitions accurate and up\-to\-date: Make spec updates part of your dev workflow and use tools to catch drift\. Consider adopting a design\-first approach for new APIs so that you think through the contract fully \(which helps catch ambiguities that an AI might misinterpret\) before coding\. If you’re code\-first, use automation to generate the spec and verify it\. An accurate spec will likely be the primary way AI agents learn to use your API\. - Provide machine\-readable hints and descriptions: LLM agents parse text, so descriptive field names and endpoint summaries help\. But also provide explicit constraints \(min/max, regex\) in the spec\. Agents might pick up on a description “status must be one of \[OPEN, CLOSED\]” and avoid sending other values\. Formalize your business logic in the spec or a companion rules document\. - Include constraints in the spec: Specify data types, lengths, allowed ranges\. If a field can only be one of a few values, use an enum in OpenAPI\. If an endpoint requires a certain sequence \(e\.g\., you must call /login before /data\), document that thoroughly\. AI might not always read prose, but if the API returns a specific error code or message when out of sequence, mention it\. Structured hints like that can be caught and learned\. - Version and document changes transparently: When you change your API, update the spec and highlight it in docs\. Agents that have seen older examples need to be updated too\. If you deprecate something, consider leaving a stub that returns a clear error message like “This endpoint is deprecated, use X instead\.” An agent can read that and adjust\. Some agent frameworks even parse error messages to adapt\. - Use the spec to generate tests and even agent prompts: For example, you could generate example prompt snippets for agents from the spec \(“To create a task, call the createTask action with parameters: \.\.\.”\)\. Including such examples in your API documentation will help developers who are specifically integrating AI, and their agents can be primed with these examples, as they often perform better after seeing sample API usages\. - Governance: create an “AI integration” focus in your API team: Just like mobile changed API access, AI will drive new changes\. Create a backlog of “AI ergonomics” improvements for your API—things like adding an endpoint that returns a summary of data \(so an agent doesn’t have to fetch and summarize in the model, costing tokens\), or enabling partial response fields selection \(to limit payload\)\. - “We’re at the start of a networked agentic AI ecosystem\. Just like the early web, enterprises need foundational guardrails — agent identity, authentication, discovery, and verifiable agent\-to\-agent \(A2A\) interactions\. Secure APIs and trust protocols will be key to driving real adoption and usage\.” — Jackie Shoback, Managing Director, 1414 Ventures ### Adapt Infrastructure and Tools - Implement an MCP or agent gateway: If you anticipate a lot of AI agent usage, build an MCP server for your API to provide a controlled interface for agents\. This can also serve human developers integrating AI – they use your MCP server or plugin rather than directly hitting the API\. If you can’t build one, at least design your API so that others \(or open\-source communities\) can easily wrap it into an MCP server\. For example, avoid complex auth flows that can’t be automated\. - Implement robust rate limiting and quotas with AI in mind: Are your rate limits suitable if one “user” is actually an AI making requests for thousands of humans? Adjust by providing higher limits to trusted integrators, with monitoring in place\. Ensure your gateway emits informative responses \(429 with Retry\-After headers\) and implement dynamic throttling\. If possible, identify agent clients \(via user\-agent string, token, or a flag\) and separate their traffic for analysis and control\. - Enhance observability specifically for agent usage patterns: Set up dashboards/alerts for things like: spike in error rate for a single client, unusual traffic patterns \(like hitting many endpoints in alphabetical order\), or a normally quiet API suddenly getting hammered at 2 AM\. Be proactive to prevent an agent from going rogue before it does damage or overwhelms your service\. - Scalability and performance: Agents will add load\. Block individual users so if one client tries to overuse, the overall system stays healthy\. Use caching layers for expensive operations to serve repetitive agent requests efficiently\. Consider enabling HTTP/2 or HTTP/3 so that agents using parallel calls will benefit from multiplexing and better throughput\. - Provide sandbox and test data: Make it easy for developers to test their agents against your API without real consequences\. This allows them to refine prompts and handling\. If you can, provide a simulator where the agent can practice\. - Offer webhooks or event streams: Agents often resort to polling if there is no better way\. Polling means lots of calls to APIs\. Offer push mechanisms so that agents can wait for notifications instead of incessantly checking\. This can drastically reduce unnecessary API calls from agents\. - Consider GraphQL or aggregated endpoints for complex queries: Agents can formulate GraphQL queries to get exactly what they need in one request\. This can reduce call count\. If GraphQL is too much, add custom endpoints that return all info an agent might typically need in one go \(e\.g\., a /dashboardSummary endpoint that returns a bunch of related info that an agent would otherwise fetch via 5 separate endpoints\)\. ### Security and Compliance Readiness In essence, treat an AI agent as a new type of client – akin to how mobile was a new client a decade ago – and optimize for it\. That means clarity, consistency, and safety in your API above all\. By doing so, you not only make integration easier for AI developers, but you also improve the API for everyone\. By implementing these recommendations, you’ll make your enterprise APIs far more ready for the agentic AI era\. You’ll reduce integration friction \(through better specs and design\), ensure stability and performance \(through agent\-aware limits and monitoring\), and guard against unintended consequences \(through robust validation, oversight, and alignment mechanisms\)\. As AI agents move from hype to everyday tools, enterprises that have prepared their APIs for this shift will enable powerful new automations and partnerships, while those that haven’t may find their APIs misused or bypassed in favor of more AI\-friendly alternatives\. The time to act is now: harden your API contract, embrace agent\-oriented design, and put guardrails in place – so you can confidently welcome your new autonomous clients\. - OAuth 2\.1 for all clients: If you still use API keys or basic auth, move to OAuth 2\.1 with scopes\. It enables fine\-grained access control, delegation, and standard flows that tools \(and agents\) understand\. With OAuth 2\.1, you can issue tokens with limited scopes for an agent, as opposed to a full admin key\. - Scope down permissions: Create special roles or scopes for AI agents\. For example, a “supportAI” role that can read cases and write comments, but not delete anything or change settings\. Use the least privilege principle\. If using JWT claims, include a claim that this token is for an AI and should not be allowed to do certain high\-risk ops\. - Audit logging: Turn on verbose audit logs for actions taken by AI agents\. If the agent updates a record, annotate a field like “last\_modified\_by=AI\_agent\_X\.” This will help later to analyze impact\. - Implement output filters or monitors for sensitive data: If your API could potentially return sensitive data \(PII, secrets\), filter or redact such data at the API level unless specifically authorized\. Alternatively, clearly label fields in responses that are sensitive, so an agent could be programmed to be careful with them\. - Enforce validation on incoming data: An agent might generate slightly\-off inputs \(e\.g\., an enum value in the wrong case\)\. Be forgiving where you can \(e\.g\., case\-insensitive matching\) or at least return very clear error messages\. Strict validation is good for security, but ensure your error messages guide the agent \(e\.g\., “Field X must be one of \[Open, Closed\]” rather than just delivering a “400 Bad Request” message\)\. ### Glossary Definitions of the agentic AI and API readiness terms used throughout the report\. - Access Token: A short\-lived credential \(often a JWT\) that grants the bearer permission to call protected API endpoints within certain scopes\. - Aggregated Endpoint: An API endpoint that returns multiple related resources in a single call—e\.g\., a /dashboardSummary—to reduce the number of requests an agent must make\. - Agent Prompt: The natural\-language or structured instruction given to an AI agent, often including context and examples of API calls it should make\. - Agentic AI: AI systems \(often based on large language models\) that can autonomously perform multi\-step tasks by orchestrating actions—such as making API calls—without human intervention\. - API Contract: The formal agreement—often expressed in an OpenAPI spec—defining an API’s endpoints, request/response shapes, behavior, and error handling\. - API Drift: The gap that grows over time between an API’s actual behavior and its documented spec—leading agents to call deprecated or changed endpoints incorrectly\. - API Gateway: A proxy layer that sits in front of APIs, handling authentication, rate limiting, routing, and observability in a centralized way\. - Audit Logging: Recording detailed, immutable logs of every API action—who \(agent/user\), when, what endpoint, parameters, and result—for compliance and debugging\. - Authorization Server: The OAuth component responsible for authenticating users or agents, obtaining consent, and issuing access and refresh tokens\. - Backpressure: A mechanism where, under high load, the API signals clients \(or MCP servers\) to slow down—often by returning 429s or by queuing requests\. - Caching: Storing recent responses \(e\.g\., GET results\) to serve repeated agent requests quickly and reduce backend load\. - Concurrency: The number of simultaneous requests allowed for a given client or token; a concurrency cap prevents agents from spawning runaway parallel calls\. - Critic Model: A secondary AI that reviews or “critiques” an agent’s proposed actions or outputs—e\.g\., to catch policy violations or potential side effects before execution\. - Deprecation: The process of marking an API endpoint, parameter, or version as obsolete, signaling clients \(and agents\) to migrate to newer alternatives while maintaining backward\-compatibility for a transition period\. - DDoS / DoS: DoS: Denial of Service—overloading a service with requests from one client\. DDoS: Distributed DoS—from multiple clients or agents acting in concert\. - Field Selection \(Partial Responses\): A mechanism allowing clients or agents to specify which fields they want in the response payload, minimizing data transfer and parsing work\. - GraphQL: A query language and runtime for APIs that lets clients define exactly the structure of the data they need—often used to aggregate related resources in one request and avoid over\- or under\-fetching\. - HITL \(Human in the Loop\): A review step where a human reviews or authorizes critical agent actions—used when full automation carries unacceptable risk\. - HTTP 200 / 4xx / 429 / 500: 200: Success status code\. 4xx: Client error \(e\.g\., 400 Bad Request, 404 Not Found\)\. 429: Too Many Requests \(rate limit exceeded\)\. 500: Server error\. Agents must interpret these codes correctly—e\.g\., treat 429 as a throttle signal\. - HTTP/2: The second major version of the HTTP protocol, introducing multiplexed streams over a single connection, header compression, and improved performance for parallel API calls\. - HTTP/3: The third HTTP version, built on the QUIC transport protocol, offering faster connection establishment, built\-in encryption, and better resilience to network changes\. - Identity Claims: Metadata within a JWT or HTTP headers \(e\.g\., sub, x\-user\-id\) that assert who \(user or agent\) is making a request\. - JWT \(JSON Web Token\): A compact, URL\-safe token format that carries signed \(and optionally encrypted\) JSON claims, commonly used as OAuth access tokens and to convey identity metadata\. - JSON\-RPC: A lightweight, text\-based remote procedure call protocol \(using JSON\) that defines how to structure requests and responses—forming the backbone of MCP messaging\. - Least Privilege: A security principle: grant only the minimal scopes or permissions necessary for an agent \(or user\) to perform its job, limiting blast radius if compromised\. - MCP \(Model Context Protocol\): An open standard that defines how AI agents \(“hosts”\) interact with tools and services \(“servers”\) via a uniform JSON\-RPC interface, enabling policy enforcement, input validation, and observability\. - MCP Client: A library or module embedded in the agent that formats action requests into MCP’s JSON\-RPC messages and handles responses\. - MCP Host: The component \(usually the AI agent or orchestrator\) that issues MCP requests for actions, passing in context and parameters\. - MCP Server: The adapter layer wrapping an existing API: it accepts MCP calls, enforces policies \(rate limits, scopes\), translates them into actual API requests, and returns normalized results\. - Observability: The practice of instrumenting APIs and MCP servers with metrics, logs, and traces so you can monitor agent usage patterns, errors, and performance in real time\. - OAuth 2\.1: The latest OAuth standard that mandates secure flows \(including PKCE\), refresh tokens, and improved security defaults for authorizing clients \(human or agentic\) to access protected APIs\. - OpenAPI / OAS: A machine\-readable standard for describing RESTful APIs \(endpoints, parameters, schemas, responses\), which agents use to discover and structure calls\. - PKCE: An extension to OAuth’s authorization code flow that prevents interception attacks by requiring a cryptographic challenge/verifier pair during the token exchange\. - Polling: A client repeatedly asking an API for updates \(e\.g\., every few seconds\), which can be costly at scale—agents often resort to polling when no push mechanism exists\. - Prompt Injection: Attacks where malicious inputs are embedded in prompts \(or API parameters\) to alter agent behavior or bypass safety guardrails\. - Rate Limiting: Controls that cap the number of API requests per time unit \(per user, per token, or per agent\) to protect backend services\. - Refresh Token: A long\-lived credential used to obtain new access tokens once the original access token expires, without requiring user re\-authentication\. - Resource Server: The API endpoint\(s\) that host protected resources; they validate incoming access tokens and enforce scope\-based access control before serving data\. - Retry Logic: Automatic client or server logic that retries transient failures \(e\.g\., network hiccups or 5xx errors\) according to backoff policies\. - Retry\-After Header: An HTTP response header \(typically in a 429 or 503 response\) indicating how long a client should wait before retrying the same request\. - Sandbox Environment: An isolated test instance of an API \(often with mock or anonymized data\) where agents can safely exercise calls without impacting production services\. - Schema Validation: Automated checking of request or response payloads against the data types, required fields, and constraints defined in an OpenAPI spec \(or JSON Schema\)\. - Scoped API Key: A credential \(token or API key\) limited to specific operations or data sets, binding the key to certain scopes for least\-privilege access\. - SDK \(Client Library\): A software development kit or code library provided \(or generated from an OpenAPI spec\) to simplify integration with an API—wrapping raw HTTP calls in native language constructs\. - Server\-Sent Events \(SSE\): A one\-way streaming protocol over HTTP where the server pushes real\-time event data to the client—useful for live updates without polling\. - Service Level Agreement \(SLA\): A formal contract between a service provider and consumer that defines expected availability, performance metrics, and remedies or penalties if those targets aren’t met\. - Service Level Objective \(SLO\): A specific performance or availability target \(e\.g\., “99\.9% uptime”\) within an SLA, used to measure and drive reliability improvements\. - Token Exchange: The process of swapping one OAuth credential for another \(e\.g\., exchanging an authorization code for an access token, or an access token for a refresh token\)\. - Tool Abstraction: Hiding the complexity of underlying APIs behind higher\-level “actions” or templates \(as in MCP\), so agents can operate on business terms rather than raw endpoints\. - Tool Poisoning: When an agent’s training data includes malicious or outdated tool descriptions/specs, leading it to generate harmful or incorrect API calls\. - Versioning: The practice of assigning distinct version identifiers \(e\.g\., v1, v2\) to an API’s changes, enabling clients and agents to adopt new features predictably while preserving older functionality\. - Verifier Chain: A sequence of automated checks \(schema validation, policy enforcement, critic model\) that each action passes through to ensure safety and correctness\. - Webhook: A push\-based mechanism where the API provider sends an HTTP callback to a client \(or agent\) when events occur, reducing the need for polling\. - x\-original\-auth\-sub: A header carrying the subject claim \(sub\) from the original user authentication token, so downstream services know which human authorized the agent’s request\. - x\-user\-id: A custom HTTP header that MCP servers or APIs use to forward the originating human user’s identifier, enabling per\-user attribution of agent actions\. ### About APIContext APIContext eliminates blind spots for enterprises across the digital delivery chain with proactive synthetic monitoring, performance analytics, and automated conformance validation\. Our platform delivers actionable insights so connected systems perform and conform—ensuring every interaction is trusted, secure, and compliant\. What are your APIs saying to AI? Contact us to find out\. - [Contact us to find out](/contact) ## Key facts - 75% had at least one nonconformant endpoint — Share of tested APIs where live behavior diverged from the published spec on one or more endpoints\. - 25% matched their spec on no endpoint at all — Share of tested APIs whose documentation was so out\-of\-sync that none of the tested endpoints matched the spec\. - 89% of specs were more than six months stale — Share of OpenAPI specifications that had not been updated in the previous six months\. - The MCP server is the enforcement layer where exposed actions, input validation, rate limits, and required scopes are decided\. - MCP requires OAuth 2\.1 with PKCE, and treats the MCP server as both resource server and authorization server\. - MCP servers must forward human identity claims \(for example x\-user\-id or x\-original\-auth\-sub\) so agent actions stay attributable\. - Rate limiting for agents needs concurrency caps per token, dynamic throttling, separate read/write quotas, and circuit breakers rather than a flat calls\-per\-second limit\. - The full report is published as HTML with no registration gate; the PDF is optional\. ## Primary entities - APIContext - Agentic AI - API drift - Model Context Protocol - MCP server - OpenAPI specification - OAuth 2\.1 - PKCE - API rate limiting - API observability ## Audience - API product owners - platform teams - technology leaders - AI engineering teams - SRE teams ## Primary links - [Read the full white paper](/resources/api-readiness-for-agentic-ai-white-paper) - [Download the PDF](/resources/api-readiness-for-agentic-ai-white-paper#download) - [Talk to APIContext](/contact) --- # API Runtime Governance: Shift Left Will Not Protect You Canonical URL: https://apicontext.com/resources/api-run-time-governance-shift-left-will-not-protect-you Source: static Description: Shift\-left catches design\-time issues, but runtime is where APIs actually fail\. Watch this APIContext video on why runtime governance is essential\. ## Summary API run\-time governance: Shift left will not protect you\. Shift\-left practices — design\-time linting, contract testing, and pre\-deployment validation — are valuable\. But they address the API as it was built, not as it behaves under real load, with real traffic, from real locations\. ## Page sections ### API run\-time governance: Shift left will not protect you Shift\-left practices — design\-time linting, contract testing, and pre\-deployment validation — are valuable\. But they address the API as it was built, not as it behaves under real load, with real traffic, from real locations\. This video makes the case for runtime governance as a distinct and necessary layer: why production behaviour diverges from design intent, and what monitoring provides that shift\-left practices simply cannot\. ## Key facts - Shift\-left practices — design\-time linting, contract testing, and pre\-deployment validation — are valuable\. But they address the API as it was built, not as it behaves under real load, with real traffic, from real locations\. - This video makes the case for runtime governance as a distinct and necessary layer: why production behaviour diverges from design intent, and what monitoring provides that shift\-left practices simply cannot\. ## Primary entities - APIContext - Video - API run\-time governance: Shift left will not protect you - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # API Security: Logic Abuse, Blind Spots and Hacking a Bank Canonical URL: https://apicontext.com/resources/api-security-challenges-logic-abuse-blind-spots-and-hacking-a-bank Source: static Description: Real API security attacks exploit logic, not just vulnerabilities\. Watch this APIContext video on the security challenges that matter most\. ## Summary API security challenges: Logic abuse, blind spots, and hacking a bank\. The most dangerous API security attacks often exploit business logic rather than technical vulnerabilities — they use the API exactly as documented, but in ways the designers never intended\. These attacks are invisible to tools that look only for known vulnerability patterns\. ## Page sections ### API security challenges: Logic abuse, blind spots, and hacking a bank The most dangerous API security attacks often exploit business logic rather than technical vulnerabilities — they use the API exactly as documented, but in ways the designers never intended\. These attacks are invisible to tools that look only for known vulnerability patterns\. This video examines the security challenges that logic abuse and blind spots create, using the example of attacking a bank API to illustrate how real\-world exploits work and why visibility into API behaviour — not just authentication and encryption — is essential\. ## Key facts - The most dangerous API security attacks often exploit business logic rather than technical vulnerabilities — they use the API exactly as documented, but in ways the designers never intended\. These attacks are invisible to tools that look only for known vulnerability patterns\. - This video examines the security challenges that logic abuse and blind spots create, using the example of attacking a bank API to illustrate how real\-world exploits work and why visibility into API behaviour — not just authentication and encryption — is essential\. ## Primary entities - APIContext - Video - API security challenges: Logic abuse, blind spots, and hacking a bank - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # API Security Tips Canonical URL: https://apicontext.com/resources/api-security-tips Source: static Description: Download the APIContext infographic on API security tips\. Practical guidance for teams securing APIs in production environments\. ## Summary API Security Tips\. API security covers a wide range of concerns — from authentication and authorisation to rate limiting, input validation, and monitoring for anomalous behaviour\. This infographic highlights the most impactful security practices for teams managing production APIs\. ## Page sections ### API Security Tips API security covers a wide range of concerns — from authentication and authorisation to rate limiting, input validation, and monitoring for anomalous behaviour\. This infographic highlights the most impactful security practices for teams managing production APIs\. Download the PDF or view the infographic below\. ## Key facts - API security covers a wide range of concerns — from authentication and authorisation to rate limiting, input validation, and monitoring for anomalous behaviour\. This infographic highlights the most impactful security practices for teams managing production APIs\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - API Security Tips - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/API%20Security%20Tips-1.pdf) - [Request a demo](/contact) --- # API Vulnerabilities, AI and Shadow IT Canonical URL: https://apicontext.com/resources/api-vulnerabilities-ai-and-shadow-it Source: static Description: AI\-generated integrations and shadow IT are expanding the API attack surface in ways most security teams haven't anticipated\. Watch this APIContext video\. ## Summary API vulnerabilities, AI, and Shadow IT\. AI\-assisted development is accelerating the creation of API integrations across organisations — including integrations that security teams never reviewed, compliance never approved, and operations never knew about\. This is shadow IT at a new scale\. ## Page sections ### API vulnerabilities, AI, and Shadow IT AI\-assisted development is accelerating the creation of API integrations across organisations — including integrations that security teams never reviewed, compliance never approved, and operations never knew about\. This is shadow IT at a new scale\. This video explores how AI\-generated code and shadow API usage are expanding the attack surface, what the specific vulnerability patterns look like, and what monitoring and governance approaches help teams maintain control of an API estate that is growing faster than traditional processes can track\. ## Key facts - AI\-assisted development is accelerating the creation of API integrations across organisations — including integrations that security teams never reviewed, compliance never approved, and operations never knew about\. This is shadow IT at a new scale\. - This video explores how AI\-generated code and shadow API usage are expanding the attack surface, what the specific vulnerability patterns look like, and what monitoring and governance approaches help teams maintain control of an API estate that is growing faster than traditional processes can track\. ## Primary entities - APIContext - Video - API vulnerabilities, AI, and Shadow IT - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Case Study – Telco Operator Canonical URL: https://apicontext.com/resources/apicontext-case-study-telco-operator Source: static Description: Learn how a telecom operator used APIContext to improve API performance, reduce incident response time, and meet SLA commitments to enterprise customers\. ## Summary Case Study: Telecom API Performance\. How a telecom operator improved API quality and SLA adherence with independent monitoring\.\. Learn how a telecom operator used APIContext to improve API performance, reduce incident response time, and meet SLA commitments to enterprise customers\. ## Page sections ### How a telecom operator improved API quality and SLA adherence with independent monitoring\. Category: Case study Telecom operators face significant pressure to deliver reliable APIs to enterprise customers, partners, and developers\. Internal monitoring frequently misses the performance and availability issues that matter most to external consumers\. This case study describes how a telecom operator implemented APIContext to gain independent visibility into their API estate, reduce incident response time, and produce the evidence needed to meet and demonstrate SLA compliance\. - How a telecom operator gained visibility that internal monitoring could not provide - The performance patterns that active monitoring surfaced in a telecom API estate - How monitoring data reduced incident detection and response time - Producing credible SLA evidence for enterprise customers and partners ## Key facts - Telecom operators face significant pressure to deliver reliable APIs to enterprise customers, partners, and developers\. Internal monitoring frequently misses the performance and availability issues that matter most to external consumers\. - This case study describes how a telecom operator implemented APIContext to gain independent visibility into their API estate, reduce incident response time, and produce the evidence needed to meet and demonstrate SLA compliance\. - How a telecom operator gained visibility that internal monitoring could not provide - The performance patterns that active monitoring surfaced in a telecom API estate - How monitoring data reduced incident detection and response time - Producing credible SLA evidence for enterprise customers and partners ## Primary entities - APIContext - Case study - Case Study: Telecom API Performance - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/apicontext-case-study-telco-operator) --- # APIContext Security Overview Canonical URL: https://apicontext.com/resources/apicontext-security-overview Source: static Description: Download the APIContext security overview — how active monitoring supports API security posture, compliance, and incident response\. ## Summary APIContext Security Overview\. How APIContext supports API security through continuous active monitoring\.\. Download the APIContext security overview — how active monitoring supports API security posture, compliance, and incident response\. ## Page sections ### How APIContext supports API security through continuous active monitoring\. Category: Product overview API security requires visibility that most security tools do not provide by default — behavioural baselines, anomaly detection across real traffic, and evidence that authentication and authorisation are working as intended\. This overview explains how APIContext's monitoring approach supports security teams, from detecting undocumented endpoints and shadow APIs to providing the audit trail that compliance and incident response require\. Complete the form to download the full overview\. - How active monitoring surfaces security\-relevant API behaviour - The specific security use cases APIContext addresses in production - How APIContext's evidence supports compliance and audit requirements - Integrating API monitoring with existing security tooling and workflows ## Key facts - API security requires visibility that most security tools do not provide by default — behavioural baselines, anomaly detection across real traffic, and evidence that authentication and authorisation are working as intended\. - This overview explains how APIContext's monitoring approach supports security teams, from detecting undocumented endpoints and shadow APIs to providing the audit trail that compliance and incident response require\. - Complete the form to download the full overview\. - How active monitoring surfaces security\-relevant API behaviour - The specific security use cases APIContext addresses in production - How APIContext's evidence supports compliance and audit requirements - Integrating API monitoring with existing security tooling and workflows ## Primary entities - APIContext - Product overview - APIContext Security Overview - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the overview](/resources/apicontext-security-overview) --- # Webcast: 5 Lessons From 3 Years of Open Banking Canonical URL: https://apicontext.com/resources/apicontext-webcast-5-lessons-learned-from-3-years-of-open-banking Source: static Description: Three years of Open Banking API monitoring has surfaced hard\-won lessons\. Watch this APIContext webcast for the key takeaways\. ## Summary APIContext Webcast: 5 Lessons Learned from 3 Years of Open Banking\. Three years of monitoring Open Banking APIs across UK banks has produced a body of evidence about what works, what doesn't, and where the industry keeps making the same mistakes\. This webcast brings together the most durable lessons from that period\. ## Page sections ### APIContext Webcast: 5 Lessons Learned from 3 Years of Open Banking Three years of monitoring Open Banking APIs across UK banks has produced a body of evidence about what works, what doesn't, and where the industry keeps making the same mistakes\. This webcast brings together the most durable lessons from that period\. From authentication reliability patterns to the relationship between documentation quality and API performance, this video distils five lessons that apply not just to Open Banking, but to any regulated API programme at scale\. ## Key facts - Three years of monitoring Open Banking APIs across UK banks has produced a body of evidence about what works, what doesn't, and where the industry keeps making the same mistakes\. This webcast brings together the most durable lessons from that period\. - From authentication reliability patterns to the relationship between documentation quality and API performance, this video distils five lessons that apply not just to Open Banking, but to any regulated API programme at scale\. ## Primary entities - APIContext - Video - APIContext Webcast: 5 Lessons Learned from 3 Years of Open Banking - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Webcast: API Lifecycle Runtime Governance Canonical URL: https://apicontext.com/resources/apicontext-webcast-series-highlights-api-lifecycle-runtime-governance Source: static Description: Runtime governance is the missing layer in most API lifecycle strategies\. Watch this APIContext webcast highlight\. ## Summary APIContext Webcast Series Highlights: API Lifecycle Runtime Governance\. Most API lifecycle frameworks focus on design, development, testing, and deployment\. Runtime governance — the ongoing verification that live APIs behave as intended — is frequently underspecified or left entirely to APM tools not designed for the job\. ## Page sections ### APIContext Webcast Series Highlights: API Lifecycle Runtime Governance Most API lifecycle frameworks focus on design, development, testing, and deployment\. Runtime governance — the ongoing verification that live APIs behave as intended — is frequently underspecified or left entirely to APM tools not designed for the job\. This highlight from the APIContext webcast series looks at how to incorporate runtime governance meaningfully into the API lifecycle, and what continuous measurement adds to the governance picture that lifecycle tooling alone cannot provide\. ## Key facts - Most API lifecycle frameworks focus on design, development, testing, and deployment\. Runtime governance — the ongoing verification that live APIs behave as intended — is frequently underspecified or left entirely to APM tools not designed for the job\. - This highlight from the APIContext webcast series looks at how to incorporate runtime governance meaningfully into the API lifecycle, and what continuous measurement adds to the governance picture that lifecycle tooling alone cannot provide\. ## Primary entities - APIContext - Video - APIContext Webcast Series Highlights: API Lifecycle Runtime Governance - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Webcast: Can You Trust Your API Data Canonical URL: https://apicontext.com/resources/apicontext-webcast-series-highlights-can-you-trust-your-api-data Source: static Description: The data your APIs return may not be as reliable as you think\. Watch this APIContext webcast highlight on API data trustworthiness\. ## Summary APIContext Webcast Series Highlights: Can you trust your API data?\. When an API returns data, teams typically assume it is accurate, current, and consistent\. But production API data is subject to caching inconsistencies, third\-party data quality issues, schema drift, and timing problems that are invisible to most monitoring setups\. ## Page sections ### APIContext Webcast Series Highlights: Can you trust your API data? When an API returns data, teams typically assume it is accurate, current, and consistent\. But production API data is subject to caching inconsistencies, third\-party data quality issues, schema drift, and timing problems that are invisible to most monitoring setups\. This highlight from the APIContext webcast series explores the data trust question from a monitoring perspective: what it means to verify that API data is actually reliable, and what active measurement reveals about the quality of what APIs return\. ## Key facts - When an API returns data, teams typically assume it is accurate, current, and consistent\. But production API data is subject to caching inconsistencies, third\-party data quality issues, schema drift, and timing problems that are invisible to most monitoring setups\. - This highlight from the APIContext webcast series explores the data trust question from a monitoring perspective: what it means to verify that API data is actually reliable, and what active measurement reveals about the quality of what APIs return\. ## Primary entities - APIContext - Video - APIContext Webcast Series Highlights: Can you trust your API data? - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Webcast: API Security Monitoring Canonical URL: https://apicontext.com/resources/apicontext-webcast-series-highlights-does-your-api-security-monitoring-do-what-you-think-it-does Source: static Description: Many teams overestimate what their API security monitoring actually covers\. Watch this APIContext webcast highlight to find out\. ## Summary APIContext Webcast Series Highlights: Does your API security monitoring do what you think it does?\. There is often a significant gap between what teams believe their API security monitoring covers and what it actually detects\. Assumptions about authentication coverage, anomaly detection, and third\-party API visibility frequently don't hold up under scrutiny\. ## Page sections ### APIContext Webcast Series Highlights: Does your API security monitoring do what you think it does? There is often a significant gap between what teams believe their API security monitoring covers and what it actually detects\. Assumptions about authentication coverage, anomaly detection, and third\-party API visibility frequently don't hold up under scrutiny\. This highlight from the APIContext webcast series examines the most common blind spots in API security monitoring setups, and what teams should verify before assuming their coverage is complete\. ## Key facts - There is often a significant gap between what teams believe their API security monitoring covers and what it actually detects\. Assumptions about authentication coverage, anomaly detection, and third\-party API visibility frequently don't hold up under scrutiny\. - This highlight from the APIContext webcast series examines the most common blind spots in API security monitoring setups, and what teams should verify before assuming their coverage is complete\. ## Primary entities - APIContext - Video - APIContext Webcast Series Highlights: Does your API security monitoring do what you think it does? - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Webcast: Give Developers the Tools Canonical URL: https://apicontext.com/resources/apicontext-webcast-series-highlights-give-developers-the-tools-they-need Source: static Description: Developers build better integrations when they have the right quality signals\. Watch this APIContext webcast highlight on equipping development teams\. ## Summary APIContext Webcast Series Highlights Give developers the tools they need\. Developers working with APIs need more than documentation\. They need real\-time performance data, meaningful error signals, and the ability to understand how their integration is behaving compared to the API's own performance baseline\. ## Page sections ### APIContext Webcast Series Highlights Give developers the tools they need Developers working with APIs need more than documentation\. They need real\-time performance data, meaningful error signals, and the ability to understand how their integration is behaving compared to the API's own performance baseline\. This highlight from the APIContext webcast series looks at what better tooling for developers looks like in practice, and how API providers can give developers the information they need to build more reliable integrations\. ## Key facts - Developers working with APIs need more than documentation\. They need real\-time performance data, meaningful error signals, and the ability to understand how their integration is behaving compared to the API's own performance baseline\. - This highlight from the APIContext webcast series looks at what better tooling for developers looks like in practice, and how API providers can give developers the information they need to build more reliable integrations\. ## Primary entities - APIContext - Video - APIContext Webcast Series Highlights Give developers the tools they need - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Webcast: Your API is a Product Canonical URL: https://apicontext.com/resources/apicontext-webcast-series-highlights-your-api-is-a-product Source: static Description: Treating your API as a product changes how you build, monitor, and improve it\. Watch this APIContext webcast highlight\. ## Summary APIContext Webcast Series Highlights: Your API is a Product\. The shift from treating APIs as internal plumbing to managing them as products changes the accountability model entirely\. API\-as\-product means defining what a good consumer experience looks like, measuring it continuously, and holding teams responsible for it\. ## Page sections ### APIContext Webcast Series Highlights: Your API is a Product The shift from treating APIs as internal plumbing to managing them as products changes the accountability model entirely\. API\-as\-product means defining what a good consumer experience looks like, measuring it continuously, and holding teams responsible for it\. This highlight from the APIContext webcast series explores what it means to run an API like a product in practice — the metrics that matter, the quality standards to set, and how active monitoring provides the feedback loop that product thinking requires\. ## Key facts - The shift from treating APIs as internal plumbing to managing them as products changes the accountability model entirely\. API\-as\-product means defining what a good consumer experience looks like, measuring it continuously, and holding teams responsible for it\. - This highlight from the APIContext webcast series explores what it means to run an API like a product in practice — the metrics that matter, the quality standards to set, and how active monitoring provides the feedback loop that product thinking requires\. ## Primary entities - APIContext - Video - APIContext Webcast Series Highlights: Your API is a Product - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Case Study – APILayer / Idera Canonical URL: https://apicontext.com/resources/apilayer-idera-api-health-transparency-case-study Source: static Description: Learn how APILayer moved from superficial uptime checks to meaningful API health insight, aligning teams and transforming its product roadmap\. ## Summary From Transparency to Trust: How APILayer Transformed its Roadmap\. How deeper API monitoring gave an API\-first business the shared visibility it needed to reshape its product strategy\.\. Learn how APILayer moved from superficial uptime checks to meaningful API health insight, aligning teams and transforming its product roadmap\. ## Page sections ### How deeper API monitoring gave an API\-first business the shared visibility it needed to reshape its product strategy\. Category: Case study As an API\-first business, APILayer depended on the reliability and performance of its platform to maintain customer trust\. But its existing monitoring relied on simple endpoint checks that failed to capture the true health of its APIs — creating a gap between reported uptime and actual customer experience\. By introducing deeper API\-level monitoring and performance insight, APILayer established a trusted, data\-driven view of product health\. The result was strategic alignment across product, engineering, and support — and a fundamental shift in roadmap priorities toward hardening existing APIs\. - How APILayer replaced superficial uptime checks with meaningful API health insight - Why aligning teams around a shared definition of API health changed the conversation - How data\-driven visibility shifted the roadmap from new development to platform hardening - The connection between trusted monitoring data and faster incident response ## Key facts - As an API\-first business, APILayer depended on the reliability and performance of its platform to maintain customer trust\. But its existing monitoring relied on simple endpoint checks that failed to capture the true health of its APIs — creating a gap between reported uptime and actual customer experience\. - By introducing deeper API\-level monitoring and performance insight, APILayer established a trusted, data\-driven view of product health\. The result was strategic alignment across product, engineering, and support — and a fundamental shift in roadmap priorities toward hardening existing APIs\. - How APILayer replaced superficial uptime checks with meaningful API health insight - Why aligning teams around a shared definition of API health changed the conversation - How data\-driven visibility shifted the roadmap from new development to platform hardening - The connection between trusted monitoring data and faster incident response ## Primary entities - APIContext - Case study - From Transparency to Trust: How APILayer Transformed its Roadmap - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/apilayer-idera-api-health-transparency-case-study) --- # APIs and the Dirty Word of Governance Canonical URL: https://apicontext.com/resources/apis-and-the-dirty-word-of-governance Source: static Description: Governance sounds bureaucratic, but without it API programs drift, break contracts, and create compliance risk\. Watch this APIContext video\. ## Summary APIs and the dirty word of governance\. API governance often gets a bad reputation — it sounds like process overhead that slows teams down\. But without it, APIs accumulate inconsistencies, break consumer contracts, and create risk that quietly compounds\. ## Page sections ### APIs and the dirty word of governance API governance often gets a bad reputation — it sounds like process overhead that slows teams down\. But without it, APIs accumulate inconsistencies, break consumer contracts, and create risk that quietly compounds\. This video examines what governance actually means in a production API context, where lightweight policies make the biggest difference, and how monitoring provides the evidence governance needs to be effective\. ## Key facts - API governance often gets a bad reputation — it sounds like process overhead that slows teams down\. But without it, APIs accumulate inconsistencies, break consumer contracts, and create risk that quietly compounds\. - This video examines what governance actually means in a production API context, where lightweight policies make the biggest difference, and how monitoring provides the evidence governance needs to be effective\. ## Primary entities - APIContext - Video - APIs and the dirty word of governance - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # APIs For Businesses Canonical URL: https://apicontext.com/resources/apis-for-businesses Source: static Description: How do APIs create business value? Download this APIContext infographic on the role of APIs in modern business operations and strategy\. ## Summary APIs For Businesses\. APIs drive business value in tangible ways: faster integrations, new product capabilities, partner ecosystem enablement, and more efficient operations\. This infographic maps the business case for APIs across different organisational contexts\. ## Page sections ### APIs For Businesses APIs drive business value in tangible ways: faster integrations, new product capabilities, partner ecosystem enablement, and more efficient operations\. This infographic maps the business case for APIs across different organisational contexts\. Download the PDF or view the infographic below\. ## Key facts - APIs drive business value in tangible ways: faster integrations, new product capabilities, partner ecosystem enablement, and more efficient operations\. This infographic maps the business case for APIs across different organisational contexts\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - APIs For Businesses - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/APIs%20for%20Businesses.pdf) - [Request a demo](/contact) --- # APIs Have Only Been Getting Faster Canonical URL: https://apicontext.com/resources/apis-have-only-been-getting-faster-report Source: static Description: Download APIContext's report on API performance trends — APIs are getting faster, but not uniformly\. See where progress is happening\. ## Summary APIs have only been getting faster – a report\. A data\-driven look at API performance trends and what is driving them\.\. Download APIContext's report on API performance trends — APIs are getting faster, but not uniformly\. See where progress is happening\. ## Page sections ### A data\-driven look at API performance trends and what is driving them\. Category: White paper Across APIContext's global measurement network, the headline finding is consistent: APIs have been getting faster over time\. But the trend is not uniform — progress has been concentrated in certain providers, regions, and API types, while others have stagnated\. This report examines the performance improvement trend in detail, identifying where gains have been most significant, what is driving them, and where the remaining performance gaps persist\. Use it as a data\-driven reference for benchmarking your API performance against the broader trend\. - The overall API performance improvement trend and what is driving it - Where performance gains have been most significant across providers and regions - The API types and environments where improvement has been slowest - How to benchmark your API performance against industry trends ## Key facts - Across APIContext's global measurement network, the headline finding is consistent: APIs have been getting faster over time\. But the trend is not uniform — progress has been concentrated in certain providers, regions, and API types, while others have stagnated\. - This report examines the performance improvement trend in detail, identifying where gains have been most significant, what is driving them, and where the remaining performance gaps persist\. - Use it as a data\-driven reference for benchmarking your API performance against the broader trend\. - The overall API performance improvement trend and what is driving it - Where performance gains have been most significant across providers and regions - The API types and environments where improvement has been slowest - How to benchmark your API performance against industry trends ## Primary entities - APIContext - White paper - APIs have only been getting faster – a report - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the report](/resources/apis-have-only-been-getting-faster-report) --- # APIs How They Help Businesses Canonical URL: https://apicontext.com/resources/apis-how-they-help-businesses Source: static Description: Download the APIContext infographic on how APIs help businesses operate, connect, and grow\. A clear overview for technical and business audiences\. ## Summary APIs How They Help Businesses\. APIs are the connective tissue of modern business operations — enabling integrations, powering digital experiences, and opening up new revenue channels\. This infographic explains the business value of APIs in concrete, accessible terms\. ## Page sections ### APIs How They Help Businesses APIs are the connective tissue of modern business operations — enabling integrations, powering digital experiences, and opening up new revenue channels\. This infographic explains the business value of APIs in concrete, accessible terms\. Download the PDF or view the infographic below\. ## Key facts - APIs are the connective tissue of modern business operations — enabling integrations, powering digital experiences, and opening up new revenue channels\. This infographic explains the business value of APIs in concrete, accessible terms\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - APIs How They Help Businesses - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/APIs%20How%20they%20help%20Businesses.pdf) - [Request a demo](/contact) --- # Are You Ready to Begin Leveraging APIs Canonical URL: https://apicontext.com/resources/are-you-ready-to-begin-leveraging-apis Source: static Description: Is your organisation ready to leverage APIs strategically? Download this APIContext infographic on the readiness factors that matter most\. ## Summary Are You Ready To Begin Leveraging APIs\. API adoption readiness involves more than technical capability\. Organisational readiness — governance structures, security posture, monitoring practices, and partner integration strategy — determines whether an API programme delivers lasting value or creates long\-term technical debt\. ## Page sections ### Are You Ready To Begin Leveraging APIs API adoption readiness involves more than technical capability\. Organisational readiness — governance structures, security posture, monitoring practices, and partner integration strategy — determines whether an API programme delivers lasting value or creates long\-term technical debt\. This infographic outlines the key readiness factors for organisations looking to leverage APIs strategically, helping teams assess where they stand and what to address before scaling their API programme\. ## Key facts - API adoption readiness involves more than technical capability\. Organisational readiness — governance structures, security posture, monitoring practices, and partner integration strategy — determines whether an API programme delivers lasting value or creates long\-term technical debt\. - This infographic outlines the key readiness factors for organisations looking to leverage APIs strategically, helping teams assess where they stand and what to address before scaling their API programme\. ## Primary entities - APIContext - Infographic - Are You Ready To Begin Leveraging APIs - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/Are%20you%20ready%20to%20begin%20leveraging%20APIs.pdf) - [Request a demo](/contact) --- # Being Aware of the Impact of API Failures Canonical URL: https://apicontext.com/resources/being-aware-of-the-impact-of-api-failures Source: static Description: API failures ripple further than most teams realise\. Watch this APIContext video on understanding the true blast radius of API incidents\. ## Summary Being Aware of the Impact of API Failures\. When an API fails, the visible symptoms — an error message, a failed transaction — are just the surface\. The real impact extends through dependent services, partner integrations, and customer journeys in ways that are often invisible to internal monitoring\. ## Page sections ### Being Aware of the Impact of API Failures When an API fails, the visible symptoms — an error message, a failed transaction — are just the surface\. The real impact extends through dependent services, partner integrations, and customer journeys in ways that are often invisible to internal monitoring\. This video explores how API failures propagate, why their full impact is so often underestimated, and how better observability changes the conversation around incident severity and response\. ## Key facts - When an API fails, the visible symptoms — an error message, a failed transaction — are just the surface\. The real impact extends through dependent services, partner integrations, and customer journeys in ways that are often invisible to internal monitoring\. - This video explores how API failures propagate, why their full impact is so often underestimated, and how better observability changes the conversation around incident severity and response\. ## Primary entities - APIContext - Video - Being Aware of the Impact of API Failures - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Best Practices for API Monitoring Canonical URL: https://apicontext.com/resources/best-practices-for-api-monitoring Source: static Description: Download the APIContext infographic on best practices for API monitoring\. Key principles for teams building reliable, observable API infrastructure\. ## Summary Best Practices For API Monitoring\. Effective API monitoring goes beyond checking whether an endpoint returns a 200\. This infographic summarises the key practices that separate teams with real API visibility from those flying blind\. ## Page sections ### Best Practices For API Monitoring Effective API monitoring goes beyond checking whether an endpoint returns a 200\. This infographic summarises the key practices that separate teams with real API visibility from those flying blind\. Download the PDF or view the infographic below\. ## Key facts - Effective API monitoring goes beyond checking whether an endpoint returns a 200\. This infographic summarises the key practices that separate teams with real API visibility from those flying blind\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - Best Practices For API Monitoring - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/Best%20Practices%20for%20API%20monitoring.pdf) - [Request a demo](/contact) --- # British High Street Bank Case Study Canonical URL: https://apicontext.com/resources/british-high-street-bank-open-banking-api-assurance Source: static Description: Learn how a major UK retail bank achieved reliable Open Banking API monitoring across regulated endpoints and real test accounts\. ## Summary British High Street Bank Open Banking API Performance\. Achieving reliable, regulated Open Banking monitoring on new cloud infrastructure\.\. Learn how a major UK retail bank achieved reliable Open Banking API monitoring across regulated endpoints and real test accounts\. ## Page sections ### Achieving reliable, regulated Open Banking monitoring on new cloud infrastructure\. Category: Case study When a major UK high street bank migrated its Open Banking APIs to new cloud infrastructure, it needed external monitoring that could handle the specific demands of regulated banking: real AISP and PISP test accounts, OBUK certificate handling, and performance measurement from the locations that matter\. APIContext was configured to test all required account types and API call paths from multiple global locations and cloud providers\. The bank now has continuous, independent visibility into its Open Banking API performance — with improved uptime and availability as the result\. - How to monitor Open Banking APIs using real production test accounts - Handling OBUK certificate requirements in an active monitoring setup - Measuring regulated API performance from multiple global locations - How independent external monitoring supports Open Banking compliance ## Key facts - When a major UK high street bank migrated its Open Banking APIs to new cloud infrastructure, it needed external monitoring that could handle the specific demands of regulated banking: real AISP and PISP test accounts, OBUK certificate handling, and performance measurement from the locations that matter\. - APIContext was configured to test all required account types and API call paths from multiple global locations and cloud providers\. The bank now has continuous, independent visibility into its Open Banking API performance — with improved uptime and availability as the result\. - How to monitor Open Banking APIs using real production test accounts - Handling OBUK certificate requirements in an active monitoring setup - Measuring regulated API performance from multiple global locations - How independent external monitoring supports Open Banking compliance ## Primary entities - APIContext - Case study - British High Street Bank Open Banking API Performance - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/british-high-street-bank-open-banking-api-assurance) --- # Caroline Lewko – Developers Key Decision Maker Canonical URL: https://apicontext.com/resources/caroline-lewko-of-revere-communications-developers-are-a-key-decision-maker-in-buying-and-using-your-tools Source: static Description: Caroline Lewko of Revere Communications on why developers are central to API tool purchase decisions and how to reach them effectively\. ## Summary Caroline Lewko of Revere Communications: Developers are a key decision maker in buying and using your tools\. Enterprise software buying decisions increasingly involve developers as active participants, not just end users\. Caroline Lewko of Revere Communications has studied how developers influence platform adoption decisions and what it takes to build credibility with them\. ## Page sections ### Caroline Lewko of Revere Communications: Developers are a key decision maker in buying and using your tools Enterprise software buying decisions increasingly involve developers as active participants, not just end users\. Caroline Lewko of Revere Communications has studied how developers influence platform adoption decisions and what it takes to build credibility with them\. This video covers why developer buy\-in matters even in top\-down enterprise sales, what developers look for when evaluating API tooling, and how organisations can better align their product and communication strategies to reach developer audiences\. ## Key facts - Enterprise software buying decisions increasingly involve developers as active participants, not just end users\. Caroline Lewko of Revere Communications has studied how developers influence platform adoption decisions and what it takes to build credibility with them\. - This video covers why developer buy\-in matters even in top\-down enterprise sales, what developers look for when evaluating API tooling, and how organisations can better align their product and communication strategies to reach developer audiences\. ## Primary entities - APIContext - Video - Caroline Lewko of Revere Communications: Developers are a key decision maker in buying and using your tools - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Caroline Lewko – How Developer Evaluates a Tool Canonical URL: https://apicontext.com/resources/caroline-lewko-of-revere-communications-how-does-a-developer-evaluate-a-new-tool Source: static Description: Caroline Lewko of Revere Communications on the developer evaluation process for new API tools and platforms\. ## Summary Caroline Lewko of Revere Communications – How does a developer evaluate a new tool?\. Developer tool adoption follows a different pattern from traditional enterprise software selection\. Developers evaluate primarily through direct experience — documentation quality, sandbox reliability, error message clarity, and the speed with which they can get something working\. ## Page sections ### Caroline Lewko of Revere Communications – How does a developer evaluate a new tool? Developer tool adoption follows a different pattern from traditional enterprise software selection\. Developers evaluate primarily through direct experience — documentation quality, sandbox reliability, error message clarity, and the speed with which they can get something working\. Caroline Lewko of Revere Communications breaks down the developer evaluation journey: the signals developers pay most attention to, the friction points that most commonly cause abandonment, and what API providers can do to optimise the experience\. ## Key facts - Developer tool adoption follows a different pattern from traditional enterprise software selection\. Developers evaluate primarily through direct experience — documentation quality, sandbox reliability, error message clarity, and the speed with which they can get something working\. - Caroline Lewko of Revere Communications breaks down the developer evaluation journey: the signals developers pay most attention to, the friction points that most commonly cause abandonment, and what API providers can do to optimise the experience\. ## Primary entities - APIContext - Video - Caroline Lewko of Revere Communications – How does a developer evaluate a new tool? - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Caroline Lewko – Developer Experience Canonical URL: https://apicontext.com/resources/caroline-lewko-of-revere-communications-talks-about-developer-experience Source: static Description: What does developer experience actually mean — and how do you measure it? Caroline Lewko of Revere Communications shares her perspective\. ## Summary Caroline Lewko of Revere Communications Talks About Developer Experience\. Developer experience has become a priority for platform teams, but it is often defined too narrowly — reduced to documentation quality or onboarding flows\. Caroline Lewko of Revere Communications argues for a broader definition that includes API reliability, performance, and the quality of the signals developers receive when things go wrong\. ## Page sections ### Caroline Lewko of Revere Communications Talks About Developer Experience Developer experience has become a priority for platform teams, but it is often defined too narrowly — reduced to documentation quality or onboarding flows\. Caroline Lewko of Revere Communications argues for a broader definition that includes API reliability, performance, and the quality of the signals developers receive when things go wrong\. This video explores what developer experience means across the full API interaction lifecycle, how it connects to platform adoption, and what teams can do to measure and improve it systematically\. ## Key facts - Developer experience has become a priority for platform teams, but it is often defined too narrowly — reduced to documentation quality or onboarding flows\. Caroline Lewko of Revere Communications argues for a broader definition that includes API reliability, performance, and the quality of the signals developers receive when things go wrong\. - This video explores what developer experience means across the full API interaction lifecycle, how it connects to platform adoption, and what teams can do to measure and improve it systematically\. ## Primary entities - APIContext - Video - Caroline Lewko of Revere Communications Talks About Developer Experience - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # CASC Scoring by APIContext Canonical URL: https://apicontext.com/resources/casc-scoring-by-apicontext Source: static Description: Download the APIContext product overview on CASC scoring — the Cloud API Service Consistency score that benchmarks API quality across dimensions\. ## Summary CASC Scoring by APIContext\. A structured approach to measuring and benchmarking API quality\.\. Download the APIContext product overview on CASC scoring — the Cloud API Service Consistency score that benchmarks API quality across dimensions\. ## Page sections ### A structured approach to measuring and benchmarking API quality\. Category: Product overview The CASC score — Cloud API Service Consistency — is APIContext's framework for measuring API quality across the dimensions that matter most: availability, performance, correctness, and consistency\. This product overview explains what CASC scoring measures, how it is calculated from active monitoring data, and how teams use it to benchmark APIs against industry standards and their own historical performance\. Complete the form to download the full overview\. - What the CASC score measures and how it is calculated - How to benchmark your APIs against industry standards - The CASC dimensions that correlate most strongly with consumer experience - How to track CASC score improvements over time ## Key facts - The CASC score — Cloud API Service Consistency — is APIContext's framework for measuring API quality across the dimensions that matter most: availability, performance, correctness, and consistency\. - This product overview explains what CASC scoring measures, how it is calculated from active monitoring data, and how teams use it to benchmark APIs against industry standards and their own historical performance\. - Complete the form to download the full overview\. - What the CASC score measures and how it is calculated - How to benchmark your APIs against industry standards - The CASC dimensions that correlate most strongly with consumer experience - How to track CASC score improvements over time ## Primary entities - APIContext - Product overview - CASC Scoring by APIContext - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the overview](/resources/casc-scoring-by-apicontext) --- # Case Study – New Zealand Ministry of Business Canonical URL: https://apicontext.com/resources/case-study-new-zealand-ministry-of-business Source: static Description: Learn how New Zealand's Ministry of Business used APIContext to monitor government API performance and support digital service delivery\. ## Summary Case Study: New Zealand Ministry of Business Government API Performance\. Independent API monitoring for government digital service delivery\.\. Learn how New Zealand's Ministry of Business used APIContext to monitor government API performance and support digital service delivery\. ## Page sections ### Independent API monitoring for government digital service delivery\. Category: Case study Government APIs support digital services that citizens and businesses depend on\. When those APIs underperform, the impact on service delivery is real and immediate — but without independent monitoring, the problems are often invisible to the teams responsible\. This case study describes how New Zealand's Ministry of Business, Innovation and Employment implemented APIContext to monitor government API performance, improve service reliability, and demonstrate quality to stakeholders\. - How independent monitoring improved government API service delivery - The performance and availability patterns found in public sector API estates - How monitoring data supported accountability and reporting requirements - Improving digital service quality through continuous API measurement ## Key facts - Government APIs support digital services that citizens and businesses depend on\. When those APIs underperform, the impact on service delivery is real and immediate — but without independent monitoring, the problems are often invisible to the teams responsible\. - This case study describes how New Zealand's Ministry of Business, Innovation and Employment implemented APIContext to monitor government API performance, improve service reliability, and demonstrate quality to stakeholders\. - How independent monitoring improved government API service delivery - The performance and availability patterns found in public sector API estates - How monitoring data supported accountability and reporting requirements - Improving digital service quality through continuous API measurement ## Primary entities - APIContext - Case study - Case Study: New Zealand Ministry of Business Government API Performance - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/case-study-new-zealand-ministry-of-business) --- # Case Study – Signify Canonical URL: https://apicontext.com/resources/case-study-signify Source: static Description: Learn how Signify used APIContext to identify and address API performance issues, improving reliability for their global connected lighting platform\. ## Summary Case Study – Signify API Performance Improvements\. How a global connected lighting leader improved API reliability with independent monitoring\.\. Learn how Signify used APIContext to identify and address API performance issues, improving reliability for their global connected lighting platform\. ## Page sections ### How a global connected lighting leader improved API reliability with independent monitoring\. Category: Case study Signify's connected lighting platform depends on APIs that perform consistently across global markets and diverse device ecosystems\. When performance issues emerged, Signify needed independent measurement to understand their true scope and location\. This case study describes how APIContext helped Signify identify performance problems that internal monitoring had not surfaced, and the improvements that followed from having accurate, geographically distributed visibility into their API estate\. - How independent monitoring surfaced performance issues invisible to internal tools - The geographic distribution of API performance problems in IoT environments - How measurement data drove targeted infrastructure improvements - The reliability improvements that resulted from addressing root\-cause performance issues ## Key facts - Signify's connected lighting platform depends on APIs that perform consistently across global markets and diverse device ecosystems\. When performance issues emerged, Signify needed independent measurement to understand their true scope and location\. - This case study describes how APIContext helped Signify identify performance problems that internal monitoring had not surfaced, and the improvements that followed from having accurate, geographically distributed visibility into their API estate\. - How independent monitoring surfaced performance issues invisible to internal tools - The geographic distribution of API performance problems in IoT environments - How measurement data drove targeted infrastructure improvements - The reliability improvements that resulted from addressing root\-cause performance issues ## Primary entities - APIContext - Case study - Case Study – Signify API Performance Improvements - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/case-study-signify) --- # 2024 Cloud Service Provider API Quality Report Canonical URL: https://apicontext.com/resources/cloud-service-provider-api-quality-industry-report-2024 Source: static Description: Download APIContext's 2024 Cloud Service Provider API Quality report\. ## Summary 2024 Cloud Service Provider API Quality Report\. Benchmark API quality across major cloud providers\.\. Download APIContext's 2024 Cloud Service Provider API Quality report\. ## Page sections ### Benchmark API quality across major cloud providers\. Category: Industry report Cloud APIs are the control plane for modern software\. When they slow down, fail, or behave inconsistently, entire digital services feel the impact\. This report looks at API quality through active measurements, helping teams compare provider behavior and understand where geography, routing, and platform choices matter\. Use it as a practical reference for cloud selection, vendor conversations, and reliability planning\. - How major cloud provider APIs compare on quality and consistency - Where network path, region, and provider differences show up - Why independent API measurements help teams make better cloud decisions - How API quality trends can inform resilience and procurement planning ## Key facts - Cloud APIs are the control plane for modern software\. When they slow down, fail, or behave inconsistently, entire digital services feel the impact\. - This report looks at API quality through active measurements, helping teams compare provider behavior and understand where geography, routing, and platform choices matter\. - Use it as a practical reference for cloud selection, vendor conversations, and reliability planning\. - How major cloud provider APIs compare on quality and consistency - Where network path, region, and provider differences show up - Why independent API measurements help teams make better cloud decisions - How API quality trends can inform resilience and procurement planning ## Primary entities - APIContext - Industry report - 2024 Cloud Service Provider API Quality Report - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the report](/resources/cloud-service-provider-api-quality-industry-report-2024) --- # Connect Times Have Dropped Dramatically Canonical URL: https://apicontext.com/resources/connect-times-have-dropped-dramatically Source: static Description: API connect times have improved significantly over recent years — but not uniformly\. Watch this APIContext video for a data\-driven look at the trend\. ## Summary Connect Times Have Dropped Dramatically\. Network connect times for APIs have fallen significantly over the past several years, driven by infrastructure investment and protocol improvements\. But the aggregate trend masks real variation across providers, regions, and API types\. ## Page sections ### Connect Times Have Dropped Dramatically Network connect times for APIs have fallen significantly over the past several years, driven by infrastructure investment and protocol improvements\. But the aggregate trend masks real variation across providers, regions, and API types\. This video presents data from APIContext's measurement network showing how connect times have evolved, where progress has been uneven, and what this means for teams benchmarking API performance\. ## Key facts - Network connect times for APIs have fallen significantly over the past several years, driven by infrastructure investment and protocol improvements\. But the aggregate trend masks real variation across providers, regions, and API types\. - This video presents data from APIContext's measurement network showing how connect times have evolved, where progress has been uneven, and what this means for teams benchmarking API performance\. ## Primary entities - APIContext - Video - Connect Times Have Dropped Dramatically - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # David O'Neill Open Banking Performance Canonical URL: https://apicontext.com/resources/david-oneill-talks-about-api-performance-security-using-data-from-a-real-open-banking-client Source: static Description: APIContext CEO David O'Neill shares real\-world Open Banking API performance and security data\. Watch the full discussion\. ## Summary David O'Neill talks about API Performance & Security using data from a real Open Banking client\. Real production data tells a different story than benchmark reports\. APIContext CEO David O'Neill walks through actual API performance and security observations from a live Open Banking client, showing what the numbers look like in practice\. ## Page sections ### David O'Neill talks about API Performance & Security using data from a real Open Banking client Real production data tells a different story than benchmark reports\. APIContext CEO David O'Neill walks through actual API performance and security observations from a live Open Banking client, showing what the numbers look like in practice\. This video covers how performance issues manifest in regulated API environments, the relationship between performance and security posture, and what the data reveals about the state of Open Banking API quality\. ## Key facts - Real production data tells a different story than benchmark reports\. APIContext CEO David O'Neill walks through actual API performance and security observations from a live Open Banking client, showing what the numbers look like in practice\. - This video covers how performance issues manifest in regulated API environments, the relationship between performance and security posture, and what the data reveals about the state of Open Banking API quality\. ## Primary entities - APIContext - Video - David O'Neill talks about API Performance & Security using data from a real Open Banking client - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Defining an API Quality Standard for SaaS and Cloud Canonical URL: https://apicontext.com/resources/defining-an-api-quality-standard-for-saas-and-cloud-services-white-paper Source: static Description: Download APIContext's white paper on defining API quality standards for SaaS and cloud services — what quality means and how to measure it\. ## Summary Defining an API Quality Standard for SaaS and Cloud Services\. The complete white paper, published in full — no registration required\.\. Download APIContext's white paper on defining API quality standards for SaaS and cloud services — what quality means and how to measure it\. ## Page sections ### The complete white paper, published in full — no registration required\. Category: White paper What does API quality actually mean for SaaS and cloud services? The answer involves more than uptime SLAs — it includes response time consistency, error rate distributions, authentication reliability, and the consumer experience across geographies\. This white paper proposes a practical quality standard framework for SaaS and cloud APIs, grounded in measurable dimensions and validated against real monitoring data from APIContext's global measurement network\. The full report is published on this page — no registration required\. The PDF version is also available through the form at the end of the page\. - The measurable dimensions of API quality in SaaS and cloud environments - How to set quality standards that are achievable and verifiable - What real monitoring data reveals about the baseline for good API quality - How to use a quality framework to drive continuous improvement ## Key facts - What does API quality actually mean for SaaS and cloud services? The answer involves more than uptime SLAs — it includes response time consistency, error rate distributions, authentication reliability, and the consumer experience across geographies\. - This white paper proposes a practical quality standard framework for SaaS and cloud APIs, grounded in measurable dimensions and validated against real monitoring data from APIContext's global measurement network\. - The full report is published on this page — no registration required\. The PDF version is also available through the form at the end of the page\. - The measurable dimensions of API quality in SaaS and cloud environments - How to set quality standards that are achievable and verifiable - What real monitoring data reveals about the baseline for good API quality - How to use a quality framework to drive continuous improvement ## Primary entities - APIContext - White paper - Defining an API Quality Standard for SaaS and Cloud Services - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Get the white paper](/resources/defining-an-api-quality-standard-for-saas-and-cloud-services-white-paper) --- # Digital Downtime is Done Canonical URL: https://apicontext.com/resources/digital-downtime-is-done-an-e-book-on-global-application-resilience-regulations Source: static Description: Download the APIContext ebook on global application resilience regulations\. ## Summary Digital Downtime is Done\. A practical guide to global application resilience regulations\.\. Download the APIContext ebook on global application resilience regulations\. ## Page sections ### A practical guide to global application resilience regulations\. Category: Ebook Regulators around the world are making operational resilience a board\-level issue\. Digital services need evidence, not assumptions, that critical journeys are working\. This ebook explains the shift toward resilience regulation and what it means for organizations that depend on APIs, partners, and cloud services\. Use it to frame monitoring, reporting, and governance work around the evidence regulators and customers increasingly expect\. - Why application resilience is becoming a regulatory priority - How API dependencies shape real customer and citizen experience - What evidence teams need when downtime becomes a governance issue - How active monitoring supports resilience reporting and accountability ## Key facts - Regulators around the world are making operational resilience a board\-level issue\. Digital services need evidence, not assumptions, that critical journeys are working\. - This ebook explains the shift toward resilience regulation and what it means for organizations that depend on APIs, partners, and cloud services\. - Use it to frame monitoring, reporting, and governance work around the evidence regulators and customers increasingly expect\. - Why application resilience is becoming a regulatory priority - How API dependencies shape real customer and citizen experience - What evidence teams need when downtime becomes a governance issue - How active monitoring supports resilience reporting and accountability ## Primary entities - APIContext - Ebook - Digital Downtime is Done - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the ebook](/resources/digital-downtime-is-done-an-e-book-on-global-application-resilience-regulations) --- # Ensuring Quality Service Delivery Canonical URL: https://apicontext.com/resources/ensuring-quality-service-delivery Source: static Description: Download the APIContext product overview on ensuring quality service delivery through active API monitoring and governance\. ## Summary Ensuring Quality Service Delivery\. How APIContext helps organisations maintain API quality at scale\.\. Download the APIContext product overview on ensuring quality service delivery through active API monitoring and governance\. ## Page sections ### How APIContext helps organisations maintain API quality at scale\. Category: Product overview Quality service delivery depends on APIs that behave consistently — for customers, partners, and internal teams\. When APIs drift, degrade, or fail, the impact on service quality is immediate and often difficult to diagnose\. This product overview explains how APIContext's active monitoring and governance capabilities help organisations maintain API quality across their entire estate, from development through production\. Complete the form to download the full overview\. - How active monitoring detects quality issues before they reach customers - The governance capabilities that maintain quality across the API lifecycle - How APIContext integrates with existing infrastructure and tooling - The monitoring approaches that deliver the most consistent quality improvements ## Key facts - Quality service delivery depends on APIs that behave consistently — for customers, partners, and internal teams\. When APIs drift, degrade, or fail, the impact on service quality is immediate and often difficult to diagnose\. - This product overview explains how APIContext's active monitoring and governance capabilities help organisations maintain API quality across their entire estate, from development through production\. - Complete the form to download the full overview\. - How active monitoring detects quality issues before they reach customers - The governance capabilities that maintain quality across the API lifecycle - How APIContext integrates with existing infrastructure and tooling - The monitoring approaches that deliver the most consistent quality improvements ## Primary entities - APIContext - Product overview - Ensuring Quality Service Delivery - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the overview](/resources/ensuring-quality-service-delivery) --- # Case Study – First Utility Power Company Canonical URL: https://apicontext.com/resources/first-utility-power-company-api-monitoring-case-study Source: static Description: Learn how First Utility \(now Shell Energy\) used APIContext to monitor their power company APIs and improve reliability for smart home integrations\. ## Summary First Utility \(Shell Energy\) Power Company API Monitoring Case Study\. API monitoring for energy company smart home and partner integrations\.\. Learn how First Utility \(now Shell Energy\) used APIContext to monitor their power company APIs and improve reliability for smart home integrations\. ## Page sections ### API monitoring for energy company smart home and partner integrations\. Category: Case study Energy companies depend on APIs to support smart home integrations, third\-party services, and partner ecosystems that customers actively use\. Reliability problems in these APIs translate directly into customer experience failures\. This case study describes how First Utility — now part of Shell Energy — used APIContext to monitor the performance and availability of their APIs across partner integrations, improving reliability and reducing the time to identify and resolve issues\. - How API monitoring supported smart home and partner integration reliability - The performance patterns found in energy company API estates - How monitoring reduced time\-to\-detect for API performance issues - Improving customer experience through reliable API infrastructure ## Key facts - Energy companies depend on APIs to support smart home integrations, third\-party services, and partner ecosystems that customers actively use\. Reliability problems in these APIs translate directly into customer experience failures\. - This case study describes how First Utility — now part of Shell Energy — used APIContext to monitor the performance and availability of their APIs across partner integrations, improving reliability and reducing the time to identify and resolve issues\. - How API monitoring supported smart home and partner integration reliability - The performance patterns found in energy company API estates - How monitoring reduced time\-to\-detect for API performance issues - Improving customer experience through reliable API infrastructure ## Primary entities - APIContext - Case study - First Utility \(Shell Energy\) Power Company API Monitoring Case Study - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/first-utility-power-company-api-monitoring-case-study) --- # Five 9s Video Canonical URL: https://apicontext.com/resources/five-9s-the-elusive-goal Source: static Description: 99\.999% uptime sounds simple, but it demands more than most teams expect from their API infrastructure\. Watch this APIContext video\. ## Summary Five 9s, the Elusive Goal\. 99\.999% availability — five nines — allows just over five minutes of downtime per year\. It is a widely cited reliability target, but one that most API\-dependent services quietly miss\. ## Page sections ### Five 9s, the Elusive Goal 99\.999% availability — five nines — allows just over five minutes of downtime per year\. It is a widely cited reliability target, but one that most API\-dependent services quietly miss\. This video breaks down what five nines actually requires in practice, where teams commonly fall short, and how independent external monitoring helps close the gap between assumed and actual uptime\. ## Key facts - 99\.999% availability — five nines — allows just over five minutes of downtime per year\. It is a widely cited reliability target, but one that most API\-dependent services quietly miss\. - This video breaks down what five nines actually requires in practice, where teams commonly fall short, and how independent external monitoring helps close the gap between assumed and actual uptime\. ## Primary entities - APIContext - Video - Five 9s, the Elusive Goal - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # How API Monitoring Improves Customer Experience Canonical URL: https://apicontext.com/resources/how-api-monitoring-improves-customer-experience-satisfaction Source: static Description: API performance directly shapes customer experience\. View this APIContext infographic on the connection between API monitoring and customer satisfaction\. ## Summary How API Monitoring Improves Customer Experience & Satisfaction\. Customer experience is increasingly mediated by APIs — every transaction, notification, and integration depends on APIs performing reliably\. When APIs are slow or unreliable, customers feel it directly, even if they never see the underlying technology\. ## Page sections ### How API Monitoring Improves Customer Experience & Satisfaction Customer experience is increasingly mediated by APIs — every transaction, notification, and integration depends on APIs performing reliably\. When APIs are slow or unreliable, customers feel it directly, even if they never see the underlying technology\. This infographic illustrates the connection between API monitoring, performance improvement, and measurable gains in customer experience and satisfaction\. ## Key facts - Customer experience is increasingly mediated by APIs — every transaction, notification, and integration depends on APIs performing reliably\. When APIs are slow or unreliable, customers feel it directly, even if they never see the underlying technology\. - This infographic illustrates the connection between API monitoring, performance improvement, and measurable gains in customer experience and satisfaction\. ## Primary entities - APIContext - Infographic - How API Monitoring Improves Customer Experience & Satisfaction - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # How APIContext Observes UK Open Banking APIs Canonical URL: https://apicontext.com/resources/how-apicontext-observes-uk-open-banking-apis Source: static Description: See how APIContext monitors UK Open Banking APIs with real credentials, global test nodes, and continuous measurement\. Watch the overview\. ## Summary How APIContext Observes UK Open Banking APIs\. Monitoring UK Open Banking APIs requires more than a simple uptime check\. It means handling real AISP and PISP credentials, OBUK certificate authentication, and running from the locations that reflect where consumers and TPPs actually connect\. ## Page sections ### How APIContext Observes UK Open Banking APIs Monitoring UK Open Banking APIs requires more than a simple uptime check\. It means handling real AISP and PISP credentials, OBUK certificate authentication, and running from the locations that reflect where consumers and TPPs actually connect\. This video walks through how APIContext approaches Open Banking API observation — the technical setup, the measurement cadence, and how the resulting data gives banks and TPPs a clear, independent picture of API quality\. ## Key facts - Monitoring UK Open Banking APIs requires more than a simple uptime check\. It means handling real AISP and PISP credentials, OBUK certificate authentication, and running from the locations that reflect where consumers and TPPs actually connect\. - This video walks through how APIContext approaches Open Banking API observation — the technical setup, the measurement cadence, and how the resulting data gives banks and TPPs a clear, independent picture of API quality\. ## Primary entities - APIContext - Video - How APIContext Observes UK Open Banking APIs - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Latency is Still a Problem Canonical URL: https://apicontext.com/resources/latency-is-still-a-problem Source: static Description: Despite decades of infrastructure investment, API latency remains a live problem\. Watch this video on where latency comes from and how to fix it\. ## Summary Latency is Still a Problem\. Improved networking, CDNs, and distributed infrastructure have reduced latency for many workloads\. But API latency — the accumulated delay across authentication, backend processing, and response serialisation — remains a significant source of user experience degradation\. ## Page sections ### Latency is Still a Problem Improved networking, CDNs, and distributed infrastructure have reduced latency for many workloads\. But API latency — the accumulated delay across authentication, backend processing, and response serialisation — remains a significant source of user experience degradation\. This video looks at where API latency problems actually come from in modern architectures, why they resist simple fixes, and how measurement from diverse locations helps teams understand and prioritise latency improvements\. ## Key facts - Improved networking, CDNs, and distributed infrastructure have reduced latency for many workloads\. But API latency — the accumulated delay across authentication, backend processing, and response serialisation — remains a significant source of user experience degradation\. - This video looks at where API latency problems actually come from in modern architectures, why they resist simple fixes, and how measurement from diverse locations helps teams understand and prioritise latency improvements\. ## Primary entities - APIContext - Video - Latency is Still a Problem - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Leading SaaS Provider Partner SLA Assurance Canonical URL: https://apicontext.com/resources/leading-saas-provider-partner-sla-assurance Source: static Description: Learn how a leading SaaS provider used APIContext to assure API SLA delivery to partners and reduce SLA dispute resolution time\. ## Summary Leading SaaS Provider Partner SLA Assurance\. How a SaaS platform used independent monitoring to back its partner SLA commitments with evidence\.\. Learn how a leading SaaS provider used APIContext to assure API SLA delivery to partners and reduce SLA dispute resolution time\. ## Page sections ### How a SaaS platform used independent monitoring to back its partner SLA commitments with evidence\. Category: Case study When a SaaS provider makes API SLA commitments to partners, the ability to produce independent evidence of SLA adherence becomes a commercial necessity — both for managing disputes and for maintaining partner trust\. This case study describes how a leading SaaS provider implemented APIContext to provide continuous, independent measurement of their API performance against partner SLA thresholds, reducing dispute resolution time and strengthening partner relationships\. - How independent monitoring provides credible SLA evidence to partners - The measurement approach that reduced SLA dispute resolution time - How continuous monitoring changed the conversation with partner teams - Building trust through transparent API performance data ## Key facts - When a SaaS provider makes API SLA commitments to partners, the ability to produce independent evidence of SLA adherence becomes a commercial necessity — both for managing disputes and for maintaining partner trust\. - This case study describes how a leading SaaS provider implemented APIContext to provide continuous, independent measurement of their API performance against partner SLA thresholds, reducing dispute resolution time and strengthening partner relationships\. - How independent monitoring provides credible SLA evidence to partners - The measurement approach that reduced SLA dispute resolution time - How continuous monitoring changed the conversation with partner teams - Building trust through transparent API performance data ## Primary entities - APIContext - Case study - Leading SaaS Provider Partner SLA Assurance - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/leading-saas-provider-partner-sla-assurance) --- # Open Banking Lesson 1: Quicksand Canonical URL: https://apicontext.com/resources/lesson-1-of-open-banking-apis-quicksand Source: static Description: Open Banking API programmes often start on unstable foundations\. Watch APIContext's first Open Banking lesson on the quicksand ahead\. ## Summary Lesson 1 of Open Banking APIs: Quicksand\. Many Open Banking API programmes launch with confident timelines and then find themselves sinking\. The causes are usually the same: underestimated complexity, missing test infrastructure, and assumptions about third\-party behaviour that turn out to be wrong\. ## Page sections ### Lesson 1 of Open Banking APIs: Quicksand Many Open Banking API programmes launch with confident timelines and then find themselves sinking\. The causes are usually the same: underestimated complexity, missing test infrastructure, and assumptions about third\-party behaviour that turn out to be wrong\. This first instalment of APIContext's Open Banking series identifies the specific traps that create the quicksand effect — the issues that feel manageable early but compound into programme\-level delays when left unaddressed\. ## Key facts - Many Open Banking API programmes launch with confident timelines and then find themselves sinking\. The causes are usually the same: underestimated complexity, missing test infrastructure, and assumptions about third\-party behaviour that turn out to be wrong\. - This first instalment of APIContext's Open Banking series identifies the specific traps that create the quicksand effect — the issues that feel manageable early but compound into programme\-level delays when left unaddressed\. ## Primary entities - APIContext - Video - Lesson 1 of Open Banking APIs: Quicksand - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Open Banking Lesson 2: Documentation Canonical URL: https://apicontext.com/resources/lesson-2-of-open-banking-apis-documentation Source: static Description: Poor API documentation is one of the biggest barriers to Open Banking adoption\. Watch APIContext's second Open Banking lesson\. ## Summary Lesson 2 of Open Banking APIs: Documentation\. API documentation is often treated as an afterthought — written once at launch and rarely updated to reflect how the API actually behaves in production\. For Open Banking, where third\-party developers and TPPs rely on accurate specifications, this gap creates real friction\. ## Page sections ### Lesson 2 of Open Banking APIs: Documentation API documentation is often treated as an afterthought — written once at launch and rarely updated to reflect how the API actually behaves in production\. For Open Banking, where third\-party developers and TPPs rely on accurate specifications, this gap creates real friction\. This second instalment of APIContext's Open Banking series looks at what good API documentation requires, where the most common gaps appear, and how active monitoring helps keep documentation honest by surfacing discrepancies between spec and reality\. ## Key facts - API documentation is often treated as an afterthought — written once at launch and rarely updated to reflect how the API actually behaves in production\. For Open Banking, where third\-party developers and TPPs rely on accurate specifications, this gap creates real friction\. - This second instalment of APIContext's Open Banking series looks at what good API documentation requires, where the most common gaps appear, and how active monitoring helps keep documentation honest by surfacing discrepancies between spec and reality\. ## Primary entities - APIContext - Video - Lesson 2 of Open Banking APIs: Documentation - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Open Banking Lesson 3: Test Monitor Repeat Canonical URL: https://apicontext.com/resources/lesson-3-of-open-banking-apis-test-monitor-repeat Source: static Description: Continuous testing and monitoring is the operational cadence that Open Banking APIs require\. Watch APIContext's third Open Banking lesson\. ## Summary Lesson 3 of Open Banking APIs: Test Monitor Repeat\. Open Banking API quality is not a one\-time certification — it requires continuous verification\. APIs that pass testing at deployment can drift over time as infrastructure changes, third\-party dependencies evolve, and traffic patterns shift\. ## Page sections ### Lesson 3 of Open Banking APIs: Test Monitor Repeat Open Banking API quality is not a one\-time certification — it requires continuous verification\. APIs that pass testing at deployment can drift over time as infrastructure changes, third\-party dependencies evolve, and traffic patterns shift\. This third instalment of APIContext's Open Banking series focuses on the test\-monitor\-repeat cycle: what it looks like in practice, how to set it up without heavy overhead, and why continuous measurement is the only reliable source of API truth\. ## Key facts - Open Banking API quality is not a one\-time certification — it requires continuous verification\. APIs that pass testing at deployment can drift over time as infrastructure changes, third\-party dependencies evolve, and traffic patterns shift\. - This third instalment of APIContext's Open Banking series focuses on the test\-monitor\-repeat cycle: what it looks like in practice, how to set it up without heavy overhead, and why continuous measurement is the only reliable source of API truth\. ## Primary entities - APIContext - Video - Lesson 3 of Open Banking APIs: Test Monitor Repeat - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Open Banking Lesson 4: Can You Prove It Canonical URL: https://apicontext.com/resources/lesson-4-of-open-banking-apis-can-you-prove-it Source: static Description: Regulators and consumers expect evidence of API performance, not just assurances\. Watch APIContext's fourth Open Banking lesson on proving compliance\. ## Summary Lesson 4 of Open Banking APIs: Can You Prove It?\. In regulated environments, claiming that your APIs meet performance and availability standards is not enough\. Regulators, auditors, and sophisticated consumers increasingly expect independent, time\-stamped evidence — not just dashboards or internal metrics\. ## Page sections ### Lesson 4 of Open Banking APIs: Can You Prove It? In regulated environments, claiming that your APIs meet performance and availability standards is not enough\. Regulators, auditors, and sophisticated consumers increasingly expect independent, time\-stamped evidence — not just dashboards or internal metrics\. This fourth instalment of APIContext's Open Banking series explores what it means to actually prove API performance, what evidence looks like in practice, and why internal monitoring alone is not sufficient to meet the standard\. ## Key facts - In regulated environments, claiming that your APIs meet performance and availability standards is not enough\. Regulators, auditors, and sophisticated consumers increasingly expect independent, time\-stamped evidence — not just dashboards or internal metrics\. - This fourth instalment of APIContext's Open Banking series explores what it means to actually prove API performance, what evidence looks like in practice, and why internal monitoring alone is not sufficient to meet the standard\. ## Primary entities - APIContext - Video - Lesson 4 of Open Banking APIs: Can You Prove It? - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Open Banking Lesson 5: Frogs in Hot Water Canonical URL: https://apicontext.com/resources/lesson-5-of-open-banking-apis-frogs-in-hot-water Source: static Description: Gradual API degradation is easy to miss until it becomes a crisis\. Watch APIContext's fifth Open Banking lesson on the frog\-in\-hot\-water effect\. ## Summary Lesson 5 of Open Banking APIs: Frogs In Hot Water\. Gradual performance degradation is one of the most dangerous patterns in API operations\. Unlike sudden outages, slow decay is easy to normalise — teams adjust their expectations, thresholds creep upward, and the problem compounds until it becomes a customer\-facing crisis\. ## Page sections ### Lesson 5 of Open Banking APIs: Frogs In Hot Water Gradual performance degradation is one of the most dangerous patterns in API operations\. Unlike sudden outages, slow decay is easy to normalise — teams adjust their expectations, thresholds creep upward, and the problem compounds until it becomes a customer\-facing crisis\. This fifth instalment of APIContext's Open Banking lessons series uses the frog\-in\-hot\-water analogy to explore how this pattern appears in regulated API environments, and what it takes to detect it early\. ## Key facts - Gradual performance degradation is one of the most dangerous patterns in API operations\. Unlike sudden outages, slow decay is easy to normalise — teams adjust their expectations, thresholds creep upward, and the problem compounds until it becomes a customer\-facing crisis\. - This fifth instalment of APIContext's Open Banking lessons series uses the frog\-in\-hot\-water analogy to explore how this pattern appears in regulated API environments, and what it takes to detect it early\. ## Primary entities - APIContext - Video - Lesson 5 of Open Banking APIs: Frogs In Hot Water - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Luxury Retail Brand Case Study Canonical URL: https://apicontext.com/resources/luxury-retail-brand-misconfiguration-case-study Source: static Description: How outside\-in monitoring gave a global luxury retailer and its suppliers one shared account of the customer experience during an edge misconfiguration\. ## Summary When Nobody Can See the Whole Journey, Every Supplier Looks Guilty\. How outside\-in assurance reduced operational uncertainty across a complex digital supply chain\.\. How outside\-in monitoring gave a global luxury retailer and its suppliers one shared account of the customer experience during an edge misconfiguration\. ## Page sections ### How outside\-in assurance reduced operational uncertainty across a complex digital supply chain\. Category: Case study When localized storefronts became difficult to access in key international markets ahead of a high\-value sales weekend, a global luxury retailer needed answers fast\. But with an edge provider, implementation partner, localization specialists, and commerce platform each holding a different slice of the evidence, no single team could explain the customer experience\. Independent, in\-market monitoring gave every party one accepted account of the journey — before, during, and after a targeted edge security change — turning fragmented supplier arguments into a shared basis for accountability\. - How fragmented evidence across suppliers delays detection, resolution, and accountability - Why a home\-market\-only monitoring view misses critical international failures - How outside\-in assurance narrows the fault domain when multiple vendors share the delivery path - The relationship outcomes: earlier detection, faster resolution, faster innocence, and persistent assurance ## Key facts - When localized storefronts became difficult to access in key international markets ahead of a high\-value sales weekend, a global luxury retailer needed answers fast\. But with an edge provider, implementation partner, localization specialists, and commerce platform each holding a different slice of the evidence, no single team could explain the customer experience\. - Independent, in\-market monitoring gave every party one accepted account of the journey — before, during, and after a targeted edge security change — turning fragmented supplier arguments into a shared basis for accountability\. - How fragmented evidence across suppliers delays detection, resolution, and accountability - Why a home\-market\-only monitoring view misses critical international failures - How outside\-in assurance narrows the fault domain when multiple vendors share the delivery path - The relationship outcomes: earlier detection, faster resolution, faster innocence, and persistent assurance ## Primary entities - APIContext - Case study - When Nobody Can See the Whole Journey, Every Supplier Looks Guilty - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/luxury-retail-brand-misconfiguration-case-study) --- # Mariana Velázquez – Benchmark Developer Experience Canonical URL: https://apicontext.com/resources/mariana-velazquez-of-platformable-benchmark-analysis-of-the-developer-experience Source: static Description: Platformable's Mariana Velázquez on benchmarking developer experience across the API ecosystem\. Watch the discussion\. ## Summary Mariana Velázquez of Platformable – Benchmark Analysis of the Developer Experience\. Benchmarking developer experience requires a systematic approach that goes beyond individual surveys or anecdotes\. Platformable has developed a methodology for measuring developer experience across API ecosystems at scale, and the results surface patterns that individual providers often miss\. ## Page sections ### Mariana Velázquez of Platformable – Benchmark Analysis of the Developer Experience Benchmarking developer experience requires a systematic approach that goes beyond individual surveys or anecdotes\. Platformable has developed a methodology for measuring developer experience across API ecosystems at scale, and the results surface patterns that individual providers often miss\. Mariana Velázquez of Platformable discusses how benchmark analysis of developer experience works, what the data shows about the current state of developer experience in the API economy, and how organisations can use this kind of analysis to improve\. ## Key facts - Benchmarking developer experience requires a systematic approach that goes beyond individual surveys or anecdotes\. Platformable has developed a methodology for measuring developer experience across API ecosystems at scale, and the results surface patterns that individual providers often miss\. - Mariana Velázquez of Platformable discusses how benchmark analysis of developer experience works, what the data shows about the current state of developer experience in the API economy, and how organisations can use this kind of analysis to improve\. ## Primary entities - APIContext - Video - Mariana Velázquez of Platformable – Benchmark Analysis of the Developer Experience - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Mariana Velázquez – Open Banking Initiatives Growing Canonical URL: https://apicontext.com/resources/mariana-velazquez-of-platformable-how-open-banking-initiatives-are-growing Source: static Description: Platformable's Mariana Velázquez on the growth of Open Banking initiatives globally and what it means for API quality and monitoring\. ## Summary Mariana Velázquez of Platformable – How Open Banking Initiatives Are Growing\. Open Banking has moved beyond its early regulatory implementations in the UK and EU\. Platformable's research tracks the global expansion of open banking and open finance initiatives, and the picture is one of sustained, broad growth\. ## Page sections ### Mariana Velázquez of Platformable – How Open Banking Initiatives Are Growing Open Banking has moved beyond its early regulatory implementations in the UK and EU\. Platformable's research tracks the global expansion of open banking and open finance initiatives, and the picture is one of sustained, broad growth\. Mariana Velázquez of Platformable discusses what that growth looks like in data, the quality challenges that come with rapid API ecosystem expansion, and what it means for organisations operating or building on open banking infrastructure\. ## Key facts - Open Banking has moved beyond its early regulatory implementations in the UK and EU\. Platformable's research tracks the global expansion of open banking and open finance initiatives, and the picture is one of sustained, broad growth\. - Mariana Velázquez of Platformable discusses what that growth looks like in data, the quality challenges that come with rapid API ecosystem expansion, and what it means for organisations operating or building on open banking infrastructure\. ## Primary entities - APIContext - Video - Mariana Velázquez of Platformable – How Open Banking Initiatives Are Growing - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Mariana Velázquez – API Performance vs Competitors Canonical URL: https://apicontext.com/resources/mariana-velazquez-of-platformable-understanding-api-performance-compared-to-competitors Source: static Description: Platformable's Mariana Velázquez on understanding how your API performance compares to competitors\. Watch the discussion\. ## Summary Mariana Velázquez of Platformable – Understanding API Performance Compared to Competitors\. Understanding your API's performance in isolation is useful\. Understanding it relative to your competitors gives you a materially different kind of intelligence — one that informs product positioning, investment decisions, and customer conversations\. ## Page sections ### Mariana Velázquez of Platformable – Understanding API Performance Compared to Competitors Understanding your API's performance in isolation is useful\. Understanding it relative to your competitors gives you a materially different kind of intelligence — one that informs product positioning, investment decisions, and customer conversations\. Platformable's Mariana Velázquez discusses how benchmarking API performance against competitors works in practice, what the data tends to show, and why independent measurement is essential for meaningful comparison\. ## Key facts - Understanding your API's performance in isolation is useful\. Understanding it relative to your competitors gives you a materially different kind of intelligence — one that informs product positioning, investment decisions, and customer conversations\. - Platformable's Mariana Velázquez discusses how benchmarking API performance against competitors works in practice, what the data tends to show, and why independent measurement is essential for meaningful comparison\. ## Primary entities - APIContext - Video - Mariana Velázquez of Platformable – Understanding API Performance Compared to Competitors - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Measuring Performance Where Your Users Are Canonical URL: https://apicontext.com/resources/measuring-performance-where-your-users-are Source: static Description: API performance measured from your data centre does not reflect what users experience\. Watch this APIContext video on geographic performance measurement\. ## Summary Measuring Performance Where Your Users Are\. API performance tests run from a single location tell you how the API performs from that location\. For most real\-world applications, your users are distributed across geographies, cloud regions, and network paths that produce meaningfully different latency and reliability profiles\. ## Page sections ### Measuring Performance Where Your Users Are API performance tests run from a single location tell you how the API performs from that location\. For most real\-world applications, your users are distributed across geographies, cloud regions, and network paths that produce meaningfully different latency and reliability profiles\. This video covers why geographic distribution of API monitoring matters, what the performance differences look like in practice, and how measuring from where your users actually are changes what you know about your API's quality\. ## Key facts - API performance tests run from a single location tell you how the API performs from that location\. For most real\-world applications, your users are distributed across geographies, cloud regions, and network paths that produce meaningfully different latency and reliability profiles\. - This video covers why geographic distribution of API monitoring matters, what the performance differences look like in practice, and how measuring from where your users actually are changes what you know about your API's quality\. ## Primary entities - APIContext - Video - Measuring Performance Where Your Users Are - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Monitoring the Untestable – Open Banking White Paper Canonical URL: https://apicontext.com/resources/monitoring-the-untestable-open-banking-psd2-white-paper Source: static Description: Download APIContext's white paper on monitoring Open Banking PSD2 APIs — how to test what can't be unit tested and measure what regulators require\. ## Summary Monitoring the Untestable – An Open Banking White Paper from APIContext\. How to achieve continuous quality assurance for APIs that can't be unit tested\.\. Download APIContext's white paper on monitoring Open Banking PSD2 APIs — how to test what can't be unit tested and measure what regulators require\. ## Page sections ### How to achieve continuous quality assurance for APIs that can't be unit tested\. Category: White paper Open Banking APIs under PSD2 are not easily testable with conventional unit or integration testing approaches\. They require real credentials, regulated authentication flows, and external measurement to verify that they are working as required\. This white paper explores the monitoring challenge that PSD2 creates, the gaps that conventional testing approaches leave, and how active monitoring from external vantage points provides the continuous quality assurance that regulated Open Banking environments require\. It is an essential reference for teams responsible for PSD2 compliance and Open Banking API quality\. - Why PSD2 Open Banking APIs require a different monitoring approach - The specific gaps that conventional testing leaves in regulated environments - How active external monitoring addresses the untestable problem - The evidence that regulators and compliance teams need from API monitoring ## Key facts - Open Banking APIs under PSD2 are not easily testable with conventional unit or integration testing approaches\. They require real credentials, regulated authentication flows, and external measurement to verify that they are working as required\. - This white paper explores the monitoring challenge that PSD2 creates, the gaps that conventional testing approaches leave, and how active monitoring from external vantage points provides the continuous quality assurance that regulated Open Banking environments require\. - It is an essential reference for teams responsible for PSD2 compliance and Open Banking API quality\. - Why PSD2 Open Banking APIs require a different monitoring approach - The specific gaps that conventional testing leaves in regulated environments - How active external monitoring addresses the untestable problem - The evidence that regulators and compliance teams need from API monitoring ## Primary entities - APIContext - White paper - Monitoring the Untestable – An Open Banking White Paper from APIContext - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the white paper](/resources/monitoring-the-untestable-open-banking-psd2-white-paper) --- # OAuth – The Standard That Isn't Canonical URL: https://apicontext.com/resources/oauth-the-standard-that-isnt-white-paper Source: static Description: Download APIContext's white paper on OAuth implementation inconsistency — why OAuth is less of a standard than teams assume\. ## Summary OAuth – The Standard That Isn't\. The implementation inconsistency that makes OAuth a reliability risk\.\. Download APIContext's white paper on OAuth implementation inconsistency — why OAuth is less of a standard than teams assume\. ## Page sections ### The implementation inconsistency that makes OAuth a reliability risk\. Category: White paper OAuth is widely described as the standard for API authentication and authorisation\. In practice, OAuth implementations vary so significantly between providers that many teams spend more time handling edge cases than the standard itself anticipated\. This white paper documents the OAuth implementation inconsistency problem — the specific divergences between providers, the authentication failures they cause in production, and what teams can do to build more reliable OAuth\-dependent integrations\. It is essential reading for teams managing APIs that use OAuth for authentication across multiple providers\. - Where OAuth implementations diverge between providers in practice - The authentication failures that OAuth inconsistency causes in production - How active monitoring helps teams detect OAuth reliability problems - Practical approaches to building more resilient OAuth\-dependent integrations ## Key facts - OAuth is widely described as the standard for API authentication and authorisation\. In practice, OAuth implementations vary so significantly between providers that many teams spend more time handling edge cases than the standard itself anticipated\. - This white paper documents the OAuth implementation inconsistency problem — the specific divergences between providers, the authentication failures they cause in production, and what teams can do to build more reliable OAuth\-dependent integrations\. - It is essential reading for teams managing APIs that use OAuth for authentication across multiple providers\. - Where OAuth implementations diverge between providers in practice - The authentication failures that OAuth inconsistency causes in production - How active monitoring helps teams detect OAuth reliability problems - Practical approaches to building more resilient OAuth\-dependent integrations ## Primary entities - APIContext - White paper - OAuth – The Standard That Isn't - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the white paper](/resources/oauth-the-standard-that-isnt-white-paper) --- # Old School Banks vs Cloud Native Canonical URL: https://apicontext.com/resources/old-school-banks-vs-cloud-native-api-first-uk-banks Source: static Description: Legacy bank APIs and cloud\-native challenger bank APIs perform very differently\. Watch this APIContext video comparing UK banking API quality\. ## Summary Old School Banks vs Cloud Native, API First UK Banks\. UK banking has two distinct cohorts: legacy institutions migrating their APIs onto new infrastructure, and cloud\-native challenger banks that built API\-first from day one\. The performance and reliability differences between them are measurable and significant\. ## Page sections ### Old School Banks vs Cloud Native, API First UK Banks UK banking has two distinct cohorts: legacy institutions migrating their APIs onto new infrastructure, and cloud\-native challenger banks that built API\-first from day one\. The performance and reliability differences between them are measurable and significant\. This video uses data from APIContext's Open Banking monitoring to compare how these two groups actually perform, where the legacy institutions are closing the gap, and what the data says about the trajectory of UK Open Banking API quality\. ## Key facts - UK banking has two distinct cohorts: legacy institutions migrating their APIs onto new infrastructure, and cloud\-native challenger banks that built API\-first from day one\. The performance and reliability differences between them are measurable and significant\. - This video uses data from APIContext's Open Banking monitoring to compare how these two groups actually perform, where the legacy institutions are closing the gap, and what the data says about the trajectory of UK Open Banking API quality\. ## Primary entities - APIContext - Video - Old School Banks vs Cloud Native, API First UK Banks - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Open Banking API Monitoring Canonical URL: https://apicontext.com/resources/open-banking-api-monitoring Source: static Description: Download the APIContext product overview on Open Banking API monitoring — how to achieve continuous, independent quality assurance for regulated APIs\. ## Summary Open Banking API Monitoring – Ensuring Quality Open Banking Service Delivery\. Continuous, independent monitoring for regulated Open Banking APIs\.\. Download the APIContext product overview on Open Banking API monitoring — how to achieve continuous, independent quality assurance for regulated APIs\. ## Page sections ### Continuous, independent monitoring for regulated Open Banking APIs\. Category: Product overview Open Banking APIs carry real consumer data and are subject to regulatory requirements that standard monitoring tools were not designed to address\. Monitoring them properly requires real test credentials, OBUK certificate handling, and measurement from locations that reflect actual TPP traffic\. This product overview explains how APIContext approaches Open Banking API monitoring — the technical capabilities required, the regulatory evidence it produces, and how it helps institutions demonstrate compliance and improve consumer experience\. Complete the form to download the full overview\. - How to monitor Open Banking APIs with real AISP and PISP credentials - Handling OBUK certificates and regulated authentication flows - The availability and performance evidence regulators expect - How independent monitoring improves Open Banking consumer experience ## Key facts - Open Banking APIs carry real consumer data and are subject to regulatory requirements that standard monitoring tools were not designed to address\. Monitoring them properly requires real test credentials, OBUK certificate handling, and measurement from locations that reflect actual TPP traffic\. - This product overview explains how APIContext approaches Open Banking API monitoring — the technical capabilities required, the regulatory evidence it produces, and how it helps institutions demonstrate compliance and improve consumer experience\. - Complete the form to download the full overview\. - How to monitor Open Banking APIs with real AISP and PISP credentials - Handling OBUK certificates and regulated authentication flows - The availability and performance evidence regulators expect - How independent monitoring improves Open Banking consumer experience ## Primary entities - APIContext - Product overview - Open Banking API Monitoring – Ensuring Quality Open Banking Service Delivery - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the overview](/resources/open-banking-api-monitoring) --- # Our Recommendations Canonical URL: https://apicontext.com/resources/our-recommendations Source: static Description: APIContext's recommendations for teams building or improving their API monitoring practice\. Watch the video overview\. ## Summary Our Recommendations\. Based on years of measuring APIs across industries, cloud providers, and geographies, APIContext has developed a set of practical recommendations for teams working to improve API reliability, performance, and governance\. ## Page sections ### Our Recommendations Based on years of measuring APIs across industries, cloud providers, and geographies, APIContext has developed a set of practical recommendations for teams working to improve API reliability, performance, and governance\. This video summarises the recommendations that have the most consistent impact — the monitoring practices, measurement approaches, and governance decisions that separate teams with genuine API visibility from those operating on assumptions\. ## Key facts - Based on years of measuring APIs across industries, cloud providers, and geographies, APIContext has developed a set of practical recommendations for teams working to improve API reliability, performance, and governance\. - This video summarises the recommendations that have the most consistent impact — the monitoring practices, measurement approaches, and governance decisions that separate teams with genuine API visibility from those operating on assumptions\. ## Primary entities - APIContext - Video - Our Recommendations - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Performance Benchmarking Meets Developer Experience Canonical URL: https://apicontext.com/resources/performance-benchmarking-meets-developer-experience-a-holistic-approach-to-api-quality-and-maturity Source: static Description: API quality requires both performance data and developer experience measurement\. Watch this APIContext video on the holistic approach\. ## Summary Performance Benchmarking Meets Developer Experience: A Holistic Approach to API Quality and Maturity\. API quality has two dimensions that are often measured separately: technical performance, captured through active monitoring and benchmarking, and developer experience, assessed through friction metrics, documentation completeness, and integration success rates\. ## Page sections ### Performance Benchmarking Meets Developer Experience: A Holistic Approach to API Quality and Maturity API quality has two dimensions that are often measured separately: technical performance, captured through active monitoring and benchmarking, and developer experience, assessed through friction metrics, documentation completeness, and integration success rates\. This video makes the case for integrating both dimensions into a single API quality and maturity model — and explores what the combined picture reveals about API health that either metric alone would miss\. ## Key facts - API quality has two dimensions that are often measured separately: technical performance, captured through active monitoring and benchmarking, and developer experience, assessed through friction metrics, documentation completeness, and integration success rates\. - This video makes the case for integrating both dimensions into a single API quality and maturity model — and explores what the combined picture reveals about API health that either metric alone would miss\. ## Primary entities - APIContext - Video - Performance Benchmarking Meets Developer Experience: A Holistic Approach to API Quality and Maturity - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # PSD2, APIs and Performance and Quality Monitoring Canonical URL: https://apicontext.com/resources/psd2-apis-and-performance-and-quality-monitoring-white-paper Source: static Description: Download APIContext's white paper on PSD2 API performance and quality monitoring requirements and how to meet them\. ## Summary PSD2, APIs and Performance, and Quality Monitoring\. Meeting the performance and quality monitoring requirements of PSD2\.\. Download APIContext's white paper on PSD2 API performance and quality monitoring requirements and how to meet them\. ## Page sections ### Meeting the performance and quality monitoring requirements of PSD2\. Category: White paper PSD2 created specific requirements for API performance and quality in European financial services — requirements that go beyond uptime and into the realm of response time, authentication reliability, and consistent service delivery\. This white paper explains what PSD2 actually requires of API performance monitoring, where institutions commonly fall short, and how a systematic active monitoring approach helps organisations meet and demonstrate compliance\. Use it as a reference for compliance teams, API architects, and operations teams working on PSD2 obligations\. - What PSD2 requires from API performance and quality monitoring - Where institutions most commonly fall short of regulatory expectations - How active monitoring provides the evidence PSD2 compliance demands - Practical approaches to continuous PSD2 API quality assurance ## Key facts - PSD2 created specific requirements for API performance and quality in European financial services — requirements that go beyond uptime and into the realm of response time, authentication reliability, and consistent service delivery\. - This white paper explains what PSD2 actually requires of API performance monitoring, where institutions commonly fall short, and how a systematic active monitoring approach helps organisations meet and demonstrate compliance\. - Use it as a reference for compliance teams, API architects, and operations teams working on PSD2 obligations\. - What PSD2 requires from API performance and quality monitoring - Where institutions most commonly fall short of regulatory expectations - How active monitoring provides the evidence PSD2 compliance demands - Practical approaches to continuous PSD2 API quality assurance ## Primary entities - APIContext - White paper - PSD2, APIs and Performance, and Quality Monitoring - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the white paper](/resources/psd2-apis-and-performance-and-quality-monitoring-white-paper) --- # RingCentral Case Study Canonical URL: https://apicontext.com/resources/ringcentral-enterprise-telecom-api-resilience-case-study Source: static Description: Learn how RingCentral used APIContext to improve developer portal resilience and identify performance issues across global locations\. ## Summary RingCentral Developer Portal API Resilience\. How a global enterprise telecom company raised the quality bar for its developer experience\.\. Learn how RingCentral used APIContext to improve developer portal resilience and identify performance issues across global locations\. ## Page sections ### How a global enterprise telecom company raised the quality bar for its developer experience\. Category: Case study RingCentral wanted to give developers using their sandbox a high\-quality, reliable experience from day one\. That meant understanding how their APIs actually performed across the regions where developers were working\. Using APIContext, RingCentral identified latency and availability issues across global locations that internal monitoring had not surfaced\. Addressing those issues led to measurable improvements in platform resilience and a meaningful increase in developer platform usage\. - How RingCentral identified hidden performance issues across global developer locations - Why internal monitoring missed what external active monitoring caught - The connection between API reliability and developer platform adoption - How APIContext supports enterprise telecom API governance at scale ## Key facts - RingCentral wanted to give developers using their sandbox a high\-quality, reliable experience from day one\. That meant understanding how their APIs actually performed across the regions where developers were working\. - Using APIContext, RingCentral identified latency and availability issues across global locations that internal monitoring had not surfaced\. Addressing those issues led to measurable improvements in platform resilience and a meaningful increase in developer platform usage\. - How RingCentral identified hidden performance issues across global developer locations - Why internal monitoring missed what external active monitoring caught - The connection between API reliability and developer platform adoption - How APIContext supports enterprise telecom API governance at scale ## Primary entities - APIContext - Case study - RingCentral Developer Portal API Resilience - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/ringcentral-enterprise-telecom-api-resilience-case-study) --- # Global Scientific Instruments E\-Commerce Case Study Canonical URL: https://apicontext.com/resources/scientific-instruments-ecommerce-outside-in-performance-case-study Source: static Description: How outside\-in monitoring revealed a nearly 3× page load gap across 28 countries that four cloud provider dashboards all said looked fine\. ## Summary Every Dashboard Said Green\. Researchers in 28 Countries Said Otherwise\.\. How an outside\-in performance baseline gave engineering, operations, and vendor teams one shared view of the customer experience\.\. How outside\-in monitoring revealed a nearly 3× page load gap across 28 countries that four cloud provider dashboards all said looked fine\. ## Page sections ### How an outside\-in performance baseline gave engineering, operations, and vendor teams one shared view of the customer experience\. Category: Case study A global scientific instruments company served researchers, laboratories, and distributors in 28 countries through a multi\-cloud digital platform\. Four cloud providers delivered the experience\. Internal dashboards showed green — availability was high, SLOs were met, and no single team had reason to escalate\. But no one had an independent view of what a customer actually experienced loading a product page in São Paulo, searching the catalog in Seoul, or starting a cart in Dubai\. Outside\-in synthetic monitoring across 110\+ nodes exposed what internal dashboards could not: page load times varied nearly 3× between the fastest and slowest markets, 84% of transaction\-page latency sat in backend processing, and cloud provider quality diverged dramatically at tail percentiles — even though every provider cleared every SLO at the median\. - How outside\-in monitoring exposed a nearly 3× regional page load gap hidden by aggregate SLOs - Why backend processing — not network paths — dominated transaction\-page latency - How cloud provider quality diverged at p95 even when every provider cleared every SLO at the median - The operational outcomes: an edge optimization roadmap, backend tuning priorities, and vendor accountability grounded in shared data ## Key facts - A global scientific instruments company served researchers, laboratories, and distributors in 28 countries through a multi\-cloud digital platform\. Four cloud providers delivered the experience\. Internal dashboards showed green — availability was high, SLOs were met, and no single team had reason to escalate\. But no one had an independent view of what a customer actually experienced loading a product page in São Paulo, searching the catalog in Seoul, or starting a cart in Dubai\. - Outside\-in synthetic monitoring across 110\+ nodes exposed what internal dashboards could not: page load times varied nearly 3× between the fastest and slowest markets, 84% of transaction\-page latency sat in backend processing, and cloud provider quality diverged dramatically at tail percentiles — even though every provider cleared every SLO at the median\. - How outside\-in monitoring exposed a nearly 3× regional page load gap hidden by aggregate SLOs - Why backend processing — not network paths — dominated transaction\-page latency - How cloud provider quality diverged at p95 even when every provider cleared every SLO at the median - The operational outcomes: an edge optimization roadmap, backend tuning priorities, and vendor accountability grounded in shared data ## Primary entities - APIContext - Case study - Every Dashboard Said Green\. Researchers in 28 Countries Said Otherwise\. - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the case study](/resources/scientific-instruments-ecommerce-outside-in-performance-case-study) --- # Security in the API Ecosystem Canonical URL: https://apicontext.com/resources/security-in-the-api-ecosystem Source: static Description: API security goes beyond authentication\. Watch this APIContext video on the security challenges teams face across the full API ecosystem\. ## Summary Security in the API Ecosystem\. API security is often discussed in terms of authentication and authorization\. But in practice, the attack surface extends to undocumented endpoints, behavioural anomalies, and third\-party integrations that were never designed with security in mind\. ## Page sections ### Security in the API Ecosystem API security is often discussed in terms of authentication and authorization\. But in practice, the attack surface extends to undocumented endpoints, behavioural anomalies, and third\-party integrations that were never designed with security in mind\. This video maps the security landscape teams need to understand when managing APIs in production, covering the gaps that static tools miss and how runtime monitoring contributes to a stronger overall posture\. ## Key facts - API security is often discussed in terms of authentication and authorization\. But in practice, the attack surface extends to undocumented endpoints, behavioural anomalies, and third\-party integrations that were never designed with security in mind\. - This video maps the security landscape teams need to understand when managing APIs in production, covering the gaps that static tools miss and how runtime monitoring contributes to a stronger overall posture\. ## Primary entities - APIContext - Video - Security in the API Ecosystem - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Tech Roundtable: Performance Benchmarking Meets Developer Experience Canonical URL: https://apicontext.com/resources/tech-roundtable-performance-benchmarking-meets-developer-experience Source: static Description: A roundtable discussion on connecting API performance benchmarking with developer experience measurement\. Watch the full discussion\. ## Summary Tech Roundtable: Performance Benchmarking Meets Developer Experience\. This roundtable brings together perspectives on API quality from performance benchmarking and developer experience disciplines — two areas that inform each other but are rarely discussed together in a structured way\. ## Page sections ### Tech Roundtable: Performance Benchmarking Meets Developer Experience This roundtable brings together perspectives on API quality from performance benchmarking and developer experience disciplines — two areas that inform each other but are rarely discussed together in a structured way\. The discussion covers where the two measurement approaches align, where they produce different signals, and how teams can build a more complete picture of API quality by combining performance data with developer experience indicators\. ## Key facts - This roundtable brings together perspectives on API quality from performance benchmarking and developer experience disciplines — two areas that inform each other but are rarely discussed together in a structured way\. - The discussion covers where the two measurement approaches align, where they produce different signals, and how teams can build a more complete picture of API quality by combining performance data with developer experience indicators\. ## Primary entities - APIContext - Video - Tech Roundtable: Performance Benchmarking Meets Developer Experience - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # The Art of Rejection: API Security Validation Canonical URL: https://apicontext.com/resources/the-art-of-rejection-mastering-failure-scenarios-for-api-security-validation-at-runtime Source: static Description: Well\-designed API rejection behaviour is a security signal\. Watch this APIContext video on mastering failure scenarios for runtime API security validation\. ## Summary The Art of Rejection: Mastering Failure Scenarios for API Security Validation at Runtime\. How an API handles invalid requests tells you a great deal about its security posture\. Verbose error messages, inconsistent rejection behaviour, and improper HTTP status code usage all create signals that attackers can exploit — and that monitoring can detect\. ## Page sections ### The Art of Rejection: Mastering Failure Scenarios for API Security Validation at Runtime How an API handles invalid requests tells you a great deal about its security posture\. Verbose error messages, inconsistent rejection behaviour, and improper HTTP status code usage all create signals that attackers can exploit — and that monitoring can detect\. This video covers what well\-designed API rejection looks like, why testing failure scenarios is essential for security validation at runtime, and how active monitoring of error behaviour contributes to a stronger overall API security posture\. ## Key facts - How an API handles invalid requests tells you a great deal about its security posture\. Verbose error messages, inconsistent rejection behaviour, and improper HTTP status code usage all create signals that attackers can exploit — and that monitoring can detect\. - This video covers what well\-designed API rejection looks like, why testing failure scenarios is essential for security validation at runtime, and how active monitoring of error behaviour contributes to a stronger overall API security posture\. ## Primary entities - APIContext - Video - The Art of Rejection: Mastering Failure Scenarios for API Security Validation at Runtime - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # The Blind Men and the Elephant: API Silos Canonical URL: https://apicontext.com/resources/the-blind-men-and-the-elephant-the-prevalence-of-silos-in-api-architecture Source: static Description: Siloed API ownership creates partial visibility that leads to systemic blind spots\. Watch this APIContext video on the silo problem in API architecture\. ## Summary The blind men and the elephant: The prevalence of silos in API architecture\. When different teams own different parts of an API architecture without a shared view of the whole, the result is the blind men and the elephant problem: each team understands their piece well, and nobody sees the systemic issues\. ## Page sections ### The blind men and the elephant: The prevalence of silos in API architecture When different teams own different parts of an API architecture without a shared view of the whole, the result is the blind men and the elephant problem: each team understands their piece well, and nobody sees the systemic issues\. This video examines how silos develop in API architectures, the specific blind spots they create, and what cross\-silo API monitoring can reveal about failures and dependencies that no single team would otherwise see\. ## Key facts - When different teams own different parts of an API architecture without a shared view of the whole, the result is the blind men and the elephant problem: each team understands their piece well, and nobody sees the systemic issues\. - This video examines how silos develop in API architectures, the specific blind spots they create, and what cross\-silo API monitoring can reveal about failures and dependencies that no single team would otherwise see\. ## Primary entities - APIContext - Video - The blind men and the elephant: The prevalence of silos in API architecture - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # The Cloud for APIs: 2022 in Review Canonical URL: https://apicontext.com/resources/the-cloud-for-apis-2022-in-review Source: static Description: Download APIContext's review of cloud API performance trends across 2022 — what changed, what improved, and where quality gaps persisted\. ## Summary The Cloud for APIs: 2022 in Review\. A data\-driven look at cloud API performance trends across 2022\.\. Download APIContext's review of cloud API performance trends across 2022 — what changed, what improved, and where quality gaps persisted\. ## Page sections ### A data\-driven look at cloud API performance trends across 2022\. Category: Industry report APIContext continuously measures API performance across cloud providers, regions, and API types\. This annual review synthesises a year of data into a clear picture of where cloud API quality improved, stagnated, or declined\. The 2022 report covers performance trends across major cloud providers, the regions where quality varied most significantly, and the patterns that persisted despite infrastructure investment\. Use it as a reference for cloud strategy, vendor negotiations, and reliability planning\. - How cloud API performance evolved across 2022 - Which providers and regions showed the most improvement - Where quality gaps persisted despite infrastructure investment - What the 2022 data suggests for cloud API strategy in subsequent years ## Key facts - APIContext continuously measures API performance across cloud providers, regions, and API types\. This annual review synthesises a year of data into a clear picture of where cloud API quality improved, stagnated, or declined\. - The 2022 report covers performance trends across major cloud providers, the regions where quality varied most significantly, and the patterns that persisted despite infrastructure investment\. - Use it as a reference for cloud strategy, vendor negotiations, and reliability planning\. - How cloud API performance evolved across 2022 - Which providers and regions showed the most improvement - Where quality gaps persisted despite infrastructure investment - What the 2022 data suggests for cloud API strategy in subsequent years ## Primary entities - APIContext - Industry report - The Cloud for APIs: 2022 in Review - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the report](/resources/the-cloud-for-apis-2022-in-review) --- # Top 3 Features in an API Monitoring Service Canonical URL: https://apicontext.com/resources/top-3-features-you-need-in-an-api-monitoring-service Source: static Description: Not all API monitoring services are equal\. Download this APIContext infographic on the three features that matter most when choosing one\. ## Summary Top 3 Features You Need In An API Monitoring Service\. Choosing an API monitoring service means evaluating a lot of options with overlapping feature sets\. This infographic cuts through the noise to identify the three capabilities that have the most impact on API reliability and observability in practice\. ## Page sections ### Top 3 Features You Need In An API Monitoring Service Choosing an API monitoring service means evaluating a lot of options with overlapping feature sets\. This infographic cuts through the noise to identify the three capabilities that have the most impact on API reliability and observability in practice\. Download the PDF or view the infographic below\. ## Key facts - Choosing an API monitoring service means evaluating a lot of options with overlapping feature sets\. This infographic cuts through the noise to identify the three capabilities that have the most impact on API reliability and observability in practice\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - Top 3 Features You Need In An API Monitoring Service - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/APIM%20Features%20Infographic.pdf) - [Request a demo](/contact) --- # UK Open Banking API Performance 2021–2022 Canonical URL: https://apicontext.com/resources/uk-open-banking-api-performance-2021-2022 Source: static Description: Download APIContext's analysis of UK Open Banking API performance across 2021 and 2022 — availability, latency, and quality trends\. ## Summary UK Open Banking API Performance 2021–2022\. Independent measurement of regulated Open Banking APIs across UK institutions\.\. Download APIContext's analysis of UK Open Banking API performance across 2021 and 2022 — availability, latency, and quality trends\. ## Page sections ### Independent measurement of regulated Open Banking APIs across UK institutions\. Category: Industry report UK Open Banking regulation requires financial institutions to provide third\-party access to customer account data through standardised APIs\. Whether those APIs actually meet quality expectations is a question that requires independent measurement to answer\. This report covers API performance data across major UK Open Banking providers for 2021 and 2022 — availability rates, latency distributions, authentication reliability, and quality differences between legacy banks and cloud\-native challengers\. It is an independent, data\-driven reference for TPPs, regulators, and institutions benchmarking their own performance\. - Availability and latency data across UK Open Banking institutions - Authentication reliability patterns in regulated API environments - Performance differences between legacy banks and cloud\-native challengers - How UK Open Banking API quality trended across 2021 and 2022 ## Key facts - UK Open Banking regulation requires financial institutions to provide third\-party access to customer account data through standardised APIs\. Whether those APIs actually meet quality expectations is a question that requires independent measurement to answer\. - This report covers API performance data across major UK Open Banking providers for 2021 and 2022 — availability rates, latency distributions, authentication reliability, and quality differences between legacy banks and cloud\-native challengers\. - It is an independent, data\-driven reference for TPPs, regulators, and institutions benchmarking their own performance\. - Availability and latency data across UK Open Banking institutions - Authentication reliability patterns in regulated API environments - Performance differences between legacy banks and cloud\-native challengers - How UK Open Banking API quality trended across 2021 and 2022 ## Primary entities - APIContext - Industry report - UK Open Banking API Performance 2021–2022 - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the report](/resources/uk-open-banking-api-performance-2021-2022) --- # UK Open Banking API Performance 2022–2023 Canonical URL: https://apicontext.com/resources/uk-open-banking-api-performance-2022-2023 Source: static Description: Read APImetrics' analysis of UK Open Banking API performance across 2022 and 2023, including availability, latency and bank quality\. ## Summary UK Open Banking API Performance 2022–2023\. Independent measurement of regulated Open Banking APIs across 29 UK bank brands\.\. Read APImetrics' analysis of UK Open Banking API performance across 2022 and 2023, including availability, latency and bank quality\. ## Page sections ### Independent measurement of regulated Open Banking APIs across 29 UK bank brands\. Category: Industry report This report examines the performance of UK Open Banking APIs using approximately 8\.4 million real FAPI consent calls made across 29 bank brands\. It compares CMA9 banks, traditional banks, and neobanks across availability, latency, CASC quality scores, cloud providers, and data center locations\. The report is published in full on this page so the findings can be read, searched, and referenced directly\. - How availability and latency differed across 29 UK Open Banking brands - Why neobanks and CMA9 banks outperformed traditional banks - How AWS, IBM, Google, and Azure compared on DNS and total call time - Why UK and Irish cloud locations were generally fastest - What API teams can do to reduce latency, outliers, and support cost ## Key facts - This report examines the performance of UK Open Banking APIs using approximately 8\.4 million real FAPI consent calls made across 29 bank brands\. - It compares CMA9 banks, traditional banks, and neobanks across availability, latency, CASC quality scores, cloud providers, and data center locations\. - The report is published in full on this page so the findings can be read, searched, and referenced directly\. - How availability and latency differed across 29 UK Open Banking brands - Why neobanks and CMA9 banks outperformed traditional banks - How AWS, IBM, Google, and Azure compared on DNS and total call time - Why UK and Irish cloud locations were generally fastest - What API teams can do to reduce latency, outliers, and support cost ## Primary entities - APIContext - Industry report - UK Open Banking API Performance 2022–2023 - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the report](/resources/uk-open-banking-api-performance-2022-2023) --- # UK Open Banking API Performance 2023\-2024 Canonical URL: https://apicontext.com/resources/uk-open-banking-api-performance-2023-2024 Source: static Description: Download APIContext's analysis of UK Open Banking API performance across 2023 and 2024\. ## Summary UK Open Banking API Performance 2023\-2024\. Independent measurement of regulated Open Banking APIs across 29 UK institutions\.\. Download APIContext's analysis of UK Open Banking API performance across 2023 and 2024\. ## Page sections ### Independent measurement of regulated Open Banking APIs across 29 UK institutions\. Category: Industry report APIContext's fourth annual UK Open Banking report measures approximately 8 million real API calls across 29 bank brands\. - Availability and latency across CMA9, traditional banks, and neobanks - How AWS, Azure, Google, IBM, and Akamai compare - CASC quality trends and p99 performance findings - Recommendations for cloud optimization and proactive monitoring ## Key facts - APIContext's fourth annual UK Open Banking report measures approximately 8 million real API calls across 29 bank brands\. - Availability and latency across CMA9, traditional banks, and neobanks - How AWS, Azure, Google, IBM, and Akamai compare - CASC quality trends and p99 performance findings - Recommendations for cloud optimization and proactive monitoring ## Primary entities - APIContext - Industry report - UK Open Banking API Performance 2023\-2024 - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the report](/resources/uk-open-banking-api-performance-2023-2024) --- # We've Invested Heavily in Design Time Canonical URL: https://apicontext.com/resources/weve-invested-heavily-in-design-time-and-api-lifecycle-tool-chain-why-do-we-need-to-add-yet-another-platform Source: static Description: Design\-time and lifecycle tooling don't cover runtime\. Watch this APIContext video on why another platform is worth the investment\. ## Summary We've invested heavily in design time and API lifecycle tool chain\. Why do we need to add yet another platform?\. It is a fair question\. Teams that have already invested in API design tools, gateways, contract testing, and lifecycle management platforms reasonably wonder whether active runtime monitoring is redundant overhead or genuinely additive\. ## Page sections ### We've invested heavily in design time and API lifecycle tool chain\. Why do we need to add yet another platform? It is a fair question\. Teams that have already invested in API design tools, gateways, contract testing, and lifecycle management platforms reasonably wonder whether active runtime monitoring is redundant overhead or genuinely additive\. This video addresses the question directly: what design\-time and lifecycle tools do well, what they cannot see by nature, and the specific cases where runtime monitoring produces information that no other layer in the API toolchain can provide\. ## Key facts - It is a fair question\. Teams that have already invested in API design tools, gateways, contract testing, and lifecycle management platforms reasonably wonder whether active runtime monitoring is redundant overhead or genuinely additive\. - This video addresses the question directly: what design\-time and lifecycle tools do well, what they cannot see by nature, and the specific cases where runtime monitoring produces information that no other layer in the API toolchain can provide\. ## Primary entities - APIContext - Video - We've invested heavily in design time and API lifecycle tool chain\. Why do we need to add yet another platform? - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Characteristics of an API Native System Canonical URL: https://apicontext.com/resources/what-are-the-characteristics-of-an-api-native-system Source: static Description: API\-native systems are designed differently from systems that added APIs later\. Watch this APIContext video on what distinguishes them\. ## Summary What are the characteristics of an API native system\. Not all APIs are created equal\. Systems built API\-native from the start have different characteristics than systems where APIs were added as an integration layer on top of existing architecture — and those differences show up clearly in production\. ## Page sections ### What are the characteristics of an API native system Not all APIs are created equal\. Systems built API\-native from the start have different characteristics than systems where APIs were added as an integration layer on top of existing architecture — and those differences show up clearly in production\. This video explores what API\-native design actually means in practice, how it affects the reliability, observability, and governance of APIs at scale, and what it tells teams about the long\-term quality of their API estate\. ## Key facts - Not all APIs are created equal\. Systems built API\-native from the start have different characteristics than systems where APIs were added as an integration layer on top of existing architecture — and those differences show up clearly in production\. - This video explores what API\-native design actually means in practice, how it affects the reliability, observability, and governance of APIs at scale, and what it tells teams about the long\-term quality of their API estate\. ## Primary entities - APIContext - Video - What are the characteristics of an API native system - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # What Do APIs Do For You Canonical URL: https://apicontext.com/resources/what-do-apis-do-for-you Source: static Description: APIs enable the integrations, automations, and digital experiences modern businesses depend on\. Download this APIContext infographic\. ## Summary What Do APIs Do For You?\. APIs are behind most of the digital interactions that businesses and consumers take for granted — from payments to notifications, data synchronisation to third\-party integrations\. This infographic explains what APIs actually do across a modern digital stack\. ## Page sections ### What Do APIs Do For You? APIs are behind most of the digital interactions that businesses and consumers take for granted — from payments to notifications, data synchronisation to third\-party integrations\. This infographic explains what APIs actually do across a modern digital stack\. Download the PDF or view the infographic below\. ## Key facts - APIs are behind most of the digital interactions that businesses and consumers take for granted — from payments to notifications, data synchronisation to third\-party integrations\. This infographic explains what APIs actually do across a modern digital stack\. - Download the PDF or view the infographic below\. ## Primary entities - APIContext - Infographic - What Do APIs Do For You? - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/How%20API%20works.pdf) - [Request a demo](/contact) --- # What Does API Monitoring Have to Do With Governance Canonical URL: https://apicontext.com/resources/what-does-api-monitoring-have-to-do-with-governance-and-what-is-the-gap-with-traditional-apm-solutions-of-the-type-that-were-using-today Source: static Description: Traditional APM tools were not built for API governance\. Watch this APIContext video on the gap between APM and what API governance actually needs\. ## Summary What does API monitoring have to do with governance, and what is the gap with traditional APM solutions of the type that we're using today\. Traditional application performance management tools measure application infrastructure — server response times, error rates, resource utilisation\. API governance needs something different: contract conformance, consumer\-perspective measurement, and evidence of SLA adherence\. ## Page sections ### What does API monitoring have to do with governance, and what is the gap with traditional APM solutions of the type that we're using today Traditional application performance management tools measure application infrastructure — server response times, error rates, resource utilisation\. API governance needs something different: contract conformance, consumer\-perspective measurement, and evidence of SLA adherence\. This video explains why APM tools leave a governance\-shaped gap, and how purpose\-built API monitoring fills it — covering the specific capabilities that matter most for teams trying to govern APIs at scale\. ## Key facts - Traditional application performance management tools measure application infrastructure — server response times, error rates, resource utilisation\. API governance needs something different: contract conformance, consumer\-perspective measurement, and evidence of SLA adherence\. - This video explains why APM tools leave a governance\-shaped gap, and how purpose\-built API monitoring fills it — covering the specific capabilities that matter most for teams trying to govern APIs at scale\. ## Primary entities - APIContext - Video - What does API monitoring have to do with governance, and what is the gap with traditional APM solutions of the type that we're using today - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Gap APIContext Fills Alongside API Security Canonical URL: https://apicontext.com/resources/what-is-the-gap-that-apicontext-fills-alongside-an-api-security-solution Source: static Description: API security and API monitoring are complementary, not duplicates\. Watch this video to see the value APIContext adds alongside security tools\. ## Summary What is the gap that APIContext fills alongside an API security solution\. API security tools are designed to detect and block threats\. They are not designed to measure whether APIs are available, performant, and behaving as specified from the consumer's perspective\. Those are different questions\. ## Page sections ### What is the gap that APIContext fills alongside an API security solution API security tools are designed to detect and block threats\. They are not designed to measure whether APIs are available, performant, and behaving as specified from the consumer's perspective\. Those are different questions\. This video clarifies the distinct role that active API monitoring plays alongside security tooling — covering the performance, availability, and conformance dimensions that security\-focused products were not built to address\. ## Key facts - API security tools are designed to detect and block threats\. They are not designed to measure whether APIs are available, performant, and behaving as specified from the consumer's perspective\. Those are different questions\. - This video clarifies the distinct role that active API monitoring plays alongside security tooling — covering the performance, availability, and conformance dimensions that security\-focused products were not built to address\. ## Primary entities - APIContext - Video - What is the gap that APIContext fills alongside an API security solution - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # What Is The Right API For You Canonical URL: https://apicontext.com/resources/what-is-the-right-api-for-you Source: static Description: REST, GraphQL, gRPC, webhooks — different API styles suit different use cases\. Download this APIContext infographic to find the right fit\. ## Summary What Is The Right API For You\. REST, GraphQL, gRPC, event\-driven, and webhook\-based APIs each have different strengths\. Choosing the right style for a given use case is one of the most consequential early decisions in API design\. ## Page sections ### What Is The Right API For You REST, GraphQL, gRPC, event\-driven, and webhook\-based APIs each have different strengths\. Choosing the right style for a given use case is one of the most consequential early decisions in API design\. This infographic maps the key API styles to their ideal use cases, helping teams make informed choices about API architecture before they build\. ## Key facts - REST, GraphQL, gRPC, event\-driven, and webhook\-based APIs each have different strengths\. Choosing the right style for a given use case is one of the most consequential early decisions in API design\. - This infographic maps the key API styles to their ideal use cases, helping teams make informed choices about API architecture before they build\. ## Primary entities - APIContext - Infographic - What Is The Right API For You - API monitoring - API best practices ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Download PDF](https://3449466.fs1.hubspotusercontent-na1.net/hubfs/3449466/5-%20Reports%20and%20Infographics/What%20is%20the%20right%20API%20for%20you.pdf) - [Request a demo](/contact) --- # What Security Leaders Expect From APIContext Canonical URL: https://apicontext.com/resources/what-security-leaders-expect-from-apicontext Source: static Description: Security leaders need specific capabilities from API monitoring\. Download this infographic on what CISOs and security teams expect from APIContext\. ## Summary What Security Leaders Expect From APIContext\. The API monitoring capabilities that matter most to security\-focused teams\.\. Security leaders need specific capabilities from API monitoring\. Download this infographic on what CISOs and security teams expect from APIContext\. ## Page sections ### The API monitoring capabilities that matter most to security\-focused teams\. Category: Infographic CISOs and security leaders approach API monitoring with a distinct set of requirements — visibility into undocumented endpoints, anomaly detection, evidence for compliance, and integration with security tooling\. This infographic outlines the capabilities security leaders look for in an API monitoring platform, and how APIContext addresses the security\-specific dimensions of API quality and governance\. Complete the form to download the full infographic\. - The API visibility gaps that security teams most commonly face - How active monitoring contributes to API security posture - What compliance\-driven security teams need from API monitoring evidence - How APIContext integrates with existing security and governance workflows ## Key facts - CISOs and security leaders approach API monitoring with a distinct set of requirements — visibility into undocumented endpoints, anomaly detection, evidence for compliance, and integration with security tooling\. - This infographic outlines the capabilities security leaders look for in an API monitoring platform, and how APIContext addresses the security\-specific dimensions of API quality and governance\. - Complete the form to download the full infographic\. - The API visibility gaps that security teams most commonly face - How active monitoring contributes to API security posture - What compliance\-driven security teams need from API monitoring evidence - How APIContext integrates with existing security and governance workflows ## Primary entities - APIContext - Infographic - What Security Leaders Expect From APIContext - API monitoring - API resilience ## Audience - technology leaders - API teams - platform teams - SRE teams ## Primary links - [Download the infographic](/resources/what-security-leaders-expect-from-apicontext) --- # You Can't Secure What You Don't Understand Canonical URL: https://apicontext.com/resources/you-cant-secure-that-which-you-dont-understand Source: static Description: API security starts with visibility\. Watch this APIContext video on why understanding your API estate is the first step to securing it\. ## Summary You can't secure that which you don't understand\. Security teams cannot protect APIs they do not know exist\. Shadow APIs, zombie endpoints, and undocumented integrations represent an attack surface that standard security tooling will not cover because it was never mapped\. ## Page sections ### You can't secure that which you don't understand Security teams cannot protect APIs they do not know exist\. Shadow APIs, zombie endpoints, and undocumented integrations represent an attack surface that standard security tooling will not cover because it was never mapped\. This video argues that API discovery and continuous inventory are security prerequisites, not nice\-to\-haves — and explores how active monitoring contributes to the visibility that effective API security depends on\. ## Key facts - Security teams cannot protect APIs they do not know exist\. Shadow APIs, zombie endpoints, and undocumented integrations represent an attack surface that standard security tooling will not cover because it was never mapped\. - This video argues that API discovery and continuous inventory are security prerequisites, not nice\-to\-haves — and explores how active monitoring contributes to the visibility that effective API security depends on\. ## Primary entities - APIContext - Video - You can't secure that which you don't understand - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # You Really Don't Know Clouds at All Canonical URL: https://apicontext.com/resources/you-really-dont-know-clouds-at-all Source: static Description: Cloud provider APIs behave differently by region, time, and load — in ways your internal monitoring won't show you\. Watch this APIContext video\. ## Summary You Really Don't Know Clouds at All\. Cloud platforms promise consistent, global infrastructure\. What teams actually get is more nuanced — API latency, availability, and behaviour vary significantly by region, provider, and time of day in ways that internal dashboards rarely surface\. ## Page sections ### You Really Don't Know Clouds at All Cloud platforms promise consistent, global infrastructure\. What teams actually get is more nuanced — API latency, availability, and behaviour vary significantly by region, provider, and time of day in ways that internal dashboards rarely surface\. This video looks at what independent external measurement reveals about cloud API quality, and why the gap between assumed and actual cloud performance matters for teams building on third\-party infrastructure\. ## Key facts - Cloud platforms promise consistent, global infrastructure\. What teams actually get is more nuanced — API latency, availability, and behaviour vary significantly by region, provider, and time of day in ways that internal dashboards rarely surface\. - This video looks at what independent external measurement reveals about cloud API quality, and why the gap between assumed and actual cloud performance matters for teams building on third\-party infrastructure\. ## Primary entities - APIContext - Video - You Really Don't Know Clouds at All - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Zombie APIs Video Canonical URL: https://apicontext.com/resources/zombie-apis-data-at-risk-for-no-incremental-business-value Source: static Description: Zombie APIs silently expose sensitive data and consume resources\. Watch this APIContext video on how to identify and eliminate them\. ## Summary Zombie APIs: Data at risk for no incremental business value\. Zombie APIs are forgotten, deprecated, or shadow endpoints that remain active long after their intended purpose has passed\. They carry real data exposure risk while delivering no measurable business value\. ## Page sections ### Zombie APIs: Data at risk for no incremental business value Zombie APIs are forgotten, deprecated, or shadow endpoints that remain active long after their intended purpose has passed\. They carry real data exposure risk while delivering no measurable business value\. This video explores how zombie APIs accumulate in production environments, why they are hard to find, and what teams can do to discover, assess, and safely retire them\. ## Key facts - Zombie APIs are forgotten, deprecated, or shadow endpoints that remain active long after their intended purpose has passed\. They carry real data exposure risk while delivering no measurable business value\. - This video explores how zombie APIs accumulate in production environments, why they are hard to find, and what teams can do to discover, assess, and safely retire them\. ## Primary entities - APIContext - Video - Zombie APIs: Data at risk for no incremental business value - API monitoring - API reliability ## Audience - API teams - technology leaders - SRE teams ## Primary links - [Request a demo](/contact) --- # Fintech & Open Banking Canonical URL: https://apicontext.com/solutions/fintech-open-banking Source: static Description: Open Banking API monitoring is about reliability, compliance, security, and quality, not just uptime\. APIContext gives financial teams production evidence from the locations partners and customers use\. ## Summary Open Banking APIs are built on trust\. Can you trust yours? Open Banking API monitoring is about reliability, compliance, security, and quality, not just uptime\. APIContext gives financial teams production evidence from the locations partners and customers use\. ## Stats - FAPI security\-ready monitoring - FDX open banking alignment - 24/7 production validation - HSM secure certificate handling ## Page sections ### See your APIs the way TPPs and regulators see them\. Category: Test Internal APM tells you your servers are healthy\. It cannot tell you that an Australian fintech cannot reach your CDR endpoint at 09:14 UTC, or that a German TPP is being throttled at the edge\. APIContext runs from the same global cloud regions your stakeholders use, so you find problems before they file complaints\. - 125\+ nodes across AWS, GCP, Azure, and Akamai - Same\-cloud testing, peer\-region or cross\-region - Optional private nodes inside your firewall - Real OAuth 2\.0 and FAPI auth with real user accounts ### Find problems hours before your APM does\. Category: Perform Internal monitoring sees the inside of your stack\. APIContext sees what your customers see across the public internet, through the edge, with real auth, against the live contract\. - Synthetic and contract checks every interval - Per\-endpoint baselining and anomaly detection - OTEL signals fed into Splunk, Datadog, and Dynatrace - Incident\-grade alerts with diff and trace attached ### Validate every layer of Open Banking security on every call\. Category: Conform FAPI is more than mTLS\. It is PKCE, signed request objects, JARM, DPoP, audience\-restricted tokens, certificate\-bound access, and a dozen header rules\. APIContext checks them against real flows on every monitored endpoint\. - FAPI 1\.0 Baseline, 1\.0 Advanced, and 2\.0 - OAuth 2\.0, OIDC, mTLS, DPoP, PKCE, PAR, and JARM - Certificate management with FIPS 140\-2 HSM storage - Client\-credential and user\-authenticated flows out of the box ## Key facts - Open Banking - FAPI and OAuth - Regulator reporting - External validation - Secure workflows - FAPI security\-ready monitoring - FDX open banking alignment - 24/7 production validation - HSM secure certificate handling - See your APIs the way TPPs and regulators see them\.: Internal APM tells you your servers are healthy\. It cannot tell you that an Australian fintech cannot reach your CDR endpoint at 09:14 UTC, or that a German TPP is being throttled at the edge\. APIContext runs from the same global cloud regions your stakeholders use, so you find problems before they file complaints\. - Find problems hours before your APM does\.: Internal monitoring sees the inside of your stack\. APIContext sees what your customers see across the public internet, through the edge, with real auth, against the live contract\. - Validate every layer of Open Banking security on every call\.: FAPI is more than mTLS\. It is PKCE, signed request objects, JARM, DPoP, audience\-restricted tokens, certificate\-bound access, and a dozen header rules\. APIContext checks them against real flows on every monitored endpoint\. - You helped us increase visibility of our APIs performance and significantly improved awareness\. ## Testimonial > You helped us increase visibility of our APIs performance and significantly improved awareness\. — Val Novikov, CTO, Fispan ## Primary entities - APIContext - Solutions - API monitoring - Open Banking - FAPI and OAuth - Regulator reporting - External validation - Secure workflows ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Discover real Open Banking API monitoring\.](/contact) ## FAQs ### What makes open banking API monitoring different from general API monitoring? Open banking APIs operate under regulatory frameworks — UK Open Banking, CFPB 1033, CDR, PSD2 — that require demonstrable availability, performance, and security compliance\. Monitoring them requires executing complete FAPI\-compliant authentication flows \(mTLS, DPoP, PAR, PKCE\) with real credentials, not just checking that an endpoint returns 200\. Conformance against the published OpenAPI specification is often a regulatory requirement, and audit trails of monitoring results may be needed to demonstrate compliance\. ### How does APIContext verify FAPI 2\.0 security requirements? APIContext executes complete FAPI 2\.0 authentication flows — including Pushed Authorization Requests, DPoP sender\-constrained tokens, mTLS client certificate binding, and JARM response validation — on every monitored check\. It verifies that each required security mechanism is present and correctly implemented, not just that the endpoint responds\. ### Can APIContext monitor open banking APIs from the regions where my customers are? Yes\. APIContext's 125\+ global nodes include cloud regions used by major open banking markets — UK, EU, Australia, and the US\. Checks verify that CDR endpoints are reachable from Australian networks, UK open banking APIs are performant from European TPP locations, and US CFPB 1033 data\-sharing endpoints meet their regulatory performance targets\. ### Does APIContext provide audit trails suitable for regulatory reporting? APIContext maintains a complete history of every monitoring check — timestamp, location, response code, latency, conformance result, and OTEL trace — accessible via export or API\. This data can produce availability reports for regulatory submissions, customer SLA reporting, or internal audit purposes\. --- # Banking and Financial Services Canonical URL: https://apicontext.com/solutions/industry-banking Source: static Description: Open Banking API monitoring is about reliability, compliance, security, and quality, not just uptime\. APIContext gives financial teams production evidence from the locations partners and customers use\. ## Summary Open Banking APIs are built on trust\. Can you trust yours? Open Banking API monitoring is about reliability, compliance, security, and quality, not just uptime\. APIContext gives financial teams production evidence from the locations partners and customers use\. ## Stats - FAPI security\-ready monitoring - FDX open banking alignment - 24/7 production validation - HSM secure certificate handling ## Page sections ### See your APIs the way TPPs and regulators see them\. Category: Test Internal APM tells you your servers are healthy\. It cannot tell you that an Australian fintech cannot reach your CDR endpoint at 09:14 UTC, or that a German TPP is being throttled at the edge\. APIContext runs from the same global cloud regions your stakeholders use, so you find problems before they file complaints\. - 125\+ nodes across AWS, GCP, Azure, and Akamai - Same\-cloud testing, peer\-region or cross\-region - Optional private nodes inside your firewall - Real OAuth 2\.0 and FAPI auth with real user accounts ### Find problems hours before your APM does\. Category: Perform Internal monitoring sees the inside of your stack\. APIContext sees what your customers see across the public internet, through the edge, with real auth, against the live contract\. - Synthetic and contract checks every interval - Per\-endpoint baselining and anomaly detection - OTEL signals fed into Splunk, Datadog, and Dynatrace - Incident\-grade alerts with diff and trace attached ### Validate every layer of Open Banking security on every call\. Category: Conform FAPI is more than mTLS\. It is PKCE, signed request objects, JARM, DPoP, audience\-restricted tokens, certificate\-bound access, and a dozen header rules\. APIContext checks them against real flows on every monitored endpoint\. - FAPI 1\.0 Baseline, 1\.0 Advanced, and 2\.0 - OAuth 2\.0, OIDC, mTLS, DPoP, PKCE, PAR, and JARM - Certificate management with FIPS 140\-2 HSM storage - Client\-credential and user\-authenticated flows out of the box ## Key facts - Open Banking - FAPI and OAuth - Regulator reporting - External validation - Secure workflows - FAPI security\-ready monitoring - FDX open banking alignment - 24/7 production validation - HSM secure certificate handling - See your APIs the way TPPs and regulators see them\.: Internal APM tells you your servers are healthy\. It cannot tell you that an Australian fintech cannot reach your CDR endpoint at 09:14 UTC, or that a German TPP is being throttled at the edge\. APIContext runs from the same global cloud regions your stakeholders use, so you find problems before they file complaints\. - Find problems hours before your APM does\.: Internal monitoring sees the inside of your stack\. APIContext sees what your customers see across the public internet, through the edge, with real auth, against the live contract\. - Validate every layer of Open Banking security on every call\.: FAPI is more than mTLS\. It is PKCE, signed request objects, JARM, DPoP, audience\-restricted tokens, certificate\-bound access, and a dozen header rules\. APIContext checks them against real flows on every monitored endpoint\. - You helped us increase visibility of our APIs performance and significantly improved awareness\. ## Testimonial > You helped us increase visibility of our APIs performance and significantly improved awareness\. — Val Novikov, CTO, Fispan ## Primary entities - APIContext - Solutions - API monitoring - Open Banking - FAPI and OAuth - Regulator reporting - External validation - Secure workflows ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Discover real Open Banking API monitoring\.](/contact) ## FAQs ### What makes open banking API monitoring different from general API monitoring? Open banking APIs operate under regulatory frameworks — UK Open Banking, CFPB 1033, CDR, PSD2 — that require demonstrable availability, performance, and security compliance\. Monitoring them requires executing complete FAPI\-compliant authentication flows \(mTLS, DPoP, PAR, PKCE\) with real credentials, not just checking that an endpoint returns 200\. Conformance against the published OpenAPI specification is often a regulatory requirement, and audit trails of monitoring results may be needed to demonstrate compliance\. ### How does APIContext verify FAPI 2\.0 security requirements? APIContext executes complete FAPI 2\.0 authentication flows — including Pushed Authorization Requests, DPoP sender\-constrained tokens, mTLS client certificate binding, and JARM response validation — on every monitored check\. It verifies that each required security mechanism is present and correctly implemented, not just that the endpoint responds\. ### Can APIContext monitor open banking APIs from the regions where my customers are? Yes\. APIContext's 125\+ global nodes include cloud regions used by major open banking markets — UK, EU, Australia, and the US\. Checks verify that CDR endpoints are reachable from Australian networks, UK open banking APIs are performant from European TPP locations, and US CFPB 1033 data\-sharing endpoints meet their regulatory performance targets\. ### Does APIContext provide audit trails suitable for regulatory reporting? APIContext maintains a complete history of every monitoring check — timestamp, location, response code, latency, conformance result, and OTEL trace — accessible via export or API\. This data can produce availability reports for regulatory submissions, customer SLA reporting, or internal audit purposes\. --- # Government Industry Canonical URL: https://apicontext.com/solutions/industry-government Source: static Description: Modern government runs on APIs — for benefits, taxes, permits, identity, and open data\. APIContext gives federal, state, and local teams an independent, outside\-in view of every public\-facing service from the networks citizens actually use, with evidence ready for FedRAMP, FISMA, and OMB customer\-experience reporting\. ## Summary Citizens depend on your APIs\. So do other agencies\. Modern government runs on APIs — for benefits, taxes, permits, identity, and open data\. APIContext gives federal, state, and local teams an independent, outside\-in view of every public\-facing service from the networks citizens actually use, with evidence ready for FedRAMP, FISMA, and OMB customer\-experience reporting\. ## Stats - 11M\+ residents served by monitored services - 73% fewer citizen\-impacting incidents - 0 scripts to write or maintain - ATO evidence generated continuously ## Page sections ### Test the service the way a resident actually uses it\. Category: Dedicated Pings tell you a server is alive\. They don't tell you that someone trying to apply for benefits gets stuck on step three at 11pm on a Sunday\. APIContext runs full multi\-step journeys — through identity, eligibility, intake, and notification — on schedule, from the networks your residents use\. - Multi\-step journeys with payload assertions - Login\.gov, OIDC, PKCE, mTLS — handled, no scripts - Mobile carrier and rural\-broadband probes ### What citizens see — not what your enclave dashboard says\. Category: Understanding Inside the agency boundary, your APM goes green\. Meanwhile, IPv6 paths are broken, mobile carriers are routing slowly, and Login\.gov redirects are stalling\. APIContext probes from outside the perimeter so you find what internal tools physically cannot see\. - Probes across every major commercial and gov cloud - DNS, TLS, IPv4/IPv6, certificate, CDN\-edge health - Side\-by\-side: inside agent vs\. outside\-in reality ### ATO evidence that writes itself\. Category: Proactive Your auditor doesn't want a dashboard screenshot — they want continuous evidence, per service, mapped to the controls\. APIContext generates run\-by\-run logs that line up with FedRAMP continuous monitoring, FISMA reporting, and NIST 800\-53 / 800\-218 expectations, with an immutable trail your ATO package can cite\. - FedRAMP Moderate · High aligned - FISMA continuous monitoring evidence - NIST 800\-53 · 800\-218 control mapping ## Key facts - FedRAMP · StateRAMP - FISMA Mod · High - NIST 800\-53 · 800\-218 - OMB M\-22\-22 - 21st Century IDEA - 11M\+ residents served by monitored services - 73% fewer citizen\-impacting incidents - 0 scripts to write or maintain - ATO evidence generated continuously - Test the service the way a resident actually uses it\.: Pings tell you a server is alive\. They don't tell you that someone trying to apply for benefits gets stuck on step three at 11pm on a Sunday\. APIContext runs full multi\-step journeys — through identity, eligibility, intake, and notification — on schedule, from the networks your residents use\. - What citizens see — not what your enclave dashboard says\.: Inside the agency boundary, your APM goes green\. Meanwhile, IPv6 paths are broken, mobile carriers are routing slowly, and Login\.gov redirects are stalling\. APIContext probes from outside the perimeter so you find what internal tools physically cannot see\. - ATO evidence that writes itself\.: Your auditor doesn't want a dashboard screenshot — they want continuous evidence, per service, mapped to the controls\. APIContext generates run\-by\-run logs that line up with FedRAMP continuous monitoring, FISMA reporting, and NIST 800\-53 / 800\-218 expectations, with an immutable trail your ATO package can cite\. - APIContext has been a very successful tool\. The alerting and performance monitoring capabilities have given very useful information to operational teams\. ## Testimonial > APIContext has been a very successful tool\. The alerting and performance monitoring capabilities have given very useful information to operational teams\. — Simon Fergusson, Ministry of Business, Innovation and Employment, New Zealand ## Primary entities - APIContext - Industry · Government - API monitoring - FedRAMP · StateRAMP - FISMA Mod · High - NIST 800\-53 · 800\-218 - OMB M\-22\-22 - 21st Century IDEA ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [API monitoring you can show to an auditor — and a citizen\.](/contact) --- # IT Industry Canonical URL: https://apicontext.com/solutions/industry-it Source: static Description: Secure, low\-code, functional API monitoring gives IT teams an external view of end\-to\-end services, customer experience, vendor dependencies, and SLA performance\. ## Summary Move your API operations outside your platform\. Secure, low\-code, functional API monitoring gives IT teams an external view of end\-to\-end services, customer experience, vendor dependencies, and SLA performance\. ## Stats - 125\+ global monitoring locations - 6 continents of coverage - CASC service comparison - OTEL observability\-ready signal ## Page sections ### Monitor the delivery chain from where users are\. Category: Connectivity Enterprise connectivity helped create API\-first operations\. APIContext monitors the whole chain with real\-time feedback from outside your stack\. - External customer\-perspective monitoring - Internal and partner API workflows - Real\-time feedback on operational quality ### Create SLA measurements everyone can agree on\. Category: Intelligence Generate actionable intelligence for vendor discussions, third\-party dependencies, and API consumers with data that is independent of the delivery team\. - Mutual SLA and SLO evidence - Benchmarking for externally consumed APIs - Reports for business and technical stakeholders ### Resolve perceived problems with hard proof\. Category: Resolution Find root causes quickly, provide third\-party assurance, and show the bigger picture when internal tools miss API\-specific behavior\. - External end\-to\-end monitoring from the regions and cloud data centers stakeholders use - Accurate 24/7 data based on production scenarios customers depend on - SLO, SLA, security, and quality reporting that different teams can trust - Integrations with observability, incident, reporting, and DevOps workflows ## Key facts - Enterprise APIs - Low\-code monitoring - Vendor evidence - SLA assurance - External view - 125\+ global monitoring locations - 6 continents of coverage - CASC service comparison - OTEL observability\-ready signal - Monitor the delivery chain from where users are\.: Enterprise connectivity helped create API\-first operations\. APIContext monitors the whole chain with real\-time feedback from outside your stack\. - Create SLA measurements everyone can agree on\.: Generate actionable intelligence for vendor discussions, third\-party dependencies, and API consumers with data that is independent of the delivery team\. - Resolve perceived problems with hard proof\.: Find root causes quickly, provide third\-party assurance, and show the bigger picture when internal tools miss API\-specific behavior\. - With APIContext, we were able to monitor API metrics, collect them in one place, and gain insight about our performance\. ## Testimonial > With APIContext, we were able to monitor API metrics, collect them in one place, and gain insight about our performance\. — David Ting, VP Engineering, Nylas ## Primary entities - APIContext - Solutions - API monitoring - Enterprise APIs - Low\-code monitoring - Vendor evidence - SLA assurance - External view ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Give IT operations an outside\-in API view\.](/contact) --- # Telecom Industry Canonical URL: https://apicontext.com/solutions/industry-telecom Source: static Description: Telecom APIs power partners, customer engagement, account setup, number portability, and monetized services\. APIContext verifies service quality from the networks and clouds those partners actually use\. ## Summary API services drive telecom operations\. See issues first\. Telecom APIs power partners, customer engagement, account setup, number portability, and monetized services\. APIContext verifies service quality from the networks and clouds those partners actually use\. ## Stats - 125\+ global monitoring locations - 24/7 critical workflow monitoring - MTLS partner auth monitoring - SLA compliance reporting ## Page sections ### Hold every partner to the contract you signed with them\. Category: Partner SLO management Whether you're integrating with messaging gateways, carrier ID services, or number portability providers, APIContext continuously measures their actual performance against the SLOs in their contract and shows you who's keeping their end of the deal\. - Continuous SLO and p95 latency tracking per partner - Auto\-detected breaches with trace\-level evidence - Service credits, escalation, and renegotiation backed by data - Independent benchmark that partners cannot dispute ### Every partner security mode, handled, no scripts\. Category: Secure by default Telecom integrations do not run on a single auth mode\. Partners use MTLS certificates, OAuth 2 client\_credentials, signed JWT assertions, and legacy WS\-Security; APIContext speaks all of it and rotates credentials automatically\. - MTLS client certificates that are auto\-renewed and monitored - OAuth 2 client\_credentials and authorization\_code flows - JWS and JWT signed assertions with ES256 and RS256 - Legacy SOAP plus WS\-Security for older carrier integrations ### From the cloud your customers run in, not the cloud you run in\. Category: Outside\-in monitoring Your APM agent says everything is fine\. Your customers say it is not\. The truth is in between DNS, TLS, edge routing, and partner upstreams, so APIContext probes from external data centers across the regions your customers and partners use\. - Probes in every major cloud and region your partners use - DNS, TLS, certificate, and routing health on every call - Independent verification, not your stack and not your bias - Comparison view: inside agent vs\. outside\-in reality ## Key facts - Carrier\-scale APIs - Partner MTLS - SOAP and REST - SLA reporting - 125\+ global monitoring locations - 24/7 critical workflow monitoring - MTLS partner auth monitoring - SLA compliance reporting - Hold every partner to the contract you signed with them\.: Whether you're integrating with messaging gateways, carrier ID services, or number portability providers, APIContext continuously measures their actual performance against the SLOs in their contract and shows you who's keeping their end of the deal\. - Every partner security mode, handled, no scripts\.: Telecom integrations do not run on a single auth mode\. Partners use MTLS certificates, OAuth 2 client\_credentials, signed JWT assertions, and legacy WS\-Security; APIContext speaks all of it and rotates credentials automatically\. - From the cloud your customers run in, not the cloud you run in\.: Your APM agent says everything is fine\. Your customers say it is not\. The truth is in between DNS, TLS, edge routing, and partner upstreams, so APIContext probes from external data centers across the regions your customers and partners use\. - APIContext helped us increase visibility of our API performance and significantly improved awareness\. ## Testimonial > APIContext helped us increase visibility of our API performance and significantly improved awareness\. — Val Novikov, CTO, Fispan ## Primary entities - APIContext - Solutions - API monitoring - Carrier\-scale APIs - Partner MTLS - SOAP and REST - SLA reporting ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Monitor telecom API scenarios end to end\.](/contact) --- # Partners & Developers Canonical URL: https://apicontext.com/solutions/partners-developers Source: static Description: APIContext partners with technology leaders, open standards stewards, and industry bodies so developers can understand the APIs behind modern applications\. ## Summary Visibility for every API, across every environment\. APIContext partners with technology leaders, open standards stewards, and industry bodies so developers can understand the APIs behind modern applications\. ## Stats - OTEL expanded alerting and webhook delivery - cloud monitoring node locations across major providers - teams developer and partner workflows - open standards and ecosystem alignment ## Page sections ### Work with the platforms your teams already use\. Category: Our partnerships APIContext integrates with cloud providers, observability platforms, incident tools, data platforms, and developer ecosystems through webhooks and OpenTelemetry\. - Expanded alerting into partner dashboards - Webhook delivery for alerts, events, and metrics - Cloud\-provider monitoring nodes for uptime monitoring ### From cloud locations to alert destinations\. Category: Technology partnerships Partnerships with providers such as AWS, Azure, Google, IBM, Akamai, Datadog, Dynatrace, BigPanda, Atlassian, Elastic, Honeycomb, and many others help teams route API signal where it matters\. - Monitoring node locations on major clouds and edge providers - OpenTelemetry webhook delivery - Incident, APM, and data\-platform integrations ### Give developers the API visibility they need\. Category: Developer ecosystem APIs are the backbone of modern applications\. APIContext helps developers and partner teams understand API behavior across environments, standards, and application workflows\. - Developer\-friendly monitoring workflows - Standards\-aware API observability - Partner and ecosystem visibility ### Technology partnerships and integration surfaces Partner integrations with logos, descriptions, and documentation links\. - [Akamai](https://www.akamai.com/resources/product-brief/managed-service-for-api-performance) - [Alibaba Cloud](https://docs.apicontext.com/guides/alerting/expanded-alerting/export-to-alibaba-cloud-via-opentelemetry) - [AWS](https://docs.apicontext.com/guides/alerting/expanded-alerting/export-to-aws-via-opentelemetry) - [Microsoft](https://docs.apicontext.com/guides/alerting/expanded-alerting/export-to-microsoft-azure-monitor-via-opentelemetry) - [IBM](https://docs.apicontext.com/guides/alerting/expanded-alerting/export-to-ibm-instana-via-opentelemetry) ## Key facts - Technology partnerships - OpenTelemetry webhooks - Developer workflows - Private nodes - Alert integrations - OTEL expanded alerting and webhook delivery - cloud monitoring node locations across major providers - teams developer and partner workflows - open standards and ecosystem alignment - Work with the platforms your teams already use\.: APIContext integrates with cloud providers, observability platforms, incident tools, data platforms, and developer ecosystems through webhooks and OpenTelemetry\. Expanded alerting into partner dashboards Webhook delivery for alerts, events, and metrics Cloud\-provider monitoring nodes for uptime monitoring - From cloud locations to alert destinations\.: Partnerships with providers such as AWS, Azure, Google, IBM, Akamai, Datadog, Dynatrace, BigPanda, Atlassian, Elastic, Honeycomb, and many others help teams route API signal where it matters\. Monitoring node locations on major clouds and edge providers OpenTelemetry webhook delivery Incident, APM, and data\-platform integrations - Give developers the API visibility they need\.: APIs are the backbone of modern applications\. APIContext helps developers and partner teams understand API behavior across environments, standards, and application workflows\. Developer\-friendly monitoring workflows Standards\-aware API observability Partner and ecosystem visibility - Akamai: Akamai's Managed Service for API Performance runs on APIContext's synthetic monitoring platform\. - Alibaba Cloud: APIContext integrates with Alibaba Cloud via OpenTelemetry webhook delivery for expanded alerting\. - AWS: APIContext runs monitoring nodes on AWS and supports OpenTelemetry webhook alerting workflows\. - Microsoft: APIContext runs monitoring nodes on Azure and supports Teams webhooks and OpenTelemetry alerting\. - IBM: APIContext sends API monitoring data to IBM Instana over OpenTelemetry\. ## Primary entities - APIContext - Partners & Developers - partners - developers - OpenTelemetry - Technology partnerships - OpenTelemetry webhooks - Developer workflows - Private nodes - Alert integrations ## Audience - partners - developers - platform teams - integration teams ## Primary links - [Connect APIContext to your ecosystem\.](/contact) - [Explore monitoring](/features/api-monitoring) --- # CISO Solutions Canonical URL: https://apicontext.com/solutions/solutions-for-ciso Source: static Description: API security isn't just about your design or monitoring for intrusion threats\. It's about whether the controls you shipped are still doing their job — right now, in production, from the locations your customers actually use\. APIContext makes it easy and secure to run functional security checks against live systems, continuously\. ## Summary Right\-shift API security monitoring into production run\-time\. API security isn't just about your design or monitoring for intrusion threats\. It's about whether the controls you shipped are still doing their job — right now, in production, from the locations your customers actually use\. APIContext makes it easy and secure to run functional security checks against live systems, continuously\. ## Stats - right\-shift checks in production run\-time - FIPS\-140 HSM for banking\-grade secrets - 24/7 OAuth · OIDC · FAPI scenarios - 0 long\-lived secrets in CI ## Page sections ### A control isn't a control until you've watched it fail closed\. Category: Active security checks Static analysis tells you what the policy says\. Penetration tests tell you what an attacker found last quarter\. Neither tells you whether the OAuth flow rejected an expired token at 14:02 today\. APIContext runs the positive and negative scenarios continuously — so the moment a control fails open, you know\. - Positive checks · valid token \+ correct scope = 200 - Negative checks · expired / tampered / wrong\-scope = rejected - Run on schedule from every region you care about - Every run is evidence — defensible to auditors ### Banking\-grade auth, monitored the way it was meant to be used\. Category: Built for OAuth, OIDC, and FAPI Low\-code, totally secure management of API authentication\. Integrated OAuth handling with full JWT support and a FIPS\-140 compliant HSM for banking protocols and finance\-level security\. Monitor OpenID Connect, FAPI compliance, token refresh, and OAuth scenarios continuously — and never put a long\-lived secret in a CI script\. - OAuth 2\.0 \+ PKCE · PAR · refresh\-token rotation - OpenID Connect · userinfo · ID\-token validation - FAPI 1\.0 Advanced · request\-object signing - JWS / JWT · RS256 · ES256 · keys live in the HSM ### Catch what shifted between Friday's deploy and Monday's audit\. Category: Configuration drift Production calls against key resources spot when security problems emerge from unexpected configuration changes — a bucket reverted to public, a JWKS rotation missed, an admin route that lost its scope check\. APIContext sees them the way an attacker would: from outside the platform, with real credentials\. - Resources accidentally opened · 200 anonymous detection - JWKS / key\-rotation overdue alerts - Scope\-widening and route\-exposure detection - TLS / cipher / cert drift, watched continuously ### The evidence pack writes itself — and it's the same one auditors trust\. Category: Audit \+ compliance reports Generate audit and compliance reports for internal and external stakeholders automatically\. Every line in the report links back to a live call: timestamp, region, status, signature, scope\. Internal stakeholders, external regulators, and your board all read the same numbers — because they all come from the same continuous feed\. - Quarterly compliance PDF · auto\-generated, signed - FAPI · PSD2 · Open Banking · regulator\-ready - Per\-call evidence · immutable run history - Custom dashboards for execs, audit, and the board ### Right\-shift checks\. Independent evidence\. Auditors get fewer arguments\. Category: Why CISOs pick APIContext Shift\-left found a place\. Shift\-right is the half nobody runs\. APIContext fills it: continuous functional security monitoring on production APIs, with the same auth and the same locations your customers use — independent of the team being audited\. - Active checks on every part of the security system - Positive \+ negative OAuth \+ JWT scenarios - Configuration\-drift detection in production - Audit \+ compliance reports — internal and external ## Key facts - Right\-shift to run\-time - OAuth · OIDC · FAPI - JWS / JWT signing - FIPS\-140 HSM - Positive \+ negative checks - right\-shift checks in production run\-time - FIPS\-140 HSM for banking\-grade secrets - 24/7 OAuth · OIDC · FAPI scenarios - 0 long\-lived secrets in CI - A control isn't a control until you've watched it fail closed\.: Static analysis tells you what the policy says\. Penetration tests tell you what an attacker found last quarter\. Neither tells you whether the OAuth flow rejected an expired token at 14:02 today\. APIContext runs the positive and negative scenarios continuously — so the moment a control fails open, you know\. - Banking\-grade auth, monitored the way it was meant to be used\.: Low\-code, totally secure management of API authentication\. Integrated OAuth handling with full JWT support and a FIPS\-140 compliant HSM for banking protocols and finance\-level security\. Monitor OpenID Connect, FAPI compliance, token refresh, and OAuth scenarios continuously — and never put a long\-lived secret in a CI script\. - Catch what shifted between Friday's deploy and Monday's audit\.: Production calls against key resources spot when security problems emerge from unexpected configuration changes — a bucket reverted to public, a JWKS rotation missed, an admin route that lost its scope check\. APIContext sees them the way an attacker would: from outside the platform, with real credentials\. - The evidence pack writes itself — and it's the same one auditors trust\.: Generate audit and compliance reports for internal and external stakeholders automatically\. Every line in the report links back to a live call: timestamp, region, status, signature, scope\. Internal stakeholders, external regulators, and your board all read the same numbers — because they all come from the same continuous feed\. - Right\-shift checks\. Independent evidence\. Auditors get fewer arguments\.: Shift\-left found a place\. Shift\-right is the half nobody runs\. APIContext fills it: continuous functional security monitoring on production APIs, with the same auth and the same locations your customers use — independent of the team being audited\. - APIContext helped us increase visibility of our APIs' performance and significantly improved awareness\. As our international footprint grew we used it to measure and confirm internal stack optimizations — it's great to have an independent benchmark to compare against\. ## Testimonial > APIContext helped us increase visibility of our APIs' performance and significantly improved awareness\. As our international footprint grew we used it to measure and confirm internal stack optimizations — it's great to have an independent benchmark to compare against\. — Val Novikov, CTO · Fispan ## Primary entities - APIContext - Persona · CISO - API monitoring - Right\-shift to run\-time - OAuth · OIDC · FAPI - JWS / JWT signing - FIPS\-140 HSM - Positive \+ negative checks ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [It's time to right\-shift your API security into run\-time\.](/contact) --- # Customer Success Canonical URL: https://apicontext.com/solutions/solutions-for-customer-success Source: static Description: Customer Success teams need independent verification when customers report API issues\. APIContext shows what customers experience from where they actually operate\. ## Summary Build trust in API performance for every customer conversation\. Customer Success teams need independent verification when customers report API issues\. APIContext shows what customers experience from where they actually operate\. ## Stats - CS customer\-ready evidence - 24/7 scenario validation - SLO shared service goals - MTTI lower issue identification time ## Page sections ### Show what the customer actually experienced\. Category: Verify When internal teams cannot reproduce a complaint, APIContext provides external performance metrics from customer\-like regions and clouds\. - Customer\-region monitoring - Independent performance verification - Evidence customers and engineering can share ### Set, measure, and agree on SLOs and SLAs\. Category: Align Use trusted metrics to make customer service\-level discussions concrete and reduce subjective disputes\. - Shared SLO and SLA reporting - Scenario\-based API checks - Customer\-facing service\-quality evidence ### Give DevOps the input internal monitoring may miss\. Category: Resolve APIContext reduces handoff friction by showing external behavior, auth health, and regional impact clearly\. - External end\-to\-end monitoring from the regions and cloud data centers stakeholders use - Accurate 24/7 data based on production scenarios customers depend on - SLO, SLA, security, and quality reporting that different teams can trust - Integrations with observability, incident, reporting, and DevOps workflows ## Key facts - Customer evidence - Issue verification - SLA agreement - Regional views - Shared reporting - CS customer\-ready evidence - 24/7 scenario validation - SLO shared service goals - MTTI lower issue identification time - Show what the customer actually experienced\.: When internal teams cannot reproduce a complaint, APIContext provides external performance metrics from customer\-like regions and clouds\. - Set, measure, and agree on SLOs and SLAs\.: Use trusted metrics to make customer service\-level discussions concrete and reduce subjective disputes\. - Give DevOps the input internal monitoring may miss\.: APIContext reduces handoff friction by showing external behavior, auth health, and regional impact clearly\. - I see everything very quickly on one page, and it makes it easy to go to a problem spot and dig in\. ## Testimonial > I see everything very quickly on one page, and it makes it easy to go to a problem spot and dig in\. — Brent Shaw, VP Customer Success, DTN ## Primary entities - APIContext - Solutions - API monitoring - Customer evidence - Issue verification - SLA agreement - Regional views - Shared reporting ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Support customers with independent API evidence\.](/contact) --- # Product Managers Canonical URL: https://apicontext.com/solutions/solutions-for-product-managers Source: static Description: As an API Product Manager, you have many responsibilities and many stakeholders\. Can you demonstrate to every one of them — engineering, success, security, leadership, partners, regulators — that systems are working the way you think they are? APIContext gives you one independent signal that answers all six conversations\. ## Summary Know everything about your API products\. As an API Product Manager, you have many responsibilities and many stakeholders\. Can you demonstrate to every one of them — engineering, success, security, leadership, partners, regulators — that systems are working the way you think they are? APIContext gives you one independent signal that answers all six conversations\. ## Stats - 6 stakeholder audiences served - 1 signal independent of engineering - 360° view across the API lifecycle - 0 scripts or test rigs to maintain ## Page sections ### See the whole product\. Category: Visibility External, end\-to\-end performance measurement and dependency analysis help product teams understand every route, every region, and every supplier their API products depend on\. - End\-to\-end customer journeys - Multi\-cloud and multi\-region monitoring - Internal and supplier dependency visibility ### Verify what engineering says\. Category: Verification APIContext measures from outside your APM stack and outside the team being measured, giving PMs a defensible number to bring to leadership, partners, customers, and regulators\. - Same auth, same routes, same regions - Inside\-versus\-outside performance comparison - Auditable evidence for regulators and leadership ### Speak every stakeholder's language\. Category: Voice One independent signal becomes meaningful data for every critical stakeholder, across the entire API lifecycle from design through operational deployment\. - Custom dashboards and reports per audience - Auto\-published PDF, CSV, and JSON evidence - Integrations with observability, incident, reporting, and DevOps workflows ## Key facts - Outside\-in - Lifecycle\-wide - Stakeholder\-shaped - Regulator\-ready - Zero scripts - 6 stakeholder audiences served - 1 signal independent of engineering - 360° view across the API lifecycle - 0 scripts or test rigs to maintain - See the whole product\.: External, end\-to\-end performance measurement and dependency analysis help product teams understand every route, every region, and every supplier their API products depend on\. - Verify what engineering says\.: APIContext measures from outside your APM stack and outside the team being measured, giving PMs a defensible number to bring to leadership, partners, customers, and regulators\. - Speak every stakeholder's language\.: One independent signal becomes meaningful data for every critical stakeholder, across the entire API lifecycle from design through operational deployment\. - Rather than an inside\-out view, we realized that we needed a specialized tool that could give us visibility into the performance of our site and apps in the same way that the rest of the internet sees us\. ## Testimonial > Rather than an inside\-out view, we realized that we needed a specialized tool that could give us visibility into the performance of our site and apps in the same way that the rest of the internet sees us\. — Richard Marshall, First Utility ## Primary entities - APIContext - Solutions · Product Managers - API monitoring - Outside\-in - Lifecycle\-wide - Stakeholder\-shaped - Regulator\-ready - Zero scripts ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Demonstrate that systems are working the way you think they are\.](/contact) --- # Site Reliability Engineering Canonical URL: https://apicontext.com/solutions/solutions-for-site-reliability-engineering Source: static Description: When your application isn't performing reliably, you need to know right away — and you need to diagnose root cause quickly\. APIContext gives SRE teams cross\-cloud, independent end\-to\-end monitoring of your entire solution, the way your customers use it\. Get paged before tickets land\. Tell network from infra from app in seconds\. ## Summary Know what's wrong in production immediately\. When your application isn't performing reliably, you need to know right away — and you need to diagnose root cause quickly\. APIContext gives SRE teams cross\-cloud, independent end\-to\-end monitoring of your entire solution, the way your customers use it\. Get paged before tickets land\. Tell network from infra from app in seconds\. ## Stats - 80% reduction in mean time to issue identification - 24/7 external validation - 125\+ global monitoring locations - OTEL native incident signal ## Page sections ### Get alerted before customers notice\. Category: Detect Run functional checks around the clock and alert on API, network, infrastructure, or workflow behavior that affects reliability\. - Immediate alerting into existing tools - External customer\-perspective monitoring - Checks for pre\-production and production ### Identify whether the issue is network, infrastructure, or application\. Category: Diagnose APIContext gives SRE teams endpoint, region, auth, workflow, and timing evidence in one place\. - End\-to\-end timing details - Cross\-cloud and regional comparison - Traceable API workflow results ### Prove reliability with measurable SLAs\. Category: Demonstrate Use real\-world measurements to define reliability goals, report on service levels, and guide remediation\. - External end\-to\-end monitoring from the regions and cloud data centers stakeholders use, including China - Accurate 24/7 data based on production scenarios customers depend on - SLO, SLA, security, and quality reporting that different teams can trust - Integrations with observability, incident, reporting, and DevOps workflows ## Key facts - Outside\-in detection - MTTI in seconds - SLO burn alerts - Pre\-prod & prod - Routes into your tools - 80% reduction in mean time to issue identification - 24/7 external validation - 125\+ global monitoring locations - OTEL native incident signal - Get alerted before customers notice\.: Run functional checks around the clock and alert on API, network, infrastructure, or workflow behavior that affects reliability\. - Identify whether the issue is network, infrastructure, or application\.: APIContext gives SRE teams endpoint, region, auth, workflow, and timing evidence in one place\. - Prove reliability with measurable SLAs\.: Use real\-world measurements to define reliability goals, report on service levels, and guide remediation\. - The analysis of issues and research for possible solutions helped us gain insight about our performance\. ## Testimonial > The analysis of issues and research for possible solutions helped us gain insight about our performance\. — David Ting, Nylas ## Primary entities - APIContext - Solutions - API monitoring - Outside\-in detection - MTTI in seconds - SLO burn alerts - Pre\-prod & prod - Routes into your tools ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Give SRE teams production clarity\.](/contact) ## FAQs ### How does APIContext fit into an SRE team's toolchain? APIContext gives SRE teams an outside\-in view of API reliability that internal APM and instrumentation cannot provide\. SREs use it to set per\-endpoint SLOs, track error budgets, receive incident\-grade alerts with full request/response diffs and OTEL traces attached, and generate evidence for post\-incident reviews and SLA reporting\. OTEL signals feed directly into existing observability stacks including Datadog, Splunk, New Relic, and Dynatrace\. ### How quickly does APIContext detect and alert on API failures? Checks run on configurable intervals down to every minute from multiple global locations, alerting on the first failure with full context: the failing location, HTTP response, request/response diff, and trace\. Alert routing integrates with PagerDuty, Opsgenie, Slack, and webhooks\. ### Can APIContext help SREs define and track SLOs? Yes\. APIContext supports native SLO definition per API endpoint with configurable availability and latency targets, automatic error budget tracking, and burn\-rate alerts that notify on\-call engineers when the error budget is being consumed faster than the target rate allows\. ### Does APIContext require modifying the APIs being monitored? No\. APIContext operates entirely outside your infrastructure as an external caller — no agents, SDKs, or code changes required\. This makes it possible to start monitoring any API, including third\-party or partner APIs you do not own, in minutes, while ensuring monitoring reflects true external behavior rather than instrumented internal behavior\. --- # API Security Use Case Canonical URL: https://apicontext.com/solutions/use-case-api-security Source: static Description: Security is not a one\-time design check\. APIContext runs real calls against production security flows to verify OAuth, FAPI, JWT, MTLS, scopes, tokens, and protected resources\. ## Summary Runtime security validation for production APIs\. Security is not a one\-time design check\. APIContext runs real calls against production security flows to verify OAuth, FAPI, JWT, MTLS, scopes, tokens, and protected resources\. ## Stats - 24/7 security flow checks - FAPI runtime validation - JWT signing support - audit security evidence ## Page sections ### Make real functional security calls from outside your stack\. Category: Secured Verify authentication, authorization, and secure API behavior the way customers and partners experience it in production\. - Positive and negative security checks - OAuth, FAPI, JWT, and MTLS support - Encrypted key and certificate handling ### Shift security assurance into production runtime\. Category: Runtime metrics Traditional shift\-left checks are essential, but API teams also need production assurance that security functions continue to work\. - Token refresh and scope behavior checks - Protected\-resource verification - Production alerting for unexpected exposure ### Generate evidence for risk and compliance teams\. Category: Auditability Create audit traces that prove security controls are functioning for internal assessors, external stakeholders, and regulators\. - External end\-to\-end monitoring from the regions and cloud data centers stakeholders use - Accurate 24/7 data based on production scenarios customers depend on - SLO, SLA, security, and quality reporting that different teams can trust - Integrations with observability, incident, reporting, and DevOps workflows ## Key facts - Shift\-right security - OAuth and FAPI - JWT and MTLS - Audit traces - Production validation - 24/7 security flow checks - FAPI runtime validation - JWT signing support - audit security evidence - Make real functional security calls from outside your stack\.: Verify authentication, authorization, and secure API behavior the way customers and partners experience it in production\. - Shift security assurance into production runtime\.: Traditional shift\-left checks are essential, but API teams also need production assurance that security functions continue to work\. - Generate evidence for risk and compliance teams\.: Create audit traces that prove security controls are functioning for internal assessors, external stakeholders, and regulators\. - APIContext helped us increase visibility of our APIs performance and significantly improved awareness\. ## Testimonial > APIContext helped us increase visibility of our APIs performance and significantly improved awareness\. — Val Novikov, CTO, Fispan ## Primary entities - APIContext - Solutions - API monitoring - Shift\-right security - OAuth and FAPI - JWT and MTLS - Audit traces - Production validation ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Right\-shift API security monitoring\.](/contact) --- # Multi\-Cloud Canonical URL: https://apicontext.com/solutions/use-case-multi-cloud Source: static Description: APIContext measures API performance from every major cloud, every region, and every edge so you can see the cloud the way it actually works\. ## Summary Your customers aren't all in one cloud\. Why should your monitoring be? APIContext measures API performance from every major cloud, every region, and every edge so you can see the cloud the way it actually works\. ## Stats - 125\+ global monitoring locations - 5\+ major cloud providers monitored - 24/7 API\-native checks - 30\+ data points per API call ## Page sections ### One API\. Every cloud\. Every region\. Category: See the cloud the way it works Your customers and partners are not all in the same cloud, so one vantage point misses the real picture\. See where there are networking bottlenecks, where peering is hurting you, and which regions need attention\. - Probe surface across AWS, GCP, Azure, and Akamai edge - Per\-customer\-region p95, not just whether the origin is up - Networking and peering issues surfaced as a first\-class signal - Cross\-cloud comparison and sector benchmarking ### Single\-cloud monitoring is single\-customer monitoring\. Category: Multi\-cloud blindspots Cloud monitoring tools and APM agents see the world from inside one cloud\. The other customer traffic coming over peering links, CDNs, and regions you do not operate in is invisible unless you stitch every vantage point together\. - Catches cross\-cloud peering regressions same\-cloud APM never sees - DNS, TLS, and routing failures spotted from the customer's side of the wire - Inside\-vs\-outside diff per cloud - Historic CASC score per cloud ### Drop a private node where the managed network does not reach\. Category: Probes anywhere you need them If your customers run in a private datacenter, a factory floor, or a region we do not yet have managed coverage in, drop a private node there and keep the same data model, dashboards, and reports\. - Lightweight private nodes that run anywhere a container runs - Same calls, same credentials, same reports as managed nodes - Air\-gapped and on\-prem deployments - Configuration\-as\-code for private probes ## Key facts - AWS - Azure - Google Cloud - Akamai - 125\+ global monitoring locations - 5\+ major cloud providers monitored - 24/7 API\-native checks - 30\+ data points per API call - One API\. Every cloud\. Every region\.: Your customers and partners are not all in the same cloud, so one vantage point misses the real picture\. See where there are networking bottlenecks, where peering is hurting you, and which regions need attention\. - Single\-cloud monitoring is single\-customer monitoring\.: Cloud monitoring tools and APM agents see the world from inside one cloud\. The other customer traffic coming over peering links, CDNs, and regions you do not operate in is invisible unless you stitch every vantage point together\. - Drop a private node where the managed network does not reach\.: If your customers run in a private datacenter, a factory floor, or a region we do not yet have managed coverage in, drop a private node there and keep the same data model, dashboards, and reports\. - APIContext helped us identify significant latency and improve the experience from more than 7 seconds to 500 milliseconds\. ## Testimonial > APIContext helped us identify significant latency and improve the experience from more than 7 seconds to 500 milliseconds\. — Atilla B\., Security Operations Engineer, Signify ## Primary entities - APIContext - Solutions - API monitoring - AWS - Azure - Google Cloud - Akamai ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [See the cloud the way it actually works\.](/contact) --- # SLA Management Canonical URL: https://apicontext.com/solutions/use-case-sla-management Source: static Description: Companies depend on APIs to enable time\-sensitive, mission\-critical business activities\. Agreeing on and actively validating SLA conformance is essential\. Third\-party verification stops internal teams from hiding or misrepresenting performance, and gives Customer Success the data they need to defend the contract\. ## Summary Service levels are only useful if both sides agree on what they mean\. Companies depend on APIs to enable time\-sensitive, mission\-critical business activities\. Agreeing on and actively validating SLA conformance is essential\. Third\-party verification stops internal teams from hiding or misrepresenting performance, and gives Customer Success the data they need to defend the contract\. ## Stats - 3rd\-party independent measurement - 125\+ global probe locations - 24/7 functional calls and low\-traffic coverage - 0 scripts to write or maintain ## Page sections ### Set Service Level Objectives, and prove you can hit them\. Category: Set & test SLOs Don't sign an SLA you can't defend\. Set targets in APIContext, run them against production from the regions your customers use, and watch budgets burn down over the contract window\. - Targets per route, per region, and per supplier - Live SLO budget tracking with burn\-rate alerts - Mutual visibility, so customer and provider see the same numbers - Configuration as code, versioned with the API contract ### Third\-party measurement\. The team being graded isn't grading themselves\. Category: Measure from where Internal APM tells you what your stack says\. APIContext tells you what your customers see\. When the two disagree, independent measurement is the tiebreaker\. - Outside\-in synthetic calls, not from inside your VPC - Trust and confidence from metrics not owned by the delivery team - Inside\-vs\-outside comparison for the real customer experience - Defensible to leadership, customers, and regulators ### One number both sides accept, because both sides see it the same way\. Category: Create standard reports Generate mutual SLA compliance reports from live traffic, using the same locations and credentials your customers actually use\. Service credits, breach evidence, and renewal data all come from the same independent feed\. - Provider\-customer mutual reports, monthly or quarterly - Auto\-calculated service credits with line\-item evidence - Per\-region, per\-route, and per\-cloud breakdowns - PDF, CSV, and JSON export for regulator\-ready reporting ### Base SLOs and SLAs on real\-world performance\. Category: Base SLOs and SLAs Base existing and future SLOs and SLAs on real\-world performance metrics\. Don't get caught offering service levels that can't be achieved\. Benchmark against the rest of your sector\. - Real\-world SLO baselining - Sector benchmarks and CASC score context - Risk\-priced SLA negotiation data - Contract clauses backed by observed availability ### From Customer Success to vendor management, one signal serves them all\. Category: Built for the people who care Customer Success teams stop getting blindsided\. Vendor managers stop arguing with suppliers about who is at fault\. Sales and legal sign SLAs they can actually defend\. - Customer Success gets pre\-emptive tickets and defensible answers - Engineering gets an independent number leadership trusts - Vendor management gets supplier credit claims backed by data - Sales and legal get contract clauses based on real\-world data ## Key facts - Third\-party verified - Mutual SLA reports - Multi\-cloud probes - Service\-credit evidence - Customer\-shaped - 3rd\-party independent measurement - 125\+ global probe locations - 24/7 functional calls and low\-traffic coverage - 0 scripts to write or maintain - Set Service Level Objectives, and prove you can hit them\.: Don't sign an SLA you can't defend\. Set targets in APIContext, run them against production from the regions your customers use, and watch budgets burn down over the contract window\. - Third\-party measurement\. The team being graded isn't grading themselves\.: Internal APM tells you what your stack says\. APIContext tells you what your customers see\. When the two disagree, independent measurement is the tiebreaker\. - One number both sides accept, because both sides see it the same way\.: Generate mutual SLA compliance reports from live traffic, using the same locations and credentials your customers actually use\. Service credits, breach evidence, and renewal data all come from the same independent feed\. - Base SLOs and SLAs on real\-world performance\.: Base existing and future SLOs and SLAs on real\-world performance metrics\. Don't get caught offering service levels that can't be achieved\. Benchmark against the rest of your sector\. - From Customer Success to vendor management, one signal serves them all\.: Customer Success teams stop getting blindsided\. Vendor managers stop arguing with suppliers about who is at fault\. Sales and legal sign SLAs they can actually defend\. - We were able to monitor the metrics of API calls, collect them in one place, and gain real insight about our performance\. Other developers building APIs where duration and speed matter would do well to consider APIContext to drive performance improvement\. ## Testimonial > We were able to monitor the metrics of API calls, collect them in one place, and gain real insight about our performance\. Other developers building APIs where duration and speed matter would do well to consider APIContext to drive performance improvement\. — David Ting, Nylas ## Primary entities - APIContext - Use Case · SLA Management - API monitoring - Third\-party verified - Mutual SLA reports - Multi\-cloud probes - Service\-credit evidence - Customer\-shaped ## Audience - API teams - SRE teams - product teams - executive teams ## Primary links - [Lower your mean time to issue identification\.](/contact) --- # Subscription Agreement Canonical URL: https://apicontext.com/subscription Source: static Description: Terms and conditions for APIContext API monitoring service subscriptions\. ## Summary This agreement governs your subscription to APIContext API monitoring services\. ## Page sections ### Subscription Agreement Category: Legal This Agreement is between the entity entering this Agreement \(“Subscriber”\) and APIContext Inc\. \(“APIContext”\) \(collectively the “Parties” and each a “Party&\#8221;\)\. Under this Agreement, Subscriber has a limited and revocable right to subscribe to, access and use the Services defined below, as described by and limited by this Agreement\. SUBSCRIBER AGREES TO BE BOUND BY THE TERMS OF THIS AGREEMENT BY REGISTERING FOR AN ACCOUNT WITH APICONTEXT OR ORDERING A SERVICE PROVIDED BY APICONTEXT\. THIS AGREEMENT WILL BE EFFECTIVE ON THE DATE SUBSCRIBER COMPLETES REGISTRATION FOR AN ACCOUNT OR ORDERS THE SERVICE \(“EFFECTIVE DATE”\)\. 1\. Selected Definitions “Agreement” means this Subscription Agreement, any Invoices, and any materials available on the APIContext website specifically incorporated by reference herein, including APIContext’s Website Terms of Service at https://apicontext\.com/tos and Privacy Policy at https://apicontext\.com/privacy, as such materials, including the terms of this Agreement, may be updated by APIContext from time to time in its sole discretion\. “APIContext Technology” means all of APIContext’s proprietary technology \(including software, hardware, products, processes, algorithms, user interfaces, know\-how, techniques, designs, and other tangible or intangible technical material or information\) made available to Subscriber by APIContext in providing the Service\. “Content” means the audio and visual information, documents, software, products, data and services contained or made available to Subscriber in the course of using the Service\. “Data Content” means the test results, performance metrics, reports, and other outputs generated by the Services from Subscriber Data or Subscriber’s use of the Services\. “Initial Term” means the Initial Term identified on any Invoice or the Subscription Management Page\. The Initial Term is free unless indicated otherwise in the Invoice or Subscription Management Page\. “Intellectual Property Rights” means any unpatented inventions, patent applications, patents, design rights, copyrights, trademarks, service marks, trade names, domain name rights, mask work rights, know\-how and other trade secret rights, and all other intellectual property rights, derivatives thereof, and forms of protection of a similar nature anywhere in the world\. “Invoice\(s\)” means the form evidencing the initial subscription for the Service and any subsequent Invoices submitted online or in written form, specifying, among other things, the number of Licenses and Services contracted for, the applicable fees, and other charges as agreed to between the Parties, each such Invoice to be incorporated into and to become a part of this Agreement \(in the event of any conflict between the terms of this Agreement and the terms of any such Invoice, the terms of this Agreement shall prevail except as otherwise stated in this Agreement\)\. The Invoice will be on the Subscription Management Page, unless the Parties have entered a separate, signed and written Invoice\. APIContext may or may not send an Invoice to Subscriber based on the type of Service that Subscriber has ordered\. All Service pricing is online unless a separate agreement has been reached\. “License Administrator\(s\)” means those Users designated by Subscriber who are authorized to purchase Licenses by executing written Invoices and to create User accounts and otherwise administer Subscriber’s use of the Service\. “Renewal Term\(s\)” means any Term after the Initial Term\. “Service\(s\)” means the APIContext online monitoring, testing, and assurance services developed, operated, and maintained by APIContext and made available to Subscriber under this Agreement, including APIContext Technology and applicable Content, whether accessed through apicontext\.com, any APIContext\-owned or operated website, domain or subdomain, or any other location designated by APIContext for delivery of the Services\. The scope of the Services depends on the subscription plan or services selected by Subscriber during registration\. “Subscriber Data” means any data, information, or other materials provided or submitted by Subscriber to the Services, together with Data Content generated from Subscriber’s use of the Services, but excluding APIContext Technology and Aggregate Data as defined in Section 4\(c\)\. “Subscription Management Page” means APIContext’s online application that allows the License Administrator, among other things, to add additional Users to the Service\. The invoice and other Service details are available on the Subscription Management Page\. “Term\(s\)” means the period\(s\) during which a specified number of Users are licensed to use the Service pursuant to the Invoices\(s\)\. Term includes both the Initial Term and Renewal Term\(s\)\. “User\(s\)” means Subscriber employees, representatives, consultants, contractors, or agents who are authorized to use the Service and have been supplied user identifications and passwords by Subscriber \(or by APIContext at Subscriber’s request\)\. 2\. Service License Grant and Restrictions a\. APIContext hereby grants Subscriber a limited, revocable, nonexclusive, nontransferable, right to use the Service globally to create, store, and run the Service within the bounds of the Service level chosen by Subscriber, for the Term, solely for Subscriber’s own internal business purposes, subject to the terms and conditions of this Agreement \(“License”\)\. All rights not expressly granted to Subscriber are reserved by APIContext and its licensors\. Subscriber may not access the Service if Subscriber is a direct competitor of APIContext, except with APIContext’s prior written consent\. In addition, Subscriber may not access API Monitor for purposes of monitoring the Services’ availability, performance or functionality, or for any other benchmarking or competitive purposes except pursuant to a separate, written and executed agreement between the Parties\. The License is subject to the limitations in Section 3 below\. b\. Subscriber shall not \(i\) license, sublicense, sell, resell, transfer, assign, distribute, or otherwise commercially exploit or make available to any third party the Service or the Content in any way; \(ii\) modify or make derivative works based upon the Service or the Content; \(iii\) create Internet links to the Service or frame or mirror any Content on any other server or wireless or Internet\-based device; or \(iv\) reverse engineer or access the Service in order to \(a\) build a competitive product or service, \(b\) build a product using similar ideas, features, functions or graphics of the Service, or \(c\) copy any ideas, features, functions or graphics of the Service\. For purposes of this Section 2\(b\), neither the Service nor Content includes Subscriber Data or Data Content owned by Subscriber under Section 3\(a\)\. The permission to use Subscriber Data and Data Content does not authorize Subscriber to resell, sublicense, or provide the Services as a managed service without a separate written agreement with APIContext\. User Licenses cannot be shared or used by more than one individual User but may be reassigned from time to time to new Users who are replacing former Users who have terminated employment or otherwise changed job status or function and no longer use the Service\. c\. Subscriber shall not use the Service to: \(i\) send spam or otherwise duplicative or unsolicited messages in violation of applicable laws, or otherwise violate any law in connection with the Services or this Agreement; \(ii\) send or store infringing, obscene, threatening, libelous, or otherwise unlawful or tortuous material, including material harmful to children or that violates third party privacy rights; \(iii\) send or store material containing software viruses, worms, Trojan horses, or other harmful computer code, files, scripts, agents, or programs; \(iv\) interfere with or disrupt the integrity or performance of the Service or the data contained therein; or \(v\) attempt to gain unauthorized access to the Service or its related systems or networks\. d\. This Agreement entitles the Subscriber the limited, revocable right to access the Service through the use of a single Subscriber account\. One License grants the Subscriber one \(1\) License Administrator account to access the Service and one \(1\) sub\-License for each User designated by the Subscriber\. Subscriber is responsible for conforming all User activities to Subscriber’s obligations and restrictions under this Agreement and is responsible for all User activities related to the Service as if they were Subscriber’s own activities\. e\. The License Administrator may add Users by updating User information on the User Admin page of the Service\. Added User Licenses will be coterminous with the preexisting Term \(either Initial Term or Renewal Term\)\. 3\. Data Content Accessed Through the Services a\. Subscribers to the Services can upload their Subscriber Data, access Data Content developed using their Subscriber Data, and download Data Content developed using their Subscriber Data\. Subscriber shall retain full right, title and interest in and to all of its Subscriber Data and Data Content generated by the Services, and may use, reproduce, modify, distribute, and share such Data Content for its lawful business purposes, including reporting, audits, compliance, and assessing or enforcing agreements or service level obligations with third parties, without APIContext’s prior approval, subject to APIContext’s rights under Section 4\(c\)\. APIContext reserves the right to publish, display, distribute, or otherwise use the results of API Monitor tests run by Subscribers registered for a free trial account\. Identifying information \(e\.g\. user name, company name, and address\) will not be made available at any time to any other Subscriber subscribing to the Service\. b\. Subscriber, not APIContext, shall have sole responsibility for the accuracy, quality, integrity, legality, reliability, appropriateness, and intellectual property ownership or right to use Subscriber Data uploaded to the Services\. APIContext shall not be responsible or liable for the deletion, correction, destruction, damage, or loss of any Subscriber Data\. c\. APIContext’s Privacy Policy further describes APIContext’s collection and use of Subscriber’s information\. d\. APIContext will use reasonable technical, physical and administrative measures to prevent unauthorized access and use of Subscriber’s Subscriber Data\. 4\. Intellectual Property Ownership a\. APIContext \(and its licensors, where applicable\) shall exclusively own all right, title, and interest, including all related Intellectual Property Rights, in and to the APIContext Technology, the Content and the Service, excluding Subscriber Data and Data Content owned by Subscriber under Section 3\(a\)\. Subscriber assigns to APIContext all ownership and intellectual property rights including any copyrights in any suggestions, ideas, enhancement requests, feedback, recommendations, or other information provided by Subscriber or its Users to APIContext related to the Service\. b\. This Agreement is not a sale and does not convey to Subscriber any rights of ownership in or related to the Service, the APIContext Technology, or the Intellectual Property Rights owned by APIContext\. APIContext’s name, APIContext’s logo, and the product names associated with the Service are trademarks of APIContext or third parties, and no right or license is granted to use them\. c\. Aggregate Data\. APIContext owns all rights to aggregated or de\-identified data and metadata generated by or derived from the Service \(“Aggregate Data”\) and may use such Aggregate Data for any purpose, provided that it does not identify Subscriber or disclose Subscriber test results or configurations\. 5\. Subscriber Responsibilities; Prohibited Data a\. Subscriber is responsible for all activity occurring under Subscriber’s License Administrator and User accounts and shall abide by all applicable local, state, national, and foreign, laws, treaties and regulations in connection with Subscriber’s use of the Service, including those related to data privacy, international communications, and the transmission of technical or personal data\. Subscriber shall: \(i\) notify APIContext as soon as possible but no less than three \(3\) days after discovery of any unauthorized use of any password or account or any other known or suspected breach of security; \(ii\) report to APIContext as soon as possible \(but no less than three \(3\) days after discovery\) and use reasonable efforts to stop immediately any copying or distribution of Content that is known or suspected by Subscriber or Subscriber Users; and \(iii\) not impersonate another APIContext user or provide false identity information to gain access to or use the Service\. b\. Subscriber will not upload or submit any personally\-identifiable information or other sensitive information to the Service other the limited technical data required to use the Service\. 6\. Third Party Interactions a\. Subscriber recognizes that certain third party providers of ancillary software, hardware, or services may require Subscriber’s agreement to additional or different licenses or other terms prior to Subscriber’s use of or access to such software, hardware or services\. APIContext and its licensors shall have no liability, obligation, or responsibility for any such agreement between Subscriber and any such third party\. 7\. Charges and Payment of Fees a\. THIS SECTION MAY BE MODIFIED OR SUPERSEDED BY A SEPARATE AGREEMENT BETWEEN APICONTEXT AND SUBSCRIBER\. b\. Subscriber shall pay all fees or charges to Subscriber’s account in accordance with the fees, charges, and billing terms in effect at the time a fee or charge is due and payable\. Payments must be made monthly in advance unless otherwise mutually agreed upon in an Invoice\. All payment obligations are non\-cancelable by Subscriber and all amounts paid are nonrefundable\. Subscriber owes all fees due for the entire Term upon the Effective Date of the Agreement unless otherwise provided in writing by the Parties\. Subscriber is responsible for paying the entire fee for the entire Term, whether or not Subscriber uses the Service\. APIContext reserves the right to modify its fees and charges and to introduce new charges at any time, upon at least ten \(10\) days prior notice to Subscriber, which notice may be provided by email\. All pricing terms are confidential, and Subscriber agrees not to disclose them to any third party\. c\. APIContext charges and collects fees in advance for use of the Service\. APIContext will automatically issue an Invoice to Subscriber at the beginning of each month or as otherwise mutually agreed upon\. The renewal charge will be set at APIContext’s discretion\. Fees for other services will be charged on an as\-quoted basis\. Unless otherwise noted, APIContext’s fees are exclusive of all taxes, levies, or duties imposed by taxing authorities, and Subscriber shall be responsible for payment of all such taxes, levies, or duties, excluding only U\.S\. \(federal or state\) taxes based solely on APIContext’s income\. d\. Subscriber agrees to provide APIContext with complete and accurate billing and contact information\. This information includes Subscriber’s legal company name, street address, email address, and name and telephone number of an authorized billing contact and License Administrator\. Subscriber agrees to update this information within ten \(10\) days of any changes\. If the contact information Subscriber has provided is false or fraudulent, APIContext reserves the right to terminate Subscriber’s access to the Service in addition to taking any other legal remedies\. e\. If Subscriber believes that an Invoice is incorrect, Subscriber must contact APIContext in writing within thirty \(30\) days of the date of the Invoice containing the amount in question to be eligible to receive an adjustment or credit\. All decisions by APIContext regarding disputed fees are final\. f\. APIContext may contract with a third\-party service provider for payment services\. In addition to this Agreement, Subscriber will comply with any additional terms required by the third\-party payment service provider\. 8\. Availability and Service Updates a\. Subject to the terms of this Agreement, APIContext will use commercially reasonable efforts to provide access to the Service twenty\-four \(24\) hours a day, seven \(7\) days a week for use by Subscriber\. b\. APIContext reserves the right to update, modify, or discontinue features of the Service at any time without notice\. If APIContext materially decreases functionality of the Service, then Subscriber may terminate this Agreement upon thirty \(30\) days advance written notice\. 9\. Nonpayment and Suspension a\. In addition to any other rights granted to APIContext herein, APIContext reserves the right to suspend or terminate this Agreement and Subscriber’s access to the Service if Subscriber’s account has an outstanding subscription balance beyond the payment terms shown on the Subscriber’s Invoice\. Delinquent payments and accounts are subject to interest of 1\.0 percent per month on any outstanding balance, or the maximum permitted by law, whichever is less, plus all expenses of collection\. Subscriber will continue to be charged for Service during any period of suspension\. If Subscriber or APIContext initiates termination of this Agreement, Subscriber will be obligated to pay the balance due on Subscriber’s account\. Subscriber agrees that APIContext may bill Subscriber for such unpaid fees\. APIContext reserves the right to impose a reconnection fee in the event Subscriber is suspended and thereafter requests access to the Service\. 10\. Termination upon Expiration/Reduction in Number of Licenses a\. The Initial Term will be one month or as otherwise mutually agreed upon in an Invoice, commencing on the date of the APIContext’s Invoice\. b\. Upon the expiration of the Initial Term, this Agreement will automatically renew for successive one\-month \(unless otherwise indicated in the Invoice\) Renewal Terms at APIContext’s then current fees\. Either Party may terminate this Agreement or reduce the number of Licenses, effective only upon the expiration of the then\-current Term, by notifying the other Party in writing at least ten \(10\) days prior to the expiration of the Term\. In the case of free trials, notifications provided through the Service indicating the remaining number of days in the free trial shall constitute notice of termination\. c\. If this Agreement is terminated \(other than by reason of Subscriber’s breach as described in Section 11\), APIContext will make available to Subscriber a file of the Subscriber Data within 30 days of termination if Subscriber so requests at the time of termination\. Subscriber agrees and acknowledges that APIContext has no obligation to retain the Subscriber Data, and may delete such Subscriber Data, more than 30 days after termination\. 11\. Termination for Cause a\. Any breach of Subscriber’s payment obligations or unauthorized use of the APIContextTechnology or Service will be deemed a material breach of this Agreement\. APIContext, in its sole discretion, may terminate Subscriber’s password, account or use of the Service on written notice if Subscriber breaches or otherwise fails to comply with this Agreement\. In addition, APIContext may terminate a free account at any time in its sole discretion\. b\. Subscriber agrees and acknowledges that APIContext has no obligation to retain the Subscriber Data, and may delete such Subscriber Data, if Subscriber has materially breached this Agreement, including but not limited to failure to pay outstanding fees, and such breach has not been cured within 10 days of notice of such breach\. 12\. Representations and Warranties a\. Each Party represents and warrants that it has the legal power and authority to enter into this Agreement\. APIContext represents and warrants that it will provide the Service in a manner substantially in accordance with the online APIContext help documentation under normal use and circumstances\. Subscriber represents and warrants that Subscriber has not falsely identified Subscriber nor provided any false information to gain access to the Service and that Subscriber’s billing information is correct\. 13\. Mutual Indemnification a\. Subscriber shall indemnify and hold APIContext, its licensors and each such entity’s parent organizations, subsidiaries, affiliates, officers, directors, employees, attorneys, and agents harmless from and against any and all claims, costs, damages, losses, liabilities, and expenses \(including attorneys’ fees and costs\) arising out of or in connection with: \(i\) a claim alleging that use of the Subscriber Data infringes the rights of, or has caused harm to, a third party; \(ii\) a claim, which if true, would constitute a violation by Subscriber of Subscriber’s representations and warranties; and \(iii\) the breach by Subscriber or Subscriber Users of this Agreement\. b\. APIContext shall indemnify and hold Subscriber and Subscriber’s parent organizations, subsidiaries, affiliates, officers, directors, employees, attorneys, and agents harmless from and against any and all claims, costs, damages, losses, liabilities, and expenses \(including attorneys’ fees and costs\) to the extent arising out of or in connection with a claim alleging that the Service directly infringes a copyright, a U\.S\. patent issued as of the Effective Date, or a trademark of a third party; provided that Subscriber \(a\) promptly gives written notice of the claim to APIContext; \(b\) gives APIContext sole control of the defense and settlement of the claim; \(c\) provides to APIContext all available information and assistance; and \(d\) has not compromised or settled such claim\. APIContext shall have no indemnification obligation, and Subscriber shall indemnify APIContext pursuant to this Agreement, for claims arising from any infringement arising from the combination of the Services with any Subscriber or third party products, service, hardware or business process\(s\)\. 14\. Disclaimer of Warranties A\. APICONTEXT AND ITS LICENSORS MAKE NO REPRESENTATION, WARRANTY, OR GUARANTY AS TO THE RELIABILITY, TIMELINESS, QUALITY, SUITABILITY, TRUTH, AVAILABILITY, ACCURACY, OR COMPLETENESS OF THE SERVICE OR ANY CONTENT\. APICONTEXT AND ITS LICENSORS DO NOT REPRESENT OR WARRANT THAT \(A\) THE USE OF THE SERVICE WILL BE SECURE, TIMELY, UNINTERRUPTED, OR ERROR\-FREE OR OPERATE IN COMBINATION WITH ANY OTHER HARDWARE, SOFTWARE, SYSTEM, OR DATA; \(B\) THE SERVICE WILL MEET SUBSCRIBER’S REQUIREMENTS OR EXPECTATIONS; \(C\) ANY DATA STORED OR GENERATED THROUGH THE SERVICE WILL BE ACCURATE OR RELIABLE; \(D\) THE QUALITY OF ANY PRODUCTS, SERVICES, DATA, INFORMATION, OR OTHER MATERIAL OBTAINED BY SUBSCRIBER THROUGH THE SERVICE WILL MEET SUBSCRIBER’S REQUIREMENTS OR EXPECTATIONS; \(E\) ERRORS OR DEFECTS WILL BE CORRECTED; OR \(F\) THE SERVICE OR THE SERVER\(S\) THAT MAKE THE SERVICE AVAILABLE ARE FREE OF VIRUSES OR OTHER HARMFUL COMPONENTS\. THE SERVICE AND ALL CONTENT ARE PROVIDED TO SUBSCRIBER STRICTLY ON AN “AS IS” BASIS\. ALL CONDITIONS, REPRESENTATIONS AND WARRANTIES, WHETHER EXPRESS, IMPLIED, STATUTORY OR OTHERWISE, INCLUDING, WITHOUT LIMITATION, ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NON\-INFRINGEMENT OF THIRD PARTY RIGHTS, ARE HEREBY DISCLAIMED TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW BY APICONTEXT AND ITS LICENSORS\. APICONTEXT IS NOT LIABLE FOR DATA LOSS\. 15\. Internet Delays A\. APICONTEXT’S SERVICES MAY BE SUBJECT TO LIMITATIONS, DELAYS, OUTAGES, AND OTHER PROBLEMS INHERENT IN THE USE OF THE INTERNET AND ELECTRONIC COMMUNICATIONS\. APICONTEXT IS NOT RESPONSIBLE FOR ANY DELAYS, DELIVERY FAILURES, OR OTHER DAMAGE RESULTING FROM SUCH PROBLEMS\. 16\. Limitation of Liability A\. IN NO EVENT SHALL APICONTEXT’S AGGREGATE LIABILITY UNDER THIS AGREEMENT FOR ANY REASON \(INCLUDING INDEMNIFICATION\) EXCEED THE AMOUNTS ACTUALLY PAID BY AND/OR DUE FROM SUBSCRIBER DURING THE INITIAL TERM\. IN NO EVENT SHALL APICONTEXT AND/OR ITS LICENSORS BE LIABLE TO SUBSCRIBER OR ANYONE ELSE FOR ANY INDIRECT, PUNITIVE, SPECIAL, EXEMPLARY, INCIDENTAL, CONSEQUENTIAL, OR OTHER DAMAGES OF ANY TYPE OR KIND \(INCLUDING LOSS OF DATA, REVENUE, PROFITS, USE, OR OTHER ECONOMIC ADVANTAGE\) ARISING OUT OF, OR IN ANY WAY CONNECTED WITH THIS SERVICE OR AGREEMENT, INCLUDING BUT NOT LIMITED TO THE USE OR INABILITY TO USE THE SERVICE, OR FOR ANY CONTENT OBTAINED FROM OR THROUGH THE SERVICE, ANY INTERRUPTION, INACCURACY, ERROR, OR OMISSION, REGARDLESS OF CAUSE IN THE CONTENT, EVEN IF APICONTEXT OR APICONTEXT’S LICENSORS HAVE BEEN PREVIOUSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES\. 17\. Confidentiality a\. During the Term of this Agreement, APIContext may provide non\-public information \(“Confidential Information”\) to Subscriber\. Subscriber will not disclose the Confidential Information publically or use it for purposes unrelated to this Agreement\. Confidential Information includes but is not limited to this Agreement and any associated pricing terms\. Information provided by APIContext is presumed to be Confidential Information unless APIContext states otherwise\. Subscriber shall return any Confidential Information to APIContext within ten \(10\) days after written request by APIContext or upon termination or expiration of this Agreement\. Subscriber will inform APIContext in writing within three \(3\) business days after it has knowledge of a violation of this section and provide sufficient facts to enable APIContext to take necessary precautionary actions\. Subscriber will delete or destroy all Customer Confidential Information within thirty \(30\) days after termination of this Agreement\. 18\. Notices a\. APIContext may give notice related to this Agreement by means of a general notice on the Service or the Subscription Management Page, email to the Subscriber address on record in APIContext’s account information, or by written communication sent by first class mail or pre\-paid post to Subscriber address on record in APIContext’s account information\. Such notice shall be deemed to have been given upon the expiration of 48 hours after mailing or posting \(if sent by first class mail or pre\-paid post\) or 12 hours after sending \(if sent by email\)\. Subscriber will give notices to APIContext \(such notice shall be deemed given when received by APIContext\) by nationally\-recognized overnight delivery service or United States Postal Service Certified Mail, return receipt requested, to APIContext, Inc\., 8 The Green, Ste R, Dover, DE 19901\. 19\. Modification to Terms a\. APIContext reserves the right to modify the terms and conditions of this Agreement or its policies relating to the Service at any time, effective upon posting of an updated version of this Agreement on the Service or on its website\. 20\. Assignment; Change in Control a\. This Agreement may not be assigned by Subscriber without the prior written approval of APIContext\. An unapproved assignment is void\. APIContext may assign this Agreement to a third party on written notice to Subscriber\. Any actual or proposed change in control of Subscriber that results or would result in a direct competitor of APIContext directly or indirectly owning or controlling 50 percent or more of Subscriber shall entitle APIContext to terminate this Agreement for cause immediately upon written notice\. 21\. Publicity a\. APIContext may use Subscriber’s name, logo and other marks to identify Subscriber as a user of the Services on APIContext’s website, marketing materials and other publicity materials\. 22\. Limitation of Remedies and Damages a\. Subscriber’s sole remedy for a breach of this Agreement is the correction or replacement of the Service by APIContext\. The decision to repair or replace the Service shall be solely at the discretion of APIContext\. APIContext reserves the right to substitute a functionally equivalent copy of the Service as a replacement\. If APIContext is unable to provide a suitable replacement or substitute Service or corrections to the Service within thirty \(30\) days of Service’ failure to perform, Subscriber’s sole alternate remedy shall be a refund for the days or months that the Subscriber was charged fees for access to the Service while it was not functioning properly\. Any claim of Subscriber under this section must be made within thirty \(30\) days after the event giving rise to the claim\. 23\. Governing Law, Jurisdiction, and Dispute Resolution a\. This Agreement is governed by the laws of the State of Delaware, without regard to Delaware’s conflict or choice of law provisions\. Disputes shall be resolved by binding arbitration as provided in Section 23\(b\)\. b\. In the event that at any time during the term of this Agreement a disagreement, dispute, controversy or claim should arise out of, or relating to, the interpretation, performance, breach, or invalidity of this Agreement, the Parties will attempt in good faith to resolve their differences\. Any dispute which is not resolvable by the Parties shall be referred to binding arbitration, with arbitration administered by a provider at APIContext's discretion 24\. General a\. No text or information set forth on any other purchase order, preprinted form, or document \(other than an Invoice issued by APIContext\) shall add to or vary the terms and conditions of this Agreement\. If any provision of this Agreement is held by a court of competent jurisdiction to be invalid or unenforceable, then such provision\(s\) shall be construed, as nearly as possible, to reflect the intentions of the invalid or unenforceable provision\(s\), with all other provisions remaining in full force and effect\. No joint venture, partnership, employment, or agency relationship exists between Subscriber and APIContext as a result of this Agreement or use of the Service\. The failure of APIContext to enforce any right or provision in this Agreement shall not constitute a waiver of such right or provision unless acknowledged and agreed to by APIContext in writing\. This Agreement, together with any applicable Invoices, comprises the entire agreement between Subscriber and APIContext and supersedes all prior or contemporaneous negotiations, discussions or agreements, whether written or oral, between the Parties regarding the subject matter contained herein\. APIContext is not liable for its failure to perform due to forces beyond its control\. Sections 1, 3, 4, 6, 7, 9 and 12 to 23 of this Agreement will survive termination, as well as any other provisions that by their nature are reasonably intended to survive\. To the extent there is an express conflict between the Privacy Policy at https://apicontext\.com/privacy , the Website Terms of Service at https://apicontext\.com/tos , and this Agreement, this Agreement will have highest precedence, followed by the Website Terms of Service, then the Privacy Policy\. Last updated: October 19, 2026 ## Key facts - This agreement governs your subscription to APIContext API monitoring services\. ## Primary entities - APIContext - Subscription Agreement ## Audience - customers - legal teams - procurement teams ## Primary links - [Contact APIContext](/contact) --- # Terms of Service Canonical URL: https://apicontext.com/tos Source: static Description: Legal terms governing use of the APIContext website and services\. ## Summary Please read these terms carefully before using the APIContext website and services\. ## Page sections ### Website Terms of Service Category: Last updated: October 2026 These Website Terms of Service \(“TOS”\) govern your access to and use of websites owned or operated by APIContext, Inc\. \(“APIContext”\), including apicontext\.com , API\.expert, and associated APIContext domains and subdomains \(collectively, the “Site”\)\. Where a separate Subscription Agreement governs subscribed Services, that agreement controls those Services in the event of a conflict\. THESE TOS ARE A CONTRACT BETWEEN YOU AND APICONTEXT AND GOVERN YOUR USE OF THE SITE\. BY USING THE SITE YOU ARE INDICATING THAT YOU HAVE READ AND AGREE TO THESE TOS, THE SUBSCRIPTION AGREEMENT \(IF YOU ORDER THE SERVICE OFFERED UNDER THE SUBSCRIPTION AGREEMENT\), THE PRIVACY POLICY, AND ANY OTHER RELATED TERMS AND CONDITIONS LOCATED ON THE SITE, ALL OF WHICH ARE INCORPORATED HEREIN BY THIS REFERENCE\. IF YOU DO NOT AGREE TO THESE TOS, YOU MAY NOT USE THE SITE\. APICONTEXT MAY MODIFY THESE TOS AT ANY TIME WITHOUT PRIOR NOTICE\. MODIFICATIONS ARE EFFECTIVE UPON POSTING ON THE SITE OR UPON NOTIFICATION TO YOU THROUGH OTHER MEANS\. ALL MODIFICATIONS APPLY TO YOU\. DESCRIPTION OF SITE All new enhancements, features and products of or associated with the Site are subject to these TOS unless explicitly stated otherwise\. APIContext may modify, terminate, suspend, or otherwise adjust any and all functions, features, options, utilities, tools or other aspects of the Site at any time without prior notice to you, for any reason\. The Site and the tools and services provided through the Site are provided “AS\-IS\.” APIContext is not responsible for availability, timeliness, deletion, failure to store any user data, communications, settings, or changes to the Site\. You are responsible for obtaining access to the Site, and that access may involve third\-party fees \(such as Internet service provider or airtime charges\)\. In addition, you must provide and are responsible for all equipment necessary to access the Site\. The Site is offered for your non\-commercial use, except for the Limited Commercial Use permitted below and as may be otherwise expressly permitted\. Except where otherwise stated, you may not reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, the Site or any portion thereof \(including, but not limited to any Content \(defined below\)\), or use the Site, or access the Site for commercial purposes\. If you are using the Site as an authorized representative for a third party entity, you may do so provided that the use: \(a\) is on behalf of the entity in your capacity as agent, \(b\) does not exceed, in aggregate, the use allowed to an individual, non\-entity account holder, \(c\) is for a limited time and purpose, \(d\) does not include a charge for access or use by a third party, and \(e\) is subject to all other terms and conditions in these TOS \(“Limited Commercial Use”\)\. APICONTEXT PRIVACY POLICY APIContext will collect and use information about you and your use of the Site\. This collection and use is described in the Privacy Policy\. You consent to the activities described in the Privacy Policy\. YOUR SUBSCRIPTION OBLIGATIONS You represent that you are the older of \(a\) eighteen \(18\) years old or \(b\) of legal age to form a binding contract\. You further represent that you are not barred from using the Site\. You may be required to provide certain information about yourself \(“Subscription Data”\) as part of the subscription and user account \(“Account”\) creation process for the Site, or as part of your continued use of the Site\. You will provide true, accurate, current and complete Subscription Data requested by the Site and maintain and promptly update the Subscription Data to keep it true, accurate, current and complete\. APIContext may suspend or terminate your Account or access to the Site or Site Content, for any reason\. You are responsible for providing APIContext with your most current e\-mail address and contact information \(“Contact Information”\), which APIContext may use to contact you for any purpose associated with the Site or these TOS\. If the Contact Information is not accurate or messages are not delivered to you for any reason, APIContext’s dispatch of the communications using the Contact Information will nonetheless constitute effective notice under these TOS\. ACCOUNT, PASSWORD AND SECURITY APIContext may give you a password and Account after you complete the Site’s subscription process\. You are responsible for maintaining the confidentiality of the password and Account and are fully responsible for all activities associated with your password or Account\. You will immediately notify APIContext of any unauthorized use of your password or Account or any other breach of security and exit from your Account at the end of each session\. APIContext is not liable for any loss or damage arising from your failure to properly safeguard your Account or password\. You have sole responsibility for adequate protection and backup of Content \(defined later\) or data of any type that you upload to, download from or otherwise create or use with, the Site, and/or equipment you use in connection with the Site\. YOUR USE OF THE SITE All information, data, text, software, music, sound, photographs, graphics, video, messages, tags, or other materials \(“Content”\), whether publicly posted or privately transmitted, are the sole responsibility of the person from whom such Content originated\. You are entirely responsible for all Content that you upload, download, post, email, transmit or otherwise make available or use via the Site\. APIContext does not control the Content posted by you or other third parties via the Site and, as such, does not guarantee the accuracy, integrity or quality of such Content\. By using the Site, you may be exposed to Content that is offensive, indecent or objectionable\. APIContext is not liable for any Content, including, but not limited to, any errors or omissions in any Content, or any loss or damage of any kind incurred as a result of the use of any Content posted, emailed, transmitted or otherwise made available via the Site, including Content created or provided by APIContext\. The Site is provided for the purposes stated in these TOS only\. The Content is made available to you without warranty, and APIContext and its licensors are not responsible or liable for the accuracy, completeness, usefulness, or availability of any information transmitted or made available via the Site\. You agree to not use the Site to: • upload, post, email, transmit or otherwise make available any Content that: violates applicable law; infringes any patent, trademark, trade secret, copyright or other proprietary rights \(“Rights”\) of any party or use, or modifies or combines the Content in any manner with any other material that infringes the Rights of any person; violates contractual or fiduciary relationships; or otherwise may harm APIContext; • impersonate any person or entity, or misrepresent your affiliation with a person or entity; • upload, post, email, transmit, or otherwise make available any unsolicited or unauthorized advertising, promotional materials, “junk mail,” “spam,” “chain letters,” “pyramid schemes,” or any other form or solicitation, except in those areas of the Site that are specifically designated for solicitation; • upload, post, email, transmit or otherwise make available any material that contains software viruses or any other computer code, files or programs designed to interrupt, destroy or limit the functionality of any computer software or hardware or telecommunications equipment; • interfere with or disrupt the Site or servers or networks connected to the Site; • provide material support or resources to any organization\(s\) designated by the United States government as a foreign terrorist organization pursuant to section 219 of the Immigration and Nationality Act; • “stalk” or otherwise harass another; • attempt to override or circumvent any digital rights management technology or usage rules embedded into the Site; and/or • collect or store personal data about other Site users in connection with the prohibited activities described in these TOS\. 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Please contact APIContext at support@apicontext\.com if you have any questions or if you believe that any aspect of the Site or the information on it violates your rights\. ## Key facts - Please read these terms carefully before using the APIContext website and services\. ## Primary entities - APIContext - Website Terms of Service ## Audience - customers - legal teams - procurement teams ## Primary links - [Contact APIContext](/contact) --- # Understanding APIs Guide Canonical URL: https://apicontext.com/understanding-api Source: static Description: APIContext's Understanding APIs guide covers the technologies behind modern API monitoring and how it fits your DevOps workflow\. ## Summary APIContext's Understanding APIs guide covers the technologies behind modern API monitoring and how it fits your DevOps workflow\. ## Page sections ### Browse Understanding APIs Category: Foundations A guide to the API ecosystem, critical monitoring technologies, and how APIContext fits into your DevOps world\. - [API Gateway](/understanding-api/api-gateway) - [API Ratings](/understanding-api/api-ratings) - [API Monitoring For Dummies](/understanding-api/api-monitoring-for-dummies) - [Service Level Objectives](/understanding-api/service-level-objectives-and-slas) - [APIContext Global Coverage](/understanding-api/apimetrics-global-coverage) - [Advanced API Monitoring](/understanding-api/advanced-api-monitoring) - [Why API Monitoring – Problems](/understanding-api/why-api-monitoring-problems) - [KPIs for APIs – Key Performance Indicators](/understanding-api/api-kpis) - [CASC – Cloud API Service Consistency Score](/understanding-api/casc-score-cloud-api-service-consistency) - [SLA for APIs: Monitoring Your API SLA \(Service Level Agreement\)](/understanding-api/api-sla-management) ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Ready To Start Monitoring? - API Gateway - API Ratings - API Monitoring For Dummies - Service Level Objectives - APIContext Global Coverage - Advanced API Monitoring - Why API Monitoring – Problems - KPIs for APIs – Key Performance Indicators - An API ecosystem is complex and vast, as are the critical technologies that make APIContext the most advanced API Monitoring solution on the market\. - This guide covers everything from how monitoring fits into your DevOps world, what other technologies you ought to be looking at and what are the critical technologies behind APIContext\. ## Primary entities - APIContext - Understanding APIs - API monitoring ## Primary links - [Human knowledge base view](/understanding-api) - [API Gateway](/understanding-api/api-gateway) - [API Ratings](/understanding-api/api-ratings) - [API Monitoring For Dummies](/understanding-api/api-monitoring-for-dummies) - [Service Level Objectives](/understanding-api/service-level-objectives-and-slas) - [APIContext Global Coverage](/understanding-api/apimetrics-global-coverage) - [Advanced API Monitoring](/understanding-api/advanced-api-monitoring) --- # Advanced API Monitoring Canonical URL: https://apicontext.com/understanding-api/advanced-api-monitoring Source: static Description: Why API monitoring matters beyond cloud\-native and stack monitoring tools, and what dedicated monitoring adds to your DevOps stack\. ## Summary Why API monitoring matters beyond cloud\-native and stack monitoring tools, and what dedicated monitoring adds to your DevOps stack\. ## Page sections ### Let’s break it down… Why API monitoring? It’s a good question\. ### Your API is not a website It looks like a web call, so why not treat it like one? Between the various flavors of OAuth, Mutual TLS on the client side, and simple API keys, getting a meaningful response back can be a challenge\. Essentially it’s doing a different thing, in a different way, with significantly different security\. Then there are the responses – what does come back? Text, JSON, XML? ### Isn’t a ‘ping’ enough? The ping tells you the server responded as expected\. But it doesn’t tell you much else\. Is the content correct? Did you get back what you wanted? If a regulator expects you to return 1800 items, can you instantly spot if you only sent three? If you have a travel site, are you sending all the hotels you should for a given date? Missing functional errors leaves the door open to poor experiences and even regulatory compliance fines\! ### My gateway or stack tool does this Your gateway and/or stack tool verifies what you’re sending – but there are several things it doesn’t tell you\. If you go down during a period of light load, you may miss that you’re down until load returns to normal, causing a simple fix to become a full blown fire drill\. If you stop returning the correct content, or something further down the chain breaks and traffic stops flowing, there might not be anything wrong in any particular section, but the systems may not see the errors\. We see this a lot in legacy based systems like banking\. ### We have networking tools for this Your networking tools are great for optimizing traffic around the internet, but they aren’t designed to spot application layer problems like an API can be\. If everything generally works except for calls made form a specific cloud in a specific geography, you might not notice that you don’t get much traffic from there, and that the reason for this is your sub\-optimal performance\. Likewise, if you fundamentally do not work with a particular service, like Azure for example, you need to tell developers and customers not to build on that stack\. ### Where APIContext comes in By analyzing, in real time, the API metrics like HTTP code, content validation, networking breakdown, from around the world and the cloud – and generating a simple trend based score from that data – APIContext identifies outliers and performance problems before they impact users, or become a regulatory compliance hassle\. Don’t get caught out by your APIs under performing – or worse, APIs you depend on but don’t own or control under performing\. Get on top of API performance monitoring today with a product built from the ground up to solve this very real problem\. Whether it’s what Service Level you actually get and not what the SLA says, or making sure you can prove API compliance to a regulator or watch dog or buyer, get things monitored\! So, to answer the question: Why API monitoring? Because you need it\. ### Further reading about API monitoring… Why API monitoring? It’s a good question\. ### API Monitoring See how APIContext monitors the APIs you rely on and provides peace of mind\. ### Service Levels See how service levels can be monitored with APIContext ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Let’s break it down… - Your API is not a website - Isn’t a ‘ping’ enough? - My gateway or stack tool does this - We have networking tools for this - Where APIContext comes in - Further reading about API monitoring… - API Monitoring - Why API monitoring? - It’s a good question\. - After all, companies and DevOps groups use LOTS of different API monitoring tools\. ## Primary entities - APIContext - Advanced API Monitoring - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/advanced-api-monitoring) --- # API Gateway Canonical URL: https://apicontext.com/understanding-api/api-gateway Source: static Description: Learn what an API gateway does, how it manages access and traffic, and how APIContext complements gateways with active monitoring\. ## Summary Learn what an API gateway does, how it manages access and traffic, and how APIContext complements gateways with active monitoring\. ## Page sections ### What is an API gateway and how is APIContext different? An API gateway allows API providers to manage and control their APIs reliably and at scale\. It manages access, policy and traffic controls, and handles run\-time activities including routing and authentication\. A gateway typically provides functionality across five broad areas: • access control • cloud\-native principles • policy definition • reporting analytics • traffic management Of these areas, reporting analytics supports passive API monitoring\. Reporting analytics provides information about the consumption of APIs, HTTP errors and warnings generated by APIs, and detects API behavior patterns, including error patterns, that can be used to optimize API performance\. Traffic management functionality can also used to measure and control load on a per API and per user basis\. ### Common API Gateways • 3scale APIcast Cloud Hosted Gateway \( https://www\.3scale\.net/api\-management/apicast/ \) • Akamai API Gateway \( https://www\.akamai\.com/site/en/documents/product\-brief/akamai\-api\-gateway\-product\-brief\.pdf \) • Akana API Gateway \( https://www\.roguewave\.com/products\-services/akana/api\-gateway \) • Amazon API Gateway \( https://aws\.amazon\.com/api\-gateway/ \) • Apigee API Gateway \( https://apigee\.com/about/cp/api\-gateway \) • Axway API Gateway \( https://www\.axway\.com/sites/default/files/datasheet\_files/axway\_datasheet\_a… \) • CA API Gateway \( https://www\.ca\.com/content/dam/ca/us/files/data\-sheet/ca\-api\-gateway\.PDF \) • Cisco API Gateway Proxy \( https://www\.cisco\.com/c/en/us/td/docs/voice\_ip\_comm/hcs/10\_6\_1/HCMF\_Product… \) • IBM API Management \( https://www\.ibm\.com/support/knowledgecenter/en/SSWHYP\_4\.0\.0/com\.ibm\.apimgmt… \) • Informatica API Management \( https://www\.informatica\.com/gb/products/cloud\-integration/integration\-cloud… \) • Intel Expressway Service Gateway \( https://www\.intel\.co\.uk/content/dam/www/public/us/en/documents/product\-brie… \) • Kong API Gateway \( https://getkong\.org/ \) • Microsoft Azure API Management \( https://azure\.microsoft\.com/en\-gb/services/api\-management/ \) • MuleSoft Anypoint Platform API Manager \( https://www\.mulesoft\.com/platform/api/manager \) • Nevatech API Gateway \( http://www\.nevatech\.com/how\-it\-works/api\-gateway \) • Software AG API Gateway \( https://www\.softwareag\.com/uk/products/api/api\_gateway/default\.html \) • TIBCO Mashery API Gateway \( https://www\.mashery\.com/api/gateway \) • Treegateway API Gateway \( http://treegateway\.com/ \) • Tyk Open Source API Gateway \( https://tyk\.io/ \) • WSO2 API Management \( https://web\.archive\.org/web/20221105100520/https://wso2\.com/ \) ### Doesn’t an API Gateway provide monitoring? Though a gateway does provide passive monitoring tools, it does not generally provide active monitoring tools\. Active monitoring of APIs is necessary to understand how APIs are performing to expectation from the end user perspective in terms of availability, latency and content of returned payload, and meeting specified Service Level Objectives\. Active monitoring can also provide an API heartbeat that indicates whether an API is operating properly at a particular time\. APIContext is the state of the art intelligent active API monitoring solution\. It is the perfect complement to an API gateway as a part of a comprehensive API management system\. Our system lets you easily create test calls that periodically exercise API endpoints by making synthetic transactions from cloud locations\. It provides a wizard for seamlessly handling a wide variety of authentication scenarios, including OAuth2\. Workflows allow business logic to be tested by making a series of back\-to\-back calls in which parameters extracted from the output of earlier calls are used as part of the input to later ones\. User\-defined conditions associated with the results of APIContext test calls such as the HTTP response code or the size of the returned payload can be used to trigger webhooks and alerts than can be reported to higher level management systems\. APIContext exposes its own API that allows it to integrated directly with other systems\. We use proprietary patent\-pending machine learning technology that blends together different API performance metrics and leverages its unique dataset of historical API test call records\. We call this an Insights CASC score for each API, a credit rating\-like score that lets you see at a glance the quality of an API compared to any other and whether the quality is getting better or worse\. If you are an API gateway user, we at APIContext would be delighted to discuss how APIContext can be integrated with your existing systems to provide the active API monitoring functionality needed to properly manage your APIs\. and see what your existing gateway might be missing\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What is an API gateway and how is APIContext different? - Common API Gateways - Doesn’t an API Gateway provide monitoring? - Ready To Start Monitoring? - An API gateway allows API providers to manage and control their APIs reliably and at scale\. - It manages access, policy and traffic controls, and handles run\-time activities including routing and authentication\. ## Primary entities - APIContext - API Gateway - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/api-gateway) --- # API KPIs Canonical URL: https://apicontext.com/understanding-api/api-kpis Source: static Description: Learn which API KPIs \(key performance indicators\) matter most for understanding how your APIs perform and impact your business\. ## Summary Learn which API KPIs \(key performance indicators\) matter most for understanding how your APIs perform and impact your business\. ## Page sections ### Measured Pass Rate The pass rate is the actual measured success rate for an API call from a specific location\. But APIs can pass at different rates from different locations\. So don’t just assume that HTTP\-200 means ‘All OK’\. Just because your API gateway or APM stack logs show 200 codes doesn’t mean that everything is working well – or even at all\. Imagine you’re in a restaurant where they only measure whether or not you get a drink – but don’t actually care if you get the drink you ordered, or whether or not it has ice in it? That can be the difference between being told an API call passed and having a dispute with a supplier, customer or regulator over what you actually delivered\. ### Effective Pass Rate It’s entirely possible to have two APIs doing the same thing, but with wildly different effective pass rates\. Even with a 100% pass rate, there may be events and performance issues that cause timeouts and other problems\. You need to take into account the performance, including latencies and items that may affect end users\. So thinking back to our restaurant, they might have a time goal where they still don’t care if there’s even a drink in the glass as long as the glass is delivered on time, or, where they check the average time, so while your drink took over an hour, on average,most drinks were served in under 5 minutes\. ### Location Impact on API KPIs Latency is complex for APIs\. Using a common ‘ping’ tool won’t tell you what you need to know\. API calls include multiple steps: • Connect Time • DNS Look Up • Server Side Processing Time • Internet Travel Time • Total Call Time And each of these vary by geography and even cloud service provider\. What works between AWS servers might not work so well if your partner is using Azure or Google\. Understanding these issues can save pain and complaints and brand impact later\. ### Statistics matter A slow API might not be a problem\. But an API that is slow only sometimes might well be\. Systems measuring average performance can miss significant performance issues lasting many hours\. So it’s important not just to think about the averages here, but also the percentiles, that is the calls that fall into a certain group – like the worst 5% or 1% of calls\. That might not sound like a lot but consider an example\. You serve 1,000,000 API calls a day and have an average latency of 500ms, that’s good? Right? But consider this, your 95th percentile, that’s the slowest 5% take over 2 seconds, and your 99th percentile is over 10 seconds\. That’s 10,000 calls a day taking over 10 seconds… is that any good? ### Learn more about API KPIs See how APIContext measures performance and SLAS – or check out some of our other articles\. ### Learn about CASC CASC scoring takes the guesswork out of your API monitoring by identifying the APIs that need attention\. ### SLAs Service Level Agreements – do you meet them? How do you know? ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Measured Pass Rate - Effective Pass Rate - Location Impact on API KPIs - Statistics matter - Learn more about API KPIs - Learn about CASC - SLAs - Ready To Start Monitoring? - Defining API KPIs \(key performance indicators\) being used is a critical part of understanding not just how they work but how well they can work and the impact they have on your services, users or partners\. - But what do you look at and track when measuring API KPIs? - Some API KPIs are ‘ soft ’ – your documentation, the formal definitions of how the API works, use metrics and adoption, and others are ‘hard’ – focusing on the underlying functionality of the service being measured\. ## Primary entities - APIContext - KPIs for APIs – Key Performance Indicators - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/api-kpis) --- # API Monitoring for Dummies Canonical URL: https://apicontext.com/understanding-api/api-monitoring-for-dummies Source: static Description: API Monitoring for Dummies: why enterprises using 1000\+ APIs still struggle to define and implement effective API monitoring\. ## Summary API Monitoring for Dummies: why enterprises using 1000\+ APIs still struggle to define and implement effective API monitoring\. ## Page sections ### API Monitoring – the basics With the average enterprise now using over 1000 APIs , why are we still being asked what is API Monitoring and how to do it? The reason is simple, it’s a complex topic that that falls between different groups inside the enterprise and can lead to a variety of approaches, not all of them as effective as others\. One challenge is there are several audiences who need to worry about API Monitoring and they are all concerned about different API KPIs \(API Key Performance Indicators\)\. As a result, they have different goals from API monitoring\. So, let’s outline some insights into the approaches and some methodologies to make API monitoring easier and more effective\. We’re going to look at this from the perspective of working out what you want to achieve with API monitoring and then look at how to deliver that\. • What are the goals of my API Monitoring? • Who is the audience? • What do I want or need to monitor? What should I monitor? • How do I want to monitor it \(and does it matter\)? This article will answer these, and other, questions and suggest some clear strategies for enterprises looking to add dedicated API monitoring or build on what they have already\. ### API Monitoring: Setting your Goals First, what is your pain point and what type of monitoring is going to help you understand that pain? For many, this is purely knowing your “API availability\.” If you want to know if your APIs are available or know about problems before your customers notice a problem, it’s the perfect place to begin\. One of the potential issues can be relying on internal observations through application monitoring \(APM\) tools like Dynatrace, New Relic, Splunk or others\. APM tools allow you to spot outages but often it takes some time for the outage to become apparent\. An example of this would be if you have time\-based use patterns \(i\.e\. customers in a single time zone or setup of time zones\) where low load during the night masks an emergent problem after an update at midnight\. In practice, we’ve seen as much as 4 hours difference between using log\-based API monitoring and purpose\-built synthetic monitoring\. The second issue with log\-based monitoring is that many APIs can appear to function but not be working as expected\. This is an issue with all APIs, but particularly bad with GraphQL where all APIs returned a HTTP 200 code even if there is an error message in the body\. Your goal should be to monitor the APIs for function not just status codes\. Third, if your goal is to validate a Service Level Objective , you need to monitor that from where your customers are\. In our experience of monitoring billions of API calls, it is extremely difficult to reach agreement over performance or quality metrics when you are looking at different metrics\. When your customer shows you data that they generated locally, you will not get very far responding with your own data that is designed to show your services in the most favorable light\. Finally, it is important to remember to monitor all the aspects of your APIs – because security is complex, it’s common for engineering teams to skip parts of the API monitoring process in order to simplify the work\. This creates gaps, and gaps can lead to unexpected outages\. Moreover, highly secure services that are protected by OAuth and other strong authentication systems can be complex and brittle \(i\.e\. prone to break\) – engineering teams sometimes install workarounds for API security in order to simplify the testing process\. This has led to credentials being exposed in the wild and other potential security problems being introduced to your API surface area\. Overall your goal should be to monitor your APIs like your end customers consume them and generate data that replicates their experience \. ### API Monitoring: Who is the audience? Most teams that monitor APIs do so for an internal audience\. If that is the case for you, consider who your stakeholders are\. APIs now cross all aspects of business operations\. Product and engineering team need completely different data and analysis than the SRE team or the compliance and risk team\. If you are monitoring for Service Level Objectives where there are external customer stakeholders involved \(possibly even ones that pay you for API access\), then their needs and the data they want to see is likely to be very different again\. If you are in a regulated industry, it’s entirely possible that your API Monitoring might potentially have a business risk impact too, which needs to be managed in addition to all of the technical considerations we have discussed\. While it increases the complexity of your API monitoring solution, the right product should be able to meet the needs of all the stakeholders and deliver the data directly to the tools and systems needed for accurate reporting\. Your API monitoring solution needs to ensure that it can output to the systems you use and gather the data that solves all your business needs for all the stakeholders involved\. ### API Monitoring: What to Monitor? Because most API calls look like HTTP web calls, there is a natural tendency to treat them like webpages, and there are classes of API Monitoring tools that have evolved from web monitoring\. This approach has some drawbacks because fundamentally API calls and web calls are different things\. They work differently, they have different security and they’re often used in very different ways\. We’re not just saying that because our API monitoring is purpose\-built from the ground up for even the most complex API use cases\. Let’s start with considering the basic things people tend to think of when talking about API Monitoring: • Availability – is it up or not? • Performance \(latency, usually in milliseconds\) – how fast is a call? But what are you missing here? There’s a lot more to the question of how well does an API work than just 2 metrics\. • Functional – did the call actually deliver the result expected? • Slow calls – how many passing calls fell outside of the expected performance range? • Did the call return the correct context as per your specification? • Are the security settings working to your expectations? • Is it performing uniformly across all possible locations? I\.e\. does one particular cloud or data center under perform – is that one that is critical to your customers? • Is the content you are sending correct for the call? Can you tell? • Are you returning the content you expected? Depending on the audience, you might need to answer lots of questions and in a regulated environment this could involve a government agency with the power to fine you\. It’s also worth mentioning at this point, that you might also want to monitor the services you consume – are you getting what you pay for and could you prove to a third party that they missed their SLA? As more APIs fall under the purview of a regulator, especially in healthcare and banking, teams need to pay careful attention to the quality of the data returned by the API\. Does it match the OpenAPI specification? Many engineering groups use linting tools in their test process but if something changes between releases, would they know? As a further complication, if you are expected to return accurate content AND be able to prove it is accurate, could you do so? Checking the content for meeting the standard AND returning the correct data could be essential in some industries to avoid fines\. ### API Monitoring: How to Monitor? When considering what to monitor, we reviewed two types of monitoring\. The first is simply an availability check – a ‘ping\.’ This will tell you quickly if an endpoint exists and responds in the way you expect\. A ping, if conducted from the right locations, might even answer some of the performance questions\. Uptime monitoring is a simple check on the availability of a specific endpoint\. Typically uptime checks use simplified security \(which might not work with complex OAuth\-based APIs\) and don’t check anything beyond the availability of the service and the overall latency of the call\. For a richer experience we would recommend full synthetic API monitoring where you are generating real calls against production systems to test all the sequences that a user would be interested in\. This should also use the same security and authentication settings as an end user would use – requiring a system to handle not just OAuth type authentication but also the process of token refreshes too\. Calls should be made from the outside in, at a frequency that enables you to catch outages when they start\. An APIContext client found that by using APIContext at a frequency of 1 functional sequence every 10 minutes they were able to reduce the time for alerting to potential outages from 4 hours \(with their gateway and APM logs in a major data analysis tool\) to under 15 minutes\. In addition to monitoring at the correct frequency, we recommend setting logic into your monitoring to handle retry scenarios\. It’s a fact that API calls don’t work, first\-time, 100% of the time, often failing for the first call and then passing for the second\. Within APIContext we offer a range of retry conditions to capture the exact moment when an outage begins\. ### Don’t we have a Monitoring tool for that? A final consideration is the assumption that all monitoring and testing is built equally\. It is not\. Something that works for a website in certain situations might miss critical API scenarios because it’s not designed to handle that type of security system\. Every team faces pressure to save costs, especially in SaaS and Tooling, but we find that good teams use different tools for different jobs, and APIs are complex enough that they do merit their own tooling\. ### Recommendations • A fully functional API monitoring synthetics tool is essential for any enterprise, especially in a regulated industry • Different audiences depend on different data – the needs of the SRE team will be different to the needs of the product or compliance teams – but the data ought to come from the same source • Monitoring should be done outside\-in, in the cloud locations from which your customers and end users call you • Service Level Objectives should be measured independent from your infrastructure to avoid contaminating the data • Data generated by your solution should be available in the tools and services you use APIContext is a world leader in synthetic API monitoring for regulated and secure APIs with a system designed to save time, effort and money for all stakeholders\. ### API Monitoring See how APIContext monitors the APIs you rely on and provides peace of mind\. ### KPIs for APIs There are lots of things you can measure with APIs\. What things are you likely missing? ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - API Monitoring – the basics - API Monitoring: Setting your Goals - API Monitoring: Who is the audience? - API Monitoring: What to Monitor? - API Monitoring: How to Monitor? - Don’t we have a Monitoring tool for that? - Recommendations - API Monitoring - API Monitoring – the basics With the average enterprise now using over 1000 APIs , why are we still being asked what is API Monitoring and how to do it? - The reason is simple, it’s a complex topic that that falls between different groups inside the enterprise and can lead to a variety of approaches, not all of them as effective as others\. - One challenge is there are several audiences who need to worry about API Monitoring and they are all concerned about different API KPIs \(API Key Performance Indicators\)\. ## Primary entities - APIContext - API Monitoring For Dummies - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/api-monitoring-for-dummies) --- # API Ratings Canonical URL: https://apicontext.com/understanding-api/api-ratings Source: static Description: Learn how to rate and monitor the quality of third\-party APIs you consume, not just the ones you build and control yourself\. ## Summary Learn how to rate and monitor the quality of third\-party APIs you consume, not just the ones you build and control yourself\. ## Page sections ### Example REST API Rating Dashboard from APIContext You may think you are monitoring your APIs, but what about the services you buy via API from other people, how do you go about rating APIs? How are you measuring the quality of those APIs and the services you use every day? ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Example REST API Rating Dashboard from APIContext - Ready To Start Monitoring? - You may think you are monitoring your APIs, but what about the services you buy via API from other people, how do you go about rating APIs? - How are you measuring the quality of those APIs and the services you use every day? - Do you rely on the supplier to tell you that everything is good? ## Primary entities - APIContext - API Ratings - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/api-ratings) --- # API SLA Management Guide Canonical URL: https://apicontext.com/understanding-api/api-sla-management Source: static Description: How to measure and manage an API SLA \(Service Level Agreement\), including which factors matter most for true agreement\. ## Summary How to measure and manage an API SLA \(Service Level Agreement\), including which factors matter most for true agreement\. ## Page sections ### How do you agree on an SLA? Both parties in the API contract have to agree on what they’re getting\. You need to know what you’re delivering to a third party\. You need to accurately track what you’re receiving\. One of the key factors is where you measure things from\. This will impact your results\. So to be in true agreement, here’s what you need to confirm: • Where do you measure from? • How do you measure up\-time? • How do you understand consistency? • How do you prove it? Have an agreed set of data points that all parties involved can agree upon – not just data, which shows what one side wants you to believe\. ### Location, location, location Did you know that API calls made in Asia can easily take twice as long as the same call made in the USA? And even inside the USA, there can be a 100% difference in speed from coast to coast\. Location affects performance more than people think\. What a ping tool tells you about connection time might not be the same experience of the end user\. The cloud matters, too\. API calls made from different providers in the same location can vary wildly – as can calls from the same provider, but in different locations\. If you’re underperfoming against an SLA because of location, you need to be able to show that it might be a matter of changing your underlying infrastructure\. ### What are you measuring, anyway? In our performance survey of across >1000 APIs, we found there was a persistent error rate of about 0\.5%\. But all services have downtime – for maintenance, for example\. So the more important metric is how consistent the service is over time\. Averages can be misleading as a metric when it comes to an SLA, especially over significant time periods\. A high average, measured over the course of a month, could easily ignore periods where your APIs are too slow to function properly\. From an API SLA management perspective both parties also need to agree that what they’re measuring is the same thing before they get to arguing about whether or not they or you have missed a critical delivery\. ### What are your actual service levels? Even before you agree on an SLA, you need to know what service levels are actually being achieved\. APImetrics can help determine accurate service levels delivered by critical APIs\. And you can avoid an SLA that cannot be enforced\. We’ve mentioned the 5 9s – 99\.999% – which is a metric from the days of telephony availability and is often set as the gold standard for service quality\. But it does have drawbacks\. If your system relies on other providers, for example, and they aren’t delivering 5 9s then there’s no mechanism for you to deliver it\. Also, cost wise, the cost of getting to that level of service can be incredibly high for small companies, do you need to? ### Pulling it all together The key things to focus on for API SLA management are: • Verify what level of service you deliver • Test your SLAs against your SLOs before hand to make sure you are delivering on it\! • Agree on the terms of measurement: how, what and where and who • Choose metrics that are meaningful – not just ones that make you feel good but actionable metrics that can be achieved ### Total SLA Assurance With APIContext, we can monitor the delivered Service Levels as an independent third party with alerts and automated reports when SLAs are missed\. We show how long issues lasted and the impact they could have had on services – even down to a region or particular cloud provider\. Never get caught out again\. Have total assurance that you’re getting the level of service you’re paying for – or not being blamed for other people’s mistakes\. ### Performance Monitoring Take a look at the features built into APIContext to support SLA monitoring and reporting ### Reporting See examples of API performance data at API\.expert, our free ranking and quality service ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - How do you agree on an SLA? - Location, location, location - What are you measuring, anyway? - What are your actual service levels? - Pulling it all together - Total SLA Assurance - Performance Monitoring - Reporting - With many different factors going into an SLA, which ones do you choose to highlight? - What does true agreement look like? - What are the ins and outs of API SLA management and how do you hit the elusive 5 9s \(99\.999% uptime\) and what does that really mean? ## Primary entities - APIContext - SLA for APIs: Monitoring Your API SLA \(Service Level Agreement\) - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/api-sla-management) --- # APIContext Global Coverage Canonical URL: https://apicontext.com/understanding-api/apimetrics-global-coverage Source: static Description: APIContext's Global Monitoring Network is built for cross\-cloud, containerized environments, with the option to deploy your own locations\. ## Summary APIContext's Global Monitoring Network is built for cross\-cloud, containerized environments, with the option to deploy your own locations\. ## Page sections ### Global Monitoring for a containerized world For a cross\-cloud, containerized world, APIContext offers the only Global Monitoring Network built for the needs of modern cloud solutions\. Not only that but if the locations we provide aren’t good enough, then we provide our users the option to deploy their own\. ### Truly Cross Cloud Your customers, partners and users aren’t all on the same cloud\. Why would you monitor from only one? With the world of serverless solutions, Kubernetes and more become how APIs are delivered, if you’re only monitoring a single cloud then you’re missing out on critical data\. ### Regional Locations and IP Addresses Please refer to the up\-to\-date list available in our help pages \. \* Note: IP addresses may change\. Postman agents do not use these IP addresses\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Global Monitoring for a containerized world - Truly Cross Cloud - Regional Locations and IP Addresses - Ready To Start Monitoring? - Global Monitoring for a containerized world For a cross\-cloud, containerized world, APIContext offers the only Global Monitoring Network built for the needs of modern cloud solutions\. - Not only that but if the locations we provide aren’t good enough, then we provide our users the option to deploy their own\. - Truly Cross Cloud Your customers, partners and users aren’t all on the same cloud\. ## Primary entities - APIContext - APIContext Global Coverage - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/apimetrics-global-coverage) --- # CASC Score Cloud API Service Consistency Canonical URL: https://apicontext.com/understanding-api/casc-score-cloud-api-service-consistency Source: static Description: What is CASC scoring? Learn how APIContext's CASC score turns API performance KPIs into a single, meaningful metric\. ## Summary What is CASC scoring? Learn how APIContext's CASC score turns API performance KPIs into a single, meaningful metric\. ## Page sections ### What it means for you Simply put, you don’t want to know just that your API is performing\. You also want to know HOW it is performing\. Our CASC Score is a number between 0 and 10 that tells you how well an API performed over a period of a week or a month\. You can see at a glance how an API is behaving and how this compares to any other measured API, whether one of your own or that of your suppliers, your partners, and customers\. The higher the CASC Score, the better\. If your CASC Score is higher this week compared to last week, you know your API is getting better\. If it’s lower, you know your API is getting worse\. Most APIs are good APIs\. A CASC Score of over 8 indicates few if any issues\. Between 6 and 8, there are some issues that need to be looked at\. And below 6? That means you are using or exposing a bad API that has very serious problems that need to be resolved as soon as possible\. And the CASC Score is an easy and transparent way of measuring confidence in how well an API is doing\. ### How do we do it? Think of the CASC Score as a bit like a credit rating or a net promoter score but for the quality of your API or microservices\. We take all of the metrics we have for each API, blend them together, then compare the result against our unrivaled data set of historical API test records\. This gives us a single number that is automatically bench\-marked against all the other APIs monitored by APIContext\. As for how we do the blending and the bench\-marking, well, that’s our little secret\! You don’t expect Coke or KFC to give away their recipe, do you? But let it be understood that it does involve state of the art machine learning technology\. ### What does the CASC score mean? CASC scoring deals with one of the challenges of understanding what your Key Performance Indicators KPIs for APIs are telling you – how you come to terms, easily and quickly with large amounts of data in a meaningful way\. This has been recognized before with systems like Apdex, but these have been, generally, very simplistic approaches to dealing with the challenges of performance and quantifying it\. ### 8\.00 up – Good\! A healthy API Everything is looking in good shape, you should have minimal problems you need to look into\. Keep it up and watch for changes\. ### 6\.00 – 7\.99 – Issues – needs attention There are issues that should be looked into – it might be latency or inconsistent service but there will be things impacting user expectations\. ### 5\.99 and lower – Poor performing API The API will have significant performance issues every week representing lost time and wasted engineering effort in response\. ### Can I improve my score? If you’re an APIContext customer, along with all the other analysis of the performance of your critical APIs that we do, we also provide you with details on why a score is what it is and what areas of the performance you need to focus on in order to improve things\. ### API Monitoring See how APIContext monitors the APIs you rely on and provides peace of mind\. ### Performance Monitoring Detailed performance metrics by latency, location, cloud\. ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - What it means for you - How do we do it? - What does the CASC score mean? - 8\.00 up – Good\! A healthy API - 6\.00 – 7\.99 – Issues – needs attention - 5\.99 and lower – Poor performing API - Can I improve my score? - API Monitoring - CASC scoring deals with one of the challenges of understanding what your Key Performance Indicators KPIs for APIs are telling you – how you come to terms, easily and quickly with large amounts of data in a meaningful way\. - This has been recognized before with systems like Apdex, but these have been, generally, very simplistic approaches to dealing with the challenges of performance and quantifying it\. - Building on the success of the ‘credit score’ in the financial sector, APIContext has developed Cloud API Service Consistency \(CASC\) scoring to give a simple indication of the quality and health of a specific API or group of APIs and allow for easy, like\-for\-like comparisons between different systems\. ## Primary entities - APIContext - CASC – Cloud API Service Consistency Score - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/casc-score-cloud-api-service-consistency) --- # Service Level Objectives Canonical URL: https://apicontext.com/understanding-api/service-level-objectives-and-slas Source: static Description: Learn how to define and measure a Service Level Objective \(SLO\) and how it relates to a Service Level Agreement \(SLA\) for APIs\. ## Summary Learn how to define and measure a Service Level Objective \(SLO\) and how it relates to a Service Level Agreement \(SLA\) for APIs\. ## Page sections ### Reliability Engineering APIContext is a tool for monitoring the performance and quality of APIs\. There are lots of good reasons why you should do that, but one particularly important one is to see if an API meets its Service Level Agreement \(SLA\)\. But as a team of Google engineers point out in their O’Reilly book Reliability Engineering: How Google Runs Production Systems , an SLA is actually a legal document \(or, in the case of an internal API, a formal agreement between business units\)\. So, the whole SLA places a legal wrapper around one of more Service Level Objectives \(SLOs\)\. For an API, examples of SLOs might be: • 99\.9% availability • a median latency less than 300 ms from all cloud locations • always returning a payload with a size greater than 25 kB Or you could use the APIContext CASC score , as this provides a blended quality measure that takes into account a number of different metrics\. Thus, another example of an SLO might be a weekly CASC score greater than 7\.5\. Although, we might recommend you use CASC for spotting potential SLO problems and not as a metric to directly track\! API monitoring systems are not yet in the business of determining whether or not a contract has been fully honored in the legal sense\. But they are very good at measuring the metrics associated with SLOs\. Now, measuring API metrics is a non\-trivial thing to do\. In a situation in which there is a formal SLA in place, you don’t want to be doing it yourself with a cURL script and cronjob, not least of which is because it’s bad practice to self certify that you’re doing as you say you are\. ### Independent Measurement: don’t mark your own work\! Using a third\-party product doesn’t only mean that there is an independent arbiter providing the information to decide whether or not an SLO has been met\. It also means that you don’t run the risk of having somebody internally making the numbers look better than they actually are, and thereby creating problems for the Customer Success teams\. Something else that can be done with APIContext is to determine SLOs\. If you are API provider, you want to know how your API performs in order to determine what kind of SLO might be reasonable to agree to\. And just as a provider doesn’t want to agree to an SLO that is too onerous, an API consumer can use APIContext to make sure that an SLO isn’t too lax\. APIs are increasingly the glue of digital age\. More and more companies on depending on APIs they expose and consume to enable time\-sensitive mission\-critical business activities\. With organizations relying on APIs, SLAs become a necessity\. APIContext allows companies to understand what reasonable SLOs might go in the SLA, and to avoid finger\-pointing when it comes whether or not the SLOs have been met\. ### Measuring the Service Level Objectives When you set up monitoring on your APIs, and before you set objectives, it is essential to see how they function normally\. We would recommend that you follow the following key guides on this: • Measure from where your customers are based – so you can see things that might impact your ability to deliver that can be fixed or accounted for in your objectives • Don’t set unrealistic goals – 99\.999% uptime is a goal but if the API can only realistically deliver 99\.9% over a given month, there’s not much point in identifying a metric you can’t hit\. • Set percentile based metrics for goals on latency not averages – not to be MEAN about this, but you can hide a lot of bad stuff under the carpet of an Average\. Set the average high enough and the API can essential be failing for hours a day and still not meet any alerting thresholds Focus on the KPIs that are meaningful for you and fix the ones that are under performing\. Read more about KPIs for APIs in the next article… ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - Reliability Engineering - Independent Measurement: don’t mark your own work\! - Measuring the Service Level Objectives - Ready To Start Monitoring? - Reliability Engineering APIContext is a tool for monitoring the performance and quality of APIs\. - There are lots of good reasons why you should do that, but one particularly important one is to see if an API meets its Service Level Agreement \(SLA\)\. - But as a team of Google engineers point out in their O’Reilly book Reliability Engineering: How Google Runs Production Systems , an SLA is actually a legal document \(or, in the case of an internal API, a formal agreement between business units\)\. ## Primary entities - APIContext - Service Level Objectives - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/service-level-objectives-and-slas) --- # Why API Monitoring Matters Canonical URL: https://apicontext.com/understanding-api/why-api-monitoring-problems Source: static Description: Why you need to monitor APIs separately from IT and cloud server monitoring, even if you already have stack monitoring in place\. ## Summary Why you need to monitor APIs separately from IT and cloud server monitoring, even if you already have stack monitoring in place\. ## Page sections ### The Problems at the Coalface We regularly get the question: why should I monitor my APIs separately? After all, we’ve had REST APIs for a long time now, relatively speaking and we have a variety of solutions in place for IT monitoring – whether it’s a cloud server monitoring, a stack monitoring solution like New Relic or App Dynamics , or the logs from your gateway\. So why do you need something else to do it? It’s a good question\. But the answer is simple, because the other tools aren’t doing it\. This still comes as a shock to us when we look at some of the APIs provided by large, public, organizations – and we see that they’re doing things that should be picked up by other tools, or just have implemented solutions that would have been problematic at the birth of the API economy, five or more years ago are still going on\. To illustrate this, we looked at some APIs provided by the government agencies of a G20 country that is recognized as one of the world leaders in digital government and a set of APIs provided by 9 different blue chip, Fortune 500 organizations which all do essentially the same thing – return data on branch locations\. We didn’t do a deep survey\. This was a high\-level look to generate some data for interested parties\. Here are some of the things we found\. They emphasize why organizations need to get on top of APIs – and not just unit test them\. They also need to make sure that the APIs you make public work as you have documented them and continue to work\. So why API monitoring? Because without it your going to be upsetting a lot of your customers or potential customers\. Let’s dive into what those things are\. ### The Simple Stuff The Problems at the Coalface We regularly get the question: why should I monitor my APIs separately? After all, we’ve had REST APIs for a long time now, relatively speaking and we have a variety of solutions in place for IT monitoring – whether it’s a cloud server monitoring, a stack monitoring solution like New Relic or App Dynamics , or the logs from your gateway\. ### Security If your API has security, then we see no reason why you would have the API key as a URL parameter, and not in the header being handled as a HTTP call\. At the very least, HTTPS should be a must\. There’s certainly not a lot of point in implementing key\-based security, only to make your users pass the keys around the internet without encryption\. ### Is that ACTUALLY a parameter – or not? In the documentation, there is a parameter called “datatype\.” You set it to define whether you want JSON or XML\. We were interested to find that in some cases, an API call worked with the parameter set to /datatype/ \(it returned XML\) – but in other cases, it returned a 4XX error\. Conducting this type of “fuzzing” on your APIs – as deployed – spots a bunch of these edge cases\. ### What does that mean? Helpful or unhelpful errors In another API, we found that if you made a call in the way the documentation said you could, it would throw an error – in this case, a 4XX\. It turned out that there was a missing a mandatory parameter that wasn’t documented\. The really helpful part was the error itself, which was contained exactly 2 bytes of error message \[ \] ,\- yes, brackets, that’s all\. It took some trial and error to get an actual working call\. ### Document what you provide – not what you wrote down In many instances, the API calls as written down in the web documentation simply didn’t work, returning a range of 5XX and 4XX when input EXACTLY as defined in the documentation\. There were no useful errors, and no clue as to why they weren’t working\. In one case, the call returned a 500 error with a confirmation of a GZIP taking place\. But the GZIP package that was returned was unreadable\. This made us think the API didn’t work, but giving us, as a user, no firm idea about what to do next\. ### Not So Simple Here we have the performance of 14 different APIs from 14 different providers\. To make this valid we did some work first: • All 14 are of similar sizes, all Fortune 500 companies • The sample covers the same period of time: 1 month • The locations the APIs are called from the same set of locations and clouds \(AWS, Amazon, Google and IBM\) • The content retrieved is similar in nature • There is no security for the API call, so no effects in the gateway to slow things down ### What do assumptions do? There’s a famous saying about assumptions and in the case of APIs it’s true\. Here’s what we assumed we would observe\. • The APIs would be largely similar in performance • There would be a correlation between the size of the returned content and the speed • The impact of networking effects from the major clouds would be negligible As we can see from the graph, none of those held up under analysis\. There’s a wide difference between the fastest and the slowest, even if we take into account content size with more than a 200ms difference between APIs returning similar quantities of data\. Even though the data is meant to be largely the same, and on inspection has all the same fields, some providers don’t populate all the fields, even though, in this case, we assume that some of them do have the data on accessibility, for example\. Finally, there remain significant differences in networking impacts on APIs\. The fastest performing service took 10% of the time to handle DNS lookup than the slowest\. Looking deeper into the DNS look up data, it was clear that the worst performing APIs had significant DNS registry problems with 3 of the 4 major clouds that were adding significant delays to all transactions\. ### What this means for monitoring? • You can’t rely on any single product or source\. You might have blistering fast search look up times on your server, but if your DNS settings or registrations aren’t working with more than half the cloud services on the planet, your customers will have a poor performance\. • A bad update to an API can take down all the users without anybody be any the wiser\. • Looking only at your services, which may be up, won’t spot if a specific backend service has stopped communicating correctly or if your load balancer is down • Mis\-set thresholds for alerting could leave you down for large chunks of the day and be hard to spot except for long, slow, crawls through thousands of Splunk records We’re not saying you have to use our product \( but, honestly, you REALLY should \), but if you do provide, or consume APIs, you do have to have something that tells you how they’re really working, and not just how you think they do\. ### API Monitoring See how APIContext monitors the APIs you rely on and provides peace of mind\. ### KPIs for APIs There are lots of things you can measure with APIs\. What things are you likely missing? ### Ready To Start Monitoring? Want to learn more? Sign up now and start using the product immediately\. ## Key facts - The Problems at the Coalface - The Simple Stuff - Security - Is that ACTUALLY a parameter – or not? - What does that mean? Helpful or unhelpful errors - Document what you provide – not what you wrote down - Not So Simple - What do assumptions do? - The Problems at the Coalface We regularly get the question: why should I monitor my APIs separately? - After all, we’ve had REST APIs for a long time now, relatively speaking and we have a variety of solutions in place for IT monitoring – whether it’s a cloud server monitoring, a stack monitoring solution like New Relic or App Dynamics , or the logs from your gateway\. - So why do you need something else to do it? ## Primary entities - APIContext - Why API Monitoring – Problems - API knowledge base - API monitoring ## Primary links - [Human knowledge base view](/understanding-api/why-api-monitoring-problems) --- # CASC Score Guide Canonical URL: https://apicontext.com/what-is-casc Source: static Description: Cloud API Service Consistency \(CASC\) scoring turns many performance signals into a single number out of 10, making API quality easier to compare, explain, and improve\. ## Summary Understand API quality with one clear score\. Cloud API Service Consistency \(CASC\) scoring turns many performance signals into a single number out of 10, making API quality easier to compare, explain, and improve\. ## Stats - 10 maximum CASC score - 9\+ minor incident range - <6 unacceptable performance - Outliers analysis beyond p99 ## Page sections ### Like an API speed test and credit rating combined\. Category: A comprehensive score CASC blends API performance data, pass/fail behavior, location outliers, and historical comparisons into a single benchmarked score that updates continuously\. ### Replace metric overload with a clear quality signal\. Category: API quality scoring Too many metrics can make API quality hard to explain\. CASC provides a simple, benchmarked number that shows how well an API is functioning\. - Single score out of 10 - Performance trends over time - Simple stakeholder communication without ambiguity ### Compare services and providers objectively\. Category: Meaningful comparisons CASC compares API quality against historical APIContext monitoring data, making it easier to understand service quality across providers, ecosystems, and APIs\. - Benchmark against APIContext historical data - Compare providers and services instantly - Spot trends that are hard to see in raw metrics ### Look beyond percentile summaries\. Category: Performance outlier detection Outlier detection algorithms analyze performance by cloud location and pass/fail behavior so teams can see quality issues that percentile summaries can hide\. - Outlier detection by cloud location - Pass/fail behavior included in scoring - Identify costly performance degradation early ### Everything you need in production\. Category: Key Features - Real API calls: Score APIs from real GET, PUT, POST, DELETE, and other HTTP requests\. - Validate responses: Set conditions, override expected return codes, and manage variables for tests\. - Functional security: Use API keys, OAuth, JWT, JWS, scopes, and token validity in quality checks\. - Trend analysis: Communicate quality changes quickly with one consistent score\. - Comparisons: Compare service quality across providers in an objective way\. - Quality insight: Understand the quality of services and ecosystems you depend on\. ### CASC quality scores give product, operations, and leadership teams a shared API quality language - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - CASC score - Quality trends - Provider comparisons - Outlier detection - API quality reports - 10 maximum CASC score - 9\+ minor incident range - <6 unacceptable performance - Outliers analysis beyond p99 - Real API calls: Score APIs from real GET, PUT, POST, DELETE, and other HTTP requests\. - Validate responses: Set conditions, override expected return codes, and manage variables for tests\. - Functional security: Use API keys, OAuth, JWT, JWS, scopes, and token validity in quality checks\. - Trend analysis: Communicate quality changes quickly with one consistent score\. - Comparisons: Compare service quality across providers in an objective way\. - Quality insight: Understand the quality of services and ecosystems you depend on\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - CASC score - Quality trends - Provider comparisons - Outlier detection - API quality reports ## Audience - API teams - SRE teams - platform teams ## Primary links - [Score your API quality clearly\.](/contact) ## FAQs ### What is the CASC score? The CASC \(Cloud API Service Consistency\) score is a composite API quality metric combining latency percentiles, availability, geographic consistency, and conformance pass rate into a single number on a 0–10 scale\. A score above 9 represents healthy performance; below 6 indicates a quality problem requiring immediate attention\. It is designed to make API quality understandable and comparable without requiring stakeholders to interpret raw latency histograms\. ### What inputs go into the CASC score? The CASC score incorporates p50–p99 latency measurements, availability \(proportion of successful checks\), location variance \(whether performance is consistent across nodes or degraded in specific regions\), and conformance pass rate\. It captures both whether an API is up and whether it is behaving correctly everywhere\. ### Can the CASC score be used to evaluate third\-party or partner APIs? Yes\. Because the CASC score normalizes multiple quality dimensions into a single comparable number, it applies to any monitored API — internal, third\-party, or partner\-operated\. Teams use CASC scores to evaluate competing API providers, hold third\-party dependencies to quality thresholds, or include API quality benchmarks in vendor procurement and SLA negotiations\. ### How does the CASC score help non\-technical stakeholders? The CASC score translates complex API telemetry into a single number comparable to a credit rating or speed test result\. Product managers and executives can track whether API quality is improving or degrading over time without interpreting latency percentile distributions, and can compare quality consistently across multiple endpoints or providers\. --- # Workflows and Traces Canonical URL: https://apicontext.com/workflows-and-traces Source: static Description: Traverse AI infrastructure, browsers, and APIs with reusable workflows, then record the full details of every step for review, investigation, and OpenTelemetry export\. ## Summary Build reusable workflows for high\-value journeys\. Traverse AI infrastructure, browsers, and APIs with reusable workflows, then record the full details of every step for review, investigation, and OpenTelemetry export\. ## Stats - 3 surfaces: AI, browser, API - 100% step\-level trace detail - OTEL review or export - 24/7 synthetic journey monitoring ## Page sections ### From authentication to downstream API dependencies\. Captured as a trace\. Category: Every event in the journey APIContext records the full journey, including each call, transition, dependency, and result, so teams can investigate failures without storing every packet of production traffic\. ### Build complex journeys across the systems users rely on\. Category: Advanced workflows Complex authentication and authorization flows? AI requests that call APIs? Browser interactions with API dependencies? Any journey that matters to you is one APIContext can verify\. - Reusable workflow steps across APIs, browsers, and AI infrastructure - Complex auth, authorization, and dependency handling - High\-value journey validation from the outside in ### See the entire path each workflow took\. Category: Full call details Every call APIContext makes is fully documented, including the route, timings, result details, and step outcomes, so teams have the information they need to investigate\. - Trace every step and segment of a workflow - Capture result details for each call - Filter the journey to find the broken dependency quickly ### Keep focused traces without drowning in traffic data\. Category: Only store what you need Storing all API traffic can be prohibitively expensive\. APIContext stores the traces for the synthetic calls it makes, reducing trace volume while preserving the journeys that matter\. - Store traces for monitored synthetic journeys - Reduce noisy production trace volume - Review or export focused evidence through OpenTelemetry ### Everything you need in production\. Category: Key Features - Reusable workflows: Build once, then reuse journey steps for critical production checks\. - AI infrastructure: Validate workflows that move between AI requests, tools, and APIs\. - Browser dependencies: Connect browser interactions with the API calls they depend on\. - Full trace detail: Capture every step, path, timing, and result for investigation\. - OTEL export: Review traces in APIContext or export them to your existing observability stack\. - Focused storage: Keep high\-value synthetic traces without storing every production call\. ### Workflow traces export cleanly into OpenTelemetry, APM, incident, and engineering review tools - Datadog - Dynatrace - Splunk - Grafana - New Relic - Honeycomb - Akamai - PagerDuty - Slack - OpsGenie ## Key facts - Reusable journeys - Full call traces - AI \+ browser \+ API steps - OTEL export - Focused trace storage - 3 surfaces: AI, browser, API - 100% step\-level trace detail - OTEL review or export - 24/7 synthetic journey monitoring - Reusable workflows: Build once, then reuse journey steps for critical production checks\. - AI infrastructure: Validate workflows that move between AI requests, tools, and APIs\. - Browser dependencies: Connect browser interactions with the API calls they depend on\. - Full trace detail: Capture every step, path, timing, and result for investigation\. - OTEL export: Review traces in APIContext or export them to your existing observability stack\. - Focused storage: Keep high\-value synthetic traces without storing every production call\. ## Primary entities - APIContext - Features - API monitoring - OpenTelemetry - Reusable journeys - Full call traces - AI \+ browser \+ API steps - OTEL export - Focused trace storage ## Audience - API teams - SRE teams - platform teams ## Primary links - [Start tracing the journeys that matter most\.](/contact)