CASC Score Guide
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.
Like an API speed test and credit rating combined.
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.
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.
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 p50, p90, and p99.
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.
- 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
Questions agents may ask
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 PoPs 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.
Agent-readable source
Browsers get this formatted Agent View. Agents can request the raw source with Accept: text/markdown.
[Human view](https://apicontext.com/what-is-casc) · [Markdown view](https://apicontext.com/what-is-casc.md) · [APIContext home](https://apicontext.com) # 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 - p50\-p99 outlier\-aware analysis ## 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 p50, p90, and p99\. 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 - p50\-p99 outlier\-aware analysis - 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 \(whether performance is consistent across PoPs or degraded in specific regions\), 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\.