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.
Which platform produces which signal
| Signal | APIContext provides | Hydrolix provides |
|---|---|---|
| Role in the pipeline | Source — generates outside-in API and network telemetry | Store and query engine — keeps that telemetry cheap, dense, and queryable |
| Vantage point | Outside your infrastructure — what customers and partners actually experience | Vantage-agnostic — stores whatever is streamed in |
| Network path telemetry | Yes — DNS, connection, TLS, transfer, and response broken out per hop; 30+ data points per call | Stores and indexes it once APIContext supplies it |
| API conformance testing | Yes — live OpenAPI, FAPI 2.0, and custom schema validation on every check | Not generated — APIContext supplies it |
| CASC quality score | Yes — composite score across latency, availability, geography, and conformance | Not generated — APIContext supplies it |
| Full request and response payloads | Yes — captured on every check | Stores them at high compression without re-hydration |
| High-cardinality query at scale | Operational dashboards and reports | Yes — core strength, across petabytes |
| Multi-year retention economics | Operational retention windows | Yes — core strength |
| Third-party and partner APIs | Yes — monitors endpoints you depend on but do not own or instrument | Stores the resulting history for as long as you need it |
| Continuous coverage regardless of traffic | Yes — synthetic checks produce a complete series with no gaps | Benefits from it — a dense, uniform dataset compresses and queries well |
| Works together | Streams telemetry, events, and payloads to 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 PoP — 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.
Frequently asked questions
- 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.