# Performance

**Canonical:** https://apis.io/providers/performance/  
**Website:** https://apievangelist.com  
**APIs profiled:** 0

An index and topic collection covering API and web performance, including load testing, performance benchmarking, real user monitoring (RUM), Core Web Vitals measurement, latency profiling, distributed tracing, and application performance monitoring (APM). Performance engineering ensures that APIs and web applications meet latency, throughput, and reliability expectations under realistic and adversarial load. This collection brings together open-source load generators like k6, Apache JMeter, Locust, Gatling, and Artillery; managed load and chaos platforms like StormForge and Speedscale; synthetic and real-user measurement tools like Google PageSpeed, Pingdom, and Akamai; and APM and tracing platforms like Datadog, New Relic, Dynatrace, AppDynamics, Sentry, Honeycomb, Instana, Lightstep, SigNoz, Uptrace, OpenTelemetry, Jaeger, Grafana Tempo, Google Cloud Profiler, Google Cloud Trace, and AWS X-Ray.

## Kin Score — 9.6 / 100 (minimal)

Scored 2026-10-23 under rubric 0.25.0. Trend: flat (+0.0 from 9.6).

| Facet | Score |
|---|---|
| Discoverability | 48.2 |
| Contract Quality | 14.7 |
| Contract Governance | 0.0 |
| Operational Transparency | 5.3 |
| Developer Ergonomics | 9.5 |
| Access Clarity | 0.0 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 4.9 (matched via fallback).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |

## Use cases (7)

- **Pre-Release Load Testing in CI/CD** — Engineering teams run k6 or JMeter scenarios on every pull request to verify that p95 latency and error rates stay within service-level objectives before merging.
- **Core Web Vitals Optimization** — Web teams use Google PageSpeed, WebPageTest, and RUM data to optimize LCP, INP, and CLS to meet Google ranking and user-experience thresholds.
- **Capacity Planning and Scalability Validation** — Platform teams use StormForge and BlazeMeter to drive sustained load tests against staging environments to determine maximum sustainable throughput and right-size infrastructure.
- **Latency Regression Detection** — APM platforms like Datadog, New Relic, and Dynatrace alert on p95 and p99 latency regressions per endpoint or trace span after each deploy.
- **Production Traffic Replay** — Teams use GoReplay or Speedscale to record real production traffic and replay it against release candidates to find performance and correctness regressions before rollout.
- **Distributed Trace Root-Cause Analysis** — SREs use Honeycomb, Lightstep, Jaeger, or Grafana Tempo to drill into slow distributed traces and pinpoint the service, query, or downstream call responsible for tail latency.
- **Continuous Profiling of Hot Paths** — Backend teams use Google Cloud Profiler or Datadog Continuous Profiler to identify CPU and memory hotspots in running services without rebuilding or redeploying.

## Tags

Performance, Load Testing, Performance Testing, Real User Monitoring, Core Web Vitals, APM, Distributed Tracing, Latency

---

Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/performance/). Scores are computed from the provider's own public artifacts under a published rubric.