Performance
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.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles Performance the way a machine reads it — 30 machine-readable artifacts, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Performance scores 9.5/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-10-03 · rubric v0.23.0
Put this on your own site. The badge is drawn live from Performance's current Kin Score — paste it once and it updates itself every time the score is recomputed. It follows your visitor's light or dark setting, and it links back here so anyone who sees it can read the full breakdown.
<!-- Kin Score · API Evangelist -->
<a href="https://providers.apievangelist.com/providers/performance/"
title="Performance on API Evangelist — API profile and Kin Score">
<img src="https://apis.io/badge/performance.svg"
alt="Performance Kin Score — API readiness rating by API Evangelist" width="150" height="150" loading="lazy">
</a>[](https://providers.apievangelist.com/providers/performance/)<!-- Kin Score · API Evangelist -->
<a href="https://providers.apievangelist.com/providers/performance/"
title="Performance on API Evangelist — API profile and Kin Score">
<img src="https://apis.io/badge/performance/card.svg"
alt="Performance Kin Score — API readiness rating by API Evangelist" width="340" height="120" loading="lazy">
</a>More shapes, themes and sizes → · Score as JSON · How badges work
How we profile Performance
Each block below is one kind of artifact we hold for Performance. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
Features 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Load and Stress Testing
Open-source and managed load generators like k6, Apache JMeter, Locust, Gatling, and Artillery simulate concurrent users and traffic patterns against APIs to characterize throug...
Performance Benchmarking
Repeatable, scripted benchmark runs establish performance baselines and detect regressions in CI/CD pipelines using tools like k6 Cloud, BlazeMeter, and StormForge.
Real User Monitoring (RUM)
RUM products like Akamai mPulse, Datadog RUM, New Relic Browser, Sentry Performance, and Pingdom capture latency, errors, and Core Web Vitals from real browser sessions in produ...
Synthetic Monitoring and Web Vitals
Synthetic checks and lab-based audits from Google PageSpeed (Lighthouse), WebPageTest, and Pingdom measure Core Web Vitals (LCP, INP, CLS) and uptime from controlled environments.
Distributed Tracing
OpenTelemetry, Jaeger, Grafana Tempo, Honeycomb, Lightstep, Google Cloud Trace, and AWS X-Ray collect distributed traces across microservice calls to attribute latency to specif...
Application Performance Monitoring (APM)
APM platforms like Datadog APM, New Relic, Dynatrace, AppDynamics, Instana, SigNoz, and Uptrace correlate traces, metrics, and logs to surface slow transactions and code-level b...
Profiling and Code Hotspots
Continuous profilers like Google Cloud Profiler and Datadog Continuous Profiler identify CPU, memory, and lock contention hotspots in running services.
Traffic Replay and Chaos
Tools like GoReplay and Speedscale capture production traffic and replay it against staging or new versions to validate performance and behavior before release.
Scroll within the panel for all 8 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Performance Context
JSON-LDJSON Schema 2
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
LoadTestRun
JSON SCHEMAWebVitalSample
JSON SCHEMAJSON Structure 2
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Performance Load Test Run Structure
JSON STRUCTUREPerformance Web Vital Sample Structure
JSON STRUCTUREExamples 2
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Use Cases 7
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
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.
Scroll within the panel for all 7 ·
Integrations 8
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
k6
Open-source Grafana Labs load testing tool that uses JavaScript test scripts to drive load against HTTP, gRPC, and WebSocket APIs, with optional k6 Cloud for distributed runs.
Apache JMeter
Open-source Apache Software Foundation load testing tool for HTTP, REST, databases, JMS, and more, widely used for protocol-level performance testing.
Gatling
High-throughput, Scala-based open-source load testing tool with code-as-test scenarios and detailed HTML reports.
Artillery
Modern Node.js load testing toolkit with YAML and JavaScript scenarios, designed for serverless and Kubernetes-native workloads.
StormForge
Performance and load testing platform that uses machine learning to optimize Kubernetes resource configurations and validate scalability.
Datadog
Observability and APM platform offering distributed tracing, real user monitoring, synthetic monitoring, and continuous profiling.
New Relic
Full-stack observability platform with APM, browser-based RUM, synthetic monitoring, distributed tracing, and infrastructure metrics.
OpenTelemetry
Vendor-neutral CNCF standard for collecting traces, metrics, and logs, used to instrument applications for any compatible APM or tracing backend.
Scroll within the panel for all 8 ·
Resources
Every other property we hold for Performance — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Build 1
SDKs, sample code, and the tooling you integrate with
← All providers · Data indexed from github.com/api-evangelist/performance · machine-readable index on apis.io
This is an independent, third-party profile of Performance, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
info@apievangelist.com
·
Read the full data-sourcing policy →
On a security or compliance team? Put security in the subject line and
you will get a person, not a form — we will tell you exactly which public URLs this profile was built from.