AI Performance Testing · No-code load tests · Full-stack

Load Testing Just Got Easy With AI Performance Tools

Built for real-world validation, ContextQA simulates realistic load and traces bottlenecks across your entire stack. Load testing finally keeps pace with your release velocity, no scripting required.

No-code load design Full-stack visibility SOC 2 Type II
Trusted by leading engineering & QA teams
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Always on

Load Tests Anyone Can Build, That Run Themselves

You no longer need an engineering degree for load testing. ContextQA builds realistic scenarios from plain language, runs them on every build, and traces any slowdown to its root cause across UI, API, and infrastructure. Your team validates performance without the scripting burden.

The problem

Why Load Testing Stalls in Most Teams

Legacy performance testing is slow, script-heavy, and hard to read. Most teams only discover problems once they hit production.

Full-stack visibility

See Performance Across the Whole Stack

One engine that traces a slowdown wherever it lives: in the browser, in your services, or deep in the database.

Front-end and browser
Measure real browser load, render time, and client behaviour under traffic, not just raw server numbers.
APIs and services
Drive HTTP/S and REST load across endpoints and microservices, with response time, throughput, and error rate per service.
Infrastructure and database
Correlate CPU, memory, and slow database queries with the exact moment performance degrades under load.
Capabilities

What ContextQA Automates for Performance

From building scenarios to reading results, ContextQA removes the scripting and guesswork from load testing.

Build load tests visually

Design complex scenarios with a no-code interface, no scripting required.

Mirror real behaviour

Model realistic traffic mixes and ramp-up, spike, soak, and random profiles at scale.

Full-stack tracing

Pinpoint bottlenecks across UI, API, infrastructure, and the database in one view.

UI and API load together

Test full-stack performance the way real users actually exercise your app.

Regression gates

Catch performance regressions before production and block releases on SLA breaches.

Actionable reports

Clear reports with response time, throughput, error rate, and root cause.

In action

Performance Testing, Working in Real Time

Watch how ContextQA builds, runs, and explains your load tests, live.

Load Spike Stress Soak
01

Load tests built from plain language

Load profile0 to 500 VUs
rampspikesoak

Describe the load you expect and ContextQA builds a realistic profile with ramp-up, spike, and soak phases from your SLA targets and traffic mix, no scripting required.

02

Regressions caught before production

perf-gate · build #214SLA
checkout p95 312ms (budget 400)✗ orders p95 612ms regression~ fix: index orders.created_at✓ orders p95 188ms resolved

Slow builds should never reach users. ContextQA compares each run to the baseline, flags the regression in the pipeline, traces the cause, and confirms the fix before it ships.

03

Every region, in parallel

Region latencywithin SLA
0ms150300450ms
US East188
EU West242
Asia Pac324
S. America288

Mirror a global user base. ContextQA generates load from multiple regions at once so you see latency differences across geographies, and it plugs into Jenkins, GitHub Actions, GitLab, or Azure DevOps.

04

Bottlenecks explained, not guessed

checkout txn · 480msat 420 VUs
request · 480ms
apprenderDB query 180ms
Bottleneck: orders DB query, add index

No more staring at raw graphs. ContextQA breaks each transaction into a flame view, highlights the slow segment, and names the root cause, so triage takes minutes.

Capabilities

Everything You Need for Performance Validation

Every capability maps to a concrete outcome for your performance testing.

The workflow

How AI Validates Performance

A closed loop that defines load, generates it, finds where things degrade, and reports back on every build.

Under the hood

Technical Capabilities

Built to validate the realities of production traffic at scale.

HTTP/S and REST

Drives HTTP/S and REST API load across endpoints and services.

Load profiles

Ramp-up, constant, spike, soak, and random traffic patterns.

Geographic distribution

Generate load from multiple regions to mirror real users.

Real-time metrics

Response time, throughput, error rate, and latency as it runs.

Backend telemetry

Correlates CPU, memory, and database queries with slowdowns.

CI/CD with SLA gates

Works with Jenkins, GitHub Actions, GitLab, and Azure DevOps.

Explore more

Connect Performance Testing With the Rest of the Platform

Performance is one surface in ContextQA. Each capability works in sync through agentic reasoning, testing and validating with steady precision at scale.

FAQs

Our Customers Also Ask

No. ContextQA uses a visual, drag-and-drop interface to build load scenarios, set ramp-up profiles, and define expectations. Teams design realistic performance tests without writing or maintaining scripts.
Yes. ContextQA runs unified load tests that combine UI and API traffic, so you can validate full-stack performance the way real users actually exercise your application.
ContextQA captures telemetry across response time, throughput, error rate, latency, CPU, memory, and database queries, then uses agentic reasoning to trace a slowdown to its root cause instead of leaving you to guess.
Yes. ContextQA integrates with Jenkins, GitHub Actions, GitLab, and Azure DevOps to run load tests on every build, enforce SLA thresholds, and block releases when performance regresses.
Yes. ContextQA can generate load from multiple regions at once to mirror a global user base and reveal latency and throughput differences across geographies.
ContextQA stores baseline metrics and trends, then compares each run against prior builds. Teams see regressions, improvements, and SLA threshold violations build over build, and can fail a pipeline automatically when targets are missed.

Keep Every Build Fast Through Continuous Change

Validate performance on every build with load tests anyone can run. ContextQA simulates real traffic, traces bottlenecks across your full stack, and blocks slow releases before they reach production.