Prompt

I need load testing that works with our CI pipeline

Technology / Testing & QA1 observationLast seen Sep 30, 2026

Latest observation

Sep 30, 2026OpenAI APIWeb search: off

If you want load testing that fits cleanly into CI, the best approach is usually:

  1. Pick a tool that runs headless from the command line
  2. Keep tests short and repeatable
  3. Fail the pipeline only on clear performance regressions
  4. Store metrics so you can compare runs over time

Good CI-friendly load testing tools

  • k6 — probably the best default choice for CI
    • Scripted in JavaScript
    • Great CLI support
    • Easy to run in Docker and CI
    • Good thresholds and exit codes for pass/fail
  • Locust
    • Python-based
    • Good if your team prefers Python
    • Also works well in CI, though a bit more setup
  • JMeter
    • Widely used, but heavier and often more awkward in CI
    • Better for legacy teams or existing test suites

Recommended CI pattern

Use a two-layer setup:

1. Fast smoke load test on every PR

  • 1–5 minutes max
  • Small virtual user count
  • Checks:
    • API is reachable
    • basic latency stays within threshold
    • error rate is acceptable

Example thresholds:

  • p95 latency < 500 ms
  • error rate < 1%

2. Full load test on scheduled builds or main branch

  • Longer duration
  • More realistic traffic profile
  • Run nightly or after merges to main
  • Track trends over time

Example: k6 in CI

A simple k6 script can define thresholds like:

export const options = {
  thresholds: {
    http_req_duration: ['p(95)<500'],
    http_req_failed: ['rate<0.01'],
  },
};

Then in CI:

k6 run script.js

If the thresholds fail, k6 exits non-zero, which is ideal for pipelines.

How to integrate with CI

Most CI systems support this easily:

  • GitHub Actions
  • GitLab CI
  • Jenkins
  • Azure DevOps
  • CircleCI

Usually the flow is:

  1. Start application in test environment
  2. Run load test against it
  3. Collect reports/artifacts
  4. Fail the job if thresholds are exceeded

Important best practices

  • Run against a dedicated test environment, not production
  • Make the environment as production-like as possible
  • Use seeded data and stable dependencies
  • Avoid huge flaky tests in PRs
  • Separate performance testing from functional tests
  • Store results in Prometheus/Grafana, InfluxDB, or CI artifacts

My recommendation

If you’re starting fresh, use k6:

  • easiest CI integration
  • lightweight
  • good threshold support
  • easy to containerize

If you want, I can give you:

  1. a ready-to-use k6 script,
  2. a GitHub Actions pipeline example, or
  3. a comparison of k6 vs Locust vs JMeter for your stack.

Observation history

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