The best developer
experience for load testing

Open source and SaaS for engineering teams

Loved by developers. Trusted by businesses

Amazon
Noaa
Serphora
Citrix
Microsoft
Yum Brands
GitLab
Carvana

Prevent failures. Improve reliability. Release with confidence.

Test early and continuously—break the QA silo in performance testing

  • Developers

    Backend and frontend engineers prevent regressions when running performance tests.

  • Site Reliability Engineers

    Test scalability to improve your reliability targets. Test SLOs and avoid SLA breaches.

  • Software Engineers in Test / QA

    Shift left and collaborate with developers for effective and continuous testing.

Script tests in Javascript

On your machines, our cloud, or both

Scale from solo developers to large enterprises

Use the same script for local, distributed, and cloud tests

Migrate from local tests to the cloud using the same script for both environments.

k6 run script.jsLocal
or
kubectl apply -f k6.yamlk8s
or
k6 cloud script.jsCloud

Run tests from 21 load zones

Simulate real global traffic patterns

More testing with one tool

k6 Open Source is designed for load testing. Extensible to support other types of testing.

  • Load testing

    Verify that applications can handle the expected traffic. Different goals require different tests: stress tests, spike tests, soak tests, smoke tests, etc.

  • End-to-end web testing

    Mix browser and API testing—interact with real browsers and collect frontend metrics to get a holistic user view.

  • Fault injection testing

    Inject faults in Kubernetes-based apps to recreate application errors. Test resilience patterns and tolerance of internal errors to improve reliability.

  • Synthetic testing

    Traditional synthetic/ping testing is not enough anymore. Reuse your k6 tests to ensure availability in production.

  • Infrastructure testing

    Test how cloud-native systems scale. Isolate bottlenecks. Plan and provision infrastructure capacity.

  • Regression testing

    Test continuously to track changes in performance and reliability. Prevent software regressions from reaching production.

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