performance-testing

Run k6 or Locust load tests to identify performance bottlenecks and validate latency under realistic and extreme traffic. This process applies SLO-based thresholds to catch regressions across API services, microservices, and backend systems.

Yes, k6 load testing integrates directly into CI pipelines to catch performance regressions. It enforces SLO-based pass/fail thresholds on API services, automatically failing builds when latency or error-rate baselines are breached.

Yes, the load testing approach supports Locust integration for Python-based load simulations. This allows you to execute realistic traffic scenarios and diagnose system bottlenecks using Python-defined workload scripts alongside k6.

Run a baseline k6 test against your staging environment to establish latency and error-rate baselines. This validates your microservices' throughput and performance under realistic traffic before production deployment.

You need SLO-based thresholds for capacity planning when validating production readiness under extreme load. They automatically enforce pass/fail criteria for latency and throughput during CI pipeline load tests and bottleneck diagnosis.