analyzing-test-results

Interpreting k6 load test results involves analyzing HTTP request duration breakdowns like waiting, connecting, and receiving times to pinpoint performance bottlenecks. This Skill evaluates metrics such as error rates and throughput to determine if issues are server-side or network-related.

In k6 metrics, http_req_waiting measures time spent waiting for the server response, while http_req_receiving measures time transferring the response payload. Analyzing these components helps identify whether performance bottlenecks are due to slow server processing or large response sizes.

Tuning k6 thresholds requires evaluating current load testing performance analysis data to set realistic pass/fail criteria. This Skill provides actionable recommendations for adjusting thresholds based on identified metrics like HTTP request durations and error rates to optimize test configurations.

High http_req_duration in k6 tests indicates slow overall request processing, which can be optimized by analyzing sub-metric breakdowns. This Skill helps diagnose whether the bottleneck stems from server-side waiting times or receiving large payloads, suggesting infrastructure adjustments or script optimizations.

Yes, analyzing k6 test results helps determine infrastructure scaling needs by evaluating throughput and error rates under load. This Skill translates performance bottlenecks and request timing breakdowns into actionable guidance for scaling infrastructure or improving script efficiency.

High error rates and low throughput in k6 test output indicate severe performance bottlenecks, often pointing to server overload or connection failures. This Skill analyzes these metrics alongside request duration components to diagnose root causes and recommend optimizations.