QA Testing (Performance)

Performance engineering guidance for validating throughput, latency, resource consumption, and scalability. Use this skill to design load tests, set CI performance budgets, profile bottlenecks, and plan capacity.

Core sources are curated in data/sources.json. Prefer primary docs and re-check volatile external facts before recommending versions, pricing, or tool features.

Quick Start

If key context is missing, ask for: SLOs/SLAs, critical user journeys, infrastructure topology, current baselines, traffic patterns (peak/sustained), database query hotspots, and frontend performance targets (Core Web Vitals).

1. Baseline — measure current latency (p50/p95/p99), throughput, error rate, and resource utilization under realistic traffic.
2. Design scenarios — model critical user journeys as scripted load test scenarios with realistic think times, data parameterization, and ramp profiles.
3. Execute — run load, stress, soak, or spike tests against a representative environment with monitoring active.
4. Analyze — compare results against baselines and budgets using percentiles, throughput curves, and error rate correlation. Identify bottlenecks with profiling.
5. Set CI budgets — define performance gates (latency thresholds, throughput minimums, error rate caps, Core Web Vitals budgets) and integrate into the pipeline.

Workflow