performance-testing

Performance testing measures how systems behave under various load conditions, including response times, throughput, resource utilization, and scalability. It helps identify bottlenecks, validate performance requirements, and ensure systems can handle expected loads. Minimal working example: Detailed implementations in the references/ directory: - Overview - When to Use - Quick Start - Reference Guides - Best Practices - Validating response time requirements - Measuring API throughput and latency - Testing database query performance - Identifying performance bottlenecks - Comparing algorithm efficiency - Benchmarking before/after optimizations - Validating caching effectiveness - Testing concurrent user capacity - Define clear performance requirements (SLAs) - Test with realistic data volumes - Monitor resource utilization - Test caching effectiveness - Use percentiles (P95, P99) over averages - Warm up before measuring - Run tests in production-like environment - Identify and fix N+1 query problems - Test only with small datasets - Ignore memory leaks - Test in unrealistic environments - Focus only on average response times - Skip database indexing analysis - Test only happy paths - Ignore network latency - Compare without statistical significance