performance-testing

Performance bottlenecks are constraints limiting system responsiveness, identified through load testing that measures latency, throughput, and resource usage under realistic traffic. Monitor CPU, memory, and database query metrics during tests to pinpoint slow components.

Load testing validates normal capacity; stress testing pushes beyond limits; spike testing handles sudden traffic surges; endurance testing checks stability over time. Each test type reveals different failure modes and helps set realistic SLOs like p95 latency targets.

Define SLOs (service level objectives) like p95 latency and error rates, construct realistic user scenarios, instrument monitoring dashboards, then execute tests using tools like k6, JMeter, or Artillery to validate system behavior meets targets across services.

Yes, performance testing coordinates testing agents across distributed services and user journeys to validate system behavior end-to-end. This orchestration ensures bottlenecks in one component don't mask issues in dependent services.

Track p95 latency, throughput, error rates, CPU and memory usage, and database query performance. These metrics validate whether your system meets SLOs and help correlate performance degradation with specific resource constraints.

Performance testing validates system resilience under controlled, realistic scenarios before production; production monitoring catches unexpected issues in live traffic. Both are needed—testing ensures capacity planning, monitoring detects real-world anomalies.