performance-testing

Load testing measures how your API responds under concurrent user traffic. Use tools like k6, Locust, or Artillery to script realistic workloads, execute tests, and collect metrics on latency, throughput, and error rates to identify capacity limits.

Load testing simulates concurrent users to measure system behavior under stress. Benchmarking establishes baseline performance metrics for comparison. Profiling identifies specific code or resource bottlenecks causing slowdowns. All three inform optimization decisions.

Performance budgets define acceptable thresholds for latency, throughput, and error rates. Define target metrics, configure monitoring in your test scripts with k6, Locust, or Artillery, and fail tests when budgets are exceeded to catch regressions early.

Yes. k6, Locust, and Artillery all support API and web service load testing with customizable workloads. Each has different scripting models and integrations; choose based on your language preference, environment, and reporting needs.

Collect latency (response time), throughput (requests per second), error rate, and resource utilization. These metrics reveal how your system performs under load and identify bottlenecks; use them to validate performance budgets and guide optimization.

Run spike tests to simulate sudden traffic surges and measure recovery time. Use sustained load tests for steady-state validation and capacity planning. Both scenarios ensure your application handles real-world conditions without degradation.