performance-testing

API load testing strategies are designed by defining expected traffic scenarios, collecting key metrics like latency percentiles and error rates, and setting SLA thresholds for throughput. This approach validates responsiveness and reliability under expected demand before deployment.

Stress testing identifies system breaking points by pushing traffic beyond capacity limits, while spike testing validates elasticity and recovery during sudden traffic bursts. Both techniques expose different failure modes in throughput and responsiveness under extreme conditions.

k6, JMeter, Gatling, and Locust are all supported tools for executing performance tests on backend web services and APIs. They enable scenario execution, metric collection, and SLA validation for load, stress, and soak testing workflows.

Stress testing measures p95 latency and error rates by executing defined scenarios that push traffic beyond capacity while collecting latency percentiles, throughput, and resource utilization metrics. These metrics expose breaking points and confirm graceful recovery after traffic bursts.