Determine Throughput Performance Testing

Throughput, commonly measured in transactions or requests per second, is a central performance-testing metric for assessing an application’s capacity, scalability, and ability to handle expected or peak traffic without unacceptable latency or errors. Determining maximum TPS requires more than increasing load until failure: teams should evaluate realistic ramp patterns, sustained loads that expose issues such as memory leaks and resource exhaustion, and sudden traffic spikes that test autoscaling, recovery, and resilience. Throughput results are most useful when correlated with latency, CPU, memory, error rates, and other infrastructure metrics to identify bottlenecks and guide optimization decisions. Production traffic replication can improve test realism by replaying captured Kubernetes traffic under configurable load patterns, allowing teams to test the same workload repeatedly with different scenarios. Using Speedscale as an example, the process involves creating a test configuration, replaying a production snapshot, reviewing throughput, latency, resource use, response success, and mock activity, and using automatic service mocks to isolate dependencies while preserving realistic inter-service behavior.

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