Performance testing is critical for understanding how applications behave under different levels of load, but interpreting the results remains a complex challenge. Traditional evaluation methods—especially those using binary pass/fail criteria—fail to capture the nuanced reality of modern software systems. As part of Continuous Integration and Continuous Deployment (CI/CD) pipelines, performance tests must provide actionable, reliable insights without manual intervention. In this post, I’ll share my insights on evaluating performance testing results. It’s the first part of a series aimed at achieving fully autonomous continuous performance testing. Why Evaluation Is Critical for CPT and Performance Testing Performance testing is no longer a one-time activity executed before release. With Continuous Performance Testing (CPT), performance checks are embedded throughout the software delivery lifecycle. This integration demands fast, reliable decision-making. But performance data—resp...
Not a feature, but the future of an app is under testing.