From Load Testing to Reliability Engineering: Making Performance Testing Predict Production Behavior | TestMu 2026
Performance testing often creates more noise than value. Teams run load tests, collect huge amounts of data, and generate detailed reports, yet still struggle to answer the question that really matters: Will this change be safe in production?
The challenge is rarely the testing tool itself. Instead, it lies in the gap between performance testing and the broader engineering practices required to make results meaningful: clear service level objectives, realistic workload models, effective observability, production feedback loops, and risk-based decision making.
In this session, we'll explore how performance engineering can evolve from isolated testing activities into a continuous reliability practice embedded throughout the software delivery lifecycle. You'll learn how to use SLOs to focus on what truly matters, select performance tests based on risk rather than habit, and connect test results with observability data to gain confidence in production outcomes.
Rather than treating performance testing as a gate at the end of delivery, we'll examine how modern teams use performance signals throughout development, CI/CD, and operations to support faster and safer releases.
Whether you're a tester, quality engineer, developer, SRE, or platform engineer, this talk provides practical techniques for turning performance testing into a meaningful predictor of production reliability.
How to determine which performance tests are worth running and when.
How SLOs influence test design, acceptance criteria, and release decisions.
How observability improves the value and trustworthiness of performance test results.
How production feedback can continuously improve testing effectiveness.
How automation and platform thinking help scale performance engineering while reducing cognitive load for development teams.

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