User Acceptance Testing (UAT) is a critical step when validating upgrades such as moving to a different Java build or deploying new versions of Ambience/Repertoire. To ensure production‑readiness, UAT should closely mirror real‑world conditions and provide measurable evidence of stability, performance, and functional correctness.
Best Practices
- Mirror Production Environment Align UAT with Production hardware, JVM build, OS settings, and configuration. This ensures that any issues observed are representative of actual deployment conditions.
- Replicate Traffic Patterns Design UAT test plans based on real Production traffic and concurrency, including peak loads. Sustained concurrency and longer uptimes should be simulated to capture potential stability issues.
- Collect GC Logs Monitor garbage collection logs for pause times, frequency of full GCs, and memory pressure. These indicators help identify performance bottlenecks or risks of instability.
- Compare Performance Baselines Establish a baseline by comparing existing and new Java metrics against current Production metrics. This highlights regressions in response times or resource utilization.
- Run Functional Regression Execute regression suites covering critical business logic. This ensures that JVM or library changes do not introduce subtle errors in calculations or workflows.
- Ensure Data Volume Parity Populate UAT databases with data volumes and complexity similar to Production. Performance can vary significantly when processing real‑world datasets versus clean test data.
- Include Failure/Recovery Scenarios Test resilience by simulating service restarts and network blips. Validate that the runtime recovers gracefully under these conditions.
- Review Logs for Errors Regularly review logs for ERROR and WARN entries, even if reports appear functional. Overlooked errors can indicate deeper issues that may surface under load.
Recommendations
- Automate UAT test execution to avoid manual overhead and ensure consistency across releases.
- Collaborate closely with QA teams to design realistic test scenarios.
- Document findings and compare against Production metrics to build confidence in readiness.