Our Five-Phase Methodology
Performance testing fails most often before any load is generated — through vague objectives, unrealistic workloads, or environments that don't resemble production. Our methodology exists to eliminate those failure modes.
- 1. Requirements & Workload Modelling — define what to prove and what load is realistic
- 2. Test Design & Scripting — build correct, maintainable test assets
- 3. Environment & Test Data — ensure results will transfer to production
- 4. Execution & Monitoring — run disciplined, observable tests
- 5. Analysis & Reporting — turn data into decisions
Principles behind the process
Explicit pass criteria before execution. Every test has written, agreed targets — latency percentiles, throughput, error budget — signed off before we run. Without them, results become a Rorschach test.
Workloads from evidence, not intuition. Transaction mixes and arrival rates come from production analytics wherever they exist. The most common cause of misleading results is a workload model that flatters the system.
Everything version-controlled and repeatable. Scripts, configuration, data generation and analysis are code. Any result can be reproduced from the repository.
Measure the system, not the tool. Load generators saturate too. We monitor injection-side health (CPU, sockets, GC) on every run so we never report a load-generator bottleneck as an application defect.