Performance Testing Standards · PT

This document provides guidance on best practices for writing performance tests for testers and developers to help ensure performance testing is consistent across projects.

Performance Tests: This is a broad category of non functional testing used to determine how a system performs in terms of responsiveness, stability, scalability, and speed under a particular workload.

Load Tests: This is a type of performance testing, these tests are designed to simulate a representative number of users accessing the system simultaneously to evaluate its performance under expected load conditions. E.g. Simulating 1,000 users accessing a website at the same time to see if it remains responsive.

Load tests must simulate the expected number of concurrent users accessing the system to ensure the results reflect real-world usage.

Performance tests must use data volumes that are representative of production environments to ensure accurate results.

Load tests must include the most frequently used API calls and user workflows to ensure critical paths are tested.

Performance tests should be scheduled to run regularly (e.g. weekly or before a release) to identify performance issues early.

Do not rely solely on load testing to assess system performance. Load testing is essential for understanding how a system behaves under expected user traffic, but it does not provide a complete picture.

Use a combination of performance testing methods to evaluate different aspects of system behavior. Examples include:

• UI performance testing – to audit front-end performance, including page load speed, interactivity, and visual stability. Various tools can be used for this purpose, such as Lighthouse.
• Stress testing - to determine how the system performs under extreme conditions and how it recovers from failure.
• Endurance testing - to identify issues such as memory leaks or performance degradation over time.
• Spike testing - to evaluate how the system handles sudden increases in load.
• Scalability Testing - to evaluate how the system performs as the workload increases.