Performance testing plays a critical role in application reliability. It enables developers and engineering teams to catch issues before they reach production or impact the end-user experience. Understanding performance test results and acting on them, however, has always been a challenge. This is due to the visibility gap between the black-box data from performance testing and the internal white-box data of the system being tested.
Observability dashboards are powerful tools that enable teams to visualize and monitor the performance, health, and behavior of their applications and infrastructure. However, building observability dashboards is not a straightforward task, and many organizations make common mistakes hindering their ability to gain meaningful insights and respond to issues effectively.
Enterprise IT is just a different animal. Whether it’s operating at scale, undertaking massive migrations, working across scores of teams, or addressing tight security requirements, engineers at these organizations can face different obstacles than their counterparts at smaller organizations and startups.
In the world of performance testing there is a heavy focus on the practice of load testing. This requires building complex automated test suites which simulate load on our services. But load testing is one of the most expensive, complicated, and time consuming activities you can do. It also generates substantial technical debt. Load testing has its time and place, but it's not the only way to measure performance.