Flexible Performance Test Metrics: Changing User Numbers Mid-Test

For years, executing performance tests meant waiting until the test concludes to examine the data. It was the natural progression of performance test metrics; it makes sense that you would need to wait for the conclusion of a test to yield actionable data.  

But at the same time, it makes optimizations of those tests time-consuming. You execute a test, find that the performance test metrics need to be adjusted, and then you run another test. Over and over and over again. 

The latest BlazeMeter feature does away with that often-tedious process by allowing users to change such performance test metrics like simulated users while the test is running. This blog discusses what performance test metrics are and the benefits of being able to adjust the number of users while the performance test is running. 

What Are Performance Test Metrics?

Performance test metrics are key performance indicators (KPIs) that determine the efficacy of a performance test. Performance test metrics include:

• Time 

• Response time 

• Concurrent users 

• Throughput 

• Queries per second 

• Bandwidth 

• CPU 

• Latency 

Among all of these performance test metrics, one of the most vital is the number of concurrent users simulated during a performance test. This KPI measures how many users are using the software being tested and how it responds in the face of that. 

The Benefits of Flexible Performance Test Metrics

Performance tests are only as good as the results they yield. The efficacy of a performance test can range wildly depending on the quality of the test, and the actionable data that results is directly affected by the quality of the performance test. 

Optimizing performance tests is at the core of producing a high-quality app; stagnation and complacency is the death knell for anything — software included. With BlazeMeter, you can now change the number of simulated users with JMeter while the test is running! 

Doing so saves the tester valuable time as they are able to optimize the performance test on the fly. The interface is incredibly easy to use — a simply sliding scale lets you increase and decrease users in the test to your heart’s desire. 

Another major upgrade is the ability to identify the changes. This means that users can see what the previous number of users was, the newly adjusted number of users, who made that change and when. This makes performance tests much more transparent and easier to keep track of. 

The ability to adjust performance test metrics like the number of users simulated in a performance test is a game-changing tool for testing teams.