Common Mistakes In Performance Testing to Avoid

Here is a summary of some of the most common performance testing mistakes you should avoid.

Have no testing environment available

We cannot do performance test without an environment. So assembling testing environment is important. The softwares and applications could pass all the tests but may get stumped in real usage environment. It could be the result of a failure in simulating a realistic test environment. If we do not spend time and thought in creating a realistic environment, we can waste efforts testing something that is not real.

Adding Improper Think Time/Delays

Using improper think time and pacing delays are the most frequent performance testing mistakes. Some either forget to add them or use unrealistic user think time. Many people bombard an application with thousands of requests in a second without pausing to think then wonder why the response time is slow. As a result, you need to carefully define think time by making a realistic test scenario that emulates how a real user would interact with your application.

Ignoring System/Scripting Errors

To ensure we are running a valid test, there are a few things to keep in mind. Performance indicators and response times sometimes are realized very quickly, while some system issues manifest themselves through scripting errors that are pretty obscure.

These mistakes reflect underlying difficulties and are not always reproducible. Though such errors may seem insignificant, they have to be examined for any potential issue.

Inadequate Testing Infrastructure

In performance testing, there are many significant elements other than load generation. The results achieved from a plan are useless until you realize how your intended infrastructure is actually dealing with the issue. Testers need to know that the source of an increase in response times might be either load creation or infrastructure.

Using an Incorrect Workload Model

The workload model of a software shows how the program will be used in the production environment. It is essentially the detailed plan that you should be writing your scripts against. Having an accurate workload model is critical to the overall success of your testing. The testing process is immediately affected if the workload model is designed incorrectly or has unclear features.

Conclusion

It is difficult to consider all these points when planning performance testing, but having the information could help you plan effective performance testing. If you're looking for a performance testing tool that's simple to use, you could try WeTest PerfDog, using tools like PerfDog will make it much easier to prevent these mistakes.

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