Avoiding Practices in Performance Testing

Common Errors to Avoid in a Performance Testing Process. #

Performance testing is a set of tests that allow us to measure the execution speed of a series of tasks on a system under certain conditions. These tests can be an enormous challenge for those who jump from manual tests even to automated ones due to the required technical level. Unfortunately, not all perform well in performance testing, and I as a tester of performance would like to share with you some errors that I have learned through my experience, documenting them and today wanting to share them with you. Here are some common errors we can avoid in our future projects, regardless of the tools we use.

Inaccurate Planning #

Many organizations do not consider performance during the initial stages of development. This can lead to problems in subsequent phases of software development. Internally in performance testing, planning each activity is crucial. It must be noted that correlation process is a complex and difficult phase, and it usually requires more time and effort.

Incorrect Workload Model Creation #

Precise workload modeling is the first step in determining performance problems. Workload models provide information on what actions of users will be tested under a given load level, which business scenarios will apply to all users and how the users will be distributed across each scenario. Remember that before you can generate load for a web or mobile application, you must learn and understand its anatomy.

Choose the realistic test environment is a challenging task that may require significant technological and organizational efforts. If the test environment is not realistic, the results of the test will not be accurate.

Lack of documentation. #

Repeating scenarios and comparing results between executions or iterations are important activities in performance testing. This process can become complicated when there are many iterations, parameters, virtual users, requests, etc. Ensure to document problems related to each iteration in result logs. It is valid to consider at least the Test Plan and Result Report documents.

Machine Generator Load Saturation #

Low hardware level or too many virtual users interacting with the application can contribute to overloading the machine generator. This will negatively impact response times. We must ensure we have machine generators for correctly distributing load.

Poorly Precise Results. #

We cannot pretend to show a performance report with response times and errors only from JMeter. It is of vital importance to take into account that we have indicators and metrics in servers where the tested applications are hosted. These indicators must be monitored correspondingly with the performance tests executed.