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Watch Out for These Rookie Mistakes During Performance Testing

Performance Testing

Clearly, performance testing comes into play in the end of the pre-production phase of the development chain. It’s that cutting corners, rushing results and getting testing on the move time so you can move forward fast enough to hit launch.

There’s no denying that performance testing is an extremely complex task and calls for your immediate attention. Planning incorrectly, creating scenarios that don’t simulate a real production environment as accurately as expected, or even overloading your load generators – and on top of that, you’ve lost precious time, money as well as resources involved in re-running the test. The worst case scenario is that you haven’t realistically load tested your system that leads your long-anticipated launch end up in a complete catastrophe.

Remember the causes of the initial failure of the Healthcare.gov website? According to the report by Forbes, “inadequate testing” was listed among the 8 reasons that had led to the website’s massive failure. Of course, you wouldn’t want something to lead to a major disappointment in your case.

Read on to educate yourself on what mistakes you need to watch out for:

No ‘Performance Targets’ Defined

The first and foremost mistake that you are likely to make is nonexistence of specific performance targets. Often targets can be understood using terms such as “demonstrate adequate performance” or use the ever-present “sub-second response.” To test performance, you need to be well-aware of what the targets are.

Incomplete and Inaccurate Testing

There are times when the testers ignore to study the end users and the consumption patterns of the application under test. Often a couple of load tests followed by a stress test (sometimes optional) is planned. The application usage characteristics are not studied to derive the right type of test (with right test duration, ramp up & steady state periods, requests/second, transactions/second, load fluctuations, etc.). There is a misunderstanding in the real objective of the test & need for carrying out the right test, etc. leading to incomplete and inaccurate tests.

Insufficient Test Data

The test data used in the performance test environment is far less compared to the production environment. Sometimes performance testers seem to miss out on the fact that for data intensive applications, the data volume becomes one of the key factors for deciding the system performance. Production database dump (with sensitive data being screened) or test data creation tools are not used during performance testing and system performance is proficient for fewer data volumes on the test environment.

Messed up Performance test environment

Typically, the performance testing environment should serve the purpose correctly, otherwise you won’t get the desired results. For that, you essentially require a thorough understanding of how the environment varies from production in relation to its configuration, horizontal and vertical scale, as well as database content. For that, there should be a reliable process maintained to restore the environment to an identified state, or otherwise, test environments should be owned, managed and provisioned centrally since shared usage can significantly lead to environment inconsistency.

Load Generation Overloaded

Despite knowing that the application under test is being used across geographical locations and in different time zones, the impact on server load because of network latency is at times ignored. Local load generation machines are used, instead of cloud-based load generation options. In addition, the load generation machine’s performance (CPU / Memory / Disk / Network) is not given due importance, thinking that the load generator will most likely spawn the configured user loads.

Undecided Environment Conditions

While conducting performance testing, it is absolutely NECESSARY to define your testing criteria. The latest performance testing tools offer sufficient useful analysis required from application client’s viewpoint. But, for solving problems efficiently or even for creating a purposeful testing standard, it is essential to recognize how the load being generated can affect the hosting infrastructure. In addition, sometimes testers fail to select a monitoring interval that provides adequate data for gathering significant statistical analysis.

Avoiding these mistakes cannot guarantee that application’s users will give you a thumb’s up in terms of experience every time they use it. However, you’ll be able to deliver a great user experience.

Just remember to be careful not to make these performance testing mistakes, which can adversely affect your performance as well as your company’s repute.

If you know of any other performance testing mistakes that should be avoided then do sound off in the comments section below.

Happy Performance Testing!

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