11 Best Practices for Continuous Performance Testing
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To develop a top-notch product, your development teams need to perform continuous performance testing because with it, they can quickly identify key functional bugs as well as those load-handling and performance bugs that are difficult to detect. If you’re ready to implement continuous performance testing, knowing these 11 best practices would help:
- Focus on performance SLAs: Introducing codes in an application for the purpose of testing shouldn’t make it fall apart or fall short of the SLAs. What this means is that you should use your performance SLAs as acceptance testing for every iteration. Thus, changes made to the iteration that affect just a small part of the overall code would be acceptable because performance issues in such a case would be limited to that particular part of the application. However, for general SLAs that cover the entire application, a broader list of constraints should be added that will be examined for each iteration to verify if it meets a nominal definition of “being completed” without breaking any of the constraints.
- Take up a test-driven approach: To give the entire project a head start, product features and test scripts should be created simultaneously. This would ensure that there’s no need for the testers to recreate or revise the test scripts if some changes are made in the software.
- Developers and testers should work closely: Testers should work closely with the developers to understand how the software or application that’s being coded currently would be tested ultimately. While developers should think like testers when working on their project, testers should stay updated about the development tasks by attending the scrum-like meetings. This close collaboration would ensure a smooth and continuous testing process.
- Develop story/scenario-based test cases: Unlike the traditional development model, modern development processes often don’t make detailed specifications available to users. In such cases, story- or scenario-based tests should be created rather than devising tests based on a rigid set of cases. Using such tests, testers can cover a broad range of tests that may not be essentially documented.
- Using dynamic tests for dynamic environments: In the past, multiple computing scenarios could have been tested using a solitary test script. However, in today’s fast changing environments, the tests too need to be dynamic. And that’s why infrastructure as code approach is becoming popular, where all virtual hardware, computing assets, and applications are represented as software. Based on the requirements at the moment that need to be met, they can be programmed accordingly. Thus, the company’s IT staff develops the scripts, which in turn create and configure the requisite virtual environments for running the tests.
- Increased use of test automation: In most cases, automation is still limited to the early stages of unit testing. However, they need to be applied all through the deployment process, particularly during the later stages. To make this happen, the best way is to create test scripts that can be encapsulated into distinct software services/components, which can then be used, as and when the need arises in different situations, in a comparatively agnostic style.
- Increased use of application performance monitoring tools: APM tools are used as important components of several testing processes today. Such tools need to be used increasingly to continue shift-right performance monitoring.
- Use a build server to initiate recurring tests: With every build, performance tests should feature among the recurring tests. You can achieve this by initiating the test via the build server, and including the test results produced within the build tool. This way, the person who started the build would be able to see the results, and know the changes that were made in that build. This means fixing performance issues (if any) that come up.
- Proper planning for tests for CI, post-sprint and nightly builds: Tests for nightly builds, CI (continuous Integration) builds, and post-sprint builds could differ significantly. And the difference could be between a solitary change made in a day against all the changes made during a sprint. Thus, performance tests for such builds should begin small and use the available internal loads. For instance, you can run a small performance test covering the most common scenarios the fastest by using a typical load on the application that’s generated by your internal load generators. The tests for CI builds should be run speedily so that you can see the results of how the changes made in the build influenced the system. The developer who started the CI should see these results as soon as possible to ensure they are leveraged the right way.
- Repurposing of testing assets: This can help bring greater efficiency in the domain of continuous performance testing. For instance, many companies these days are using AI to examine operational system logs to identify the URLs connected with the most called user paths. The next step uses automation that leverages this identification to give these paths a priority for testing. Several companies are also repurposing their functional assets against test targets at a later stage in the deployment pipeline. By leveraging modern techniques, knowledge, and expertise acquired through automation, these companies are decreasing testing overheads and paving the way toward greater efficiency.
- Opt for mocking: By using mocking for component testing, you can check components in isolation. This way, you can ensure high-quality tests that facilitate continuous delivery.
If you haven’t been doing performance testing, get started right away. Remember – even the basic performance tests, when run continuously, can bring major benefits your way.
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