11 Best Practices for Continuous Performance Testing

Your development teams must do continuous performance testing in order to produce a high-quality product. This is because such testing enables them to promptly spot load-handling and performance defects that are hard to find in addition to important functional bugs. When it comes to putting continuous performance testing into practice, being aware of these 11 best practices will be beneficial:

Pay attention to performance SLAs: 

Adding codes to an application for testing shouldn’t cause it to malfunction or fail to meet the SLAs. This means that for each iteration, you should use your performance SLAs as acceptance testing. Therefore, modifications to the iteration that impact a tiny portion of the total code would be justified because, in such a scenario, performance problems would be confined to that specific area of the program. A more comprehensive list of constraints should be added for generic SLAs that span the entire program, though, as they will be reviewed at each iteration to ensure that it satisfies a notional definition of “being completed” without violating any of the constraints.

Adopt a test-driven methodology:

Test scripts and product features should be developed concurrently to jumpstart the project as a whole. This would guarantee that in the event that software modifications are made, the testers won’t need to duplicate or modify the test scripts.

Testers and developers ought to collaborate closely:

In order to comprehend how the software or program that is presently being created will ultimately be tested, testers and developers should collaborate closely. Testers should attend scrum-like meetings to be informed about the development tasks, while developers should approach their projects with a tester’s mindset. Close cooperation like this would provide a seamless, ongoing testing procedure.

Create test cases based on scenarios or stories:

In contrast to the conventional development model, contemporary development procedures frequently deny customers access to comprehensive specifications. Instead of building tests based on a strict set of cases in these situations, story- or scenario-based tests ought to be developed. Testers can cover a wide range of tests with such tests, some of which may not be fully described.

Using dynamic tests for dynamic environments:

Previously, a single test script might have been used to evaluate several computing scenarios. But, given how quickly settings are changing in today’s world, tests also need to be dynamic. Because of this, the infrastructure as code approach—in which all applications, computational resources, and virtual hardware are represented as software—is growing in popularity. 

They can be programmed in accordance with the requirements that now need to be satisfied. Therefore, the scripts are developed by the company’s IT staff, who also design and set up the necessary virtual environments for the tests to execute.

The use of test automation has increased:

Selenium automation testing is still typically restricted to the initial phases of unit testing. However, they must be used throughout the deployment process, especially in the later phases. The best approach to achieve this is to write test scripts that can be isolated into discrete software services or components, which can subsequently be utilized in a somewhat agnostic manner as and when the need arises in various contexts.

Increasing the usage of tools for application performance monitoring

These days, APM tools are crucial parts of many testing procedures. For shift-right performance monitoring to continue, these tools must be employed more frequently.

Start recurrent tests with a build server:

Performance tests ought to be included in the recurring tests for each build. This can be accomplished by starting the test through the build server and including the test output generated by the build tool. In this manner, the person initiating the build would be able to view the outcomes and be aware of the modifications performed throughout that build. This entails resolving any performance problems that may arise.

Appropriate preparation for CI, post-sprint, and nightly build tests:

There may be substantial differences between the tests for post-sprint, continuous integration (CI), and nightly builds. The distinction can be between all the modifications made over the course of a sprint and a single change made in a single day. For such builds, performance tests should therefore start modestly and make use of the available internal loads. For example, you can use a typical load on the application created by your internal load generators to execute a quick performance test covering the most common scenarios the fastest. It is important to run the tests for continuous integration builds quickly in order to observe the effects of the build’s modifications on the system. 

To make sure they are used appropriately, the developer who initiated the continuous integration (CI) should view these outcomes as soon as feasible.

Repurposing testing assets: 

This has the potential to improve continuous performance testing efficiency. For example, a lot of businesses these days use artificial intelligence (AI) to go through operational system logs and find the URLs associated with the most popular user pathways. The following procedure takes advantage of automation to prioritize testing various pathways based on their identification. Additionally, a number of businesses are using their functional assets again later in the deployment pipeline to target test objectives. By utilizing cutting-edge methods, as well as the information and experience gained from Automation testing with selenium, these businesses are reducing testing costs and clearing the path for increased productivity.

Choose mocking: 

You can test components separately by utilizing mocking for component testing. In this manner, you can guarantee top-notch tests that support continuous delivery.