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Your application might fulfil all its required use cases perfectly. Yet, users will only become discontent if it performs as intended under stress or reacts quickly enough to user interaction input. Developers can utilize performance tests to pinpoint when changes slow down an app and which parts suffer from poor performance issues.
Performance testing environment is a common practice among top-performing teams. With this type of performance test, their applications are fast, scalable and reliable enough. Types of performance tests help ensure an application can manage thousands of concurrent users while offering positive user experiences - but before beginning with the performance testing process, it's wise to know more about its types and associated advantages before diving in headfirst.
Types Of Performance Testing
What are the types of performance testing? Each is tailored for a different scenario and used to help us identify whether there's an issue with our application and where it lies.
Load Testing
Load testing is a type of performance testing which simulates real-life situations. With load functional testing tools available today, user load tests send realistic requests or inputs in short increments (typically several minutes) to reproduce an authentic load time on an application - this might reflect its average resource usage or its highest peak rate in its history.
Stress Testing
Stress testing and load testing tools often need clarification. In contrast, load tests attempt to simulate realistic conditions; stress tests aim to gradually increase application resources until their maximum limit has been utilized. Stress testers usually increase load incrementally until an application fails; at that tipping point, their application can no longer withstand further loads (for instance, a maximum latency threshold should not be crossed).
Spike Testing
Stress testing resembles spike testing by simulating regular app usage followed by short bursts of requests - similar to spike testing but without gradually pushing systems past their capacity limits. Stress tests simulate normal app usage with intermittent bursts of requests as an indicator of the system response to an expected spike in traffic or peak to assess recovery afterwards and how well an application manages under such pressure.
Spike testing is particularly essential when anticipating such points at certain moments: for instance, ticket sales websites often see spikes when customers start buying tickets for popular events - stress tests allow cloud providers to test how their systems will handle this potential spike test when customers start purchasing tickets ahead of schedule.
Scalability Testing
The previous three types of tests are interdependent; we use those to stress test our system under various loads to see how our application responds. Running these tests could serve multiple purposes - users have complained about slow optimal performance in our code. We need to identify its troublesome areas or functional test how many new users we can accommodate before the experience degrades significantly.
Scalability testing refers to measuring how well our software scales. When we start developing software, it can be hard to predict how many users may need access to it in five years; scaling tests allow us to see just how far our applications will stretch before more extensive architectural changes may become necessary.
Endurance Testing
Endurance testing is similar to spike testing, except the spike is held over an extended period. The goal of endurance testing is to gauge how your system responds under prolonged high loads, such as, for instance, memory leakage that frequently surfaces after several hours or days of usage. Some applications may handle high spikes well, but over time, their performance could decrease; testing endurance may reveal flaws such as this, which needed to be apparent when spike testing only involved momentary spikes of requests being sent at one time.
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Volume Testing
Volume testing is another form of performance testing that can provide valuable information. We increase one or more resources an application uses during volume testing by increasing database entries or feeding an over-large file into it. Suppose any help can't handle such an increased load, and future volumes will increase accordingly. In that case, modification may occur, such as changing queries or altering how files are read from memory.
Read More: Automated vs. Manual Testing: Which Saves You More Time and Money?
Benefits Of Automating Performance Testing
Now that we understand the various types of performance testing let us explore their benefits. Companies perform performance testing to ensure their app provides an enjoyable user experience; specific reasons vary based on usage but should include applications with complex calculations, high usage spikes or large databases as a starting point. Companies want their application to remain enjoyable to use quickly while satisfying user issues as soon as possible if any arise. If performance issues are present, teams can work towards optimizing them quickly.
Although performance testing can be completed by manual testing, automated solutions offer many advantages for teams operating under a DevOps culture. Automation makes the unit more agile by quickly providing feedback about performance issues as they arise and running test scripts regularly - let's examine these benefits more deeply here.
Prevent Performance Relapse
Teams often become so focused on adding new features that they fail to recognize warning signs that an application's performance has gradually declined over time, ultimately reaching a tipping point where performance drops off sharply and dramatically, requiring many teams to switch into emergency response mode quickly to identify and address it; when this occurs end users become understandably upset.
Running regular performance tests is critical to mitigating such situations since these will inform the team if something seems amiss and needs investigation - potentially before end users notice. Automating performance tests is in the team's best interests since ensuring regular runs is critical for their success. With automated performance testing, tests run quickly and effortlessly; daily builds can incorporate them, and dashboards showing current levels can display them easily; all this would otherwise be virtually impossible when performing tests manually.
Improve User Experience
Performance plays an integral part in their software development process thanks to automated performance tests conducted by their team, which keep user experiences high or even improve them. By analyzing test results, team members can identify areas for further improvements that would enhance both user satisfaction and overall performance.
Avoid Launch Failures
Too frequently, new versions of an application are released only to have their performance decline dramatically and dissatisfy end users. Automation makes running tests and delaying a potentially disastrous release easy and lets teams confidently remove after solving performance issues; running them manually increases the odds they won't happen before release.
Eliminate Bottlenecks
Performance testing can aid developers in quickly pinpointing problematic code areas. For instance, REST API endpoints that respond slowly could create an unpleasant user experience for mobile app users; engineers then need to conduct further investigation to uncover its cause and implement fixes accordingly.
Avoid Manual Missteps
Manual performance testing can undoubtedly be carried out manually; however, automation offers several distinct advantages over its manual counterparts in avoiding human mistakes and mistakes due to human forgetfulness or mishandling steps during the execution of testing processes. If we automate, however, our test system will run the same way and perform your performance tests reliably every time.
Shift Performance Testing Left
Shifting left refers to performing testing early in the software development lifecycle, an increasingly popular concept among DevOps teams. Imagine your software development lifecycle as an anamorphic tree. Every feature goes through different steps, from gathering requirements to deployment into production. Consequently, when performance issues only surface in production environments, and end users perform performance testing, production becomes the test bed for our testing needs.
Shifting left means moving quality checks closer to production with unit tests, modern analysis techniques such as event storming, and automated security scans all becoming part of "shift left." Shifting left can also be accomplished via automated performance tests. Instead of waiting until production performance issues arise, our performance tests could run against our QA environment or developer computer and detect performance problems early.
Performance Testing Procedures
How to do performance testing? Before embarking on a performance testing team, testers must decide which metrics they want to evaluate based on the application software. Web applications often need response times of critical endpoints considered, while CPU or memory usage might also play a part. Furthermore, how users are expected to utilize an app determines its type.
After this initial testing phase, the tester must determine acceptable values for metrics. They could also choose an exploratory testing approach wherein the result of initial run tests will decide upon good matters; your team has agreed that response times need to increase by 20% after initial tests are run.
The team must then set up the capacity testing environment, install any necessary testing frameworks, write test cases and set frequency and trigger parameters; for instance, they could run daily tests before releases occur or just prior. Finally, teams must act upon test results. If performance begins to deteriorate, strategies must be devised to increase it and repeat and iterate on this cycle if they want the benefits we discussed earlier to reap their entire effect.
What To Look For In A Performance Testing Tool
There are automated performance testing tools available today, from general to more specialized solutions. Here are a few items to keep an eye out for when conducting performance analyses:
- Ascertain if the tool matches your requirements. A memory profiler cannot analyze web response times; you should narrow down your selection based on which aspect of an app and performance test you intend to run.
- Check whether the tool can fit seamlessly into your software development process. As previously noted, automated performance tests should be the goal. At the same time, devices requiring logins or clicking multiple links won't fit seamlessly into continuous integration flows.
- Many businesses place great significance on pricing, licensing and support issues when investing time into tools for pricing or licensing purposes. Before doing this, however, it's wise to identify all relevant requirements and seek approval from management before investing time or energy in them.
Conclusion
Performance testing is integral to modern applications focusing on scaling and user experience. After performing manual tests, it should follow naturally as part of a robust testing program. After running some manual tests, automated performance tests are the next logical step in testing processes.
Automated performance tests should be integrated into teams' daily workflow for maximum effect and benefit. About mobile applications, things may become more challenging as performance testing must include different devices, platforms, resolutions and network conditions in performance tests.
