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Alternatively, if there’s a requirement of a strategy very particular to your use case, you can always draw a custom graph with different peaks and valleys, and different measures, at different times. Baseline for establishing SLA, peak for managing heavy volumes, stress to find the number of boundaries that can be serviced with your defined SLA, and soak to identify any kind of hardware memory leaks. Overall, these are the most common load tests.
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The decrease in performance can indicate that the server code has some issues. Ideally, at the end of a test run, the server performance should be the same as it was at the beginning of the test. After running the load test for a few hours to a day, you can go in and see if there’s been any kind of increases in memory consumption. A soak load test involves a low number of users but is run for a long period of time – say 12 to 24 hours. From there, you can find out how high your concurrent user count was before the test broke.Įverything might work and everything might be configured well for a burst of heavy traffic, but is your system setup right for the long haul? Testing your system under such conditions is important, as there might be a memory issue that will get uncovered only when hit by traffic for a long duration of time. As the users get closer to the point that exceeds 300 milliseconds in response time, that’s where you would stop the test. In a stress test you’re going to ramp up the profile from no users to some undefined, unlimited amount. It can mean that errors start happening or that the server performance or response time is below the level that your SLA defines. The crash point does not necessarily mean that the server crashes or hangs.
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This number is also called a crash point. Stress testing means simulating a heavy load on the server to find the maximum number of users the server can handle. One question a lot of people ask when we’re talking about peak load tests: “Can I configure a load test that would add load to the point where the API breaks?” This type of scenario is called a stress test. Whereas if you ran it as a baseline test, you might see it crash immediately even though your system actually may have the capacity to withstand 10,000 users. The peak scenario is much more life-like, and it can give you piece of mind that your APIs can grow to service that many transactions. This is fundamentally different than the baseline scenario where, in the first second there’s no one – and then suddenly you have a stampede of 10,000 requests hammering down on your system. When you have thousands of people in the system, you gradually grow up to it. In LoadUI Pro, the peak scenario literally starts at zero, then the system simulates more and more usage, until it’s at peak throughput (10,000 users in this example). Yes, there’s a heavier load, but it involves a buildup. People do not get on the shopping sites all at once! In the morning, they gradually wake up and then go out shopping. They say, “I’m going to have a situation like the rush on Black Friday and I’m going to have 10,000 users, so let’s generate a baseline scenario with 10,000 users.” But that’s not what happens – even on Black Friday. But truth be told, this scenario often causes some confusion with testers. Simply put, peak testing is used to check how your server works during the busiest periods. You’ll be able to see real numbers and check how your server performs to determine an SLA. Using the baseline load test template, your test will help you determine what response is normal for the server. So, you can’t just say, “Under three seconds I think.” With the built-in baseline scenario in LoadUI, you’ll be able to calculate this exactly. It might cause a breach of contract and ruin a great relationship. If you’re an API provider and someone wants to interact with your API, they might say: “What’s the service-level-agreement (SLA) you’re willing to commit to?” Just coming up with a number in your head obviously isn’t the right approach here. Which begs the question … what type of test should I run? Let’s go over some of the most common types so you can successfully start your API performance testing journey. The templates highlight that performance testing is not a particular type of test, but a collective set of test types that provide information about how your API performs under different conditions.