Your API needs to perform under real-world conditions – this makes API performance testing an essential part of your QA process. What is API Performance Testing and why is it important? API performance testing is the process of measuring and assessing the performance of an API under simulated usage conditions that accurately represent the real world both in the content of the transaction and in stress. We can differentiate between two types of API performance testing: load and stress testing. The first type refers to the process of putting demand on the API in order to see its behavior under normal versus peak load conditions. Stress testing involves going beyond the limits of normal operations over a period of time, in order to determine the robustness of the API and identify what conditions cause its performance to deteriorate. APIs work behind the scenes, at the product's logic layer, and have to respond quickly to the ebb and flow of requests and utilization of information. There are many variables that impact how an API performs. The fact that your API works well in the morning, doesn't mean it will do so in the afternoon when usage traffic rises or the type of traffic and transactions shift. The goal of API performance testing is to identify potential bottlenecks not only in load but transaction mix for your product's performance such that corrective action can be taken to eliminate the problems before the users have a "bad" experience. API Performance Testing Challenges A critical part of API performance testing is establishing the test scenarios so that they match as close as possible the real-world conditions under which the product will be used. For a product that hasn't been released, but is only in Alpha or Beta testing, defining real-world conditions is a real challenge that requires insight and knowledge of your target market, launch plans, etc.. Below are some guidelines and best practices that can be employed to model API performance testing scenarios. \tCall the API from different modules in your software, so simulate that to the extent that you can via the different call types and parameters. \tCheck the API response to different modules and then if the response will be used for further action, so be sure to incorporate validation of that response. \tCheck that the API responds to invalid calls correctly either with an error message or valid expected behavior. \tCheck that the API can handle being called simultaneously by different modules under load. \tVary the load under all these conditions above to create your own performance matrix both for sustained load and peak load. The other major element of API performance testing is fine-tuning your load. This is where API performance testing is most useful because you want to test performance during development and BEFORE it goes live to see where you've got potential problems. To do this, you'll have to determine common user stories or use cases and then estimate your transaction mix via estimates of # of concurrent users, frequency of use, time of day usage, relative usage of various features/functions, etc. You may want to verify your assumptions with other parts of the organization or get usage statistics from your dev-ops team. If you need assistance conquering and addressing your API performance testing challenges, our dedicated team of experts at XBOSoft are here to help! To get started, please contact us today. Thanks!