In API testing you need to guarantee performance. Running a stress test is a worthy technique for determining the boundaries of the existing system. In this article, we will be learning three things that people should pay attention to while designing and running their load tests: the test environment, traffic patterns, and conditions. Before we go to things to look out for when stress testing, let's get the basic terms straight for making sure we are on the same page.
Stress Tests and API Tests
What's a stress test first of all? The stress testing procedure is a series of tests that assess how resilient a system is when it is stressed. This means for software that the server operating the product receives a large demand, twice the number of competitor users you normally expect.
For example, Stress tests are aimed at identifying breakpoints that do not operate as intended in the software. Things to look out for when stress testing may be further categorized into peak tests and soak tests, depending on the duration, ramp-up, and ramp-down time required for the number of viral users that impact the program.
So what's a test for the API? Well, postman API testing is a procedure that confirms that an API works according to expectations. In comparison with other software testing forms, such as the user interface and end-to-end testing, the API testing operates at the level of the API requests and does not involve an application front or client code. In other words, instead of user interactions, your test design utilizes raw HTTP requests.
3 Things to be Considered When Stress Testing Your API
Let us look at the three things to look out for when stress testing-
1. Test Environment
Any performance test can ask for a production environment, i.e. your live API or a test or staging environment expressly developed. Naturally, you may retain a different copy of your system and infrastructure while you work with your production environment. There is a high risk, though, that things will break during stress testing. After all, your program gets brought to its knees by the very objective of the stress test. It is important for your users who utilize it productively to evaluate the ramifications.
The apps utilizing your API should handle problems such as your API falling down, but you never know how effective their error handling is unless you've tested it, too. When you have certain use patterns, such as typically only having considerable traffic on weekdays, you may avoid this using scheduling. For example, by performing your tests on weekends. Ensure you set up dedicated test users in your production environment, remove or disable them after the test runs, and do not include them in business KPIs (they aren't actual customers!).
You must look at the data in this environment while setting up a specific test environment. A typical approach is to clone your production system so that you have a database of equal dimensions. If, however, you run the danger of genuine customer information leaking during a test (e.g. through larger logging or stress-opening security troughs), you run the risk of infringing the privacy of your customers and the data protection rules. A test environment containing unique test data that resembles production data but works best with no personal data, even if it takes extra effort to set up.
2. Traffic Patterns
You may always select to test individual API calls or a chain of API queries according to the usual API interactive patterns of your API users when you perform rest API testing. In a testing plan, both techniques are given their proper position. Functional tests of the API enable you to confirm that the right replies and error messages for input errors are returned by your API. The contract is for APIs. Not only should they, like all agreements, determine what will happen when things go wrong, but also what happens. Failure to handle is an API design component.
You may assess whether or not your API is also gracious in overload situations with stress testing. Therefore, make sure that your stress tests contain assertions about API replies and do not simply prove that you have a response. These tests are easy to create and let you find actions that function as a bootstrap to the entire program, which is the advantage of testing each request. We recommend starting with them when you perform your initial stress tests. If these errors already cause the API or infrastructure to fail, they might signal deeper issues.
To discover which of the most demanding activities your program can manage, you may compare alternative postman API testing. However, it does not always indicate that everything is well if you don't detect difficulties with simple endpoint testing. Computers are wonderful to accomplish the same multiple times because of caching. That is why traffic patterns should preferably be simulated. Typical scenarios for your API may be passed and the test can be designed.
For example, through high-consumption applications or public API documentation. Even better, your log files may be retrieved from the production, your real requests performed, common patterns identified, and your rest of API testing replayed. These demand chains give the most insight into possible breakdown points about things to look out for while stress testing in real users' workflows. A third technique, which has been slightly medium-sized, is the proportion of your logs and the grouping of your API endpoints. You may then do your stress test with similar ratios. Your system will not perform real workflows, but the overall request profile will be comparable.
3. Test Assertions
What does it mean that an API breaks down? Well, this conduct can have significant differences in insignificance. One well-defined error message in its OpenAPI description might be returned. Alternatively, API applications might remain open until a period of time is finished without receiving an answer. Your server can cease serving them and return a low-level TCP error or transmit an HTTP error like 502 Bad Gateway to your web server before the application. All these problems must be dealt with and reported by your testing.
Functional tests of the API enable you to confirm that the right replies and error messages for input errors are returned by your API. The contract is for APIs. Not only should they, like all agreements, determine what will happen when things go wrong, but also what happens. Failure to handle is an API design component. You may assess whether or not your API is also gracious in overload situations with stress testing. Therefore, make sure that your stress tests contain assertions about API replies and do not simply prove that you have a response.
If you start developing and performing stress tests, pay attention to your test environment and how it interacts with your production configuration. Review your traffic in order to ensure that you run realistic test scripts or understand simplification constraints. Finally, make sure you test your API response and be careful about the unexpected manner in which failures occur. You may then relax and rest certain that you know your API's strength!
Also read- Basics of API Testing