API Virtualization for Robust Testing

Testing is an essential part of software development. It’s similarly an important part of the API lifecycle and it helps developers discover errors in their APIs before it even gets to production. One of the most effective methods to test production-grade APIs is through API virtualization.

In this article, I’ll briefly explain the concept of API virtualization and how to include it in your API testing plans. 

What is API Virtualization?

API virtualization is the process of using a tool that creates an exact copy of your production API with all of its specifications for testing purposes. This is useful because it saves you from manually mimicking your production API.It allows software development teams to create copies of their production API virtually and test various endpoints even when the API is still being developed.

In many cases production APIs are connected to data sources that you wouldn’t want tests to alter. For example, imagine removing an object from a user account—the user might notice that it’s missing. However, API virtualization can replay real calls against a production API, with the actual response data and status codes of the original request.

API virtualization makes it easier to produce and automate your tests, which encourages frequent testing of APIs since it is now easy to create an exact copy of a production API.

Differences Between API Virtualization and API Mocking

At first glance, API virtualization sounds like mock API servers. API mocking creates an imitation of the components of an API for developers to execute real-life scenarios. Like virtualization, you can use mock servers for testing, but they can’t test all of the same things. 

API mocking can only allow developers to imitate very specific functions and behaviors. All of these need to be predetermined and built into your mock interface. While mock servers can be generated from OpenAPI and other description formats, you are still constrained by expected requests and responses. Often, the data within responses is faked, so it does not provide a complete test.

API virtualization, on the other hand, helps developers with all their development intent and test cases. Because virtualization replays production requests, you can include calls outside the documented usage of the API. The responses will be realistic in size and content, because they came from real requests. 

Best Practices for API Virtualization Testing

API virtualization can make a positive impact to your software development cycle when done right. Consider these best practices for teams looking to adopt virtualization testing:

  • Use real-world data: This will ensure that you get accurate responses for various test cases, and sets it apart from simpler mocks.
  • Simulate various network conditions and server capacity: Test various network conditions and server capacity, so you know how your application would respond in these scenarios.
  • Don’t test on live APIs: Virtual APIs are based on your production API, but are intentionally not your live API. Don’t mistake virtualization for real-time API monitoring.
  • Provide broad test cases: Include typical and unexpected requests to ensure you know how your application will respond in various conditions and you will be able to catch any errors before users discover them.

API virtualization will provide your team with more robust testing. It also saves the manual effort of writing mocks and gives developers the flexibility and power to make use of APIs that mimic the production specification. Once you have adopted virtualization, you can work automated testing into each API release.

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