No Code API automation – API Monkey

Why did we build APIMonkey?

APIMonkey was built from our own pain points when we were  building rest API’s for some of the applications. In our team, the developer will create the API’s and will create the mock test or integration tests. Nice. How about non technical users? For a non-technical user, how will they test the API’s? How will business users verify if the API works as expected? For starters, they can use Postman or Insomnia, add the APIs and add the test data. Click run and you can see the results. Great!!

Well how do you share your test cases and test results with team members?

Postman offers a free team account for upto 3 users which could have solved our problem at least.

Well how do you make sure after every build, your api’s are not broken and are working as expected? Run the tests in postman. Correct but someone needs to click the button. 

Well there are postman automation scripts. But this means my non tech users have to learn how to script it. And then I am tied too closely to postman for life since all my automation is based around it. 

Another alternative we considered was to create automated test cases for the APis using Karate or Cucumber. 

Advantages

  1. Flexibility 
  2. Dev/tester knows the data structure and combination 

Disadvantages

  1. Test automation frameworks are developer centric which means developer/test engineer has to write and maintain the test cases and data
  1. Code need to be written for functional and negative test cases
  2. Developer has to create the mock test data
  3. Configure these test cases to run on jenkins or some other build server
  4. Pick a reporting framework to display reporting results 
  5. Maintenance

We went through the exercise with a few of the projects and I can tell you, it was not fun. And since test engineers and developers were writing the test cases and maintaining it, our business users never actually could feel 100% confident of what these were doing. They still wanted to test the APIs manually after every release. 

This led me to start thinking, what if you could create the test data and run the tests by pointing to the API’s docs and not depend on the developer or test engineer to create the data?

What if a non-tech user can manage the tests data?

Why can’t we run the tests on the cloud on a continuous basis?

And this gave birth to the APIMonkey.

APIMonkey is a self service, no code, API automation testing platform

The goal is to build a self service, no-coding, web based platform, on the cloud. The end user can be a non programmer who can point to the API docs a.k.a swagger/openAPI ,and expect the test cases to be created. 

There should be no need for an qa test engineer to write the test.

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