TEST THE RISK!

Automated tests for API and services are very important so there are lots of solutions for API test automation in the market. These solutions can be commercial-off-the-shelf (COT) or opensource libraries also, there are many frameworks created around these opensource libraries. Testing APIs with tools that have IDE can be easy to start and learn but it can be challenging to customize for your unique problems or integration to CI/CD tools can be hard. Therefore I can suggest you use one of the opensource libraries by implementing it with your favorite language. In this way, it can run faster,  easily extendable, and configurable.  I have created a framework with Airborne and Rspec for automating API tests, you can  check it from Github .  In this post, I want to explain what is Airborne and how I implemented a framework around it. You can simply update the environment variables and write your specs file in the ` specs ` folder.  What is API Testing API stan

Postman seems to become a defacto tool for service testing because the Postman is very user-friendly, easy-to-learn, all-in-one, lightweight and collaborating tool. Postman has been used for a long time but recently it has growing popularity because of a stable native application, collaboration feature after version 6.2, sharing of collections for team, interactive working with the team, mocks for isolated testing, environments for running the test for different test environments such as local, development, stage ... and many more features. For me, one of the biggest features is easy-to-use for everyone in a team so everyone in a team can use and update a postman collection easily. In this post, I want to explain how postman can be used efficiently. Testing a Service and Writing Tests With postman testing service is simple. Postman supports many methods like POST , GET , PUT , PATCH . Just select the correct method and hit the service URL you want to test. Postman also has everyth

When a software comes to production the weakest points are mostly related to performance of the application. The reason is that most of the organization test the application functionally by testers and on acceptance testing period again the applications is under testing to check functional requirements. The missing point is non-functional testing like performance of the application.  Another failure point is testing the performance as the last level of development process. This means that any misleading failures in the service level can cause a very big problem on production stage so it requires extra source if possible and extra budget. As the terminology says "finding the big issue earlier stage of the development can reduce the fixing effort exponentially " . Therefore test the performance of the software output whenever it is ready, this could be an api end point, a function servers data to system, a web servers, and etc.  Another failure is related to technolo