Service Virtualization Improves Applications Testing

Service Virtualization Improves Applications Testing

Anyone who is intended to develop the applications connecting to multiple microservices then creating a robust testing environment might not be easy. Let’s suppose one API you are validating is to a microservice your team developed then probably you must have devops capabilities, such as continuous integration and continuous delivery (CI/CD), infrastructure as code, and tools in order to create test data sets to enable a testing environment for this service. Well, even with these capabilities, there is a possibility that it can become costly to spin up multiple testing services when teams develop many cloud-native applications and microservices.

Service and API virtualization platforms are addressing these complexities as they create and simulate API and service endpoints. The service virtualization platform serves as the endpoints for testing downstream applications and composite services rather than spinning up a testing environment. Moreover, it also responds to a connecting application’s or service’s requests and transactions.

Service Virtualization Improves Applications Testing

For reader’s information, service virtualization emulate the behavior of specific components in heterogeneous component-based applications like API-driven applications, cloud-based applications and service-oriented architectures. With the help of service virtualization, the software development and QA/testing teams can get access to dependent system components that are needed to exercise an application that is passing under test.

Following are the highlighted benefits of service virtualization:

  1. Service virtualization is a natural extension of developing unit tests and instituting continuous testing for microservices. As part of the development process, developers or quality assurance engineers should configure endpoints in the service virtualization platform that simulate the API’s responses. All the developers can use these endpoints when building downstream apps and services.
  2. Service virtualizations can be bundled with test data sets and used to validate transactions. Once developers complete a testing scenario, they can refresh the endpoint back to the original test data set and repeat the testing as needed.
  3. When operating on a cloud, service virtualization platforms can ramp up and down capacity based on testing volume. As a result, the infrastructure can scale to handle many developers running simultaneous tests or more robust performance testing.

You might also be interested in: Marketing Strategies for Software Development Companies

Newsletter sign up