Organizations at some stage of their journey switch to a microservices architecture, which is a collection of self-contained and autonomous services that help execute a business capability, from a monolithic architecture to derive key business benefits.
In a microservices architecture, an entire codebase doesn’t have to be rewritten to add or modify an application feature. Organizations thus reduce time-to-market for their applications and products. Debugging and testing applications are simpler too, and it helps organizations significantly improve their rate of delivering error-free applications.
However, with microservices, testing is not straightforward.
For starters, each independent service is communicating with other services in multiple and often unexpected ways. Dependency is one of the challenges: while each microservice must function on its own, it’s not uncommon for one part of the system to access data managed by another (known as data sharing). New dependencies emerge as new features are added. A microservices architecture must be able to handle potential issues (database errors, network congestion and latency, service unavailability, to name a few) with increase in the number of services.
To test microservices, software testing companies must be aware of not only an isolated service but also its dependencies and build their test strategy accordingly.
AI-enabled test automation of microservices helps create reliable tests, thereby reducing the time for test creation, analysis and maintenance. The tests help check inter-service communication, test communication pathways and more.
The following strategies could be employed to test microservices:
An effective test automation process requires automating at three levels namely unit, service and user interface (UI).
However, with microservices, testers must not only be cognizant of the service they test but also its dependencies. Also, due to the granular nature of microservices, boundaries at different levels must be tested, too: unit, component and integration.
It helps validate the code of application components to ensure they comply with the business logic.
This is usually the stage where the largest number of individual test units are processed and is especially vital in microservices testing.
For effective and accurate microservices testing, it’s essential to limit to small test units. Large units could result in randomly complex tests as the services maximize resource consumption with time.
Open-source xUnit testing frameworks or VCR recording code functionality could be utilized to perform unit testing.
For microservices architectures, integration testing is conducted to verify the communication between subsystems that interact with external components such as data stores and other services.
Since microservices communicate and execute together to complete a business goal, tests must examine requests flowing through the services to ensure communication channels function as intended.
Test automation suites such as Katalon Studio or open-source Selenium could be used to run integration tests.
As the name suggests, this type of testing is employed to test a component or the services of an application. The test checks microservices by forming mock services that resemble the deployed services.
It helps validate the communication between distributed services and their dependencies such as a database and third-party components.
Component testing can be performed with the help of Hoverfly and similar API simulators.
It’s a test strategy that helps validate if two separate systems (two microservices, in this case) are compatible with each other.
The interactions between the services are stored in a contract which is verified to ensure both parties comply with it.
RAML, OpenAPI and API Blueprint are some of the tools that automatically create documentation when an API is defined against a recognized standard.
End-to-end testing of microservices helps validate the entire system’s ability to meet business goals irrespective of the component architecture that’s in use. Testers use this type of testing to verify the accuracy of the message moving between the services.
The following strategies could be employed when writing an end-to-end test suit:
Martin Fowler, an international public speaker on software development, says: “End-to-end test may also have to account for asynchrony in the system whether in the GUI (Graphical User Interface) or due to asynchronous backend process between the services.”
Java’s JBehave and similar frameworks could be deployed to automate functional testing by using user stories to verify if the system behaves as intended.
Abovementioned are the tests (unit, integration, component, contract and end-to-end) conducted on microservices to ensure the entire system functions as it’s meant to. Test automation of microservices may not remove issues associated with software testing but it certainly helps expedite the software testing process while making it efficient and smarter too.
By Uma Raj
By Uma Raj
By Abishek Balakumar
Suhith Kumar is a digital marketer working with Indium Software. Suhith writes and is an active participant in conversations on technology. When he’s not writing, he’s exploring the latest developments in the tech world.