There is now constant pressure on technologies to adopt and align themselves to the changing needs of the business environment. Modern day engineering demands greater scalability, cross-platform capabilities, and faster deliveries. Hence the need for a software architecture that is flexible and that helps in creating systems that are more scalable, more resilient, flexible and can facilitate faster development.Unlike monolithic services architectures, Microservices architecture helps organizations create decoupled and independent processes and services that are easier to deploy and manage. The aim is not have inter-modular dependencies. Hence faster releases are facilitated by separating the application in smaller components that can be composed easily, and independently. The application developed using microservices architecture thus, is the sum of these individual components that communicate freely with one another and deliver greater functionality. Since the application components are independent of one another it makes them independently deployable and testable as well. However, designing a testing strategy for Microservices can be challenging. It demands the right use of tools, technologies, and frameworks to provide support to every testing layer. The independent micro-units must be thoroughly tested before integration with the larger application or application ecosystem. Otherwise, the cost of correction post integration can be huge.
Challenges in Microservices testing
Given that microservices development is distributed and independent in nature, testing strategies that applied to monolithic architectures cannot apply here. Microservices applications have to deliver on high performance and functionality, which demands that each layer of the application is thoroughly tested. Some of the challenges faced during microservices testing are:
- Inclination to use Web API testing tools that are typically built around SOA testing
- Timely availability of all services for testing since these services are developed by different teams
- Since the services are expected to be independent of one another despite being a part of an interconnected structure it becomes essential to test each component individually and also as a complete system
- Dependencies on other services for data and layered interactions, makes end to end flows challenging to accomplish
- Guarantee of a dedicated test environment can be a challenge as the development process is agile and not integrated. Also the development of each microservice might proceed on separate timelines. Hence deploying a system that is testable end-to-end might not always be possible.
- Complicated extraction of logs during testing and data
To overcome the challenges in Microservices testing and in automating that testing, it helps to adopt a bottom-up approach to testing as depicted in Mike Cohn’s Testing Pyramid. This approach also helps in identifying how much automation effort needs to be factored in at each stage of the testing process.
Since unit tests are larger in volume and number and internal to the service, they render themselves well to automation testing. Unit testing in microservices has to check the module behaviors by observing their interactions between objects and their dependencies and also has to observe the change in their state. The testing approach demands an amalgamation of solitary unit testing and sociable unit testing. At the same time, it is imperative to ascertain that testing of the behavior under test does not constrain the implementation. This can be achieved by constantly questioning the value a unit test provides in comparison to the maintenance costs or the number of implementation constraints.
The microservices architecture depends heavily on the communication between service components. Hence it is essential to check the communication while the internal implementation of services remains independent. The API’s and interfaces remain consistent as well. Since API’s can be subject to change when the service is exposed, it becomes key to define a contract for the API. By automating contract testing, testing teams can check if the agreed contract is well preserved and that the input and output of service calls meet the contract expectation.
Integration testing in microservices checks the several communication paths and the service components and assesses if the modules under test collaborate as intended. For integration tests, the aim is to closely test the behavior of the unit being tested and not the entire subsystem. While automating testing for integration tests, it is essential to write the tests for the modules that interact with external components to ascertain that the module can communicate clearly with those external components. Gateway integration tests and persistence integration tests provide fast feedbacks by assessing the correctness of logic by assessing the logic regressions and identifying breakage between external components.
End-to-end testing comes at the top of the testing pyramid with the intent of verifying that the whole system meets the external requirements and the business goals. End-to-End tests are essential to check that all the moving parts within the microservices architecture work as intended. This stage must verify if there are any gaps between services, assess the correctness of the system by observing state changes, and see how the integrated system functions.
We should add this point as this is very relevant in this context. Especially when you are testing end-to-end system and some microservices are not ready, how would you test the system? Service virtualization is used in such circumstances.
Along with this, testing teams also can look at automating UI and Functional testing to ensure that all interfaces, databases, third-party, as well as internal sources, can work seamlessly and in a cohesive manner with one another. Given the scope of automation testing in microservices, testers can also leverage scriptless test automation to simplify the automation process and get the test automation ball rolling faster to test each component with greater precision to deliver a thoroughly tested and superior microservices product.