What are the differences between testing monolithic and microservices architectures?

Testing is an essential part of any application in order to deliver high-quality solutions that match the needs of customers. On the other hand, testing might present a variety of issues depending on the application's architecture. I've seen organizations struggle with designing test cases and test scenarios based on the application's architecture throughout the years. Between monoliths vs. microservices, testing is easier in the case of monoliths architecture. While testing and debugging, there is only one codebase to go through and track. Comprehensive testing is always an issue when it comes to microservices architecture.

You should test each microservice individually, but you should also pay close attention to inter-microservice interaction testing. Business processes frequently pass through several microservices, and QA teams must account for all possible interactions.

Microservices also include a failure isolation cushion in the event of a failure. It's less probable that the entire application will fall down if several things go down. Monolithic applications, on the other hand, have several potential single points of failure.

How is testing different in Monolithic architecture?

A monolithic application is made up of a single code chunk that contains many application features. The disadvantage of this architecture is that it can sometimes expose a few of its APIs to third-party providers. When frequent upgrades aren't required, a monolithic design is ideal. Otherwise, scaling and reacting to requirement changes will increase the cost of development and testing by tenfolds.

How is testing different in Microservices architecture?

Microservices architecture is made up of a collection of separate apps that may be designed, deployed, tested, and delivered individually. Unlike testing in chunks, microservices allow us to design and test apps in pieces, allowing for a faster application delivery. Microservices expose APIs in the same way that monoliths do, but because monoliths contain all of the features together, API exposure can have an impact on the entire application. Microservices, on the other hand, may offer both public and private APIs for testing purposes. It may appear to be extra labour at first, but it saves money in the long run.

Testing: Microservices vs. Monoliths

During testing, these architectures behave in very different ways.

The developer writes unit testing to ensure that the generated feature's logic and functioning are correct. Both monolithic and microservices architectures require it. However, based on architectural changes, there is no difference in how unit testing should be done.

Integration testing is used to detect bugs that were missed during unit testing. In this testing type, the program is thoroughly checked for problems such as API misuse and threading concurrency. Integration testing is critical for monolithic architectures since it addresses API exposure issues. However, it's worth noting that getting the application ready for integration testing is usually not a difficult effort. Microservices architecture, on the other hand, typically necessitates separate build systems for each microservice that must be deployed and tested. As a result, the microservices architectural integration framework becomes significantly more difficult.

Contract testing is especially beneficial for the architecture because microservices share a few public and private APIs. The following is how it works: The API provider shares the contract with all of the API's users, and the provider ensures that the contract is being followed. Otherwise, the provider and the consumer will exchange several requests and responses. Contract testing is considerably more effective than integration testing at detecting API misuse.

Conclusion

As you may have noted, both architectures have their advantages and disadvantages. Microservices are better suited for scalability than monolithic design, which is better suited for basic, lightweight applications. Both have their own set of issues when it comes to testing, as previously said. Do you recall any particular difficulties you had while working on them? Please post them in the comments section below.