A beginner’s guide to microservice testing

Picture this: 2 a.m., and we’re still in the office. The deployment was supposed to go out at midnight, but our tests had other plans.

My team and I saw several of our integration tests that run across several microservices failing, and we were constantly refreshing the dashboard waiting for our numbers to turn green.

We had broken our monolith into microservices to move faster, yet here we were, moving at the speed of a turtle (don’t judge, I love them, especially if they’re mutants and eat pizza), all because our testing strategy hadn’t caught up.

As Eric Evans (the creator of domain-driven design) observed: “Teams adopting microservices inadvertently end up enforcing clear boundaries and domain focus”—perhaps the most successful application of DDD’s principles.

However, those same boundaries mean we must rigorously test the seams between services to avoid nasty surprises in production. In fact, without a solid testing plan, you might even regret breaking up the monolith in the first place.

Let’s dive into microservice testing.

Microservice testing vs. other types of testing

Testing microservices is a whole different game compared to testing a traditional monolithic application. Monolithic testing tends to be straightforward in scope, simply because you’re testing one big integrated system.

You might write a bunch of unit tests for internal code and a suite of end-to-end tests that drive the UI or API, and that covers the bases. In a monolith, all components run in one process or server, so integration issues are limited to within that single application. When something breaks, you run the whole app’s test suite as one unit.

Testing microservices is a whole different game compared to testing a traditional monolithic application.

In contrast, microservice testing means dealing with many independent pieces. Each microservice has its own mini-application, modules, and exposed API. You have to test each service in isolation and ensure it plays nicely with others. Simply running a few end-to-end tests on the entire system isn’t enough. Instead, you need to write a mix of tests at different levels.

With microservices, you need to test the inter-service interactions. For example, you might test that Service A gives the expected response after it calls Service B, which might require simulating or orchestrating multiple services.

This is where contract testing comes in. Unlike traditional tests, microservice tests often verify that the contracts or interfaces between services match up on both sides. In a monolith, internal modules might just call each other and you’d catch integration issues with simple unit tests.

You can already see that microservice testing puts a focus on API-level tests and integration tests.

Types of microservice testing

Now, let me go through the types of testing you could use, the ones I wish I knew about when I started my journey. When testing microservices, we generally talk about several layers or types of tests, each targeting a different scope, so let’s explore the ones I’m referring to.

1. Unit testing

This is the foundation. Unit tests cover the smallest pieces of functionality in a microservice. These tests are fast and isolated, meaning they don’t touch databases, networks, or other services.

For example, if you have a user service, a unit test might verify that the password encryption function works correctly in isolation. Unit tests give you quick feedback and can tell where a problem is in the code.

2. Integration testing

Integration tests check that different parts of the system work together properly. In a microservices context, this often means spinning up a couple of services together to see if they interact as expected.

For instance, you might run Service A and a test instance of Service B and validate that A’s requests to B succeed. Integration tests are slower and heavier than unit tests, but they catch issues that unit tests can’t, and they’re needed.

When testing microservices, we generally talk about several layers or types of tests, each targeting a different scope, so let’s explore the ones I’m referring to.

3. Contract testing

Contract tests focus specifically on the promises that services make to each other, known as the “contract” of an API. In microservices, each service might be both a provider and a consumer. A contract test ensures that if Service A expects Service B to return data in a certain format, B actually returns it as expected.

It’s like checking that two puzzle pieces fit together correctly. Contract tests are especially useful when services are developed by different teams, and they prevent the classic “my service didn’t know you changed that field name” scenario.

This helps to avoid breaking backward compatibility after every release, which I wish I had known about after a time we removed a field without knowing others were still using it.

4. End-to-end Testing

End-to-end (E2E) tests validate the entire system flow, from the user’s perspective or from the perspective of a client calling through several services. In these tests, you have multiple microservices running in a test environment, and you simulate real scenarios.

For example, an E2E test might invoke a REST API on the front-end service of your application and then confirm that a complex transaction works. End-to-end tests are the safety net that everything is wired together correctly—or at least they should aim for that.

Now that we have explored the types of testing, let’s see how you can test microservices.

How to perform microservice testing

Now that we know the what and why, let’s talk about the how. How do you actually test microservices in practice? It helps to break it into a few pieces: setting up the right environment, using the right tools, and integrating tests into your development process.

1. Test environment setup

To test microservices effectively, you need to be able to bring up the necessary services on demand. Containerization is your friend here. Many teams use Docker or Kubernetes to spin up microservices in a test environment that mirrors production on a smaller scale.

For example, if your app consists of five microservices, you might use a Docker Compose file to launch all five (or as many as needed for a given test) with one command. Additionally, each service might need seed data or config tweaks for testing (like pointing to a test database, or using an in-memory queue instead of a real one).

Managing test environments can get complex, but automation and infrastructure-as-code will help you maintain consistency.

2. Tools and techniques

For unit testing, you’ll use the usual suspects (JUnit, pytest, NUnit, etc., depending on your language) within each service’s codebase. For integration testing, frameworks like Spring Boot’s test slices or testcontainers are incredibly handy.

When it comes to contract testing, tools like Pact or OpenAPI/Swagger schemas are commonly used to define and verify contracts. Additionally, Tricentis Tosca (for API and UI test automation) and its API Simulation feature can help create realistic mocks of microservices (so you can test Service A without needing Service B running).

For end-to-end testing, you might use Selenium or Cypress for UI-driven flows, or write API-level smoke tests that call through the system’s entry points.

3. Process and automation

A common approach for automation is to have a pipeline that runs unit tests on each commit, then perhaps runs contract tests and some integration tests in an integration environment. You might have nightly or on-demand jobs that spin up a full set of microservices in a staging environment to run the heavier end-to-end and performance tests.

The deployment pipeline can promote a build to production only after it passes all required tests. This gating is crucial for microservices because changes are frequent and can impact other services unexpectedly.

All of this might sound daunting, but with each service carrying its own suite of tests and a well-orchestrated pipeline, testing becomes just another part of the development process.

Best practices for microservice testing

Let me share a quick example that taught me the value of microservice testing best practices. A few years ago, I joined a company in the middle of a microservices transformation. They had eagerly broken the monolith into about 20 microservices.

But when it came to testing?

The strategy hadn’t evolved, and they were relying almost entirely on a giant integration test suite that spun up every service and ran through end-to-end scenarios. It worked… at first. With only a few services, running all the tests for each change was manageable.

But deployments started getting delayed because a single-line change in Service X meant running the full test suite to make sure nothing else broke. It became a deployment bottleneck and a source of team frustration.

We knew we had to fix our approach. We stepped back and essentially redesigned our testing strategy. The lessons we learned were in line with using a balanced, layered testing strategy. So, here are some key best practices from that experience and others I’ve had:

• Build a test pyramid: Favor a higher number of small, fast tests and fewer broad, slow tests. This helps you to have quick feedback and keeps maintenance manageable.
• Test services in isolation: Don’t wait to test a service until the whole system is up. Use mocks, stubs, or service virtualization to test a service’s logic with its dependencies simulated. This decouples teams and allows testing to happen earlier and more often.
• Automate in CI/CD: Make tests run automatically on every code change. Set up your CI pipeline to run the relevant service’s tests on commit.
• Keep tests independent and reliable: Each microservice’s test suite should be self-contained. If a test depends on an external service or data, it should use a controlled substitute or dataset.
• Monitor and adapt: Treat your test suite as a living thing. Monitor how often tests fail and why. If an end-to-end test is flaky or too slow, consider replacing it with more granular tests or improving its stability.

By following these practices, you’ll find that microservice testing becomes far more manageable.

The goal is confidence: confidence that each microservice does what it should, and that the whole system works together as intended.

Conclusion

Microservice testing can seem intimidating at first because there are a lot of moving pieces and new concepts to juggle. But with the right approach, it becomes an achievable part of delivering quality software.

Remember that the goal is confidence: confidence that each microservice does what it should, and that the whole system works together as intended.

For those starting out, my advice is to begin small. Pick one microservice and improve its tests. Introduce a contract test for one integration point. Gradually build up your practice and expand it to other services.

Microservice architecture often goes hand-in-hand with faster development and deployment cycles, so testing has to keep up. And as you refine your strategy, you’ll likely find your own team’s “story” of growth, much like the one I shared.

If you want to learn more, there are plenty of resources and tools to support you. The Tricentis Learn section and product documentation offer deeper dives into topics like API testing and performance testing for microservices.

The journey to effective microservice testing is iterative, but with the fundamentals and best practices we’ve discussed, you’re well on your way to getting better at microservice testing and deploying with confidence.

This post was written by David Snatch. David is a cloud architect focused on implementing secure continuous delivery pipelines using Terraform, Kubernetes, and any other awesome tech that helps customers deliver results.