Software

Tests are an essential part of any codebase. At a minimum, they help prevent regressions as the code evolves. But not all tests are created equal: unit, integration, component, contract, and end-to-end tests each serve a distinct purpose.

This article outlines a practical testing strategy for Java Spring Boot microservices, covering the role, scope, and tooling for each test type to help you get the most value from your test suite.

Component tests check full use cases from start to finish. They’re essential for verifying and documenting how an application or service behaves overall. But they can be expensive, especially in terms of setup and execution time, which is why it’s important to define their scope carefully.

That said, I’ve often found them cost-effective in distributed architectures. They’re usually simple to set up, since you can reuse the service’s external API without needing extras like fake servers. And since each microservice tends to have a narrow focus, you can test its behavior thoroughly in isolation.

This article explores how to make component tests more robust, with one key idea: keep them independent of implementation details.

In a microservices architecture, many things can go wrong: middleware can fail, the network may be unstable, or the service you’re calling might be down. In this uncertain environment, anticipating failures is crucial to prevent breaking the entire chain and delivering errors to the end-user, when you could instead offer a partially degraded experience.

This article explains how to implement the circuit breaker pattern using Hystrix, Feign Client, and Spring Boot.

I often come across code snippets like this:

public class Day {
  public void start(Weather weather) {
    switch(weather) {
      case RAINY:
          takeAnUmbrella();
          break;
      case SUNNY:
          takeAHat();
          break;
      case STORMY:
          stayHome();
          break;
      default:
          doNothing();
          break;
    }
  }
}

Here, a specific action depends on the weather. This kind of code is both difficult to test and maintain. In this short article, I’ll show how to refactor it using a Map.