This week’s post is the third and final in my series about running tests on Kubernetes for each pull request. In the first post, I described the app and how to test locally using Testcontainers and in a GitHub workflow. The second post focused on setting up the target environment and running end-to-end tests on Kubernetes. I concluded the latter by mentioning a significant quandary. Creating a dedicated cluster for each workflow significantly impacts the time it takes to run.

Imagine an organization with the following practices: Commits code on GitHubRuns its CI/CD pipelines with GitHub ActionsRuns its production workload on KubernetesUses Google Cloud A new engineer manager arrives and asks for the following: On every PR, run integration tests in a Kubernetes cluster similar to the production one. It sounds reasonable.

The subject of testing is vast. It may seem simple from outside, but it’s not. For example, one may define testing as checking that the software is fit for its purpose. But it encompasses a lot more: for example, mutation testing verifies that assertions do actually assert. In this post, I’d like to touch some testing flavors, what’s their purpose and how they compare to each other. The need for testing In an ideal world, we wouldn’t need testing.

I have devoted a significant portion of my time thinking about designing and writing tests of all kinds. I believe my perspective can bring something to the table. In the rest of this post, I’ll follow the terminology proposed in the article.

Most of our day-to-day job is learned through mentorship and experience and not based upon scientific research. Once a dogma has permeated a significant minority of practitioners, it becomes very hard to challenge it. Yet, in this post, I’ll attempt to not only challenge that sometimes tests must be ordered but prove that in different use-cases.

Object-Oriented Programming advocates for modularization in order to build small and reusable components. There are however other reasons for this. In the case of the Spring framework, modularization enables Integration Testing, the ability to test the system or parts of it, including assembly configuration. Why is it so important to test the system assembled with the final configuration? Let’s take a simple example, the making of a car.

My job as a software architect is to make sure the builds I provide have the best possible quality, and more specifically internal quality. While Unit Testing sure helps creating less regressions, relying only on it is akin to testing a car by testing its nuts and bolts. Integration Testing is about getting the car on a circuit. Last week, I finally released the fist version of Integration Testing from the Trenches.

Even the most extreme Spring opponents have to admit it is all about making developers life easier. Version 3.2 of Spring MVC brings even more sweetness to the table. Sweetness #1: No web.xml The ability to run a webapp without any web deployment descriptor comes from Servlet 3.0. One option would be to annotate your servlet with the @WebServlet annotation to set mapping and complementary data.

In most contexts, when something doesn’t work, you just Google the error and you’re basically done. One good thing about working for organizations that lag behind technology-wise is that it generally is more challenging and you’re bound to be creative. Me, I’m stuck on JBoss 5.1 EAP, but that doesn’t stop me for trying to use modern approach in software engineering.