Why this combination you ask? Load testing is my passion, and I am partial to Kubernetes. I challenged myself to share a use case that many could relate to, focused on a business critical application. Websites came to mind and WordPress is the world’s most popular website management system. Of course, nginx is the most popular web server so let’s throw that into the mix. And Kubernetes? With more than 50% of corporations adopting Kubernetes in 2021, what better system to run in.

While Go provides a testing package and a go test command, the former only offers basic testing capabilities. The package also has some drawbacks, such as missing assertions and increasing repetition with large-scale tests. As a result, several Go testing frameworks have been created to augment it. Go testing frameworks consist of tools and resources for creating and designing tests. Some of these frameworks incorporate the testing package and go test command, while others take a different approach.

In my prior blog, Continuous Test Data Management for Microservices, Part 1, we offered an introduction to the key approaches for applying continuous test data management (TDM) to microservices. The continuous TDM process for microservices applications is similar to that for general continuous TDM (see figure below), but tailored to the nuances of the architecture. In this post, I’ll outline the key steps for applying TDM across the lifecycle.

In today’s blog post, I want to present something related to Icinga DB that you most likely will not come in touch with as a regular user: some of the test cases we built for Icinga DB and the tooling created to support them.

Grafana k6 is our open source tool to help you ship reliable applications by doing performance testing in a modern and developer-friendly way. Performance testing is still unknown to many, but it is not a new topic. In fact, performance testing courses are everywhere — even at colleges and universities. One of our passions is to educate others on the best practices of performance testing, working together with the Grafana k6 community.

In my previous blog posts on test data management (TDM), I have discussed principles for continuous TDM and outlined how TDM for microservices-based applications differs from traditional applications. In this blog post, the first in a two-part series, I will combine both of these concepts to discuss key approaches for applying continuous TDM to microservices. In my second post, I’ll detail the key steps for applying continuous TDM in various phases of the delivery lifecycle.

Software testing is important enough to have its own phase in the software development life cycle (SDLC). The software testing life cycle (STLC) is a step-by-step process that improves the quality of software by applying rigorous planning and analysis to the testing process. Testing is a development tool that adds value to your team’s applications. Embracing testing as a vital component of software development can save you and your team a lot of time debugging and fixing errors in the future.

Postman is a great tool for API testing during development. It’s GUI is simple to learn and ubiquitous. However, manually writing test cases for local development gets tedious fast if you have a lot of endpoints. Meticulously entering every detail for every use case takes forever. Also, if you get one HTTP Header or parameter wrong, it can take hours to diagnose. And even when it’s done, the API tests are almost immediately out of date because the API contract changes.

The software testing data provided by CI/CD tools is valuable, but it is not always comprehensive enough to give managers the insights they need to make improvements. To make effective business decisions, managers need visibility into the entire testing process, in a way that will help them understand what needs to be done and how.