One of the most well-known problems when it comes to testing applications is the amount of time required by all test suites. Integration tests, in particular, are usually very slow to execute and depending on the type of application, several minutes (or even hours in extreme cases) are needed in order to get the final execution result. You can reduce the test execution time with several techniques, but one of the most effective methods is running your tests in parallel.

What is the bare minimum you need to build, test and run your Java application in Docker container? The recipe: Create a separate Docker image for each step and optimize the way you are running it. I started working with Java in 1998, and for a long time, it was my main programming language. It was a long love–hate relationship. During my work career, I wrote a lot of code in Java. Despite that fact, I don’t think Java is usually the right choice for microservices.

At Codefresh we are all about collaboration and reusing existing standards instead of implementing proprietary solutions. A Codefresh pipeline is based on a series of Docker containers that act as individual steps. All Codefresh plugins are also just Docker images which means that extending a Codefresh pipeline is the same thing as writing a Dockerfile. Github has recently announced an integrated automation solution called Actions.