This is the first part of a two-part blog post that is concerned with extracting data from Jira and using it for further applications such as visualization, evaluation, and using the power of machine learning to gain valuable insights in the data.

Integrating external services into an application is often challenging. Instead of doing the testing manually, the setup could be tested also automated. In case you are using Spring Boot, for a couple of services there exist an integration. This blog post will show how you can setup your Kafka tests to use an embedded Kafka server.

Storing dates in databases was traditionally done with java.sql.Date and java.sql.Timestamp. Since we would like to write modern applications, with Java 8 or 11, it is preferable to use an OffsetDateTime or a LocalDateTime. Spring Data JPA, for example, is mapping those fields automatically to the correct database field. There are still some challenges in combination with PostgreSQL.

Recently we achieved great maintainable API documentation with Spring REST Docs. Let's learn how Spring Auto REST Docs can make it even easier.

One of the goals I set for this year is to explore Machine Learning (ML), so after having done a couple of courses here and there, I decided to do a -rather simple- starting project, where I could deal with some of the basic stages of the ML: Get the data, prepare it, choose a model, train it, evaluate it, export it, and make the predictions available for use. For this first project, I chose: