Assume a new developer or test engineer is added to your team. You develop an application with obviously some kind of database and you want them to get up to speed as soon as possible. You could ask them to install the application and database themselves or you could support them with it, but this would cause a lot of effort. What if you handed them over a simple YAML file which would get them up to speed in a few minutes? In this post we will explore some of the capabilities of Docker Compose in order to accomplish this.
In the first part of this post, we explained the Performance Diagnostic Methodology (PDM) and how to use it. But, the proof of the pudding is in the eating and therefore it is now time to apply the methodology. Of course, the best proof would be to apply the methodology to a real world performance issue, but instead of waiting for that, we will try to simulate some performance issues and verify whether the methodology can work.
Last June I saw an interesting conference talk at J-Spring given by Martijn Verburg (from jClarity) about the Performance Diagnostic Methodology (PDM), a structured approach in order to find the root cause of Java performance problems. In this post I will try to highlight the key concepts but I do recommend watching a recording of the talk from Devoxx UK. In the next part of this post, we will try to apply the theory to some problem applications.
This week, we will take a look at Red Hat Container Development Kit (CDK). CDK provides a pre-built Container Development Environment based on Red Hat Enterprise Linux to help you develop container-based applications quickly. We will install CDK on a Windows machine and deploy our mykubernetesplanet Docker image from our last post to the Kubernetes cluster.
On Thursday the 31st of May I went to the J-Spring conference at Utrecht, the Netherlands. J-Spring is the largest one day Java conference in the Netherlands in the spring organised by the NLJUG (Dutch Java User Group). The title of the event might be a bit misleading as you may think that it is only about Pivotal’s Spring, but it is more than that. In this post I want to share my experiences that day.
In part 1 of this post, we learned how to create a Spring Boot application, create a Docker image for it and push it to a Docker registry. At the end, we installed Minikube in an Ubuntu VM. In this second part, we will get familiar with some Kubernetes terminology, deploy the application to our Minikube cluster and update the application. The sources used for the application can be found at GitHub. The Docker registry which we use can be found here (or you can use your own Docker registry).
In this post we will take a look how we can build a Spring Boot application, create the Docker image, deploy it to a Docker registry and deploy it to a Kubernetes cluster. This will give us the opportunity to get acquainted with the basics from building an application up to deploying it to Kubernetes. Sources can be found at GitHub.