Do you want to experiment with Jenkins CI in a local setup? In this post we will setup a local Jenkins CI server, create a build job for a simple Spring Boot Maven project and push the created Docker image to DockerHub. It will be a setup for local experimenting only, but really handy if you want to try out a Jenkins plugin for example.
You are using Docker for development and testing purposes but did not yet take the step to use it in production? Then read on, because in this blog post we will take a look at how you can ensure that you run your Docker containers in a secure way.
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.
Although Git is well known as Version Control System nowadays, the usage of Git LFS (Large File Storage) is often unknown to Git users. In this post I will try to explain why and when Git LFS should be used and how to use it. The source code of this post can be found at GitHub.
In part 1 of this post we explained how we can create a Helm Chart for our application and how to package it. In part 2 we will cover how to install the Helm package to a Kubernetes cluster, how to upgrade our Helm Chart and how to rollback our Helm Chart.
In this post we will explain how we can use Helm for installing our application. In part 1 we will take a look how we can create a Helm Chart for our application and how to package it. In part 2 we will cover how to install the Helm package to a Kubernetes cluster, how to upgrade our Helm Chart and how to rollback our Helm Chart.
In this post we will take a closer look at Helm: a package manager for Kubernetes. We will take a look at the terminology used, install the Helm Client and Server, deploy an existing packaged application and take a look at some useful Helm commands.
I often receive questions about software versioning. Although it seems something trivial and simple, when people start thinking about it, several questions pop up: How can we uniquely identify our software? Which versioning scheme should we use for our software? Which version of the software is delivered to our test or production system? … With this post I hope to give some answers to these questions and provide some of the choices you have.