In the previous post TDD for infrastructure with Vagrant I explored Vagrant, VirtualBox and Chef Inspec for implementing a simple workflow for test driven development of infrastructure code. I showed that using virtual machines as target machines for testing is just not fast enough and probably hard to run in a build environment.
For many years (almost decades) developers have been practicing test driven development and write tests to get confidence that their code works.
However, with the rise of infrastructure as code where DevOps engineers try to describe infrastructure provisioning using code, this is something that is not observed generally. In many situations I have encountered infrastructure that
With this post we close the series of articles taking a deep dive on building Docker images. We look at a building Docker images for running Java applications in a Docker container with Jib which is part of the Google Container Tools.
Jib is highly opinionated about building Java Docker containers using Maven or Gradle as build tool. So it offers plugin support for the above mentioned build tools.
In the previous blog post of the building docker images series we had a look at Docker image build pipelines. We revealed typical problems and looked at how to overcome some by utilizing multistage builds.
In part 4 of this series we work with an addition to the Docker tooling which is BuildKit.
Let’s recap what we have covered in this blog post series so far. In Building a Docker Image we had a look at the anatomy of a Docker image. And Optimizing a Docker Image shed some light on optimizations when building an image.
This post continues where we left off with Building a Docker Image. We are looking into how we can optimize the process of building a Docker image. This optimization can aim at reducing the size of images built or the time it takes for packaging an image.
This post starts a series of articles taking a deep dive on building Docker images. But before we look at building a Docker image let’s briefly recap the essentials we need to know about container images.
A Docker image is built up from a series of layers where each layer represents an instruction in the image’s Dockerfile. When Docker materializes an image and creates a container from this image, a storage driver handles the details about the way these layers interact with each other. Different storage drivers are available, which have advantages and disadvantages in different situations (e.g. AUFS, overlay, overlay2, btrfs,zfs). All drivers have in common that they use stackable image layers and the copy-on-write (CoW) strategy for writing files.
