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Continuous Delivery with Docker and Jenkins, 3rd Edition

Continuous Delivery with Docker and Jenkins, 3rd Edition

By : Leszko
4.5 (12)
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Continuous Delivery with Docker and Jenkins, 3rd Edition

Continuous Delivery with Docker and Jenkins, 3rd Edition

4.5 (12)
By: Leszko

Overview of this book

This updated third edition of Continuous Delivery with Docker and Jenkins will explain the advantages of combining Jenkins and Docker to improve the continuous integration and delivery process of app development. You’ll start by setting up a Docker server and configuring Jenkins on it. Next, you’ll discover steps for building applications and microservices on Dockerfiles and integrating them with Jenkins using continuous delivery processes such as continuous integration, automated acceptance testing, configuration management, and Infrastructure as Code. Moving ahead, you'll learn how to ensure quick application deployment with Docker containers, along with scaling Jenkins using Kubernetes. Later, you’ll explore how to deploy applications using Docker images and test them with Jenkins. Toward the concluding chapters, the book will focus on missing parts of the CD pipeline, such as the environments and infrastructure, application versioning, and non-functional testing. By the end of this continuous integration and continuous delivery book, you’ll have gained the skills you need to enhance the DevOps workflow by integrating the functionalities of Docker and Jenkins.
Table of Contents (16 chapters)
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1
Section 1 – Setting Up the Environment
5
Section 2 – Architecting and Testing an Application
9
Section 3 – Deploying an Application

Custom Jenkins images

So far, we have used Jenkins images pulled from the internet. We used jenkins/jenkins for the master container and jenkins/agent (or jenkins/inbound-agent or jenkins/ssh-agent) for the agent container. However, you may want to build your own images to satisfy the specific build environment requirements. In this section, we will cover how to do it.

Building the Jenkins agent

Let's start with the agent image because it's more frequently customized. The build execution is performed on the agent, so it's the agent that needs to have the environment adjusted to the project we want to build – for example, it may require the Python interpreter if our project is written in Python. The same applies to any library, tool, or testing framework, or anything that is needed by the project.

There are four steps to building and using the custom image:

  1. Create a Docker file.
  2. Build the image.
  3. Push the image...
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