Book Image

HashiCorp Packer in Production

By : John Boero
Book Image

HashiCorp Packer in Production

By: John Boero

Overview of this book

Creating machine images can be time-consuming and error-prone when done manually. HashiCorp Packer enables you to automate this process by defining the configuration in a simple, declarative syntax. This configuration is then used to create machine images for multiple environments and cloud providers. The book begins by showing you how to create your first manifest while helping you understand the available components. You’ll then configure the most common built-in builder options for Packer and use runtime provisioners to reconfigure a source image for desired tasks. You’ll also learn how to control logging for troubleshooting errors in complex builds and explore monitoring options for multiple logs at once. As you advance, you’ll build on your initial manifest for a local application that’ll easily migrate to another builder or cloud. The chapters also help you get to grips with basic container image options in different formats while scaling large builds in production. Finally, you’ll develop a life cycle and retention policy for images, automate packer builds, and protect your production environment from nefarious plugins. By the end of this book, you’ll be equipped to smoothen collaboration and reduce the risk of errors by creating machine images consistently and automatically based on your defined configuration.
Table of Contents (18 chapters)
1
Part 1: Packer’s Beginnings
7
Part 2: Managing Large Environments
11
Part 3: Advanced Customized Packer

Summary

In this chapter, we showed a basic template to provide us with a first base image for Packer to build further images. We selected CentOS 9 Streams as a Linux distribution to simulate enterprise environments, but next, we will add other options to our template, including other Linux distributions and Windows. Templates can be written in either HCL2 or JSON. HCL2 is the recommended template format for new projects, but JSON templates are widely available on the internet and easily converted to HCL2 if necessary. JSON can still help when automation is used to build templates, but from here forward, we will focus on writing example templates in HCL2.

Simple templates like the one in this chapter cut a lot of corners and hardcode a lot of attributes, but in the next chapter, it will be apparent how limiting that can be and how variables can be used to simplify templates and improve reusable attributes.