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

CI testing against multiple OS releases

In this chapter, we discussed additional builder types for cloud and VMware, and we added a single example of each to our sample code. With a single-build template crossing multiple sources with multiple provisioners, we can build a single image across multiple clouds with ease. If we need to test multiple base images or OSs against our application, that is a different problem to solve. You might think of image complexity as a four-dimensional problem, described like this:

C = (Base OSs) * (Clouds) * (Provisioners) * (Architectures)

We have just built images for a single OS (RHEL 9) on multiple clouds (AWS, Azure, and GCP). We also assumed that each build would be running Intel’s x86_64 architecture. If AWS Graviton instances go on sale with savings of 40%, your business can benefit from having ARM images ready to switch. If AliCloud suddenly releases RISC-V instances with savings of 50%, then the business could save even more by...