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

Starting with LXC/LXD images

Early container images used plain archives of an entire directory for deployment. In 2006, Google engineers started to experiment with a new kernel feature they called process containers. This feature was renamed control groups and added to the mainline Linux kernel in v2.6.24. These control groups provided a global way to limit resources for a group of processes, including CPU, memory, and storage resources, in a way that’s not available to the existing mechanism of chroots. The kernel feature itself was fairly straightforward but image management turned out to be the main challenge of containers.

What if you wanted more than a single directory archive for an application container? Orchestrators added the ability to cluster containers and also the ability to distribute multiple containers in groups. This is where Google’s Borg and the Kubernetes concept of a pod originates. Fun fact: the name pod comes from a group of whales, and the Docker...