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

Troubleshooting logs in a parallel world

We briefly touched on logs earlier. Remember that Packer randomly colorizes logs to distinguish multiple build streams appearing in the same terminal. Now that we’re preparing to automate builds, we will need to plan to keep all logs for each build. They should be organized in a way that makes it easy to troubleshoot problems.

Logs should be archived and saved from each build. Store each log in its own directory, named with a timestamp or unique identifier that makes them easy to find. Retention policies should be established for archival, compression, and indexing of the logs, which can become quite large. This can be a simple time retention or a size retention policy. Using a size retention policy can help keep raw logs small enough that grep or file indexing can search the logs with ease:

  • Logs less than 1 month old are kept raw in directories
  • Logs 1 month to a year old are compressed as tar.zstd archives
  • Logs older...