Introduction to Packer

Building machine images manually is tedious and error-prone. You spin up a server, install packages, configure services, test everything, then capture an image. When you need to update it, you either start from scratch or try to remember what you changed. Team members build images differently, leading to inconsistencies. Documentation gets outdated, and nobody's quite sure what's in production.

Packer solves this by codifying the entire image building process. You write a configuration file that describes exactly what you want in your image - the base image to start from, packages to install, files to copy, commands to run. Packer then automates building that image for one or more platforms. Need the same image for AWS, Azure, and VMware? One Packer template builds all three.

Unlike configuration management tools like Ansible or Chef that configure servers after they boot, Packer creates pre-configured images. This means faster deployment times - your servers start with everything already installed. It also means more consistency - every instance launched from the image is identical.

What You'll Learn

This guide takes you from zero Packer knowledge to building production-ready machine images. We'll cover both fundamentals and practical patterns you'll use daily.

Getting Started: Understand what Packer does and when to use it. Install Packer and verify your setup across different operating systems.

Core Concepts: Learn about builders, provisioners, and post-processors. Understand how these components work together to create machine images.

Writing Templates: Create your first Packer template using HCL2 syntax. Define builds, configure sources, and use provisioners to customize images.

Builders Deep Dive: Work with different builders - Amazon AMI, Docker, VirtualBox, and more. Understand builder-specific configuration and authentication.

Provisioners: Use shell scripts, file transfers, Ansible, and other provisioners to configure your images. Learn the order of operations and error handling.

Variables: Make templates reusable with variables. Use variable files for different environments. Understand sensitive variables and validation.

Multi-Platform Builds: Build the same image for multiple platforms in parallel. Share provisioning logic across different builders.

Post-Processors: Tag images, push to registries, create manifests, and integrate with artifact management systems.

CI/CD Integration: Automate image building in your pipelines. Implement testing and validation. Version and distribute images.

Best Practices: Structure Packer projects for maintainability. Handle secrets securely. Optimize build times. Test images before deployment.

Why Image-Based Deployment

Building images upfront offers several advantages:

Speed: Launching pre-configured images is much faster than configuring blank servers. What takes 10 minutes to configure can launch in 30 seconds from an image.

Consistency: Every instance is identical. No "it works on my machine" problems. No drift between servers over time.

Testing: Test your image once before deploying hundreds of instances. Find configuration issues during the build, not in production.

Rollback: Keep old image versions. Problems with a new image? Launch instances from the previous version.

Immutability: Servers become replaceable. Instead of patching running servers, build new images and replace instances.

Packer vs Configuration Management

Packer and tools like Ansible, Chef, or Puppet serve different purposes:

Packer: Builds images before deployment. Runs once to create an artifact. Fast instance launch, slow to update.

Configuration Management: Configures servers after they're running. Can continuously update systems. Slower initial launch, faster updates.

Many teams use both: Packer creates base images with common configuration, configuration management handles dynamic settings and secrets at runtime.

What We'll Build

Throughout this guide, we'll build progressively more complex images:

• A basic Ubuntu image with updated packages
• A web server image with Nginx pre-installed
• A Docker image with a Python application
• Multi-platform images (AWS and DigitalOcean)
• A complete application stack with monitoring

By the end, you'll understand how to build images for your infrastructure and integrate Packer into your deployment workflow.

Let's start by understanding what Packer is and how it works.