Using HashiCorp Packer

Location: On-Site or Online
Pricing: $1,250 per seat (6-seat minimum)
Length: 3 Days

Course Summary

Using HashiCorp Packer is a practical, hands-on course designed to teach students how to build, automate, and manage machine images with HashiCorp Packer.

Students learn how Packer fits into modern infrastructure and DevOps workflows by enabling immutable infrastructure patterns across cloud and on-prem platforms. The course emphasizes building repeatable, versioned images for AWS, Azure, and other environments, integrating configuration management tools, and supporting CI/CD pipelines.

By the end of the course, students are comfortable writing Packer templates, building images consistently, troubleshooting builds, and integrating Packer into real production workflows.

Course Outline

Day 1 – Packer Fundamentals and Image Automation Concepts

• 💬 Lecture: Why image-based automation matters

• 💬 Lecture: Mutable vs immutable infrastructure

• 💬 Lecture: Where Packer fits in modern DevOps workflows

• 💬 Lecture: Packer architecture (builders, provisioners, post-processors)

• 💬 Lecture: HCL2 basics for Packer templates

• ⚙️ Lab: Installing Packer and validating the environment

• ⚙️ Lab: Exploring Packer CLI commands and workflow

• ⚙️ Lab: Writing a basic Packer template

• ⚙️ Lab: Running a local image build

• ⚙️ Lab: Inspecting build output and logs

• 💬 Lecture: Builders and supported platforms

• ⚙️ Lab: Configuring a cloud builder (AWS or Azure)

• ⚙️ Lab: Authenticating Packer to a cloud provider

Day 2 – Provisioning, Customization, and Debugging

• 💬 Lecture: Provisioners and image customization strategies

• 💬 Lecture: Shell vs configuration management provisioners

• ⚙️ Lab: Using shell provisioners to install software

• ⚙️ Lab: Creating reusable provisioning scripts

• 💬 Lecture: Integrating Packer with Ansible

• ⚙️ Lab: Using Ansible as a Packer provisioner

• ⚙️ Lab: Passing variables from Packer to Ansible

• 💬 Lecture: Variables, parameterization, and reuse

• ⚙️ Lab: Defining and using input variables

• ⚙️ Lab: Using variable files for multiple environments

• 💬 Lecture: Debugging and troubleshooting Packer builds

• ⚙️ Lab: Running Packer in debug mode

• ⚙️ Lab: Diagnosing failed provisioning steps

Day 3 – Production Workflows and Best Practices

• 💬 Lecture: Image versioning and lifecycle management

• 💬 Lecture: Naming conventions and tagging strategies

• 💬 Lecture: Security considerations for golden images

• ⚙️ Lab: Versioning images using variables and metadata

• ⚙️ Lab: Applying tags and labels to built images

• 💬 Lecture: Packer in CI/CD pipelines

• ⚙️ Lab: Running Packer non-interactively

• ⚙️ Lab: Integrating Packer builds into a pipeline

• 💬 Lecture: Packer with Terraform and deployment workflows

• ⚙️ Lab: Using Terraform to deploy infrastructure from Packer images

• ⚙️ Lab: Validating image usage in downstream automation

• 💬 Lecture: Real-world Packer patterns and anti-patterns

• ⚙️ Lab: Building a complete golden image workflow

• ⚙️ Lab: Combining builders, provisioners, and variables

• ⚙️ Lab: Reviewing reliability, security, and repeatability

Outcomes

Students who complete HashiCorp Packer will be able to:

• Explain image-based automation and immutable infrastructure concepts

• Write and maintain Packer templates using HCL2

• Build consistent machine images across environments

• Customize images safely using shell and Ansible provisioners

• Troubleshoot and debug failed image builds

• Integrate Packer into CI/CD and infrastructure pipelines