The Packer EBS builder lets you forge custom Amazon Machine Images (AMIs) directly from Elastic Block Store (EBS) snapshots, bypassing the need for a running EC2 instance to capture the final image.
Let’s see it in action. Imagine you’ve just provisioned a pristine Ubuntu 22.04 instance, installed your application dependencies, and configured your services. Instead of manually creating an AMI from that running instance’s root volume, which involves instance downtime or potential data inconsistencies, you can use Packer to take that configured root volume, snapshot it, and build a new AMI directly from that snapshot.
Here’s a simplified packer.json snippet demonstrating this:
{
"builders": [
{
"type": "amazon-ebs",
"region": "us-east-1",
"source_ami_filter": {
"filters": {
"name": "ubuntu/images/hvm-ssd/ubuntu-jammy-22.04-amd64-server-20230101",
"virtualization-type": "hvm",
"root-device-type": "ebs"
},
"owners": ["099720109477"]
},
"snapshot_description": "My custom Ubuntu 22.04 AMI for application X",
"ami_name": "my-app-ubuntu-22.04-{{timestamp}}",
"tags": {
"Project": "MyApp",
"Version": "1.0.0"
}
}
],
"provisioners": [
{
"type": "shell",
"inline": [
"sudo apt-get update",
"sudo apt-get install -y nginx",
"sudo systemctl enable nginx"
]
}
]
}
When Packer runs this, it first finds a suitable base AMI (defined by source_ami_filter). It then launches an ephemeral instance using that AMI. The provisioners section executes commands on this temporary instance. Crucially, after the provisioners complete, instead of stopping the instance and creating an AMI from its root volume, the amazon-ebs builder takes a snapshot of that root volume. It then uses this snapshot to create a new AMI. The ephemeral instance is then terminated, leaving you with only the newly created AMI.
The core problem this solves is the repeatable, automated creation of golden AMIs. You define your desired base image, your necessary software, and your configurations in code (the packer.json). This allows you to:
- Ensure Consistency: Every AMI built from this template will be identical.
- Automate Updates: When a security patch or new software version is available, you update your
packer.jsonand rebuild, rather than manually updating instances. - Reduce Downtime: AMI creation from a snapshot is generally faster and less disruptive than creating an AMI from a running instance that needs to be stopped.
- Version Control Your Images: Your AMI definition lives in your Git repository alongside your application code.
Internally, the amazon-ebs builder orchestrates a series of AWS API calls. It finds the source_ami, launches an EC2 instance, attaches a temporary EBS volume (which becomes the root volume for the AMI), runs your provisioners on that volume, creates a snapshot of that volume, and finally registers a new AMI using that snapshot. The source_ami_filter is powerful; you can specify AMI IDs, names, owners, and other EC2 filters to precisely select your starting point. The ami_name can include Go templating, like {{timestamp}}, to ensure unique names for each build.
The snapshot_description and ami_name are not just labels; they directly translate to the Description and Name fields of the resulting AMI and its underlying snapshot in your AWS account. This is vital for organization and identifying your custom images later. You can also pass tags directly to the builder, which will be applied to the created AMI.
One subtle but critical aspect is how Packer handles the root device type. By default, the amazon-ebs builder assumes you’re building an AMI for an instance that will use EBS as its root device. If your source_ami uses an instance store volume, you’ll run into issues. The source_ami_filter is the place to ensure you’re starting with an AMI that has an EBS root device. The virtualization-type filter is also important; most modern AMIs are hvm, but older ones might be paravirtualization.
The snapshot_description field is often overlooked but is crucial for auditing and understanding the lineage of your AMIs. When you have many AMIs, being able to quickly see what software or configuration is baked into a particular snapshot via its description saves a lot of time. If you omit it, AWS assigns a default, often unhelpful, description.
The next logical step after mastering AMI creation is automating the deployment of these AMIs into your infrastructure.