Create AWS AMI using Packer and streamline cloud provisioning with an IaC workflow that delivers consistent, policy-aligned machine images. Upgrade your Cloud Management strategy through image automation.
Cloud teams continually seek ways to enhance control over provisioning, accelerate deployment speed, and maintain environments in alignment with organizational standards. Image automation is a major part of that effort. Packer helps engineers turn OS configuration into code, enabling predictable and repeatable machine images. When used alongside established cloud management practices, it becomes part of a wider IaC workflow that improves reliability and cuts down manual setup efforts.
This guide walks you through the process of installing Packer inside an AWS Cloud9 workspace, creating a template, generating a custom AMI, and launching an EC2 instance from it. The goal is to help teams understand how image automation strengthens controlled provisioning pipelines.
Overview
Set Up Packer in Cloud9
Cloud9 provides a development environment inside AWS, eliminating local configuration challenges and keeping everything close to the AWS API. Start by opening the Cloud9 IDE and switching to elevated privileges:
sudo suMove to the directory used for system utilities:
cd /usr/local/binNow, download the Packer archive using the link copied earlier:
wget <PACKER_LINK>Next, unpack the archive:
unzip packer_1.5.5_linux_amd64.zipTo remove the archive after extraction:
rm packer_1.5.5_linux_amd64.zipTo exit superuser mode:
exitTo check that Packer responds correctly:
packer –versionCloud9 is now equipped to build AMIs directly through code.
Write the Packer Template
A Packer template acts as a blueprint for AMI creation. In Cloud9, create a new file named packer.json and insert the template structure. Replace `<USERNAME>` with any identifier you prefer.
{
"variables": {
"instance_size": "t2.small",
"ami_name": "ami-",
"base_ami": "ami-1853ac65",
"ssh_username": "ec2-user",
"vpc_id": "",
"subnet_id": ""
},
"builders": [
{
"type": "amazon-ebs",
"region": "us-east-1",
"source_ami": "{{user `base_ami`}}",
"instance_type": "{{user `instance_size`}}",
"ssh_username": "{{user `ssh_username`}}",
"ssh_timeout": "20m",
"ami_name": "{{user `ami_name`}}",
"ssh_pty": "true",
"vpc_id": "{{user `vpc_id`}}",
"subnet_id": "{{user `subnet_id`}}",
"tags": {
"Name": "App Name",
"BuiltBy": "Packer"
}
}
],
"description": "AWS image",
"provisioners": [
{
"type": "shell",
"inline": [
"sudo yum update -y",
"sudo yum install -y git"
]
}
]
}
To validate the file in the terminal:
packer validate packer.jsonValidation ensures the template is ready for automated AMI creation.
Start automating your AWS images now.
Gather AWS Configuration Details
Before running the build, collect the resource identifiers used as variables.
- Base image ID
Open the EC2 console, start the Launch Instance flow, and copy the ID of the Amazon Linux AMI.
- VPC ID
Navigate to the VPC section and record the ID of your main VPC. - Subnet ID
Open the Subnets page, choose the first subnet, ensure public IP assignment is active, and copy its ID.
These values connect your template to your AWS environment.
Build the AMI
Run the build command after inserting the AMI, VPC, and subnet values:
packer build -var 'ami_name=ami-' -var 'base_ami=<AMI_ID>' -var 'vpc_id=<VPC_ID>' -var 'subnet_id=<SUBNET_ID>' packer.json
Packer launches a temporary instance, runs the provisioning steps, captures the result as a reusable AMI, and outputs the ID once complete.
Open EC2 < AMIs to confirm that the new image appears in your list.
Launch an EC2 Instance from the AMI
To start a new instance launch and select the t2.small type. Proceed through storage and tags. Add the tag:
- Key: Name
- Value: test-ami
Move to the security group page, then launch without a key pair and acknowledge the notice. After deployment begins, open the instance ID and wait for the status to turn Running.
This confirms that the AMI works as expected and can be used in automated provisioning pipelines. If you encounter delays during image creation, our guide on resolving AWS AMI creation pending issues provides practical steps to troubleshoot and restore your automation workflow quickly.
How This Supports Cloud Management and IaC
This workflow forms a concrete example of controlled image creation inside an IaC framework:
- A single template guarantees consistent AMIs across development, staging, and production.
- Engineers avoid repeated configuration tasks, freeing time for high-value cloud optimization work.
- Packer templates act as documentation and policy enforcement tools, ensuring that every image follows approved guidelines.
- The template and build steps can integrate into CI/CD pipelines, allowing automatic AMI creation triggered by code changes.
- Hardening scripts, patch updates, and compliance checks can be included directly in the template.
Together, these advantages support a mature cloud management model where infrastructure is defined, controlled, and deployed through code.
Packer gives cloud teams a reliable method to generate consistent AMIs through a code-driven process. Building images inside Cloud9 simplifies the workflow, keeps everything within AWS, and supports broader IaC strategies that help organizations maintain predictable, secure, and policy-aligned environments.
Conclusion
Autocomplete search has become a vital part of modern digital platforms. Users expect quick suggestions and a guided search experience that feels intuitive. Elasticsearch’s search_as_you_type datatype offers a practical and effective way to deliver this, thanks to its automated creation of n-grams, prefixes, and multi-word combinations. As organizations continue modernizing their technology and prioritizing customer experience, features like autocomplete help shape smoother and more engaging interactions.
