Define Root Volume Size in AWS Batch: A Complete Guide (2026)

Amazon Web Services (AWS) Batch is a powerful tool for managing batch computing workloads. However, configuring the right environment to accommodate your workload's storage needs can sometimes be challenging, particularly when it comes to defining the root volume size. In this guide, we'll walk through how to specify the root volume size for your AWS Batch jobs, ensuring your tasks have the necessary resources to run efficiently.

Key Takeaways

• Learn how to configure root volume size for AWS Batch jobs.
• Understand the role of custom AMIs in defining root volume size.
• Discover how to modify the root volume size in a launch template.
• Explore common pitfalls and troubleshooting tips.

In this tutorial, you'll learn to set a custom root volume size for your AWS Batch jobs using Amazon Machine Images (AMIs) and launch templates. This is crucial for tasks that require more storage than the default configuration provides. By the end of this guide, you'll be able to customize your AWS Batch environments to better meet the storage demands of your applications.

Prerequisites

• Basic understanding of AWS and AWS Batch.
• An active AWS account with permissions to create and modify EC2 instances and AMIs.
• A working AWS Batch environment or the ability to set one up.

Step 1: Create a Custom AMI with Desired Root Volume Size

The first step in customizing your AWS Batch job's root volume size is to create a custom Amazon Machine Image (AMI) with the desired configuration.

Create an EC2 Instance

aws ec2 run-instances --image-id ami-12345678 --count 1 --instance-type t2.micro --key-name MyKeyPair

Use an Amazon Linux 2 AMI as a base. Launch the instance and configure it as needed.

Resize the Root Volume

Once your EC2 instance is running, you can resize the root volume. Connect to your instance and execute the following commands:

# Stop the instance first
aws ec2 stop-instances --instance-ids i-1234567890abcdef0

# Modify the volume size
aws ec2 modify-volume --volume-id vol-049df61146c4d7901 --size 500

Restart your instance after modification. Verify the size change by checking the volume's properties in AWS Console.

Create an AMI from Your Instance

After confirming that the root volume size is as desired, create a new AMI:

aws ec2 create-image --instance-id i-1234567890abcdef0 --name "CustomAMIWith500GBRoot"

This AMI will serve as the foundation for your AWS Batch compute environments.

Step 2: Configure a Launch Template with the Custom AMI

Next, you'll configure a launch template using the custom AMI. This template will be used in your AWS Batch compute environment.

Create a Launch Template

{
  "LaunchTemplateName": "BatchLaunchTemplate",
  "VersionDescription": "v1",
  "LaunchTemplateData": {
    "ImageId": "ami-0abcdef1234567890",
    "InstanceType": "t2.micro",
    "BlockDeviceMappings": [
      {
        "DeviceName": "/dev/xvda",
        "Ebs": {
          "VolumeSize": 500
        }
      }
    ]
  }
}

Use the AWS CLI to create this template, ensuring the VolumeSize matches your requirements.

Step 3: Update AWS Batch Compute Environment

With your launch template ready, update your AWS Batch compute environment to use it.

aws batch update-compute-environment --compute-environment MyBatchEnv --compute-resources {
  "type": "EC2",
  "minvCpus": 0,
  "maxvCpus": 16,
  "desiredvCpus": 8,
  "instanceTypes": ["optimal"],
  "launchTemplate": {
    "launchTemplateId": "lt-0abcdef1234567890",
    "version": "1"
  }
}

This command links your compute environment to the new launch template that specifies the custom AMI and root volume size.

Common Errors/Troubleshooting

Configuring AWS Batch environments can sometimes lead to errors. Here are some common issues and their solutions:

• Launch Template ID Not Found: Ensure the launch template exists and you have the correct permissions.
• Volume Size Inconsistency: Double-check your JSON configuration and ensure the AMI has the correct root volume size.
• Permission Denied Errors: Verify IAM roles and policies attached to your AWS account.

Frequently Asked Questions

Can I change the root volume size after creating a job queue?

No, you need to adjust the size before queuing jobs, by customizing the AMI and launch template.

Why isn't my new launch configuration applied?

Ensure your compute environment is set to use the new launch template with the correct version.

What AWS permissions are required to change volume size?

You need EC2 full access or specific permissions for modifying volumes and creating images.

Frequently Asked Questions

Can I change the root volume size after creating a job queue?

No, you need to adjust the size before queuing jobs, by customizing the AMI and launch template.

Why isn't my new launch configuration applied?

Ensure your compute environment is set to use the new launch template with the correct version.

What AWS permissions are required to change volume size?

You need EC2 full access or specific permissions for modifying volumes and creating images.