Launch template support

Amazon Batch supports using Amazon EC2 launch templates with your EC2 compute environments. With launch templates, you can modify the default configuration of your Amazon Batch compute resources without needing to create customized AMIs.

You must create a launch template before you can associate it with a compute environment. You can create a launch template in the Amazon EC2 console. Or, you can use the Amazon CLI or an Amazon SDK. For example, the following JSON file represents a launch template that resizes the Docker data volume for the default Amazon Batch compute resource AMI and also sets it to be encrypted.

{
    "LaunchTemplateName": "increase-container-volume-encrypt",
    "LaunchTemplateData": {
        "BlockDeviceMappings": [
            {
                "DeviceName": "/dev/xvda",
                "Ebs": {
                    "Encrypted": true,
                    "VolumeSize": 100,
                    "VolumeType": "gp2"
                }
            }
        ]
    }
}

You can create the previous launch template by saving the JSON to a file that's called lt-data.json and running the following Amazon CLI command.

aws ec2 --region <region> create-launch-template --cli-input-json file://lt-data.json

For more information about launch templates, see Launching an Instance from a Launch Template in the Amazon EC2 User Guide for Linux Instances.

If you use a launch template to create your compute environment, you can move the following existing compute environment parameters to your launch template:

The following launch template parameters are ignored by Amazon Batch:

Amazon Batch only updates the launch template with a new launch template version during infrastructure updates. For more information, see Updating compute environments.

Amazon EC2 user data in launch templates

You can supply Amazon EC2 user data in your launch template that's run by cloud-init when your instances launch. Your user data can perform common configuration scenarios, including but not limited to the following:

Amazon EC2 user data in launch templates must be in the MIME multi-part archive format. This is because your user data is merged with other Amazon Batch user data that's required to configure your compute resources. You can combine multiple user data blocks together into a single MIME multi-part file. For example, you might want to combine a cloud boothook that configures the Docker daemon with a user data shell script that writes configuration information for the Amazon ECS container agent.

If you're using Amazon CloudFormation, the AWS::CloudFormation::Init type can be used with the cfn-init helper script to perform common configuration scenarios.

A MIME multi-part file consists of the following components:

The following are example MIME multi-part files that you can use to create your own.

{
    "LaunchTemplateName": "base64-user-data",
    "LaunchTemplateData": {
        "UserData": "ewogICAgIkxhdW5jaFRlbXBsYXRlTmFtZSI6ICJpbmNyZWFzZS1jb250YWluZXItdm9sdW..."
    }
}

Example: Mount an existing Amazon EFS file system

MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="==MYBOUNDARY=="

--==MYBOUNDARY==
Content-Type: text/cloud-config; charset="us-ascii"

packages:
- amazon-efs-utils

runcmd:
- file_system_id_01=fs-abcdef123
- efs_directory=/mnt/efs

- mkdir -p ${efs_directory}
- echo "${file_system_id_01}:/ ${efs_directory} efs tls,_netdev" >> /etc/fstab
- mount -a -t efs defaults

--==MYBOUNDARY==--

Example: Override default Amazon ECS container agent configuration

MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="==MYBOUNDARY=="

--==MYBOUNDARY==
Content-Type: text/x-shellscript; charset="us-ascii"

#!/bin/bash
echo ECS_IMAGE_CLEANUP_INTERVAL=60m >> /etc/ecs/ecs.config
echo ECS_IMAGE_MINIMUM_CLEANUP_AGE=60m >> /etc/ecs/ecs.config

--==MYBOUNDARY==--

Example: Mount an existing Amazon FSx for Lustre file system

MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="==MYBOUNDARY=="

--==MYBOUNDARY==
Content-Type: text/cloud-config; charset="us-ascii"

runcmd:
- file_system_id_01=fs-0abcdef1234567890
- region=us-east-2
- fsx_directory=/scratch
- amazon-linux-extras install -y lustre2.10
- mkdir -p ${fsx_directory}
- mount -t lustre ${file_system_id_01}.fsx.${region}.amazonaws.com@tcp:fsx ${fsx_directory}

--==MYBOUNDARY==--

{
    "volumes": [
        {
            "host": {
                "sourcePath": "/scratch"
            },
            "name": "Scratch"
        }
    ],
    "mountPoints": [
        {
            "containerPath": "/scratch",
            "sourceVolume": "Scratch"
        }
    ],
}