Compute environment - Amazon Batch
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Compute environment

Job queues are mapped to one or more compute environments. Compute environments contain the Amazon ECS container instances that are used to run containerized batch jobs. A specific compute environment can also be mapped to one or more than one job queue. Within a job queue, the associated compute environments each have an order that's used by the scheduler to determine where jobs that are ready to be run will run. If the first compute environment has a status of VALID and has available resources, the job is scheduled to a container instance within that compute environment. If the first compute environment has a status of INVALID or can't provide a suitable compute resource, the scheduler attempts to run the job on the next compute environment.

Managed compute environments

You can use a managed compute environment to have Amazon Batch manage the capacity and instance types of the compute resources within the environment. This is based on the compute resource specifications that you define when you create the compute environment. You can choose either to use Amazon EC2 On-Demand Instances and Amazon EC2 Spot Instances. Or, you can alternatively use Fargate and Fargate Spot capacity in your managed compute environment. When using Spot Instances, you can optionally set a maximum price. This way, Spot Instances only launch when the Spot Instance price is under a specified percentage of the On-Demand price.


Fargate Spot instances are not supported on Windows containers on Amazon Fargate. A job queue will be blocked if a FargateWindows job is submitted to a job queue that only uses Fargate Spot compute environments.

Managed compute environments launch Amazon EC2 instances into the VPC and subnets that you specify and then registers them with an Amazon ECS cluster. The Amazon EC2 instances need external network access to communicate with the Amazon ECS service endpoint. Some subnets don't provide Amazon EC2 instances with public IP addresses. If your Amazon EC2 instances don't have a public IP address, they must use network address translation (NAT) to gain this access. For more information, see NAT gateways in the Amazon VPC User Guide. For more information about how to create a VPC, see Creating a virtual private cloud .

By default, Amazon Batch managed compute environments use a recent, approved version of the Amazon ECS optimized AMI for compute resources. However, you might want to create your own AMI to use for your managed compute environments for various reasons. For more information, see Compute resource AMIs.


Amazon Batch doesn't automatically upgrade the AMIs in a compute environment after it's created. For example, it doesn't update the AMIs in your compute environment when a newer version of the Amazon ECS optimized AMI is released. You're responsible for the management of the guest operating system. This includes any updates and security patches. You're also responsible for any additional application software or utilities that you install on the compute resources. There are two ways to use a new AMI for your Amazon Batch jobs. The original method is to complete these steps:

  1. Create a new compute environment with the new AMI.

  2. Add the compute environment to an existing job queue.

  3. Remove the earlier compute environment from your job queue.

  4. Delete the earlier compute environment.

In April 2022, Amazon Batch added enhanced support for updating compute environments. For more information, see Updating compute environments. To use the enhanced updating of compute environments to update AMIs, follow these rules:

  • Either don't set the service role (serviceRole) parameter or set it to the AWSServiceRoleForBatch service-linked role.

  • Set the allocation strategy (allocationStrategy) parameter to BEST_FIT_PROGRESSIVE, SPOT_CAPACITY_OPTIMIZED or SPOT_PRICE_CAPACITY_OPTIMIZED.

  • Set the update to latest image version (updateToLatestImageVersion) parameter to true.

  • Don't specify an AMI ID in imageId, imageIdOverride (in ec2Configuration), or in the launch template (launchTemplate). In that case, Amazon Batch selects the latest Amazon ECS optimized AMI that's supported by Amazon Batch at the time the infrastructure update is initiated. Alternatively, you can specify the AMI ID in the imageId or imageIdOverride parameters, or the launch template identified by the LaunchTemplate properties. Changing any of these properties starts an infrastructure update. If the AMI ID is specified in the launch template, it can't be replaced by specifying an AMI ID in either the imageId or imageIdOverride parameters. It can only be replaced by specifying a different launch template. Or, if the launch template version is set to $Default or $Latest, by setting either a new default version for the launch template (if it's $Default) or by adding a new version to the launch template (if it's $Latest).

If these rules are followed, any update that starts an infrastructure update will cause the AMI ID to be re-selected. If the version setting in the launch template (launchTemplate) is set to $Latest or $Default, the latest or default version of the launch template are evaluated up at the time of the infrastructure update, even if the launchTemplate was not updated.

Consideration when creating multi-node parallel jobs

Amazon Batch recommends creating dedicated compute environments for running multi-node parallel (MNP) jobs and non-MNP jobs. This is due to the way compute capacity is created in your managed compute environment. When creating a new managed compute environment, if you specify a minvCpu value greater than zero then Amazon Batch creates an instance pool for use with non-MNP jobs only. If a multi-node parallel job is submitted, Amazon Batch creates new instance capacity to run the multi-node parallel jobs. In cases where there are both single-node and multi-node parallel jobs running in the same compute environment where either a minvCpus or maxvCpus value is set, if the required compute resources are unavailable Amazon Batch will wait for the current jobs to finish before creating the compute resources necessary to run the new jobs.

Unmanaged compute environments

In an unmanaged compute environment, you manage your own compute resources. You must verify that the AMI you use for your compute resources meets the Amazon ECS container instance AMI specification. For more information, see Compute resource AMI specification and Creating a compute resource AMI.


Amazon Fargate resources aren't supported in unmanaged compute environments.

After you created your unmanaged compute environment, use the DescribeComputeEnvironments API operation to view the compute environment details. Find the Amazon ECS cluster that's associated with the environment and then manually launch your container instances into that Amazon ECS cluster.

The following Amazon CLI command also provides the Amazon ECS cluster ARN.

$ aws batch describe-compute-environments \ --compute-environments unmanagedCE \ --query "computeEnvironments[].ecsClusterArn"

For more information, see Launching an Amazon ECS container instance in the Amazon Elastic Container Service Developer Guide. When you launch your compute resources, specify the Amazon ECS cluster ARN that the resources register with the following Amazon EC2 user data. Replace ecsClusterArn with the cluster ARN that you obtained with the previous command.

#!/bin/bash echo "ECS_CLUSTER=ecsClusterArn" >> /etc/ecs/ecs.config