Amazon Batch examples using Amazon CLI - Amazon Command Line Interface
Actions
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Amazon Batch examples using Amazon CLI

The following code examples show you how to perform actions and implement common scenarios by using the Amazon Command Line Interface with Amazon Batch.

Actions are code excerpts from larger programs and must be run in context. While actions show you how to call individual service functions, you can see actions in context in their related scenarios and cross-service examples.

Scenarios are code examples that show you how to accomplish a specific task by calling multiple functions within the same service.

Each example includes a link to GitHub, where you can find instructions on how to set up and run the code in context.

Topics

Actions

The following code example shows how to use cancel-job.

Amazon CLI

To cancel a job

This example cancels a job with the specified job ID.

Command:

aws batch cancel-job --job-id bcf0b186-a532-4122-842e-2ccab8d54efb --reason "Cancelling job."

  • For API details, see CancelJob in Amazon CLI Command Reference.

The following code example shows how to use create-compute-environment.

Amazon CLI

To create a managed compute environment with On-Demand instances

This example creates a managed compute environment with specific C4 instance types that are launched on demand. The compute environment is called C4OnDemand.

Command:

aws batch create-compute-environment --cli-input-json file://<path_to_json_file>/C4OnDemand.json

JSON file format:

{
  "computeEnvironmentName": "C4OnDemand",
  "type": "MANAGED",
  "state": "ENABLED",
  "computeResources": {
    "type": "EC2",
    "minvCpus": 0,
    "maxvCpus": 128,
    "desiredvCpus": 48,
    "instanceTypes": [
      "c4.large",
      "c4.xlarge",
      "c4.2xlarge",
      "c4.4xlarge",
      "c4.8xlarge"
    ],
    "subnets": [
      "subnet-220c0e0a",
      "subnet-1a95556d",
      "subnet-978f6dce"
    ],
    "securityGroupIds": [
      "sg-cf5093b2"
    ],
    "ec2KeyPair": "id_rsa",
    "instanceRole": "ecsInstanceRole",
    "tags": {
      "Name": "Batch Instance - C4OnDemand"
    }
  },
  "serviceRole": "arn:aws:iam::012345678910:role/AWSBatchServiceRole"
}

Output:

{
    "computeEnvironmentName": "C4OnDemand",
    "computeEnvironmentArn": "arn:aws:batch:us-east-1:012345678910:compute-environment/C4OnDemand"
}

To create a managed compute environment with Spot Instances

This example creates a managed compute environment with the M4 instance type that is launched when the Spot bid price is at or below 20% of the On-Demand price for the instance type. The compute environment is called M4Spot.

Command:

aws batch create-compute-environment --cli-input-json file://<path_to_json_file>/M4Spot.json

JSON file format:

{
  "computeEnvironmentName": "M4Spot",
  "type": "MANAGED",
  "state": "ENABLED",
  "computeResources": {
    "type": "SPOT",
    "spotIamFleetRole": "arn:aws:iam::012345678910:role/aws-ec2-spot-fleet-role",
    "minvCpus": 0,
    "maxvCpus": 128,
    "desiredvCpus": 4,
    "instanceTypes": [
      "m4"
    ],
    "bidPercentage": 20,
    "subnets": [
      "subnet-220c0e0a",
      "subnet-1a95556d",
      "subnet-978f6dce"
    ],
    "securityGroupIds": [
      "sg-cf5093b2"
    ],
    "ec2KeyPair": "id_rsa",
    "instanceRole": "ecsInstanceRole",
    "tags": {
      "Name": "Batch Instance - M4Spot"
    }
  },
  "serviceRole": "arn:aws:iam::012345678910:role/AWSBatchServiceRole"
}

Output:

{
    "computeEnvironmentName": "M4Spot",
    "computeEnvironmentArn": "arn:aws:batch:us-east-1:012345678910:compute-environment/M4Spot"
}

The following code example shows how to use create-job-queue.

Amazon CLI

To create a low priority job queue with a single compute environment

This example creates a job queue called LowPriority that uses the M4Spot compute environment.

Command:

aws batch create-job-queue --cli-input-json file://<path_to_json_file>/LowPriority.json

JSON file format:

{
  "jobQueueName": "LowPriority",
  "state": "ENABLED",
  "priority": 10,
  "computeEnvironmentOrder": [
    {
      "order": 1,
      "computeEnvironment": "M4Spot"
    }
  ]
}

Output:

{
    "jobQueueArn": "arn:aws:batch:us-east-1:012345678910:job-queue/LowPriority",
    "jobQueueName": "LowPriority"
}

To create a high priority job queue with two compute environments

This example creates a job queue called HighPriority that uses the C4OnDemand compute environment with an order of 1 and the M4Spot compute environment with an order of 2. The scheduler will attempt to place jobs on the C4OnDemand compute environment first.

Command:

aws batch create-job-queue --cli-input-json file://<path_to_json_file>/HighPriority.json

JSON file format:

{
  "jobQueueName": "HighPriority",
  "state": "ENABLED",
  "priority": 1,
  "computeEnvironmentOrder": [
    {
      "order": 1,
      "computeEnvironment": "C4OnDemand"
    },
    {
      "order": 2,
      "computeEnvironment": "M4Spot"
    }
  ]
}

Output:

{
    "jobQueueArn": "arn:aws:batch:us-east-1:012345678910:job-queue/HighPriority",
    "jobQueueName": "HighPriority"
}

  • For API details, see CreateJobQueue in Amazon CLI Command Reference.

The following code example shows how to use delete-compute-environment.

Amazon CLI

To delete a compute environment

This example deletes the P2OnDemand compute environment.

Command:

aws batch delete-compute-environment --compute-environment P2OnDemand

The following code example shows how to use delete-job-queue.

Amazon CLI

To delete a job queue

This example deletes the GPGPU job queue.

Command:

aws batch delete-job-queue --job-queue GPGPU

  • For API details, see DeleteJobQueue in Amazon CLI Command Reference.

The following code example shows how to use deregister-job-definition.

Amazon CLI

To deregister a job definition

This example deregisters a job definition called sleep10.

Command:

aws batch deregister-job-definition --job-definition sleep10

The following code example shows how to use describe-compute-environments.

Amazon CLI

To describe a compute environment

This example describes the P2OnDemand compute environment.

Command:

aws batch describe-compute-environments --compute-environments P2OnDemand

Output:

{
    "computeEnvironments": [
        {
            "status": "VALID",
            "serviceRole": "arn:aws:iam::012345678910:role/AWSBatchServiceRole",
            "computeEnvironmentArn": "arn:aws:batch:us-east-1:012345678910:compute-environment/P2OnDemand",
            "computeResources": {
                "subnets": [
                    "subnet-220c0e0a",
                    "subnet-1a95556d",
                    "subnet-978f6dce"
                ],
                "tags": {
                    "Name": "Batch Instance - P2OnDemand"
                },
                "desiredvCpus": 48,
                "minvCpus": 0,
                "instanceTypes": [
                    "p2"
                ],
                "securityGroupIds": [
                    "sg-cf5093b2"
                ],
                "instanceRole": "ecsInstanceRole",
                "maxvCpus": 128,
                "type": "EC2",
                "ec2KeyPair": "id_rsa"
            },
            "statusReason": "ComputeEnvironment Healthy",
            "ecsClusterArn": "arn:aws:ecs:us-east-1:012345678910:cluster/P2OnDemand_Batch_2c06f29d-d1fe-3a49-879d-42394c86effc",
            "state": "ENABLED",
            "computeEnvironmentName": "P2OnDemand",
            "type": "MANAGED"
        }
    ]
}

The following code example shows how to use describe-job-definitions.

Amazon CLI

To describe active job definitions

This example describes all of your active job definitions.

Command:

aws batch describe-job-definitions --status ACTIVE

Output:

{
    "jobDefinitions": [
        {
            "status": "ACTIVE",
            "jobDefinitionArn": "arn:aws:batch:us-east-1:012345678910:job-definition/sleep60:1",
            "containerProperties": {
                "mountPoints": [],
                "parameters": {},
                "image": "busybox",
                "environment": {},
                "vcpus": 1,
                "command": [
                    "sleep",
                    "60"
                ],
                "volumes": [],
                "memory": 128,
                "ulimits": []
            },
            "type": "container",
            "jobDefinitionName": "sleep60",
            "revision": 1
        }
    ]
}

The following code example shows how to use describe-job-queues.

Amazon CLI

To describe a job queue

This example describes the HighPriority job queue.

Command:

aws batch describe-job-queues --job-queues HighPriority

Output:

{
    "jobQueues": [
        {
            "status": "VALID",
            "jobQueueArn": "arn:aws:batch:us-east-1:012345678910:job-queue/HighPriority",
            "computeEnvironmentOrder": [
                {
                    "computeEnvironment": "arn:aws:batch:us-east-1:012345678910:compute-environment/C4OnDemand",
                    "order": 1
                }
            ],
            "statusReason": "JobQueue Healthy",
            "priority": 1,
            "state": "ENABLED",
            "jobQueueName": "HighPriority"
        }
    ]
}

The following code example shows how to use describe-jobs.

Amazon CLI

To describe a job

The following describe-jobs example describes a job with the specified job ID.

aws batch describe-jobs \
    --jobs bcf0b186-a532-4122-842e-2ccab8d54efb

Output:

{
    "jobs": [
        {
            "status": "SUBMITTED",
            "container": {
                "mountPoints": [],
                "image": "busybox",
                "environment": [],
                "vcpus": 1,
                "command": [
                    "sleep",
                    "60"
                ],
                "volumes": [],
                "memory": 128,
                "ulimits": []
            },
            "parameters": {},
            "jobDefinition": "arn:aws:batch:us-east-1:012345678910:job-definition/sleep60:1",
            "jobQueue": "arn:aws:batch:us-east-1:012345678910:job-queue/HighPriority",
            "jobId": "bcf0b186-a532-4122-842e-2ccab8d54efb",
            "dependsOn": [],
            "jobName": "example",
            "createdAt": 1480483387803
        }
    ]
}

  • For API details, see DescribeJobs in Amazon CLI Command Reference.

The following code example shows how to use list-jobs.

Amazon CLI

To list running jobs

This example lists the running jobs in the HighPriority job queue.

Command:

aws batch list-jobs --job-queue HighPriority

Output:

{
    "jobSummaryList": [
        {
            "jobName": "example",
            "jobId": "e66ff5fd-a1ff-4640-b1a2-0b0a142f49bb"
        }
    ]
}

To list submitted jobs

This example lists jobs in the HighPriority job queue that are in the SUBMITTED job status.

Command:

aws batch list-jobs --job-queue HighPriority --job-status SUBMITTED

Output:

{
    "jobSummaryList": [
        {
            "jobName": "example",
            "jobId": "68f0c163-fbd4-44e6-9fd1-25b14a434786"
        }
    ]
}

  • For API details, see ListJobs in Amazon CLI Command Reference.

The following code example shows how to use register-job-definition.

Amazon CLI

To register a job definition

This example registers a job definition for a simple container job.

Command:

aws batch register-job-definition --job-definition-name sleep30 --type container --container-properties '{ "image": "busybox", "vcpus": 1, "memory": 128, "command": [ "sleep", "30"]}'

Output:

{
    "jobDefinitionArn": "arn:aws:batch:us-east-1:012345678910:job-definition/sleep30:1",
    "jobDefinitionName": "sleep30",
    "revision": 1
}

The following code example shows how to use submit-job.

Amazon CLI

To submit a job

This example submits a simple container job called example to the HighPriority job queue.

Command:

aws batch submit-job --job-name example --job-queue HighPriority  --job-definition sleep60

Output:

{
    "jobName": "example",
    "jobId": "876da822-4198-45f2-a252-6cea32512ea8"
}

  • For API details, see SubmitJob in Amazon CLI Command Reference.

The following code example shows how to use terminate-job.

Amazon CLI

To terminate a job

This example terminates a job with the specified job ID.

Command:

aws batch terminate-job --job-id 61e743ed-35e4-48da-b2de-5c8333821c84 --reason "Terminating job."

  • For API details, see TerminateJob in Amazon CLI Command Reference.

The following code example shows how to use update-compute-environment.

Amazon CLI

To update a compute environment

This example disables the P2OnDemand compute environment so it can be deleted.

Command:

aws batch update-compute-environment --compute-environment P2OnDemand --state DISABLED

Output:

{
    "computeEnvironmentName": "P2OnDemand",
    "computeEnvironmentArn": "arn:aws:batch:us-east-1:012345678910:compute-environment/P2OnDemand"
}

The following code example shows how to use update-job-queue.

Amazon CLI

To update a job queue

This example disables a job queue so that it can be deleted.

Command:

aws batch update-job-queue --job-queue GPGPU --state DISABLED

Output:

{
    "jobQueueArn": "arn:aws:batch:us-east-1:012345678910:job-queue/GPGPU",
    "jobQueueName": "GPGPU"
}

  • For API details, see UpdateJobQueue in Amazon CLI Command Reference.