Batch / Client / create_service_environment

create_service_environment

Batch.Client.create_service_environment(**kwargs)

Creates a service environment for running service jobs. Service environments define capacity limits for specific service types such as SageMaker Training jobs.

See also: AWS API Documentation

Request Syntax

response = client.create_service_environment(
    serviceEnvironmentName='string',
    serviceEnvironmentType='SAGEMAKER_TRAINING',
    state='ENABLED'|'DISABLED',
    capacityLimits=[
        {
            'maxCapacity': 123,
            'capacityUnit': 'string'
        },
    ],
    tags={
        'string': 'string'
    }
)
Parameters:

  • serviceEnvironmentName (string) –

    [REQUIRED]

    The name for the service environment. It can be up to 128 characters long and can contain letters, numbers, hyphens (-), and underscores (_).

  • serviceEnvironmentType (string) –

    [REQUIRED]

    The type of service environment. For SageMaker Training jobs, specify SAGEMAKER_TRAINING.

  • state (string) – The state of the service environment. Valid values are ENABLED and DISABLED. The default value is ENABLED.

  • capacityLimits (list) –

    [REQUIRED]

    The capacity limits for the service environment. The number of instances a job consumes is the total number of instances requested in the submit training job request resource configuration.

    • (dict) –

      Defines the capacity limit for a service environment. This structure specifies the maximum amount of resources that can be used by service jobs in the environment.

      • maxCapacity (integer) –

        The maximum capacity available for the service environment. This value represents the maximum amount of resources that can be allocated to service jobs.

        For example, maxCapacity=50, capacityUnit=NUM_INSTANCES. This indicates that the maximum number of instances that can be run on this service environment is 50. You could then run 5 SageMaker Training jobs that each use 10 instances. However, if you submit another job that requires 10 instances, it will wait in the queue.

      • capacityUnit (string) –

        The unit of measure for the capacity limit. This defines how the maxCapacity value should be interpreted. For SAGEMAKER_TRAINING jobs, use NUM_INSTANCES.

  • tags (dict) –

    The tags that you apply to the service environment to help you categorize and organize your resources. Each tag consists of a key and an optional value. For more information, see Tagging your Batch resources.

    • (string) –

      • (string) –

Return type:

dict

Returns:

Response Syntax

{
    'serviceEnvironmentName': 'string',
    'serviceEnvironmentArn': 'string'
}

Response Structure

  • (dict) –

    • serviceEnvironmentName (string) –

      The name of the service environment.

    • serviceEnvironmentArn (string) –

      The Amazon Resource Name (ARN) of the service environment.

Exceptions