AWS Batch

AWS Batch enables you to run batch computing workloads on the AWS Cloud. Batch computing is a common way for developers, scientists, and engineers to access large amounts of compute resources. AWS Batch removes the undifferentiated heavy lifting of configuring and managing the required infrastructure.

Prerequisite Tasks

To use these operators, you must do a few things:

Operators

Submit a new AWS Batch job

To submit a new AWS Batch job and monitor it until it reaches a terminal state you can use BatchOperator.

tests/system/providers/amazon/aws/example_batch.py[source]

submit_batch_job = BatchOperator(
    task_id="submit_batch_job",
    job_name=batch_job_name,
    job_queue=batch_job_queue_name,
    job_definition=batch_job_definition_name,
    overrides=JOB_OVERRIDES,
)

Create an AWS Batch compute environment

To create a new AWS Batch compute environment you can use BatchCreateComputeEnvironmentOperator.

tests/system/providers/amazon/aws/example_batch.py[source]

create_compute_environment = BatchCreateComputeEnvironmentOperator(
    task_id="create_compute_environment",
    compute_environment_name=batch_job_compute_environment_name,
    environment_type="MANAGED",
    state="ENABLED",
    compute_resources={
        "type": "FARGATE",
        "maxvCpus": 10,
        "securityGroupIds": security_groups,
        "subnets": subnets,
    },
)

Sensors

Wait on an AWS Batch job state

To wait on the state of an AWS Batch Job until it reaches a terminal state you can use BatchSensor.

tests/system/providers/amazon/aws/example_batch.py[source]

wait_for_batch_job = BatchSensor(
    task_id="wait_for_batch_job",
    job_id=submit_batch_job.output,
)

In order to monitor the state of the AWS Batch Job asynchronously, use BatchSensor with the parameter deferrable set to True.

Since this will release the Airflow worker slot , it will lead to efficient utilization of available resources on your Airflow deployment. This will also need the triggerer component to be available in your Airflow deployment.

Wait on an AWS Batch compute environment status

To wait on the status of an AWS Batch compute environment until it reaches a terminal status you can use BatchComputeEnvironmentSensor.

tests/system/providers/amazon/aws/example_batch.py[source]

wait_for_compute_environment_valid = BatchComputeEnvironmentSensor(
    task_id="wait_for_compute_environment_valid",
    compute_environment=batch_job_compute_environment_name,
)

Wait on an AWS Batch job queue status

To wait on the status of an AWS Batch job queue until it reaches a terminal status you can use BatchJobQueueSensor.

tests/system/providers/amazon/aws/example_batch.py[source]

wait_for_job_queue_valid = BatchJobQueueSensor(
    task_id="wait_for_job_queue_valid",
    job_queue=batch_job_queue_name,
)

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