Execute a job on AWS Batch

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Last Updated: Apr. 12, 2023

Access Instructions

Install the Amazon provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.


job_nameRequiredthe name for the job that will run on AWS Batch (templated)
job_definitionRequiredthe job definition name on AWS Batch
job_queueRequiredthe queue name on AWS Batch
overridesRequiredthe containerOverrides parameter for boto3 (templated)
array_propertiesthe arrayProperties parameter for boto3
parametersthe parameters for boto3 (templated)
job_idthe job ID, usually unknown (None) until the submit_job operation gets the jobId defined by AWS Batch
waitersan BatchWaiters object (see note below); if None, polling is used with max_retries and status_retries.
max_retriesexponential back-off retries, 4200 = 48 hours; polling is only used when waiters is None
status_retriesnumber of HTTP retries to get job status, 10; polling is only used when waiters is None
aws_conn_idconnection id of AWS credentials / region name. If None, credential boto3 strategy will be used.
region_nameregion name to use in AWS Hook. Override the region_name in connection (if provided)
tagscollection of tags to apply to the AWS Batch job submission if None, no tags are submitted


Execute a job on AWS Batch

See also

For more information on how to use this operator, take a look at the guide: Submit a new AWS Batch job


Any custom waiters must return a waiter for these calls: .. code-block:: python

waiter = waiters.get_waiter(“JobExists”) waiter = waiters.get_waiter(“JobRunning”) waiter = waiters.get_waiter(“JobComplete”)

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