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Amazon Managed Workflows for Apache Airflow (MWAA)

Description

This module:

  • creates an Amazon Managed Airflow Environment to execute DAGs created by other modules
  • creates an IAM Role (the MWAA Execution Role) with least privilege permissions
  • Optionally creates an S3 Bucket to store DAG artifacts

Limitations

When deploying an MWAA environemnt, an S3 bucket is used to store supporting files such as requirements, plugins and dags. This module will create a bucket if not one provided in the parameter dag-bucket-name. IDF does support multiple MWAA modules in a single deployment, but due to the nature of how MWAA is managed at AWS, MWAA modules CANNOT SHARE the buckets that store the requirements, plugins or dags. EACH MWAA module deployed requires a separate bucket for these artifacts.

In other words, if the dag-bucket-name is MY_AWESOME_BUCKET_NAME then ONLY ONE MWAA module can refer to that bucket to store dags (as well as plugins and requirements). So, pick a unique bucket per MWAA module deployment.

Inputs/Outputs

Input DataFiles

Required

NA

Optional

  • dataFiles: User can optionally provide filePath reference to a custom airflow requirements.txt file(available locally/remote) and should make sure to provide the value of the filepath as an environment variable under Parameters. Following is the reference implementation using dataFiles:
  • solution-id: a unique identifier for this deployment (must be used with solution-description)
  • solution-name: a unique name for this deployment (must be used with solution-id)
  • solution-version: a unique version for this deployment

The parameters (solution-*) will resolve a custom text that is used as a description of the stack if populated.

name: mwaa
path: modules/orchestration/mwaa/
dataFiles:
  - filePath: data/mwaa/requirements/requirements-emr-serverless.txt
parameters:
  - name: custom-requirements-path
    value: data/mwaa/requirements/requirements-emr-serverless.txt

Input Paramenters

Required

  • vpc-id: VPC Id where the MWAA Environment will be deployed
  • private-subnet-ids: List of Private Subnets Ids where the MWAA Environment will be deployed

Optional

  • dag-bucket-name: name of the S3 Bucket to configure the MWAA Environment to monitor for DAG artifacts. An S3 Bucket is created if none is provided
  • dag-path: path in the S3 Bucket to configure the MWAA Environment to monitor for DAG artifacts. Defaults to dags if none is provided
  • environment-class: the MWAA Environement Instance Class. Defaults to mw1.small if none is provided
  • max-workers: the Maximum number of workers to configure the MWAA Environment to allow. Defaults to 25 if none is provided
  • airflow-version: The Airflow version you would want to set in the module. It is defaulted to 2.5.1
  • mwaa-requirements-file - Support for customized requiremements file installed on MWAA
    • ANY file referenced MUST be located modules/core/mwaa/requirements/*.txt and be python requirements compliant
    • in if not provided, default is requirements.txt

Module Metadata Outputs

  • DagBucketName: name of the S3 Bucket configured to store MWAA Environment DAG artifacts
  • DagPath: name of the path in the S3 Bucket configured to store MWAA Environment DAG artifacts
  • MwaaExecRoleArn: ARN of the MWAA Execution Role created by the Stack

Output Example

{
    "DagBucketName": "some-bucket",
    "DagPath": "dags",
    "MwaaExecRoleArn": "arn:::::"
}