mwaa-dr

import os from airflow import DAG from airflow.utils.dates import days_ago from mwaa_dr.v_2_10.dr_factory import DRFactory_2_10 # Ensure DR_BACKUP_BUCKET Airflow Variable is set in your MWAA environment # and MWAA execution role has read/write permissions on it. # Example: DR_BACKUP_BUCKET = 'your-mwaa-backup-bucket' # Initialize the DRFactory for your MWAA/Airflow version # For local testing with aws-mwaa-local-runner, use storage_type='LOCAL_FS' # and create a 'data' folder in your dags directory. factory = DRFactory_2_10( dag_id='backup_metadata_example', path_prefix='data', # Relative path within the S3 bucket or local_fs storage_type='S3' # Or 'LOCAL_FS' for local development ) # Create a backup DAG backup_dag: DAG = factory.create_backup_dag( schedule_interval='@daily', # Example schedule start_date=days_ago(1) ) # Create a restore DAG (typically disabled by default, meant for manual trigger) restore_dag: DAG = factory.create_restore_dag( dag_id='restore_metadata_example', start_date=days_ago(1), is_paused_upon_creation=True # Recommended for restore DAGs ) # Create a cleanup DAG (for emptying metadata tables before restore, use with caution) cleanup_dag: DAG = factory.create_cleanup_dag( dag_id='cleanup_metadata_example', start_date=days_ago(1), is_paused_upon_creation=True # Recommended for cleanup DAGs )