mwaa-dr
DR Solution for Amazon Managed Workflows for Apache Airflow (MWAA)
Decision gist · record as of 2026-08-14
Yes. If you operate Amazon MWAA and need disaster recovery for metadata, this library eliminates boilerplate code and provides a tested, actively maintained solution. Install friction is minimal, and the package is production-stable. The unclear license requires review, but the permissive grant language suggests low risk for most use cases.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires MWAA execution role to have read/write permissions on the target S3 bucket; an Airflow variable DR_BACKUP_BUCKET must be set with the bucket name (not ARN)
- Low friction: pure Python wheel with a single runtime dependency (smart-open).
- Actively maintained with recent commits and production-stable classification.
License · maintenance · safety
(unclear) — License treatment is unclear—the package carries an Amazon copyright with a permissive grant but lacks an SPDX identifier. Review the full license text before use in proprietary or commercial contexts.
last release 2026-03-30 (137 days) · last repo commit 2026-04-27 · 12 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 384,178 downloads/mo, #7,067 on PyPI
Alternatives
Verify before relying
from mwaa_dr.v_2_10.dr_factory import DRFactory_2_10
factory = DRFactory_2_10(
dag_id='backup',
path_prefix='data',
storage_type='S3'
)
dag = factory.create_backup_dag()- Whether the unclear license is compatible with your organization's licensing policy
- Minimum MWAA version compatibility beyond the documented examples (2.7.2, 2.10.3)
- Whether smart-open's dependencies introduce additional install friction or licensing constraints
What it is and what it does
mwaa-dr is a Python library that generates DAGs to automate backup, restore, and cleanup of Amazon MWAA metadata stores. It addresses the constraint that MWAA metadata access is only available through DAGs by providing factory classes that generate these DAGs for you, eliminating manual DAG creation.
The library handles metadata export to S3 or local filesystem, supports configurable restore strategies for variables and connections (DO_NOTHING, APPEND, REPLACE), and allows customization through inheritance to include or exclude specific tables. It depends on smart-open for storage abstraction and requires Python 3.7 or later.
Use it for
- Automate regular metadata backups of your MWAA environment to S3 for disaster recovery
- Restore a MWAA metadata store from backup after environment failure or data loss
- Exclude sensitive tables from backup when using AWS Secrets Manager for variables and connections
- Customize backup scope by extending factory classes to add or remove specific metadata tables
- Test configurations locally using the LOCAL_FS storage type
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
If you operate Amazon MWAA and need disaster recovery for metadata, this library eliminates boilerplate code and provides a tested, actively maintained solution. Install friction is minimal, and the package is production-stable. The unclear license requires review, but the permissive grant language suggests low risk for most use cases.
Install
mwaa-dr on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (smart-open). Actively maintained with recent commits and production-stable classification.
Requires MWAA execution role to have read/write permissions on the target S3 bucket; an Airflow variable DR_BACKUP_BUCKET must be set with the bucket name (not ARN)
License in practice
License treatment is unclear—the package carries an Amazon copyright with a permissive grant but lacks an SPDX identifier. Review the full license text before use in proprietary or commercial contexts.
Quickstart
from mwaa_dr.v_2_10.dr_factory import DRFactory_2_10
factory = DRFactory_2_10(
dag_id='backup',
path_prefix='data',
storage_type='S3'
)
dag = factory.create_backup_dag()Verify before relying
- Whether the unclear license is compatible with your organization's licensing policy
- Minimum MWAA version compatibility beyond the documented examples (2.7.2, 2.10.3)
- Whether smart-open's dependencies introduce additional install friction or licensing constraints
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagesmart-open |
| Maintenance | Actively maintained 137 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 384,178 / month, #7,067 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableProgramming Language :: Python |
Evidence: mwaa_dr-2.2.0-py3-none-any.whl
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See also dag-factory · openlineage-airflow · acryl-datahub-airflow-plugin · airflow-exporter · astronomer-starship · airflow-code-editor · apache-airflow-core · apache-airflow-providers-git · astro-airflow-mcp · django-dbbackup