Individual skill
migrating-dagster-to-airflow
Guide for migrating Dagster projects to Apache Airflow 3 on Astro. Use when the user mentions migrating, converting, or porting Dagster (or Dagster+) code to Airflow or Astro, wants to plan or assess such a migration, or asks what a Dagster construct maps to in Airflow. Covers assets, partitions, schedules, sensors, declarative automation, resources, IO managers, ops/jobs, dbt, Pipes, Components, and Dagster+ platform config. Always load this skill as the first step for any Dagster-to-Airflow request.
skills/migrating-dagster-to-airflow/SKILL.md
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- agents Repository topic
- ai Repository topic
- airflow Repository topic
- data-engineering Repository topic
- mcp Repository topic
- skills Repository topic
- claude Repository topic
- cursor Repository topic
- apache-airflow Repository topic
- agentic-workflow Repository topic
- engineering Derived category
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README.mddoc · 4,196 bytesSKILL.mdcore · 15,137 bytesSKILL.mdcore · 15,137 bytesSKILL.mdcore · 15,137 bytesSKILL.mdcore · 15,137 bytesSKILL.mdcore · 15,137 bytesSKILL.mdcore · 15,137 bytesSKILL.mdcore · 15,137 bytesreference/assets.mddoc · 5,219 bytesreference/astro-deployment.mddoc · 12,564 bytesreference/automation.mddoc · 12,067 bytesreference/components.mddoc · 5,302 bytesreference/dbt.mddoc · 26,692 bytesreference/io-and-data-passing.mddoc · 10,693 bytesreference/mapping.mddoc · 25,880 bytesreference/partitions.mddoc · 12,554 bytesreference/quickstart.mddoc · 5,423 bytesreference/troubleshooting.mddoc · 16,366 bytesreference/validation.mddoc · 17,829 bytesscripts/inventory.pyruns · 43,551 bytesscripts/pyproject.tomlasset · 653 bytesscripts/status.pyruns · 15,374 bytesscripts/tests/conftest.pyruns · 3,909 bytesscripts/tests/test_inventory.pyruns · 6,150 bytesscripts/tests/test_merge.pyruns · 4,626 bytesscripts/tests/test_status.pyruns · 4,662 bytesscripts/tests/test_validate_dag.pyruns · 4,622 bytesscripts/uv.lockasset · 24,202 bytesscripts/validate_dag.pyruns · 18,958 bytes
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# Dagster → Airflow 3 (Astro) migration
Migrate a Dagster project to Airflow 3 on Astro Runtime, honestly. The migration is asset-first (Dagster asset graphs translate to Airflow assets and asset-aware schedules, not flattened DAGs), incremental (domain by domain, Dagster stays authoritative until parity), and honest (every definition gets an explicit disposition; semantic deltas are documented, never papered over).
First time driving this? Read `reference/quickstart.md` first: hour-one commands, the glossary, and what can and cannot break.
## Migration at a glance
1. Baseline the source project's tests, then inventory it read-only (`scripts/inventory.py` → manifest).
2. Review classifications (MECH/JUDG/REDESIGN/NONE per `reference/mapping.md`); make the go/no-go call (three outcomes; migrate-with-conditions is the common case, stay is the narrow one); plan DAG boundaries, per-edge IO decisions, and Gate 3 expectations into the manifest.
3. Trial-migrate 2-3 representative units end-to-end through every validation gate.
4. Migrate domain by domain through the six-gate ladder (`reference/validation.md`), tracking per-unit state (`scripts/status.py`); fix failure classes via `reference/troubleshooting.md`, never stub.
5. Map the platform layer (secrets, alerts, CI/CD, Deployments) per `reference/astro-deployment.md`.
6. Run side by side, then cut over per domain (consumers unpause first; see the checklist), keeping rollback one step away.