Managed Airflow Migrations
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- Workflow
- Cloud and DevOps
- Apache-2.0
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill assists developers in migrating Apache Airflow DAGs from existing Managed Service for Apache Airflow environments to Airflow 2.11.1 or Airflow 3. It provides a systematic approach including environment inspection, dependency mapping, code scanning for breaking changes, and deployment verification. The skill covers specific remediation steps for provider package updates, core Airflow changes, and deprecated features, ensuring compatibility with the target environment.
What it does
- Guides the inspection and download of existing DAG files from Managed Service for Apache Airflow environments.
- Maps dependency version progressions for Google, SSH, and HTTP providers.
- Provides scan commands to identify breaking changes in DAG code, such as deprecated operators and API changes.
- Offers remediation steps for upgrading to Airflow 2.11.1 and Airflow 3.
- Facilitates deployment of migrated DAGs to target GCS buckets.
- Supports verification of migrated DAGs using Airflow CLI and Cloud Logging.
When to use it
- When planning to migrate existing DAGs to Airflow 2.11.1 or Airflow 3 in Managed Service for Apache Airflow.
- When identifying necessary code changes due to provider package upgrades.
- When refactoring legacy DAG features like SubDAGs or SLAs for newer Airflow versions.
- When verifying the successful registration and parsing of migrated DAGs in a target environment.
Advantages
- Provides a clear, phased approach to complex Airflow version migrations.
- Includes specific grep-based scan patterns to quickly locate code requiring updates.
- Offers actionable remediation advice for common breaking changes.
- Ensures consistent deployment and verification practices using standard CLI tools.
Usage examples
- “How do I identify if my DAGs use operators that were removed in recent Google provider versions?”
- The agent will provide specific grep commands to scan your local DAG directory for deprecated operators like BigQueryExecuteQueryOperator or AutoML operators.
- “I am migrating to Airflow 3. What changes do I need to make to my imports?”
- The agent will guide you through updating imports to the decoupled Airflow SDK and standard provider bundles, such as changing airflow.DAG to airflow.sdk.DAG.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/google/managed-airflow-migrations/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip managed-airflow-migrations.zip -d .agents/skills
Documentation by Google
Managed Service for Apache Airflow (formerly Cloud Composer) Migration Guide
This skill guides you through the process of adjusting Airflow DAGs from an existing Managed Service for Apache Airflow (formerly Cloud Composer) environment (or available locally) to make them compatible with Airflow 2.11.1 (MSAA Gen 2 or 3) or Airflow 3 (MSAA Gen 3).
Attribution
MUST READ: Before executing any gcloud, REST API, or MCP command, you
MUST read Usage Attribution. For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix gcloud with
CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:managed-airflow-migrations)"
and append agent-skills/1.0 (skill:managed-airflow-migrations) to User-Agent headers.
Phase 1: Discovery & Download
Before making any changes, download the existing DAG files if explicitly requested. Inspect the source environment to confirm source version only if explicitly requested. For detailed instructions about environment inspection and downloading files check references/environment-inspection.md.
Phase 2: Target Version & Dependency Mapping
2.1 Airflow 2.11.1+ Dependency Mapping
If migrating to Airflow 2.11.1 (MSAA Gen 2) or Airflow 3, use the list below to trace the version progression of key dependencies. The list covers changes needed to get to Airflow 2.11.1. Take them into account when migrating from Airflow 2 (earlier than 2.11.1) to Airflow 3.
Composer 2.10.0 (Airflow 2.10.2)
Google Provider:
10.26.0SSH Provider:
3.14.0HTTP Provider:
4.13.3Breaking Changes: Baseline for oldest fully documented source.
Composer 2.15.3 (Airflow 2.10.5)
Google Provider:
18.0.0SSH Provider:
4.1.4HTTP Provider:
5.3.4Breaking Changes:
SSH Provider 4.0.0: Hook
timeoutremoved;get_conn()context manager.HTTP Provider 5.0.0:
SimpleHttpOperator->HttpOperator.Google Provider 11.0.0:
BigQueryExecuteQueryOperatorremoved.Google Provider 12.0.0: Legacy Data Pipeline operators removed.
Google Provider 13.0.0:
AutoMLBatchPredictOperatorremoved.Google Provider 17.0.0:
BigQueryCreateEmptyTableOperatorandBigQueryCreateExternalTableOperatorremoved; Life Sciences operators removed.Google Provider 18.0.0: Legacy DV360 operators removed.
Composer 2.16.1 (Airflow 2.10.5)
Google Provider:
19.0.0SSH Provider:
4.1.6HTTP Provider:
5.5.0Breaking Changes: Google Provider 19.0.0: AutoML operators removed (use Vertex AI).
Composer 2.17.0 (Target Airflow 2.11.1)
Google Provider:
20.0.0SSH Provider:
5.0.0HTTP Provider:
6.0.2Breaking Changes:
SSH Provider 5.0.0:
sshtunnelremoved (native tunneling).HTTP Provider 6.0.0: JSON serialization.
Google Provider 20.0.0: ADLS Gen2 migration.
2.2 Airflow 3 Migration
If migrating to Airflow 3 (MSAA Gen 3), note that this is a major version upgrade with significant changes, including:
Decoupled Task SDK (imports change from
airflowtoairflow.sdk).Removal of direct metadata DB access.
Renaming of
DatasettoAsset.Removal of SubDAGs and SLAs.
Changes to context variables availability.
Take into account all applicable changes within Airflow 2 (e.g. when migrating from Airflow 2.10.2, apply changes needed to move to Airflow 2.11.1 and Airflow 3 migration changes on top of that).
Phase 3: Analysis & Remediation (Scanning Downloaded Files)
Run the scan commands from the root of your local workspace
(./migration_workspace unless indicated otherwise).
3.1 Airflow 2.11.1 Core & Dependency checks
Use these scans if migrating to Airflow 2.11.1+ (intermediate step when migrating to Airflow 3).
3.1.1 Dataset Scheduling (Airflow 2.11.0)
Change: DAGs scheduled on datasets only trigger if events occur while the DAG is unpaused.
Scan Command:
grep -rn "Dataset(" ./dagsRemediation: You MUST document that these DAGs must remain unpaused to catch events, or plan manual triggers for catch-up.
3.1.2 HTML in Descriptions (Airflow 2.11.0)
Change: Raw HTML in DAG docs / params is escaped by default.
Scan Command:
grep -rn -E "doc_md.*<|doc_md.*>|description.*<|description.*>" ./dagsRemediation: Convert HTML to Markdown, or set
AIRFLOW__WEBSERVER__ALLOW_RAW_HTML_DESCRIPTIONS=Truein target.
3.1.3 Teardown Tasks (Airflow 2.10.5)
Change: Teardowns always run when a DAG is marked failed.
Scan Command:
grep -rn "as_teardown" ./dagsRemediation: Ensure teardown tasks are idempotent.
3.1.4 Pendulum 3 Upgrade (Airflow 2.11.0)
Change:
Periodrenamed toInterval, testing helpers removed.Scan Command (Code):
grep -rn -E "pendulum\.Period|pendulum\.period" ./dagsScan Command (Tests):
grep -rn -E "\.test\(|set_test_now\(" ./tests 2>/dev/null || trueRemediation: Replace
PeriodwithInterval, andperiod(...)withinterval(...).
3.2 Path A: Airflow 2.11.1 Provider Package Scan
3.2.1 SSH Provider (SSH 4.0.0 & 5.0.0)
Scan Command (Timeout):
grep -rn "SSHHook" ./dags | grep "timeout"Scan Command (Context Manager):
grep -rn "with SSHHook" ./dagsScan Command (Tunnel Attributes):
grep -rn "\.get_tunnel" ./dagsRemediation:
Replace
timeoutwithconn_timeoutinSSHHook.Replace
with hook as conn:withwith hook.get_conn() as conn:.Use
get_tunnel()as context manager:with hook.get_tunnel(...) as tunnel:.
3.2.2 HTTP Provider (HTTP 5.0.0 & 6.0.0)
Scan Command:
grep -rn "SimpleHttpOperator" ./dagsRemediation: Replace
SimpleHttpOperatorwithHttpOperator.
3.2.3 Google Provider (v11 to v20)
Scan Command (BigQuery query):
grep -rn "BigQueryExecuteQueryOperator" ./dagsRemediation: Replace with
BigQueryInsertJobOperator(useconfigurationdict).
Scan Command (BigQuery table):
grep -rn -E "BigQueryCreateEmptyTableOperator|BigQueryCreateExternalTableOperator" ./dagsRemediation: Replace with
BigQueryCreateTableOperator(usetable_resourcedict).
Scan Command (AutoML):
grep -rn -E "AutoMLTrainModelOperator|AutoMLPredictOperator|AutoMLCreateDatasetOperator|AutoMLBatchPredictOperator" ./dagsRemediation: Migrate to Vertex AI operators.
Scan Command (Dataflow):
grep -rn -E "CreateDataPipelineOperator|RunDataPipelineOperator" ./dagsRemediation: Replace with
DataflowCreatePipelineOperator/DataflowRunPipelineOperator.
Scan Command (Life Sciences):
grep -rn "LifeSciencesRunPipelineOperator" ./dags`Remediation: Migrate to Google Cloud Batch operators (
BatchCreateJobOperator).
Scan Command (ADLS to GCS):
grep -rn "ADLSToGCSOperator" ./dagsRemediation: Ensure
file_system_nameis provided.
3.3 Airflow 3 Migration checks
Use instructions from references/airflow-3.md when migrating to Airflow 3.
Phase 4: Deployment & Verification
Perform deployment and verification steps only if explicitly requested to do so.
4.1 Static Verification (when migrating to Airflow 3)
After applying code changes for Airflow 3, verify syntax correctness. If available in the development environment, run static lint checks:
ruff check {target_dag_file} --select AIR30Resolve any reported deprecation warnings before finalization. If ruff is not available, recommend installing one.
4.2 Deployment to MSAA
4.2.1 Get Target GCS Bucket Path (only when requested)
gcloud composer environments describe <TARGET_ENV> \
--location <TARGET_REGION> \
--format="value(config.dagGcsPrefix)"Expected Output: gs://<target-bucket-name>/dags
4.2 Upload Modified DAGs and Bucket Dependencies (Only when requested)
Perform this step only if explicitly requested to do so. Copy the modified
DAGs and any backed-up bucket dependencies from your local workspace to the
target GCS bucket. If you skipped the inspection step, ensure you have the
correct <target-bucket-name>.
Upload DAGs:
gcloud storage cp -r ./dags/* gs://<target-bucket-name>/dags/Upload Other Bucket Dependencies (If applicable):
gcloud storage cp -r ./migration_workspace/<dependency-folder> gs://<target-bucket-name>/<dependency-folder>
4.3 Verify DAGs via Airflow CLI
Perform this step only if explicitly requested to upload modified DAGS to a target environment (and after uploading).
You can verify that your DAGs have been successfully uploaded, parsed, and registered by the Airflow scheduler in the target environment using the Airflow CLI.
List Registered DAGs: Run the following command to list all DAGs registered in the target environment. Verify that your migrated DAGs appear in this list.
gcloud composer environments run <TARGET_ENV> \ --location <TARGET_REGION> \ dags listCheck for Import Errors: If some DAGs are missing from the list, or to ensure there are no parsing issues, check for import errors:
gcloud composer environments run <TARGET_ENV> \ --location <TARGET_REGION> \ dags list-import-errorsExpected Output:
If there are no errors, the command will output
No data found.If there are errors, it will list the file path and the traceback of the error.
Note: It may take a couple of minutes for the Airflow scheduler to parse the new files and for changes to reflect in these commands.
4.4 Verify in Cloud Logging
Perform this step only if explicitly requested to upload modified DAGS to a target environment (and after uploading). Monitor Cloud Logging for the target environment to detect any runtime errors or import errors.
Run the following query in the GCP Cloud Logging Console (or via gcloud logging read):
resource.type="cloud_composer_environment"
resource.labels.environment_name="<TARGET_ENV>"
log_id("airflow-scheduler")
severity>=ERRORAppendix: Local Environment Verification
If you want to verify your changes locally before deploying to the target
environment, you can use the Composer Local Development CLI tool
(composer-dev). Use
references/local-development-environment.md
as a reference for interactions with local development environments.
Files
- ATTRIBUTION.mdAdded by AutoGineer870 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md12.1 KiB
- references/airflow-3.md8.0 KiB
- references/attribution.md1.9 KiB
- references/environment-inspection.md2.9 KiB
- references/local-development-environment.md919 B
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
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- google/skills · skills/cloud/managed-airflow-migrations · commit 2194d3b
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