Apache Airflow DAG Patterns

airflow-dag-patterns

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

boisenoise/skills-collections·0installs10starsDevOps & CI/CD

SKILL.md

Full skill instructions

Apache Airflow DAG Patterns

Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.

Use this skill when

Creating data pipeline orchestration with Airflow
Designing DAG structures and dependencies
Implementing custom operators and sensors
Testing Airflow DAGs locally
Setting up Airflow in production
Debugging failed DAG runs

Do not use this skill when

You only need a simple cron job or shell script
Airflow is not part of the tooling stack
The task is unrelated to workflow orchestration

Instructions

Identify data sources, schedules, and dependencies.
Design idempotent tasks with clear ownership and retries.
Implement DAGs with observability and alerting hooks.
Validate in staging and document operational runbooks.

Refer to resources/implementation-playbook.md for detailed patterns, checklists, and templates.

Safety

Avoid changing production DAG schedules without approval.
Test backfills and retries carefully to prevent data duplication.

Resources

resources/implementation-playbook.md for detailed patterns, checklists, and templates.

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/boisenoise/skills-collections --skill antigravity-airflow-dag-patterns

View on GitHub

skills/antigravity-airflow-dag-patterns/SKILL.md

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