airflow-dag-patterns

This skill provides production-ready patterns for Apache Airflow, focusing on DAG design, operators, sensors, testing, and deployment strategies. It enables users to create robust and maintainable data pipelines, orchestrate complex workflows, and schedule batch jobs with confidence.

The skill offers guidance on designing DAG structures, implementing custom operators and sensors, testing Airflow DAGs locally, setting up Airflow in production environments, and effectively debugging failed DAG runs. It emphasizes best practices for idempotency, observability, and alerting to ensure reliable and efficient workflow execution.

Refer to the provided implementation playbook for detailed patterns, checklists, and templates to accelerate the development and deployment of production-grade Airflow DAGs.

What It Does

Provides production-ready patterns and best practices for designing, building, testing, and deploying Apache Airflow DAGs for data pipeline orchestration and workflow management.

When To Use

Use this skill when creating data pipelines, orchestrating workflows, scheduling batch jobs with Apache Airflow, and requiring guidance on best practices for DAG design, testing, and deployment.

Installation

Copy SKILL.md to your skills directory