Apache Airflow is a platform to programmatically author, schedule, and monitor workflows. It enables defining complex data pipelines as code with rich scheduling and monitoring.
Key Concepts
DAGs (Directed Acyclic Graphs)
Operators and hooks
Task dependencies
XCom for communication
Sensors for waiting
Common Use Cases
ETL pipelines
ML pipelines
Data orchestration
Batch processing
Workflow automation
Best Practices
Keep DAGs simple and flat
Use proper task grouping
Implement retry strategies
Use connections properly
Monitor with Airflow UI
Resources
Airflow.apache.org: airflow.apache.org/docs
Related Skills: data-engineering, python, kubernetes
1---2name: airflow-23description: Apache Airflow4---5# Apache Airflow67Apache Airflow is a platform to programmatically author, schedule, and monitor workflows. It enables defining complex data pipelines as code with rich scheduling and monitoring.89## Key Concepts1011- DAGs (Directed Acyclic Graphs)12- Operators and hooks13- Task dependencies14- XCom for communication15- Sensors for waiting1617## Common Use Cases1819- ETL pipelines20- ML pipelines21- Data orchestration22- Batch processing23- Workflow automation2425## Best Practices2627- Keep DAGs simple and flat28- Use proper task grouping29- Implement retry strategies30- Use connections properly31- Monitor with Airflow UI3233## Resources3435- Airflow.apache.org: airflow.apache.org/docs36- Related Skills: data-engineering, python, kubernetes
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Apache Airflow It is listed under AI & ML on SkillMD.
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