Apache Airflow
UnclaimedAuthor, schedule, and monitor workflows programmatically with Python
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About Apache Airflow
Orchestrating complex data pipelines with basic cron jobs and static configuration files makes dependencies hard to track. Teams struggle to scale execution, monitor task failures, and maintain custom integration code across multiple cloud services.
Apache Airflow is an open-source platform used to programmatically author, schedule, and monitor workflows. Pipelines are defined directly in Python, enabling teams to build dynamic workflows, configure parameterization with Jinja templating, and write custom operators.
The system uses a modular architecture with message queues to distribute tasks across an arbitrary number of workers. A built-in web interface lets users manage task execution, inspect logs, and track pipeline status in real time.
Airflow includes plug-and-play integrations for third-party platforms such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure, allowing users to orchestrate data transfers, infrastructure management, and machine learning pipelines.
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- Custom workflows
- Plugins and actions
- Review scheduling
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