What you can do with Apache Airflow
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13 things you can do
Apache Airflow
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows, developed by the Apache Software Foundation. It allows you to define workflows as Directed Acyclic Graphs (DAGs) in Python code, making them maintainable, versionable, testable, and collaborative. Airflow provides a stable REST API for managing DAGs, DAG runs, tasks, connections, variables, pools
13 multi-step recipesRecipes: multi-step jobs
Audit DAG Runs Across the FleetBatch-report failed runs and task instances across many DAGs in a time window.Collect DAG Run Results from XCom
Retrieve the XCom value a finished DAG run's task published.Deployment Preflight Check
Gate on Airflow health, then report import errors and DAG warnings.Diagnose a Failed DAG Run
Find the failed task in a DAG run, retrieve its log, and annotate the finding.Force a Task Instance State
Override a task instance's state after previewing the affected instances.Onboard a DAG
Assemble a complete read-only briefing on a single DAG.Provision a User with a Role
Create a role if needed, then create a user assigned to it and verify.Register a Connection After Testing It
Validate connection credentials, then persist and verify the connection.Retry Failed Tasks in a DAG Run
Dry-run a clear, execute it, and wait for the resulting re-run to finish.Trace Dataset-Driven Lineage
Trace a dataset's producers, consumers, update events, and the run it triggered.Trigger a DAG Run and Wait for Completion
Trigger an Airflow DAG run and block until it succeeds or fails.Upsert a Slot Pool
Create an Airflow pool or resize it if it already exists.Upsert a Variable
Create or update an Airflow variable by key.