Airflow Background Jobs
Apache Airflow is a platform to programmatically author, schedule, and monitor workflows. It is used for data processing pipelines, data migration, and data processing tasks.
- Since:2015
- Discord:@airflow
- Dockerhub:airflow
- Docs:airflow.apache.org
- Github Topic:apache-airflow
- License:github.com
- Official:airflow.apache.org
- Reddit:r/apacheairflow
- Repository:github.com
- Twitter:@ApacheAirflow
- Wikipedia:Apache_Airflow
#What is Airflow?
Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It allows users to define workflows as Directed Acyclic Graphs (DAGs) of tasks and dependencies, which can be executed on a variety of platforms. Airflow includes a scheduler, a web interface for monitoring and managing workflows, and an extensive library of connectors and operators to interact with external systems.
#Airflow Key Features
Most recognizable Airflow features include:
- DAG-based task scheduling and execution
- Dynamic task generation and scheduling
- Advanced task dependencies and triggers
- Rich set of operators and connectors for integration with external systems
- Web-based interface for monitoring and managing workflows
- Extensible architecture for custom operators and plugins
#Airflow Use-Cases
Some of the Airflow use-cases are:
- ETL (Extract, Transform, Load) pipelines
- Machine learning workflows
- Data processing and analysis
- Reporting and visualization
- CI/CD (Continuous Integration/Continuous Deployment)
- Task automation and orchestration
#Airflow Summary
Airflow is an open-source platform for authoring, scheduling, and monitoring workflows, based on DAGs of tasks and dependencies. Its key features include dynamic task generation, advanced task dependencies, a rich set of operators and connectors, a web-based interface, and an extensible architecture. Airflow is used for various purposes, such as ETL pipelines, machine learning workflows, and CI/CD automation.
