Description: Apache Airflow is an open-source platform used for programmatically authoring, scheduling, and monitoring workflows. It provides a way to define complex workflows as code, allowing users to easily manage and orchestrate tasks across different systems and technologies. Airflow uses Directed Acyclic Graphs (DAGs) to represent workflows, where each task is a node in the graph and the dependencies between tasks are represented by edges. It offers a rich set of operators to perform various tasks, such as running scripts, executing SQL queries, transferring data, and more. Airflow also provides a web-based user interface for visualizing and monitoring workflow execution. Additional information: Apache Airflow is designed to be highly scalable, fault-tolerant, and extensible. It allows users to define workflows using Python code, making it flexible and customizable. Airflow supports various integrations with popular technologies like databases, cloud platforms, message queues, and more, enabling seamless integration with existing systems. It provides features like task retries, task dependencies, parallel execution, and monitoring capabilities, making it suitable for managing complex data pipelines, ETL processes, and batch processing workflows. With its modular architecture and active community support, Apache Airflow has become a popular choice for workflow management in the IT industry. Example: An example of using Apache Airflow is to create a data pipeline for processing and analyzing customer data. The workflow can include tasks like extracting data from multiple sources, transforming and cleaning the data, loading it into a database, running machine learning models, and generating reports. By defining this workflow in Airflow, it becomes easy to schedule and monitor the execution of each task, handle failures, and ensure the overall data pipeline runs smoothly. The web-based UI of Airflow provides a visual representation of the workflow, allowing users to track the progress, view logs, and troubleshoot any issues that may arise during execution. Publisher: Apache Airflow Documentation Source: https://airflow.apache.org/docs/ LOST view: TVA-Orchestration Enablers [Motivation] Identifier: http://data.europa.eu/dr8/egovera/ApacheAirflowApplicationService EIRA traceability: eira:DigitalSolutionApplicationService EIRA concept: eira:SolutionBuildingBlock Last modification: 2023-07-20 dct:identifier: http://data.europa.eu/dr8/egovera/ApacheAirflowApplicationService dct:title: Apache Airflow Application Service