Running Airflow DAGs with ADF
ADF’s Managed Airflow service provides a streamlined and effective solution for creating and managing Apache Airflow environments, simplifying the execution of data pipelines at scale. Apache Airflow, an open-source platform, empowers users to programmatically design, schedule, and monitor intricate data workflows. By defining tasks as operators and arranging them into directed acyclic graphs (DAGs), Airflow facilitates the representation of data pipelines. It enables scheduled or event-triggered execution of DAGs, real-time workflow monitoring, and task status visibility, making it a popular choice in data engineering and science for orchestrating data pipelines due to its adaptability, extensibility, and user-friendliness. In this recipe, we will run an existing pipeline with Managed Airflow.
Getting ready
Before we start, please ensure that you have an Azure subscription, Azure storage account, and ADF pipeline set up.
