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Airflow Architecture: Key Components & Best Practices

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Data pipelines and workflows have become an inherent part of the advancements in data engineering, machine learning, and DevOps processes. With ever-increasing scales and complexity, the need to orchestrate these workflows efficiently arises. Table of Contents That is where Apache Airflow steps in —an open-source platform designed to programmatically author, schedule, and monitor workflows. In this blog, we will explain Airflow architecture, including its main components and best practices for implementation. So let’s dive right in! Apache Airflow is an open-source platform responsible for authoring, scheduling, and monitoring workflows. Airflow workflows are defined as Directed Acyclic Graphs(DAGs), implying that the tasks in a workflow should be executed in a specific order to ensure that one task is completed before starting the execution of the next. It was designed by Airbnb to replace the need for a scalable platform to maintain workflows. It quickly became one of the most popula

Table of Contents Try Hevo for Free Share Share To LinkedIn Share To Facebook Share To X Copy Link Data pipelines and workflows have become an inherent part of the advancements in data engineering, machine learning, and DevOps processes. With ever-increasing scales and complexity, the need to orchestrate these workflows efficiently arises.  That is where Apache Airflow steps in —an open-source platform designed to programmatically author, schedule, and monitor workflows. In this blog, we will explain Airflow architecture, including its main components and best practices for impleme

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