![]() ![]() As a result, is an ideal solution for ETL and MLOps use cases. ![]() What is Airflow?Īpache Airflow is a tool for authoring, scheduling, and monitoring pipelines. It also enables you to automatically re-run them after failure, manage their dependencies and monitor them using logs and dashboards.īefore we build the aforementioned pipeline, let’s understand the basic concepts of Apache Airflow. On the other hand, Airflow offers the ability to schedule and scale complex pipelines easily. ![]() Most importantly, they won’t allow you to scale effectively. How would you schedule and automate this workflow? Cron jobs are a simple solution but they come with many problems. Train a deep learning model with the downloaded images Read an image dataset from a cloud-based storage Imagine that you want to build a machine learning pipeline that consists of several steps such as: In this article, I will attempt to outline its main concepts and give you a clear understanding of when and how to use it. It has gained popularity, contary to similar solutions, due to its simplicity and extensibility. In Airflow 1.x, this task is defined as shown below:Īirflow/example_dags/tutorial_dag.Apache Airflow has become the de facto library for pipeline orchestration in the Python ecosystem. Let’s examine this in detail by looking at the Transform task in isolation since it is in the middle of the data pipeline.
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