O essencial sobre Apache Airflow

Airflow: A Comprehensive Introduction to Workflow Orchestration

Discover Apache Airflow, a powerful open-source workflow management platform originally created by Airbnb and now maintained by the Apache Foundation. This Python-based software, released in 2015, has become a leading solution for orchestrating data pipelines and scheduling tasks.

At its core, Airflow uses Directed Acyclic Graphs (DAGs) defined in Python to sequence and manage complex workflows. These DAGs provide a clear and organized way to define dependencies between tasks, ensuring they run in the correct order.

Key Components of Apache Airflow:

• Airflow.cfg: Configuration file for managing Airflow settings.
• Web Server: Provides a user-friendly interface for monitoring and managing workflows.
• Scheduler: Responsible for monitoring DAGs and triggering tasks based on defined schedules and dependencies.
• Metadata Database: Stores information about DAGs, tasks, and their execution status.
• Executors: Execute the tasks defined in the DAGs, supporting various execution environments.

This course provides a detailed introduction to these tools and how they work together to enable you to program and automate complex data workflows. You'll learn how to define and manage acyclic task sequences using a wide range of execution options, including Python interpreters, Docker containers, and bash commands.

Who is this course for?

This course is designed for individuals with no prior experience with Apache Airflow or other DAG-based workflow management systems. It's a perfect starting point for anyone looking to master workflow automation and data pipeline management.

This course was developed as part of a scientific initiation project at the Federal University of São Francisco Valley.