Apache Airflow: automation features and setup

Overview

Apache Airflow suits teams that want to describe data pipelines and workflows as a graph of tasks in code, schedule them, and see what is running or has failed. Write a DAG, define dependencies, and monitor runs. It is a community platform, not a single cloud product. Before adopting it, plan hosting, interface permissions, and who maintains plugins. A simple business workflow with two integrations may be more platform than you need.

Features

• Write workflows as a graph of tasks in code
• Schedule runs and monitor successes and failures
• Plugins for connecting data sources and systems

Business uses

• A daily pipeline that extracts, transforms, and loads data into a warehouse
• A chain of tasks that waits for a file and then runs checks

Getting started

• Start a development environment and add a short DAG with two tasks.
• Run it manually and check the dependency graph in the interface.
• Make a task fail and check the alert and retry.

What to check

• The team is responsible for hosting and updates unless it chooses a managed service.
• A DAG with broad permissions can access many systems at once.