Apache Airflow: A Beginner's Guide

Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It was developed by Airbnb to manage their data pipelines. The platform is used to create complex workflows composed of multiple tasks, and it allows for easy maintenance and monitoring of these workflows.

In this article, we'll cover the basics of Apache Airflow and how to install it using Docker. For more detailed instructions, check out this medium post.

What is Apache Airflow?

Apache Airflow is a platform that allows you to create, schedule, and monitor workflows. Workflows are created using Python code and are made up of multiple tasks that are executed independently. Each task can be run on a different machine, making it possible to scale workflows as needed.

Airflow has a web interface that allows you to monitor the status of your workflows, view logs, and see the dependencies between tasks. It also has a powerful scheduler that can handle complex dependencies and retry failed tasks.

Installing Apache Airflow with Docker

Installing Apache Airflow can be a complex process, but using Docker can make it much simpler. Docker is a platform that allows you to create, deploy, and run applications in containers. Containers are lightweight, portable, and self-contained, making them ideal for running complex applications like Apache Airflow.

To install Apache Airflow with Docker, follow these steps:

1. Install Docker on your machine. You can download Docker from the official website.

2. Create a directory for your Airflow installation. This directory will contain your Airflow configuration files and your Docker Compose file.

3. Create a Docker Compose file in your Airflow directory. This file will define the services that make up your Airflow installation. Here's an example:

`version: '2'

services:
postgres:
image: postgres:9.6
environment:
POSTGRES_USER: airflow
POSTGRES_PASSWORD: airflow
POSTGRES_DB: airflow
volumes:
- postgres_data:/var/lib/postgresql/data

webserver:
image: apache/airflow:2.1.2
depends_on:
- postgres
environment:
- LOAD_EX=n
- FERNET_KEY=your_fernet_key_here
- EXECUTOR=Local
- POSTGRES_USER=airflow
- POSTGRES_PASSWORD=airflow
- POSTGRES_DB=airflow
ports:
- "8080:8080"
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./plugins:/opt/airflow/plugins
command: webserver

volumes:
postgres_data:`

1. Start your Airflow installation by running docker-compose up in your Airflow directory. This will start the Postgres database and the Airflow webserver.

2. Access the Airflow web interface by navigating to http://localhost:8080 in your web browser. You should see the Airflow dashboard, which shows the status of your workflows.

Conclusion

Apache Airflow is a powerful platform for managing complex workflows. Using Docker to install Airflow can make the process much simpler and more manageable. With Airflow, you can create, schedule, and monitor your workflows with ease, allowing you to focus on your data instead of worrying about the infrastructure.