DevOps for DataOps: Building a CI/CD Pipeline for Apache Airflow DAGs

Build an effective CI/CD pipeline to test and deploy your Apache Airflow DAGs to Amazon MWAA using GitHub Actions

Introduction

In this post, we will learn how to use GitHub Actions to build an effective CI/CD workflow for our Apache Airflow DAGs. We will use the DevOps concepts of Continuous Integration and Continuous Delivery to automate the testing and deployment of Airflow DAGs to Amazon Managed Workflows for Apache Airflow (Amazon MWAA) on AWS.

Fork and pull model of collaborative Airflow development used in this post

Technologies

Apache Airflow

According to the documentation, Apache Airflow is an open-source platform to author, schedule, and monitor workflows programmatically. With Airflow, you author workflows as Directed Acyclic Graphs (DAGs) of tasks written in Python.

Amazon Managed Workflows for Apache Airflow

According to AWS, Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a highly available, secure, and fully-managed workflow orchestration service for Apache Airflow. MWAA automatically scales its workflow execution capacity to meet your needs and is integrated with AWS security services to help…