Run unit tests for python ETL jobs in AWS Glue using the pytest framework

This template offers a CI/CD pipeline designed to automate unit testing for AWS Glue Python ETL jobs using the Pytest framework. It integrates key AWS services such as CodePipeline, CodeBuild, CodeCommit, and CloudFormation to manage the entire process, from storing code to running tests and deploying error-free ETL jobs. It ensures your data transformations are accurate, tested, and production ready.
 

Why This Template Transforms Data Team Operations ?

This template provides a structured and automated solution for a process that is often manual and error prone. By implementing Pytest-based unit tests within a fully automated pipeline, it allows teams to identify issues early, improve code quality, and reduce failures in production environments. The result is a reliable, scalable, and efficient testing workflow for cloud-based data pipelines.
 

Who needs this template, and when is the best time to use it ?

This template is perfect for data engineers, Python developers, and cloud architects who work with AWS Glue. It is particularly for managing complex ETL workflows or scaling data platforms. Teams that are preparing regular deployments or looking to shift to a DevOps model for data pipelines will benefit greatly from adopting this automated testing framework.
 

What features does it offer? 

• AWS CodePipeline – Manages the overall CI/CD pipeline for ETL testing and deployment

• AWS CodeCommit Repository – Stores Python ETL scripts and test code

• AWS CodeBuild – Runs unit tests using the Pytest framework

• Amazon ECR – Stores containerized libraries required for Glue jobs

• AWS Glue ETL Job – Executes the actual data transformation logic

• AWS CloudFormation – Automates the infrastructure needed for testing and deployment

• IAM Roles – Manages secure access for pipeline components

• Source Stage – Handles version control and source management.

• Build Stage – Executes testing scripts and generates test results.s

• Deployment Stage – Deploys validated jobs into AWS Glue.

• CloudWatch Logs – Tracks test outputs and errors

• Lambda Functions – Automates post-test triggers for workflows

• S3 Buckets – Stores logs and testing results

• Notification System – Sends alerts when test cases fail.
   

How to get started with Cloudairy ?

Set up your workflow easily with a few simple steps in Cloudairy :

• Log in to your Cloudairy account and navigate to the Templates section.
   
• Search for “AWS Glue ETL Unit Testing Workflow” and open the template.

•  Review its pre-configured components, customize it based on your test scripts, and configure the pipeline stages.

•  Save your setup or deploy it directly into your environment for automated testing and deployment.

Summary 
 

This template makes it easier to conduct unit tests for AWS Glue Python ETL jobs with Pytest while seamlessly integrating with a CI/CD pipeline. By using tools like CodePipeline, CodeBuild, and CloudFormation, you can boost automation, improve accuracy, and speed up your data workflows. It’s a great option for teams who want to create more reliable, test-driven, and production-ready cloud data pipelines.