Working with YAML Files in GitHub Actions Using YQ

Working with YAML Files in GitHub Actions Using YQ


Hello, tech gurus! In today’s exploration of Cloud and DevOps technologies, we will dive into the world of YAML manipulation using a versatile tool in our GitHub Actions workflows – YQ. For those unfamiliar, YQ is a portable command-line YAML processor. It allows us to read, write, and manipulate YAML data efficiently, which can be crucial in the realm of CI/CD pipelines and configuration management. So, let’s get started!

YQ – The YAML Processor

YQ is a lightweight and portable command-line YAML processor. The same way you use jq for JSON, you can use yq for YAML. It provides a multitude of operations, such as reading specific fields, modifying them, deleting them, or creating new ones, making it a powerful tool for YAML manipulation.

GitHub Actions with YQ

YQ has been encapsulated into a GitHub Action available on the marketplace, allowing us to seamlessly integrate YAML processing capabilities into our GitHub Actions workflows.

Step-by-step Guide to Using YQ in GitHub Actions

Here’s a step-by-step guide to using YQ in your workflows:

Step 1: Create a GitHub Actions Workflow

Create a new file under the .github/workflows directory in your repository. Let’s call it yq-processor.yml.

Step 2: Configure the Workflow

Open the yq-processor.yml file and configure it as follows:

This configuration will check out your code and then use YQ to read the value at .some.yaml.path in path/to/your/file.yaml. You can replace the cmd and file values with your desired YQ command and YAML file path, respectively.


YQ is an incredibly powerful tool for manipulating YAML files, and its encapsulation as a GitHub Action makes it a breeze to include in our workflows. Whether you need to read, write, or transform your YAML files, YQ has got you covered, making your CI/CD processes more efficient and streamlined.

Remember, in the ever-evolving world of DevOps, tools and practices will come and go, but the principles of automation, efficiency, and constant learning will always remain. So, keep exploring, keep learning, and happy coding!