Unlock the Power of Lighthouse: Boosting Website Performance and Usability
Streamlining Performance Audits with Lighthouse and GitHub Actions
Lighthouse is a game-changer for optimizing website performance and usability. By integrating it into your Continuous Integration (CI) pipeline, you can automate audits and ensure that every pull request meets your quality standards. In this article, we’ll explore how to seamlessly integrate Lighthouse into a GitHub Actions workflow, providing actionable insights directly in pull requests.
Building a Simple Web Application with Docusaurus
We’ll start by creating a Docusaurus site within an empty GitHub repository. This will serve as our example static site, perfect for demonstrating the power of Lighthouse.
Deploying to Azure Static Web Apps
Next, we’ll set up an Azure Static Web App, leveraging its built-in staging environments and deployment previews. This allows us to deploy a fully functional version of our site with each pull request, making it easy to test and validate changes.
Preparing for Lighthouse Integration
With our groundwork in place, we’re ready to add Lighthouse to the mix. We’ll update our GitHub Actions workflow file to include Lighthouse jobs, acquiring the necessary information along the way, such as our custom domain and resource group location.
Plugging in Lighthouse
Now it’s time to create a new Lighthouse report job in our GitHub Actions workflow file. We’ll construct the preview URL of our static web app, wait for the site to be up and running, and then run Lighthouse using the lighthouse-ci-action GitHub Action.
Configuring Lighthouse
We’ll create a lighthousesrc.json file to configure our Lighthouse setup, pointing to a lighthouse-config.js file that defines the audit parameters. You can customize this configuration to suit your needs, skipping audits or adjusting settings as required.
Formatting Lighthouse Scores
After running Lighthouse, we’ll use the github-script GitHub Action to format the results into a readable comment, complete with emojis and Markdown. This comment will be added to our pull request, providing a concise overview of our Lighthouse scores.
Adding Lighthouse Stats as a Comment
Finally, we’ll use the sticky-pull-request-comment GitHub Action to add the comment to our pull request. With each PR, you’ll now see a Lighthouse report attached, allowing you to identify and resolve performance regressions before they impact customers.
By following these steps, you’ll unlock the full potential of Lighthouse, ensuring that every pull request meets your performance and usability standards. Say goodbye to manual audits and hello to a more efficient, automated workflow.