danger-js VS lighthouse-ci

Make sure to not accept any Pull Request with commented ESLint errors to ensure a continuous improvement of your codebase quality. Some tools can help you to automate this part of the review, such as Danger JS.

commitlint & dangerjs. Linters that help maintain consistency in all user-provided information related to Git and GitHub (commits, branch names, PR titles, etc.).

Does your team use any automatic code formatting or linting tools? E.g. for TypeScript or JavaScript, a combination of Prettier and ESLint, with a well understood and agreed-upon configuration, can avoid this kind of back and forth. Danger.js is a good way to handle the higher level concerns that cannot be addressed at the syntax level.

This tool is run in our CI pipeline for every PR and the result is shown in the Github PR (it uses Danger behind it).

- referred to https://github.com/GoogleChrome/lighthouse/issues/6512 but didnt see network.disable error - added staticdistdir as per https://github.com/GoogleChrome/lighthouse-ci/blob/main/docs/configuration.md,

This approach would suit most of the cases however to achieve more accurate performance audits you should be conducting Lighthouse tests on a dedicated server to avoid results being affected by the machine capabilities. In other words, if you are running Lighthouse audits on a repository where there are several pull requests/workflows/pushes going on, the result of this audit may not be accurate and this is what we want to avoid. For that you would need a separate machine with Lighthouse Server installed on it. So on a pull request you would trigger this machine to conduct a performance audit and return response to your repository.

And finally, Lighthouse has a CI version you can run in your continuous integration. We’ll use this method to schedule periodical benchmarks.

TLDR; I use the Google Chrome Lighthouse CI with a .lighthouserc json configuration to test next start. The Lighthouse CI GitHub app is used to return a pass or fail status check in a PR.

You should also incorporate performance checks into your CI/CD pipeline. Use Lighthouse CI to run a synthetic Lighthouse test on each PR (PS: Learn why you shouldn't believe the Lighthouse score alone) and bundlesize package to raise alerts if your bundle size exceeds a certain threshold. For more nuanced data you should use WebPageTest.

You can also run Google’s Lighthouse CI tool against multiple URLs, and then hook that up to their self-hosted dashboard service: https://github.com/GoogleChrome/lighthouse-ci

You can also set up lighthouse-ci as a github action to evaluate the web vitals on push or in pull requests.

You can have more consistent results if you set up Lighthouse CI in an external environment to test your page or use tools like SpeedCurve, but if you need to quickly inspect a website, I suggest taking a look at Page Speed Insights.

This name is already self-explanatory, and developers just need to run Lighthouse or its CI.

They also have a powerful CI tool (https://github.com/GoogleChrome/lighthouse-ci) with custom timelines, may look to implement it at some point