next-seo VS lighthouse-ci

The third one is Schema.org JSON-LD. I actually question the usefulness of this feature, but if it is relatively easy to implement without a glaring downside, just give it a shot I guess? In Next.js, there is next-seo package that greatly simplifies the implementation of Schema.org JSON-LD.

Next SEO

Next Seo GitHub Repository

I would recommend checking out https://github.com/garmeeh/next-seo. It does SEO for you. Additionally, going to recommend precisely what u/saarnav mentioned. https://vercel.com/docs/concepts/functions/edge-functions/og-image-generation

Any opinions on https://github.com/garmeeh/next-seo ?

To simplify this, we can use a package called next-seo. Next SEO makes managing SEO easier in your Next.js projects.

For SEO there is next-seo.

Meta tags exist in the head element of the page providing important information about the page that can used by search engines and social media sites. There are a variety of meta tags that represent different types of information for different search engines. A popular subset of standardized meta tags are described in the open graph protocol. Managing these tags for every page and generating them dynamically for blog pages has it’s own overhead. Thus for that reason, I have used the Next-SEO plugin. The Next-SEO plugin provides DefaultSEO component that contains tags that will be defined for all routes by default which subsequently can be overwritten at a page level by then using the NextSEO component. Below is the default SEO config used by me.

I have also used this package to make the SEO tag section easier to manage: https://github.com/garmeeh/next-seo

We will have to populate SEO-related meta tags with the relevant information for each page. To do so, we will use garmeeh/next-seo.

- 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