We Rendered A Million Web Pages to Find Out What Makes The Web Slow

We Rendered A Million Web Pages to Find Out What Makes The Web Slow

In this article, we analyze what the data can tell us about creating high performance web sites. Let's see We Rendered A Million Web Pages to Find Out What Makes The Web Slow.

We rendered the top 1 million pages  on the web, tracking every conceivable performance metric, logging every error, noting every requested URL. To our knowledge, this produces the first dataset that connects performance, errors, and library use on the web. In this article, we analyze what the data can tell us about creating high performance web sites.

Can you do better than our analysis? We published the dataset to Kaggle, so you can crunch the numbers yourself.

Why render a million web pages?

A common sentiment these days is that the web is somehow slower and buggier than it was 15 years ago. Because of an ever-growing pile of JavaScript and frameworks and webfonts and polyfills, we’ve eaten up all the gains that faster computers, networks and protocols have given us. Or so the argument goes. We wanted to check if this was actually true and try to find what common factors are causing slow and broken websites in 2020.

The high level plan was simple: Scripting a web browser, having it render the root page of the top 1 million domains, and logging every conceivable metric: render times, request counts, repaints, JavaScript errors, libraries used, etc. With all this data, we can ask questions about how one factor correlates with another. What factors contribute most to slow render times? Which libraries are correlated with long time-to-interactive? What are the most common errors, and what’s causing them?

Gathering the data was a matter of writing a bit of code to use Puppeteer to script Chrome, firing up 200 EC2 instances, rendering a million web pages over the weekend, and praying that you’ve actually understood how AWS pricing works.

javascript

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