HackerTube

THE VIDEO SHELF · web performance

How is this Website so fast!?

Wes Bos breaks down the techniques behind the McMaster-Carr website's speed: server-rendered HTML, prefetching, CDN and service worker caching, preloading, critical CSS and fixed-size images. He also notes its old-school jQuery and YUI JavaScript.

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Why HN readers recommended it

HN points to it as the clearest frontend explanation of why McMaster-Carr feels so snappy, often contrasted with slow modern UIs.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Wes Bos
Topic
web performance
Format
explainer
Level
intermediate
HN recommenders in dataset
4
HN mentions in dataset
5
Recommendation years in dataset
2024–2025

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • To save you a click: apparently [LINK] is very fast. A person who worked there chimes in [LINK] saying they focused on speed (competing with paper catalogue), used VB.net and SQL Server with stored procs. Some other guy explains [LINK] : · Agressive pre-loading pages …

    yread on Hacker News · 2024-10
    In how come a company founded over 100 years ago has the fastest site

  • The low lag part is especially impressive. Here is Wes Bos taking a deeper dive into the intricacies of technologies used to accomplish this: [VIDEO]

    CleanCoder on Hacker News · 2025-05
    In Ask HN: What are good high-information density UIs (screenshots, apps, sites)?

  • I am SO glad jofzar posted this - I remember this website but couldn't recall the company name. Here's a good video on how the site is so fast, from a frontend perspective: [VIDEO]

    _nivlac_ on Hacker News · 2025-07
    In A 14kb page can load much faster than a 15kb page (2022)

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.

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