I’ve been kicking around this idea for quite some time and finally sat down to get it published. Four Kitchens has always taken performance very seriously, but traditionally most people only focus on backend server performance when thinking about these types of issues. I’m not a hardcore backend dev, but I have plenty of experience making things fast and useful within a web browser.
To that end, I’d like to spread the word about frontend performance by publishing a periodic blog post series highlighting techniques, articles, and other webperf stuff that we’re talking about day-to-day in the office. So without further ado, here are this week’s links:
Ilya Grigorik presents an extremely compelling case for putting speed at the top of your priority list, especially on responsive and otherwise mobile websites. He explores the realities of network latency and suggests methods that could be used to break the 1000ms “time-to-glass” barrier. It’s a low-level, deep dive into the effects of TCP/IP and HTTP requests on your site’s loading speed, and contains tons of great information to help you build fast sites. To make the most of these slides, you’ll have to work closely with backend and/or deployment people who help manage your sites, but the payoff is well worth it.
Double-whammy from Alex Sexton
Next are his slides from HTML5 Developer Conference that highlight the awesome new Modernizr v3 workflow. Very closely related to deploying JS apps, he outlines how the Modernizr v3 will help you build applications which adapt to the browser loading it, allowing for tiered, optimized experiences that match each browser’s capabilities while minimizing the loading of unnecessary assets. Having helped out with the v3 work, I’m especially excited to see people begin to use it.
A couple weeks back I wrote about a feature of Chromium that Ilya has helped publicize in his upcoming book, High-Performance Browser Networking. It’s a
<link> tag which lets you suggest pages that Chrome should prerender in cases where your traffic funnels are extremely predictable. This is a great example of using data to accurately predict user actions rather than directly altering the load time of your pages. Although they still load at the speed of the network, the end result can reduce apparent load times to 0.0s in some cases! Check out my example which is live on Pressflow.org.
I hope you enjoyed these links! As I mentioned earlier, these posts won’t always be limited to links, so check back for code snippets, full implementation walkthroughs, and other goodies in the future.
Feel free to leave feedback or topic requests in the comments, and happy perfing!
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