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Waterfalls 101: How to use a waterfall chart to diagnose your website’s performance pains If you’ve been following along with this site over the past four years, you may recall this post, which offered an introduction to waterfall charts. Given that the post is now a few years old, I think it merits a refresh. Who this post is for If you already live and breathe waterfalls, this post isn’t for you
Last week, I had the pleasure of being invited to speak at the CMG’s annual Performance & Capacity Conference. One of my sessions was a presentation of Radware’s research into mobile web stress. The other was a brand-new talk that I’m frankly kind of surprised I’ve never done before: a shallow dive into the topic of measuring the financial impact of slow performance versus the financial impact of
www.webperformancetoday.com
Early findings: Mobile browser cache persistence and behaviour If you’ve spent any time in the mobile space, you know that the browser cache is a critical limiting factor for performance. I often talk about: how unreliable the mobile browser cache is, how poorly it persists data, and how poorly it observes basic caching headers. You may also know that one of the key benefits that front-end optimiz
4 awesome slides showing how page speed correlates to business metrics at Walmart.com When one of the first slides in a presentation offers this level of candor, you know you’re in for a treat: File this presentation under “I wish I’d been there in person.” Cliff Crocker, Aaron Kulick, and Balaji Ram joined forces at February’s SF Web Performance Meetup to tell a RUM (real user monitoring) story t
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