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CS193H: High Performance Web Sites Lecture 25: 2008 State of Performance Steve Souders Google

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Presentation on theme: "CS193H: High Performance Web Sites Lecture 25: 2008 State of Performance Steve Souders Google"— Presentation transcript:

1 CS193H: High Performance Web Sites Lecture 25: 2008 State of Performance Steve Souders Google

2 announcements Final exam: not inclusive – only includes material since midterm about the same size as midterm 2 hour time limit (but should only take 1 hour) two time slots, pick the one you want: Tues Dec 9, 12:15-2:15 – Gates B03 Fri Dec 12, 12:15-2:15 – Gates B01

3 State of Performance Web 100 Future of Performance Steve's Little Red Book

4 Web 100 the data was very noisy issues due to unclear assignment and variability of test conditions: HTML, JS, CSS compressed or uncompressed? logged in or not logged in? web site content changes ads for timing, variability of testers' setup

5 Web 100 sites 100 160 web sites from Alexa Top 500

6 Web 100 stats average size: 466K average # of requests: 70 average response time: 4.75 seconds average backend: 337 ms average frontend: 4431 ms average ratio: 11% average YSlow grade: 54 corr(size, time) = 0.43 corr(requests, time) = 0.52 corr(yslow, time) = -0.43

7 Future of Performance developers think "Web 2.0" visibility into the browser deferred JavaScript prefetch services speed as a distinguishing feature standards, benchmarks user-driven transparency performance off the desktop

8 web devs think "Web 2.0" the days of Web 1.0 are fading away... but web developers still think in terms of the page reloading on every user action Web 2.0 pages may persist for hours need to evolve the way we program to keep our eyes on the long run, for example: watch for memory leaks # of DOM elements optimize JS and CSS for ongoing DHTML

9 visibility into the browser hard to measure the exact things we're trying to optimize HTML parsing CSS parsing JS parsing and execution (as the page loads) DOM manipulation

10 web page profiler (concept) paint events memory CPU JavaScriptCSS

11 deferred JavaScript tools to automatically split (huge) Web 2.0 JavaScript payload into smaller initial module and larger later module(s) a la Doloto ability to specify defer using HTML

12 prefetch services ensure resources are cached for sites I always visit browser support user-specified and auto-detected "favorite sites" two caches: transient and persistent persistent cache isn't purged or flushed by default clientside support e.g., Gears prefetch standard protocol /prefetch.xml – manifest list

13 speed as a feature sites use speed as a competitive advantage remember Yahoo! and Google search? Facebook vulnerability? aggregators & vendors prioritize based on speed Google incorporates load time into Adwords Quality Score time-will-soon-be.html

14 performance standards test suites for web sites benchmarks for browsers standards for "response time" web page digest archive of all relevant information about a page load shared instrumentation and reporting

15 user-driven transparency Internet community contributes to performance data warehouse examples: UA Profiler – PBWiki JavaScript Library loading speed Cloud Four Mobile Connection Test

16 off the desktop proliferation of web clients besides desktop browsers... requires investigation and evangelism of performance best practices for these platforms mobile, PDA auto, mass transit airplane 3 rd world

17 Steve's Little Red Book think like a scientist question assumptions more data is not always better (and it's frequently worse) don't plan too far ahead there's a difference between bad decisions and bad outcomes strive for perfection, but don't rely on it if you're not failing, you're not pushing hard enough TRUST YOUR GUT!


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