This link has been bookmarked by 5 people . It was first bookmarked on 26 Apr 2008, by Daniel Andrlik.
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06 Jun 08
Ben GodfreySerious response to the Twitter downtime question. Written by guy with extremely large brain.
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28 Apr 08
John EckmanLeonard Lin's take on Mike Arrington's savage attack on Blaine Cook.
magnolia Bookmarks twitter scale mike_arrington tech_crunch snark blaine_cook scalability rails performance webdev database
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26 Apr 08
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Daniel AndrlikI was going to ignore this story altogether, but this post from Leonard Lin nails the issue so perfectly that I had to share it with all of you.
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As to the rest of the wannabees, it really is true that if you haven't done it, that is: been intimately involved growing a social web app from prototype to Internet-scale on a UNIX stack, then you really don't know shit. (I know more than my fair share of people that have, and I didn't see any of them posting armchair bs on the comments). I'm not trying to say this just to be dismissive, but only to say, you really really, don't understand the technical challenges involved. Generating target sets on social objects is extremely expensive and ill-suited to traditional 4NF data models in RDBMSs. So is social activity fan-out and any number of activities core to Twitter's message routing/storage and to social web apps in general. These are not traditional problems and standard, HA solutions just aren't available.
Even if you're architecturally sound, you're dealing with development with extremely tight timelines/pressures, so you have to make decisions to pick things that will work but will probably need to eventually be replaced (e.g. DRb for Twitter) -- usually you won't know when and what component will be the limiting factor since you don't know what the uses cases will be to begin with. Development from prototype on is a series of compromises against the limited resources of man-hours and equipment. In a perfect world, you'd have perfect capacity planning and infinite resources, but if you've ever experienced real-world hockey-stick growth on a startup shoestring, you know that's not the case. If you have, you understand that scaling is the brick that hits you when you've gone far beyond your capacity limits and when your machines hit double or triple digit loads. Architecture doesn't help you one bit there.
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