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Facebook gave a MySQL Tech Talk where they talked about many things MySQL, but one of the more subtle and interesting points was their focus on controlling the variance of request response times and not just worrying about maximizing queries per second. But first the scalability porn. Facebook's
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Two forces account for the trend of moving behavior to data: larger values used in key-value stores and spotty cloud networks. For some time we've seen functions pushed close to data with MapReduce, which is a batch process, but we are now seeing this model extend to interactive
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For everything given something seems to be taken. Caching is a great scalability solution, but caching also comes with problems. Sharding is a great scalability solution, but as Foursquare recently revealed in a post-mortem about their 17 hours of downtime, sharding also has problems. MongoDB, the database Foursquare uses, also
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Robert Haas in his SURGE Recap of the Surge conference, reflected a bit, and came up with an interesting checklist of general themes from what he was seeing. I'm directly quoting his post, so please see the post for a full discussion. He uses this framework to think
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As a tasty pairing with Facebook And Site Failures Caused By Complex, Weakly Interacting, Layered Systems, is another excellent tale of caching gone wrong by Peter Zaitsev, in an exciting twin billing: Cache Miss Storm and More on dangers of the caches. This is fascinating case where the cause turned
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Facebook has been so reliable that when a site outage does occur it's a definite learning opportunity. Fortunately for us we can learn something because in More Details on Today's Outage, Facebook's Robert Johnson gave a pretty candid explanation of what caused a rare
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This strategy is from the Large Hadron Collider project:Improvements in performance per Watt have caused CERN to no longer sign hardware support contracts longer than three years. Machines run until they die. They have a very high utilization of equipment (‘duty cycle’, 7 x 24 x 365). Replacing hardware
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Jesper Söderlund not only put together a few interesting scalability patterns, he also came up with a few interesting scalability lessons: * Lesson #1. Put Smarty compile and template caches on an active-active DRBD cluster with high load and your servers will DIE! * Lesson #2. Don't use out-of-the-box configurations.
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Jesper Söderlund put together an excellent list of four general scalability patterns and four subpatterns in his post Scalability patterns and an interesting story: * Load distribution - Spread the system load across multiple processing units * Load balancing / load sharing - Spreading the load across many components with equal properties for
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This is a guest post by Steffen Konerow, author of the High Performance Blog. Learning how to scale isn’t easy without any prior experience. Nowadays you have plenty of websites like highscalability.com to get some inspiration, but unfortunately there is no solution that fits all websites and needs.
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This is a guest post by Frédéric Faure (architect at Ysance), you can follow him on twitter. How do you scale an AWS (Amazon Web Services) infrastructure? This article will give you a detailed reply in two parts: the tools you can use to make the most of Amazon’s
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This is an interesting tidbit from near the end of the Packet Pushers podcast Show 15 – Saving the Web With Dinky Putt Putt Firewalls. The conversation was about how SSL connections need to terminate before they can be processed by a WAF (Web Application Firewall), which inspects HTTP for security