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Jared Rosoff concisely, effectively, entertainingly, and convincingly gives an 8 minute MongoDB tutorial on scaling MongoDB at Scale Out Camp. The ideas aren't just limited to MongoDB, they work for most any database: Optimize your queries; Know your working set size; Tune your file system; Choose the right
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Sean Hall with some really good MySQL advice: 1. Tune those queries. Biggest bang for your buck. Enable the slow query log and watch it. Once you've found a heavy resource intensive query, optimize it! Tune what receives real-world traffic. 2. Employ Master-Master Replication. Immediately have a read-only
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In How to take advantage of Redis just adding it to your stack Salvatore 'antirez' Sanfilippo shows how to solve some common problems in Redis by taking advantage of its unique data structure handling capabilities. Common Redis primitives like LPUSH, and LTRIM, and LREM are used to accomplish
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The most common complaint against NoSQL is that if you know how to write good SQL queries then SQL works fine. If SQL is slow you can always tune it and make it faster. A great example of this incremental improvement process was written up by StackExchange's Sam
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Good article from manageability.com summarizing design patterns from Pat Helland's amazing paper Life beyond Distributed Transactions: an Apostate's Opinion. 1. Entities are uniquely identified - each entity which represents disjoint data (i.e. no overlap of data between entities) should have a unique key. 2.
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Ricky Ho in Scalable System Design Patterns has created a great list of scalability patterns along with very well done explanatory graphics. A summary of the patterns are: 1. Load Balancer - a dispatcher determines which worker instance will handle a request based on different policies. 2. Scatter and Gather
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This presentation and video by Jason Yan and David Cramer discusses how they scaled DISQUS, a comments as a service service for easily adding comments to your site and connecting communities. The presentation is very good, so here are just a few highlights: * Traffic: 17,000 requests/second peak; 450,
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The BBC's iPlayer site averages 8 million page views a day for 1.3 million users. Technical Architect Simon Frost describes how they scaled their site in Scaling the BBC iPlayer to handle demand: 1. Use frameworks. Frameworks support component based development which makes it convenient for team
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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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DynaTrace in Top 10 Performance Problems taken from Zappos, Monster, Thomson and Co, has provided a useful compilation of performance problems, with potential solutions, that they've found while working with their clients. 1. Too Many Database Calls - too many database query per request/transaction. 2. Synchronized to
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Aditya Agarwal, Director of Engineering at Facebook, gave an excellent Scale at Facebook talk that covers their architecture, but the talk is really more about how to scale an organization by preserving the best parts of its culture. The key take home of the talk is: You can get the