Latency is Everywhere and it Costs You Sales - How to Crush it - High Scalability -
« Handle 700 Percent More Requests Using Squid and APC Cache | Main | Paper: Parallelizing the Web Browser » Update 8: The Cost of Latency by James Hamilton. James summarizing some latency info from Steve Souder, Greg Linden, and Marissa Mayer. Speed [is] an undervalued and under-discussed asset on the web. Update 7: How do you know when you need more memcache servers?. Dathan Pattishall talks a
Colmux - Finding Memory Leaks, High I/O Wait Times, and Hotness on 3000 Node Clusters - High Scalability -
« Stuff The Internet Says On Scalability For August 26, 2011 | Main | The Cloud and The Consumer: The Impact on Bandwidth and Broadband » Todd had originally posted an entry on collectl here at Collectl - Performance Data Collector. Collectl collects real-time data from a large number of subsystems like buddyinfo, cpu, disk, inodes, infiniband, lustre, memory, network, nfs, processes, quadrics, sl
Neo4j - a Graph Database that Kicks Buttox | High Scalability
Update: Social networks in the database: using a graph database. A nice post on representing, traversing, and performing other common social network operations using a graph database. If you are Digg or LinkedIn you can build your own speedy graph database to represent your complex social network relationships. For those of more modest means Neo4j, a graph database, is a good alternative. A graph
Product: dbShards - Share Nothing. Shard Everything. - High Scalability -
I met the CodeFutures folks, makers of dbShards, at Gluecon. They occupy an interesting niche in the database space, somewhere between NoSQL, which jettisons everything SQL, and high end analytics platforms that completely rewrite the backend while keeping a SQL facade. High concept: I think of dbShards as a sort of commercial OLTP mashup of features from HSCALE (partitioning) + MySQL Proxy (trans
A Bunch of Great Strategies for Using Memcached and MySQL Better Together - High Scalability -
The primero recommendation for speeding up a website is almost always to add cache and more cache. And after that add a little more cache just in case. Memcached is almost always given as the recommended cache to use. What we don't often hear is how to effectively use a cache in our own products. MySQL hosted two excellent webinars (referenced below) on the subject of how to deploy and use memcach
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