InfoQ Homepage Performance & Scalability Content on InfoQ
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Embracing Concurrency At Scale
Justin Sheehy explains the principles behind concurrent distributed systems: no global state, no ACID but rather BASE, no RPC but protocols over APIs, prepare for failure, degradation, measurement.
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Project Voldemort at Gilt Groupe: When Failure Isn't an Option
Geir Magnusson explains why Gilt Groupe is using Project Voldemort to scale out their e-commerce transactional system, what are the benefits and what is the current architecture after ditching SQL.
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Scaling Your Cache & Caching at Scale
Alex Miller presents typical difficulties encountered when setting up a cache, plus available choices for designing a distributed caching architecture, and ways to test a cache for performance.
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The Wizardry of Scaling
Oren Eini presents several architectural concepts – divide and conquer, background evaluation, one way messaging, the single responsibility principle - helpful to build highly scalable systems.
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Scale at Facebook
Beside presenting the overall Facebook architecture and scaling solutions used, Aditya Agarwal talks about the iterative process of constantly improving the site, making sure to avoid over-engineering
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Facebook: Moving Fast at Scale
Robert Johnson talks about: the need to prepare for horizontal scalability, very short release cycles associated with a streamlined deploying process, and making the entire process faster every day.
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Project Voldemort: Scaling Simple Storage
Jay Kreps discusses the architecture, algorithms, implementation and deployment of Voldemort, a distributed storage system. He also presents the problems solved using Voldemort at LinkedIn.
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Horizontal Scalability via Transient, Shardable, and Share-Nothing Resources
Adam Wiggins details how memcached, CouchDB, Hadoop, Redis, Varnish, RabbitMQ, Erlang apply the transient, shardable and share-nothing principles to achieve horizontal scalability.
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Open Source at Unibet.com - 10x Scalability at Half the Cost
Stefan Norberg presents Unibet.com’s architecture which uses XHTML 1.0, CSS 2.1, YUI, caching, compression, image spriting, and CDN striping for front-end plus multiple replicas for scaling out.
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Rails in the Large: How Agility Allows Us to Build One Of the World's Biggest Rails Apps
Neal Ford shows what ThoughtWorks learned from scaling Rails development: infrastructure, testing, messaging, optimization, performance.
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Rails 3
Yehuda Katz explains Rails 3: the performance improvements, the new architecture, the influence of Merb, and much more. Also: a look at the Bundler tool.
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Facebook’s Petabyte Scale Data Warehouse using Hive and Hadoop
Ashish Thusoo and Namit Jain explain how Facebook manages to deal with analysis of 12 TB of compressed new data everyday with Hive’s help, an open source data warehousing framework built on Hadoop.
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