InfoQ Homepage Performance & Scalability Content on InfoQ
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Scaling Foursquare: From Check-ins to Recommendations
Jon Hoffman discusses the general architecture, storage systems and development practices created to handle the ever increasing volume and complexity at Foursquare.
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Scaling Chartbeat from 8 Million Open Browsers to Realtime Analytics and Optimization
Wesley Chow presents Chartbeat's real-time analytics platform and how able to handle the requests in a cost efficient manner using a custom written analytics engine in C and Lua.
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Machine Learning at Netflix Scale
Aish Fenton discusses Netflix' machine learning algorithms, including distributed Neural Networks on AWS GPUs, providing insight into offline experimentation and online AB testing.
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Scaling Continuous Deployment
Avleen Vig discusses the changes Etsy has implemented to scale continuous deployments over the last 12 months, in both software and infrastructure.
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Planning for Overload
Fred Hebert introduces two strategies for handling overload -load-shedding and back-pressure- along with different ways to make them work in Erlang focusing on the importance of planning for overload.
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Scaling HTTP Connections
Benoît Chesneau discusses creating, scaling and reusing HTTP connections, summarizing techniques used to reduce memory usage in Erlang and ways to handle massive client connections efficiently.
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High Performance Reactive Applications with Vert.x
Tim Fox discusses the design principles and motivation behind Vert.x and why the future is reactive.
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Wix Architecture at Scale
Aviran Mordo introduces Wix's architecture, a highly available eventually consistent system, along with patterns for rendering many websites with a relatively small number of servers.
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10 Billion a Day, 100 Milliseconds Per: Monitoring Real-Time Bidding at AdRoll
Brian Troutwine shares insight on using Erlang for a highly concurrent and very low latency bidding system implemented by Adroll.
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Web & Database Load Testing with JMeter
Michael Dowden introduces JMeter and explains how to develop a data-driven methodology to determine some of the limits of a web application: max number of concurrent users, bottlenecks, etc.
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The Haxl Project at Facebook
Simon Marlow describes a concurrency-based system built with Haskell that allows front-end programmers to write business logic to access all the back-end services in a concise and consistent way.
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Fault Tolerance 101
Joe Armstrong discusses fault tolerant systems, summarizing the key features of Erlang and showing how they can be used for programming fault-tolerant and scalable systems on multi-core clusters.