InfoQ Homepage Twitter Content on InfoQ
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Functional Systems @ Twitter
Marius Eriksen explains Twitter's experiences with functional programming (with Scala) @ Twitter: where functional techniques worked and where not. Also: how the Scala language has scaled with Twitter
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TSAR: How to Count Tens of Billions of Daily Events in Real Time Using Open Source Technologies
Gabriel Gonzalez introduces TSAR (TimeSeries AggregatoR), a service for real-time event aggregation designed to deal with tens of billions of events per day at Twitter.
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Real-Time Systems at Twitter
Brian Degenhardt discusses lessons that Twitter learned managing a high rate of change and complexity, and how those can be applied anywhere.
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Scaling Engineering Culture at Twitter
Raffi Krikorian discusses the software engineering challenges met re-architecting Twitter and the cultural change impact that came with it.
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Decomposing Twitter: Adventures in Service-Oriented Architecture
Jeremy Cloud discusses SOA at Twitter, approaches taken for maintaining high levels of concurrency, and briefly touches on some functional design patterns used to manage code complexity.
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Timelines at Scale
Raffi Krikorian explains the architecture used by Twitter to deal with thousands of events per sec - tweets, social graph mutations, and direct messages-.
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Scaling Scalability: Evolving Twitter Analytics
Dmitriy Ryaboy shares some of the lessons learned scaling Twitter’s analytics infrastructure: Data loves a schema, Make data sources discoverable, and Make costs visible.
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Storm: Distributed and Fault-Tolerant Real-time Computation
Nathan Marz introduces Twitter Storm, outlining its architecture and use cases, and takes a look at future features to be made available.
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Real-Time Delivery Architecture at Twitter
Raffi Krikorian details Twitter’s timeline architecture, its “write path” and “read path”, making it possible to deliver 300k tweets/sec.
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Storm: Distributed and Fault-tolerant Real-time Computation
Nathan Marz discusses Storm concepts –streams, spouts, bolts, topologies-, explaining how to use Storms’ Clojure DSL for real-time stream processing, distributed RPS and continuous computations.
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Timelines @ Twitter
Arya Asemanfar presents Twitter’s timeline architecture, the entire sequence of steps a tweet goes through until it reaches the timeline of each user following the person who tweeted.
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Everything I Ever Learned about JVM Performance Tuning @twitter
Attila Szegedi shares lessons learned tuning the JVM at Twitter, spending most of his talk discussing memory tuning, CPU usage tuning, and lock contention tuning.
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