Simon Marlow explains how to use Haxl to automatically batch and overlap requests for data from multiple data sources.
Eugene Dvorkin provides an introduction to Storm framework, explains how to build real-time applications on top of Storm with Groovy, how to process data from Twitter in real-time, etc.
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
Martin Fowler keynotes on the importance of building a healthy social environment where software development can thrive. Part 1 of this presentation: www.infoq.com/presentations/workflow-refactoring
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.
David Nolen introduces Om, a ClojureScript library providing a functional layer on top of Facebook React for building MVC UIs.
Adam Ernst shows how his team at Facebook encountered spiraling complexities and declining reliability and decided to make the shift to functional, in the data model and the view layer of News Feed.
David Nolen introduces Om, a ClojureScript library that adds a functional layer on top of Facebook React, providing OO abstractions in a MVC environment.
Justin Moore shares how Facebook's own advances in Data Science have solved intricate location technology problems and how these lessons can be applied to other verticals to achieve similar gains.
Jeff Johnson introduces Apollo, a hierarchical NoSQL data system meant to deal with Facebook's distributed storage needs.
Brian Degenhardt discusses lessons that Twitter learned managing a high rate of change and complexity, and how those can be applied anywhere.
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.