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.
Aish Fenton discusses Netflix' machine learning algorithms, including distributed Neural Networks on AWS GPUs, providing insight into offline experimentation and online AB testing.
Avleen Vig discusses the changes Etsy has implemented to scale continuous deployments over the last 12 months, in both software and infrastructure.
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.
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.
Tim Fox discusses the design principles and motivation behind Vert.x and why the future is reactive.
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.
Brian Troutwine shares insight on using Erlang for a highly concurrent and very low latency bidding system implemented by Adroll.
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.
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.
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.
Nathan Marz discusses building NoSQL-based data systems that are scalable and easy to reason about.