Vaclav Petricek discusses how to train models, architect and build a scalable system powered by Storm, Hadoop, Spark, Spring Boot and Vowpal Wabbit that meets SLAs measured in tens of milliseconds.
Dustin Whittle explains how to evaluate performance and scalability on the server-side and the client-side with tools like Siege, Bees with Machine Guns, Google PageSpeed, WBench, and more.
Dan Macklin explains why bet365 has adopted Erlang as a core development platform and goes through the highs and lows of managing change in one of the world's biggest on-line bookmakers.
Gunnar Hillert and Chris Schaefer examine various scalability options in order to improve the robustness and performance of the Spring Batch applications.
Fangjin Yang, creator of Druid, shows how approximation algorithms can help system scale out linearly and process huge amount of data quickly with small memory footprint.
Yoni Goldberg describes some of the technological innovations that have helped Gilt to reach its current size, and highlight some of the core challenges that the company's engineering team faces.
Jon Hoffman discusses the general architecture, storage systems and development practices created to handle the ever increasing volume and complexity at Foursquare.
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.