Rajiv Eranki shares the pains and lessons learned scaling up Dropbox from a few thousands to tens of millions of users.
Theo Schlossnagle keynotes on the role of open source software and the breaking up of silos in the enterprise in creating scalable systems.
Jeremy Edberg shares some of the lessons learned scaling Reddit, advising on pitfalls to avoid.
Joe Armstrong outlines the architectural principles needed for building scalable fault-tolerant systems built from small isolated parallel components which communicate though well-defined protocols.
Mike Hadlow explains why RabbitMQ makes a compelling solution for building scalable systems, overviewing its exchange-binding-queue routing topology and showing how to build messaging patterns with it.
Alex Papadimoulis conducts a tutorial on delivery and deployment at scale.
Robbie Clutton takes a look at the tools assisting a startup in making technical decisions needed for scaling and growing.
Jay Kreps discusses the evolution of LinkedIn's architecture and lessons learned scaling from a monolithic application to a distributed set of services, from one database to distributed data stores.
Nicolas Spiegelberg discusses Facebook Messages built on top of HBase, the systems involved and the scaling challenges for handling 500TB of new data per month.
Alex Papadimoulis discusses various deployment strategies, scalable delivery, with examples from real-world organizations such as AllRecipes.com, Twitter, and Google.
Raffi Krikorian explains the architecture used by Twitter to deal with thousands of events per sec - tweets, social graph mutations, and direct messages-.
Mike Solomon shares some of the experiences and lessons learned scaling YouTube over the years.