Sid Anand uses examples from LinkedIn, Netflix, and eBay to discuss some common causes of outages and scaling issues. He also discusses modern practices in availability and scaling in web sites today.
Jesper Richter-Reichhelm shares lessons learned from failures while scaling Wooga games to millions of daily users.
Robin Johnson discusses using a data management model for games that can be scaled, and the bottlenecks and challenges met by OMGPOP scaling to millions of users.
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.
Marc Pacheco tells how Songkick made radical changes to increase the performance of the site while retaining a productive development team.
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.
Adrian Cockcroft presents Netflix globally distributed architecture, the benchmarks used, scalability issues, and the open source components their implementation is based upon.
Raffi Krikorian explains the architecture used by Twitter to deal with thousands of events per sec - tweets, social graph mutations, and direct messages-.