The authors discuss Netflix's new stream processing system that supports a reactive programming model, allows auto scaling, and is capable of processing millions of messages per second.
Terence Yim from Continuuity showcases a transactional stream processing system that supports full ACID properties without compromising scalability and high throughput.
The authors discuss some of the unique challenges they've faced delivering highly personalized search over semi-structured data at massive scale.
Raymond Blum discusses some of the challenges, solutions and discarded alternatives in creating durable storage systems at Google scale.
The authors discuss patterns and technologies needed to scale large enterprise mobile systems, covering handling network connectivity, data reliability and real-time communication.
Michael Bryzek shares lessons learned from startup to a leading ecommerce companies, starting with behavioral psychology and reflecting on the decisions made and tradeoffs considered as they scaled.
Brett Meyer demos using multiple-tenancy, geographic data, auditing/versioning, sharding, OSGi, and integration with Hibernate.
Rick Reed shares scalability and reliability insights, techniques, and hacks used and learned developing WhatsApp on an Erlang/FreeBSD infrastructure.
Joakim Recht discusses how Tradeshift moved from manual deployment processes to automation and what this means in terms of organizational scalability, technology, transparency, and culture.
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.
Sponsored by Basho. Sean Cribbs discusses the theory behind several rich data types introduced with Riak 2.0 and then walking through some example applications that use them in popular languages.