Ryan Vanderwerf explains setting up Terracotta and clustering an applications using Ehcache, HTTP Session in Tomcat, and Quartz.
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
John O’Hara discusses banking business and technology integration, covering: low-latency, high-frequency trading, in-memory caches, multi-terabyte time-series databases, complex contracts in NoSQL stores and advanced systems integration.
Yashwanth Nelapati and Marty Weiner share lessons learned growing Pinterest: sharding MySQL, caching, server management, all on Amazon EC2.
Tim Stokes discusses various URI caching strategies providing real life examples relying on some of the natural behaviors that are built into the HTTP 1.1 protocol.
John Davies shares insight into SQL, NoSQL, grid, virtualization and caching technologies from his personal experience using them in financial institutions.
Chris Meadows introduces Redis, explaining what it is good for, what does it take to be run, and what’s under the hood through a social networking code example.
Israel Hilerio presents how to cache data locally with HTML5 technologies: IndexedDB, App Cache, DOM Storage and File API.
Sean Comerford unveils ESPN.com’s architecture, what components are used and why, and the current changes the website goes through.
Charles Fry presents MapMaker, an in-memory caching solution on the JVM, discussing its API and implementation evolution along with internal details.
Jason Sirota explains with code samples how to combine caching with asynchronous IO using memcached, Membase and Ketchup in order to maximize the throughput of an application.
Sean Lynch and Matt Ingenthron introduce Membase, detailing how they added clustering features in Erlang, what they built and what lessons they leaned along the way.