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.
Scott Delap and Randy Stafford explain the architectural decisions made in order to scale, monitor and operate 24/7 the game League of Legends, bringing insight on how they use Oracle Coherence for that.
Uri Cohen presents the key characteristics of SQL and NoSQL databases and how to create a layer on top of distributed data stores in order to use SQL to query for data. For further information please contact Gigaspaces.
Burt Beckwith discusses potential performance problems using mapped collections and Hibernate 2nd-level cache in GORM, along with strategies for avoiding such performance penalties.
Sam Newman and Chris Read describe the architectural change of a large European website by introducing a caching layer based on Squid in order to scale out to handle increased demand, and the cultural change done by breaking down the dev-ops silos.
Matthias Matook and Ari Zilka share the real-world experience of implementing Enterprise Ehcache at Australia's most visited online news sites. The talk will focus on the challenges and technical solutions to deal with massive page hits, high concurrency and how to achieve linear scalability without additional hardware.
Alex Miller explains shortly why caching is useful, followed by examples of typical difficulties encountered when setting up a cache, like large datasets, data eviction, stale data, replication, loading, duplication. Miller also discusses available choices for designing a distributed caching architecture, and ways to test a cache for performance.