Jan Neumann presents how Comcast uses machine learning and big data processing to facilitate search for users, for capacity planning, and predictive caching.
Yongsheng Wu talks about how to build highly-resilient systems at scale. Wu presents also failure cases that prompted engineers at Pinterest to build such systems, and how they test these systems.
Chris Dennis and Alex Snaps discuss introducing caching into a Spring application to solve real world problems.
Jason McCreary takes a look at using background job processes, messaging queues, and cache to help an application scale.
Michael Plöd addresses the advanced usage of Spring's caching abstraction such as integrating a cache provider that is not integrated by the default Spring Package and overviews JCache. Demos.
Ryan Vanderwerf speaks about the roles of cache clustering, session clustering, and quartz clustering with open source Terracotta, Quartz, and BigMemory.
Juergen Hoeller and Stéphane Nicoll present major new features in Spring Framework 4.1: the numerous improvements around the caching abstraction, and messaging-related features.
Rajeev Borborah, Matthew Wilson discuss using NoSQL at WebMD -architecture, benefits, roadmap-, with details on caching and key-value storage implementation behind a few of the WebMD applications.
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, and contracts in NoSQL stores.
Yashwanth Nelapati and Marty Weiner share lessons learned growing Pinterest: sharding MySQL, caching, server management, all on Amazon EC2.