John Bunting talks about different services Tumblr has built and how their architecture helps them be fault tolerant as they continue to grow.
Andy Vaughn gives attendees a case study of how changing the development model and release cycle of a 5 year old software product to continuous delivery greatly improved the product.
Mike Keane presents how Conversant migrated to Flume, managing 1000 agents across 4 data centers, processing over 50B log lines per day with peak hourly averages of over 1.5 million log lines/sec.
Jeremy Stieglitz discusses best practices for a data-centric security , compliance and data governance approach, with a particular focus on two customer use cases.
Lisa Van Gelder provides simple tips and tricks for improving delivery without investing lots of time up front creating complex deployment frameworks.
Melody Meckfessel explores how Google's engineering teams use CD to build products and scale them, and how their strain of DevOps speeds launches and helps their engineering culture thrive.
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.
Dean Wampler argues that Spark/Scala is a better data processing engine than MapReduce/Java because tools inspired by mathematics, such as FP, are ideal tools for working with data.
Matei Zaharia talks about the latest developments in Spark and shows examples of how it can combine processing algorithms to build rich data pipelines in just a few lines of code.
Bob Kelly presents case studies on how Platfora uses Hadoop to do analytics for several of their customers.
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
Carlos Queiroz introduces the lambda architecture and showcases how it can be implemented with SpringXD, GemFireXD and Hadoop in a CDR(Call Detail Record) mining application.