Oleg Zhurakousky discusses architectural tradeoffs and alternative implementations of real-time high speed data ingest into Hadoop.
Clay McCoy discusses using Groovy’s metaprogramming capabilities and AWS SWF to deal with unreliable remote services, parallelization, scheduling critical timers, and server failures.
Andy Gross discusses the challenges introduced by distributed systems and the need for developing new skills and tools for dealing with them.
Michael Hausenblas introduces Apache Drill, a distributed system for interactive analysis of large-scale datasets, including its architecture and typical use cases.
Gilles Di Guglielmo and Julien Baudry present patterns for solving UI issues –large forms, linked form fields, conditional field display, dynamic list content, incremental validation-, using modeling.
Daniel Woods focuses on leveraging the strengths and flexibility of Groovy to create a maintainable and simple application architecture.
Uri Laserson reviews the different available Python frameworks for Hadoop, including a comparison of performance, ease of use/installation, differences in implementation, and other features.
Paul Fremantle conducts a hands on tutorial on Stratos and App Factory showing how to create a development and runtime PaaS.
Sebastian Ohm and Tomás Senart discuss the evolution of an AMQP implementation at SoundCloud.
Rajiv Eranki shares the pains and lessons learned scaling up Dropbox from a few thousands to tens of millions of users.
Michael Rauch and Christoph Gutmann explain how Eclipse Modeling technology is successfully applied to establish forward engineering in the domain of technical SOA. Modeling and code generation help them to drive standardization, increase quality and portability, reduce development effort and gain insight into dependencies.
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