Matt West explains how to use technologies like CloudStack, Beanstalk, Gearman, mod_gearman, Nagios, nagconf and other tools to monitor large web applications at scale deployed in the zCloud.
Leo Meyerovich introduces Superconductor, a browser-based language for massive interactive visualizations using end-to-end parallel DSLs and a synthesis DSL for parallel layout.
Daniel Cukier shares insight in using cloud services to scale web applications, dealing with load balancing, session sharing, email, asynchronous processing, logging, monitoring, CD, RUM, etc.
Maxime Chevalier-Boisvert discusses making dynamic languages faster providing various examples of optimizations: SmallTalk, LISP machine, Google V8 and others.
Alex Gaynor explains how he solved the usual Ruby VM speed problems with Topaz, a high performance VM built on the same technologies that power PyPy.
Craig Smith, Renee Troughton discuss improving visual management: different types of story walls, ways to visualize the product backlog, the important of queue columns and WIP limitation, etc.
Keith Adams shares HHVM insights showing how a system can become very performant if it is well tuned.
Ariel Tseitlin discusses Netflix' failure-based suite of tools, collectively called the Simian Army, used to improve resiliency and maintain the cloud environment.
Chris Oldwood discusses what it takes to create robust software: correct error detection and recovery, testing systemic effects, app monitoring and configuration.
Zach Tellman discusses instrumenting and analyzing running systems using real world examples from Factual's production systems.
Michael Kopp explains how to run performance code at scale with Hadoop and how to analyze and optimize Hadoop jobs.
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