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' suite of tools, collectively called the Simian Army, used to improve resiliency and maintain the cloud environment. The tools simulate failure in order to see how the system reacts to it.
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.
Charlie Hunt and Monica Beckwith describe the operational basics of G1 and how to tune it, along with tips on what to expect when migrating from Parallel GC or CMS to G1 GC.
Charlie Hunt presents the fundamentals of JVM tuning and provides advice for developers on writing a Java application that performs well at runtime.
I'll talk about a few of the monitoring solutions and approaches I've used during my career as a monitoring architect at a large financial services institution, as well as present a few case studies of customers who have managed to make the leap from bigger data to smarter data.
Gil Tene discusses JVM observation-based runtime optimizations, ordering and memory model rules, basics GC functions, memory management, and JVM mechanics.
Ben Evans discusses garbage collection in Java along with some tooling for understanding and visualizing how it works.
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