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.
Keith Adams shares details on building HHVM, a PHP VM built by Facebook, along with lessons learned doing it and tuning it for high performance.
Gil Tene discusses some common pitfalls encountered in measuring and characterizing latency, demonstrating and discussing some false assumptions and measurement techniques that lead to dramatically incorrect reporting results, and covers simple ways to sanity check and correct these situations.
Martin Thompson discusses the need to measure what’s going on at the hardware level in order to be able to create high performing lock-free algorithms.
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Featured Blog Posts
We get a lot of questions about our analytics-driven Application Performance Management (APM) collection and analysis technology. Specifically, people want to know how we capture so much detailed information while maintaining such low overhead levels. Read More.
Most technology folks have heard Marc Andreessen’s provocative statement, “Software is eating the world.” Whether you agree fully or not, you’re realizing that your business critical software applications increasingly drive both the top-line revenue growth and the bottom-line operational efficiency of your company – and often form the pillar of your business... Read More.
Wouldn’t do website load/performance testing any more without having an APM tool in place. Period. Full stop. End of story. I’ve been involved in website load testing for over 10 years, as a “end-user” when I was web operations manager for an online job board, as a team leader for a... Read More.
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