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.
Martin Thompson explores performance testing, how to avoid the common pitfalls, how to profile when the results cause your team to pull a funny face, and what you can do about that funny face. Specific issues to Java and managed runtimes in general will be explored, but if other languages are your poison, don't be put off as much of the content can be applied to any development.
Emad Benjamin explains how to deploy and tune a JVM on a virtual infrastructure (vSphere), and how to tune the garbage collector in this environment.
Gareth Rushgrove overviews Ruby on Rails and Django: object caches, fragment and HTTP caching, asset compilation, profiling, log file measurement and framework hooks for instrumentation.
Roy Rapoport discusses how Netflix uses metrics to monitor and manage their operating environment along with some notes about their event management system.
Gary P Russell shows an application used for managing and monitoring apps built with Spring Integration, and overviews the JMX support provided by Spring Integration.
Kevin Lynagh provides the rationale behind visual interfaces, and presents a sample example written in ClojureScript.
Johan Oskarsson explains how Twitter is using Zipkin to trace a pages in order to see their execution path and to determine the time spent for loading for performance monitoring and analysis.
Lloyd Dugan discusses using the BPMN visual programming language for designing composite services and service orchestration.
Bhaven Avalani and Yuri Finklestein discuss 4 aspects encountered at eBay when dealing with monitoring data: reduction of data entropy, robust data distribution, metric extraction, efficient storage.
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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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