InfoQ Homepage Performance Content on InfoQ
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The Fundamentals of JVM Tuning
Charlie Hunt presents the fundamentals of JVM tuning and provides advice for developers on writing a Java application that performs well at runtime.
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Dumb and Dumber: How smart is your monitoring data
Big Data is all the rage right now. Everyone from a social media company to your grandmother's online knitting store is suddenly a big data shop.
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Racing Thru the Last Mile: Cloud Delivery Web-Scale Deployment
Alex Papadimoulis discusses various deployment strategies, scalable delivery, with examples from real-world organizations such as AllRecipes.com, Twitter, and Google.
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JVM Mechanics – A Peek Under the Hood
Gil Tene discusses JVM observation-based runtime optimizations, ordering and memory model rules, basics GC functions, memory management, and JVM mechanics.
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Running with the Devil: Mechanical Sympathetic Networking
Todd Montgomery discusses messaging: application level batching, UDP datagram size’s impact on performance, sendmmsg/recvmmsg, implementing asynchronous calls.
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Visualizing Java Garbage Collection
Ben Evans discusses garbage collection in Java along with some tooling for understanding and visualizing how it works.
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Go at Google
Rob Pike explains how Google designed Go to address major development issues they encounter while using other languages: long build times, poor dependency management, lack of robustness, etc.
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PHP on the Metal with HHVM
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.
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How NOT to Measure Latency
Gil Tene introduces and demonstrates how simple and recently open sourced tools can be used to improve and gain higher confidence in both latency measurement and reporting.
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Timelines at Scale
Raffi Krikorian explains the architecture used by Twitter to deal with thousands of events per sec - tweets, social graph mutations, and direct messages-.
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Lock-Free Algorithms For Ultimate Performance
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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(un)Common Sense
Mike Solomon shares some of the experiences and lessons learned scaling YouTube over the years.
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