InfoQ Homepage Performance Tuning Content on InfoQ
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Yao Yue on Making Twitter's Pelikan Cache Fast And Reliable
Yao Yue explains the motivation for building Twitter's Pelikan cache, how Pelikan differs from other caches, what to do and what to avoid when building reliably low latency software, and much more.
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David Riddoch on Bypassing the Kernel and Hypervisor for Network I/O, Solarflare, OpenOnload
David Riddoch explains how bypassing the OS kernel's networking stack can improve latency and throughput, networking with Solarflare and OpenOnload, hypervisor bypass, and much more.
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Gil Tene on Understanding Latency
Gil Tene explains latency and how it relates to service and response times, measuring latency, common misconceptions about latency, what to do when a system's latency can't meet SLAs, and much more.
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Monica Beckwith on Tuning and Optimizing Java Garbage Collection
Performance engineer Monica Beckwith covers tuning java garbage collection, including: defining customer requirements; methodology; baselining and measurement; strengths and weaknesses of the different collectors; heap usage; causes of GC pauses; the distribution of pauses; tuning pause characteristics; going off-heap to avoid collection; scaling GC on multi-core and high memory machines.
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Ashley Puls on the How and Why of Java Bytecode Manipulation
Ashley Puls explains Java bytecode manipulation: reasons for manipulating bytecode, libraries that help, how NewRelic is using it, and more.
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Cliff Click on In-Memory Processing, 0xdata H20, Efficient Low Latency Java and GCs
Cliff Click explains 0xdata's H20, a clustering and in-memory math and statistics solution (available for Hadoop and standalone), writing H20's memory representation and compression in Java, low latency Java vs GCs, and much more.
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Demystifying Protocols and Serialization Performance with Todd Montgomery
Todd Montgomery talks about improving serialization times and throughput can by understanding how your computer processes and stores data. With this new understanding, architects and developers can build their own protocols to efficiently transmit data. Todd's advice sheds new light on why software developers choose their current serialization and marshaling techniques and how they can improve.
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Jim Hirschauer on Application Monitoring, AppDynamics 3.7
Jim Hirschauer describes the application monitoring tool landscape, KPIs and metrics to consider when monitoring, and compares monitoring traditional vs. cloud-based applications. He talks about performance considerations when instrumenting code, how organizations can be 'Smarter' about their Big Data, and looks at what's new in AppDynamics 3.7.
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John Nolan on the State of Hardware Acceleration with GPUs/FPGAs, Parallel Algorithm Design
John Nolan shows the state of hardware acceleration with GPUs and FPGAs, why it's hard to write efficient code for them, and why to favor polymorphism over if statements for performance.
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Cliff Click on Azul's Pauseless GC, Zing, JVM Languages
Cliff Click discusses the Pauseless GC algorithm and how Azul's Zing implements it on plain x86 CPUs. Also: what keeps dynamic languages slow on the JVM, invokedynamic, concurrency and much more.
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Jon Travis on Hyperic HQU and Monitoring with Spring Insight
Jon Travis explains Hyperic HQU as well as Spring Insight, a tool for monitoring Java web apps, how it uses AspectJ to instrument Java code, how to use it to find performance problems and more.
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Chris Wanstrath on GitHub
Chris Wanstrath discusses the state of GitHub's architecture, how GitHub is used and its impact on open source collaboration.
