InfoQ Homepage Performance Content on InfoQ
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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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Javascript Performance with Stoyan Stefanov
Stoyan talks about the tools and practises that help developers deal with the issues that affect performance of JavaScript applications. He also comments on the evolution of the language and the popularity of transpilers like CoffeeScript and TypeScript.
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Michael Nygard - Redefining CAP
In this InfoQ interview, Michael Nygard explores some of the available loopholes in the CAP theorem helping architects to engineer distributed systems that meet their needs. He also discusses new patterns he’s observed since his book, Realease IT and shares his thoughts on continuous delivery, DevOps and ALM.
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Rick Hudson on Parallel JavaScript (RiverTrail)
In this interview, Intel's Rick Hudson talks about Parallel JavaScript (formerly known as "RiverTrail"), a new parallel programming API designed specifically for JavaScript. Rick describes RiverTrail and its vision of how to leverage current and future parallel hardware from within the browser and JavaScript.
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Ken Little on Scaling Tumblr
Ken Little talks about scaling Tumblr to keep up with their blogging users: scaling the data model, sharding, their PHP frontend and the Scala backend, and much more.
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Serkan Piantino on Scaling Facebook
Serkan Piantino explains how Facebook has managed to scale up, what types of errors occur in an architecture that size and how to handle them, RAM vs disk, and much more.
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Rich Hickey and Justin Sheehy about Datastores, NoSql and CAP
Rich Hickey and Justin Sheehy talk about scalability and transactionability of datastores. They explain tradeoffs for achieving read and/or write scalability on top of Datomic and Riak.
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Optimizing for Big Data at Facebook
Hive co-creator Ashish Thusoo describes the Big Data challenges Facebook faced and presents solutions in 2 areas: Reduction in the data footprint and CPU utilization. Generating 300 to 400 terabytes per day, they store RC files as blocks, but store as columns within a block to get better compression. He also talks about the current Big Data ecosystem and trends for companies going forward.
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Operating Node.js in Production, with Bryan Cantrill
Bryan talks about the challenges of operating Node.js in real production environments and the experiences he had working with it at Joyent. He also talks about DTrace, SmartOS, V8 and compares with other platforms.
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Attila Szegedi on JVM and GC Performance Tuning at Twitter
Attila Szegedi talks about performance tuning Java and Scala programs at Twitter: how to approach GC problems, the importance of asynchronous I/O, when to use MySQL/Cassandra/Redis, and much more.
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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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Hardware friendly, high performance Java-Applications
Martin Thompson and David Farley discuss how to use the scientific method to create high performance systems by measuring performance and adapting the implementation to approach the limits of current hardware. The disruptor architecture is an open sourced result of their work at low-latency, high throughput systems for the retail trading platform of LMAX Ltd.
