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InfoQ Homepage Performance Tuning Content on InfoQ

  • How We Reduced Our React App’s Load Time by 60%

    React handles UI updates efficiently but it does not magically make your web app faster. As our application grew in size, we started noticing some drawbacks of our setup. Although we knew how React worked and how Redux manages state, our application had bloated in size. We started seeing application crashes and jank. It was time to drive down the technical debt and make performance improvements!

  • Book Review: Optimizing Java

    InfoQ reviewed the book Optimizing Java, a comprehensive in-depth look at performance tuning in the Java programming language written by Java industry experts, Ben Evans, James Gough and Chris Newland. InfoQ spoke to the authors for more insights on their experiences, learnings and obstacles in authoring this book.

  • Under The Hood with the JVM's Automatic Resource Management

    The deprecation of Object::finalize is an unusual step for the Java ecosystem. We dive deep into the Hotspot JVM to see how it works. We also compare it to RAII and the Java 7, try-with-resources syntax. The article contrasts these very different approaches to automatic resource management, and explains why TWR should be used in place of finalization by application programmers.

  • Want to Know What’s in a GC Pause? Go Look at the GC Log!

    Sometimes a superficial analysis of our application performance can incorrectly have the Garbage Collector point to itself. A proper GC log analysis can lead us past the “blame the collector” game. When this happens, we can make amazing discoveries that improve the performance and stability of our applications.

  • Learning Paths: QCon London Expert Recommendations

    Advice on the best talks to attend at QCon London 2017 from London Thought Leaders.

  • Improve Your Node.js App Throughput One Micro-optimization at a Time

    To improve the performance of a Node.js application that involves IO, you need to understand how your CPU cycles are spent and what is preventing higher degrees of parallelism in your application. In this article, Jorge Bay shares his insights on areas that cause throughput degradation and tips on how to boost performance.

  • Book Review: Learn Apache JMeter by Example

    JMeter is an indispensable tool for testing load and functionality of multi-tiered applications comprised of web front ends, JVM servers and a wealth of NoSQL and relational databases. This book is the manual that should have been included to help surmount the learning curve.

  • On Abstractions and For-Each Performance in C#

    Donald Knuth famously said, “We should forget about small efficiencies, say about 97% of the time”. But when faced with the other 3%, it is good to know what’s going on behind the scenes. So in this article we’ll be taking a dive into the foreach loop.

  • Top 10 Performance Mistakes

    Martin Thompson, co-founder of LMAX, keynoted at QCon São Paulo 2016, outlining the top 10 performance related mistakes that he has encountered in production.

  • Diagnosing Common Database Performance Hotspots in our Java Code

    Java performance issues are often attributable to bad database access patterns. In this article a top performance field engineer demonstrates his patterns for diagnosing database related issues.

  • Getting Started with Monitoring using Graphite

    Setting up a new monitoring system might seem daunting at first. Franklin guides us through the first steps and explains the architecture and inner workings of a Graphite-based monitoring system. Key takeaways are understanding time series data and configuration, datapoint formats, aggregation methods and retention.

  • The Fatal Flaw of Finalizers and Phantoms

    Most developers know that finalizers should not be depended on, but sometimes they are necessary. PhantomReferences, often cited as a good alternative, also suffer from the same fundamental problems. In this article we reveal how to contend with the many issues surrounding finalization in Java.

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