We mostly ship software by date, squeezing all development and testing efforts toward that deadline. We prioritize what we think is important, and once our application passes a certain quality level, we’re ready to go live. But even when we do ship, can we tell the readiness status of our application?
Netflix is a widely referenced case study for how to operate a cloud application at scale. In this interview, InfoQ spoke with Adrian Cockcroft who is the Cloud Architect for the Netflix platform.
In July Monica Beckwith explored the theory of the new G1 GC Garbage First Garbage Collector. In this second installment, Monica delves into more practical aspects and provides guidance for tuning. 10
A question that often comes up on Performance Management – Agile talks about team performance so why am I measured on individual goals which have little to do with team performance? 4
In this article, we look at the HotSpot Java Virtual Machine, and its implementation in the OpenJDK, both from a VM perspective and also in terms of its interaction with the Java class libraries. 1
Writing applications in C++/CX is not like writing normal C++ applications. The interoperability between pure C++ code and the Windows Runtime (WinRT) can be surprisingly expensive.
InfoQ brings together four experts in low latency Java to discuss some of the best practices when using Java in these situations.
Many articles describe how a poorly tuned garbage collector can bring an application's SLA to its knees. The G1 collector replaces the conventional algorithms with a concept of “regions” 4
In the world of application delivery, performance tuning still eludes the mainstream. InfoQ spoke to 5 luminaries of the performance monitoring space about it. The result was quite an active debate.
Do the hundreds of JVM start-up flags baffle you when trying to tune the garbage collector? This article will explain the tradeoffs when choosing and tuning garbage collection algorithms 1
Over the past 18 years Java has evolved into the premiere language of the enterprise. Yet cognitive fallacies persist about Java performance. In this article we examine some popular misconceptions. 23
CONTENT IN THIS BOX PROVIDED BY OUR SPONSOR
White Papers and Assets
Featured Blog Posts
Navigating APM: How Garmin Improved Java Performance with Run Book Automation
Top 3 Automated Tasks for Finding and Fixing Problems
Proactive APM: How Expedia Increased Response Times - for 10,000 partners - with AppDynamics
The Most Important Lesson I Ever Learned About Solving Performance Problems
The Real Cost of Downtime