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.
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.
Martijn Verburg discusses his new start-up jClarity, which offers performance tooling for the Cloud. He also provides an update on the Adopt a JSR and Adopt OpenJDK programs.
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.
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.
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.
Larva is a runtime monitoring system that uses AspectJ to weave monitoring into Java code and can check the correctness of the program using an FSM; Elarva is an Erlang version of the tool.
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.
Jon Brisbin discusses his experience with Virtualization and reasons why companies would use Private Clouds, eg. regulation compliance. Also: the future role of operations, monitoring, and more.
John Leach explains how Brightbox uses Virtualization in the data center and whether Virtualization causes performance problems. Also: a look at a few Unix tools and Linux features that Ruby developers might not know about.
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.
In this interview from SpringOne 2009, Javier Soltero discusses the challenges of managing a complex Java application, the Hyperic toolset, out-of-the-box versus developer-built application management/monitoring hooks, the effect of both the SpringSource and the VMWare acquisition on Hyperic development, and the result of combining SpringSource and VMWare's offerings.
CONTENT IN THIS BOX PROVIDED BY OUR SPONSOR
Featured Blog Posts
The term “Big Data” is quite possibly one of the most difficult IT-related terms to pin down ever. There are so many potential types of, and applications for Big Data that it can be a bit daunting to consider all of the possibilities ... Read More.
The biggest difference between cloud-based applications and the applications running in your data center is scalability. The cloud offers scalability on demand, allowing you to expand and contract your application as load fluctuates ... Read More.
In the last post I covered several architectural techniques you can use to build a highly scalable, failure resistant application in the cloud. However, these architectural changes – along with the inherent unreliability of the cloud ... Read More.
White Papers and Assets
|QCon SF||Nov 3-5|
|AppSphere 2014||Nov 3-5|