Maxime Chevalier-Boisvert discusses making dynamic languages faster providing various examples of optimizations: SmallTalk, LISP machine, Google V8 and others.
Alex Gaynor explains how he solved the usual Ruby VM speed problems with Topaz, a high performance VM built on the same technologies that power PyPy.
Craig Smith, Renee Troughton discuss improving visual management: different types of story walls, ways to visualize the product backlog, the important of queue columns and WIP limitation, etc.
Keith Adams shares HHVM insights showing how a system can become very performant if it is well tuned.
Ariel Tseitlin discusses Netflix' suite of tools, collectively called the Simian Army, used to improve resiliency and maintain the cloud environment. The tools simulate failure in order to see how the system reacts to it.
Chris Oldwood discusses what it takes to create robust software: correct error detection and recovery, testing systemic effects, app monitoring and configuration.
Zach Tellman discusses instrumenting and analyzing running systems using real world examples from Factual's production systems.
Michael Kopp explains how to run performance code at scale with Hadoop and how to analyze and optimize Hadoop jobs.
Charlie Hunt and Monica Beckwith describe the operational basics of G1 and how to tune it, along with tips on what to expect when migrating from Parallel GC or CMS to G1 GC.
Charlie Hunt presents the fundamentals of JVM tuning and provides advice for developers on writing a Java application that performs well at runtime.
I'll talk about a few of the monitoring solutions and approaches I've used during my career as a monitoring architect at a large financial services institution, as well as present a few case studies of customers who have managed to make the leap from bigger data to smarter data.
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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.
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