Lean has proved to be instrumental in moving beyond Agile to set up a practice of continuous improvement with direct effects on team performance and engagement. Making a clear distinction between bugs and problems has proved to be instrumental in this improvement.
In this article we present some of the most common performance analysis antipatterns in the enterprise platform, expressed in terms of their basic causes along with remediation strategies.
In this article, authors discuss the role of big data and Hadoop in security analytics space and how to use MapReduce to process data for security analysis.
Raffi Krikorian, Vice President of Platform Engineering at Twitter, gives an insight on how Twitter prepares for unexpected traffic peaks and how system architecture is designed to support failure. 1
Garbage Collection takes minutes to learn and a lifetime to master. In this article Master trainer/consultant Ben Evans summarizes his recent InfoQ presentation "Visualizing Garbage Collection"
In this article, author explores Cassandra CLI architecture model using JArchitect tool and CQLinq language to analyze its code base.
Anatomy of a light-weight, lockless, inter-thread communication framework in Java. 17
On certain occasions you will need to build your own parser, eg if there is nothing standard that fits the bill. This article walks through the steps of building a high performance parser 7
Sometimes memory profiling is better than execution profiling for finding execution hot spots. In this article Kirk Pepperdine talks through some indicators for determining when to use which profiler 7
Chris Smith offers insights on how to leverage the increasing employee adoption of cloud services (Bring Your Own Cloud) to perform their work. Understanding the risks and benefits becomes essential.
We mostly ship software by date, prioritizing what we think is important, and shipping once out app passes a certain quality level. But can we tell the readiness status of our application?
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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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