Tag Archives: Performance

Data Grid Performance Factors

April 16, 2013

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The technical white paper that I wrote on JBoss Data Grid performance factors is now available for download.

It details the performance impact of configuration options in three basic configurations: distributed (XA) transactions, local (auto-commit) transactions, and no transactions.

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Garbage Collector Performance Comparison

April 10, 2013

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For the Red Hat / Intel webinar on big data and JBoss Data Grid (JDG), I executed a performance test against JBoss Data Grid with RadarGun on dedicated Intel hardware. Prior to executing the performance test, I executed a scaled down version of it with a number of garbage collector configurations including the new G1 collector. […]

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Application Performance Management with JON & RTI

February 28, 2013

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RTI (RootCause Transaction Instrumentation) is an APM (Application Performance Management) solution for Red Hat’s JBoss Middleware stack. RTI handles profiling, alerting & deep dive diagnostics and can be used across the software lifecycle. RTI is a fully integrated plug in to JBoss Operations Network. JON tells you when a problem occurs, RTI will tell you more – like where, how long and why.

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RHEL / OpenJDK – Performance Tuning

January 8, 2013

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This post highlights three performance tuning techniques for Red Hat Enterprise Linux (6.2) and OpenJDK (1.6): TCP send / receive windows, large page memory, and i-CMS.

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JBoss Data Grid v Terracotta BigMemory

December 19, 2012

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Introduction

I am currently working on a technical white paper that details the performance of a number of JBoss Data Grid configurations using RadarGun. While working on it, I found out that Terracotta published a technical white paper covering BigMemory performance here. I decided to create a JBoss Data Grid / RadarGun configuration using the same parameters as the Terracotta BigMemory performance test, and execute it on my performance testing hardware.

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Concurrent, High Throughput Performance Testing with JMeter

July 31, 2012

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This post highlights a few tips that may be necessary to identify the maximum concurrent throughput of one or more application servers with JMeter. They include TCP / IP tuning, load balancer tuning, and garbage collection tuning.

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Know your ulimits.

July 27, 2012

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When running Apache HTTP Server 2.2 and / or JBoss Enterprise Application Platform (EAP) 6 on Red Hat Enterprise Linux (RHEL) 6 with a high number of concurrent connections, the user resource limits may need to be changed.

This post highlights two scenarios where the user resource limits may need to be changed: the maximum number of user processes is too low, the maximum number of open files is too low.
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Improving Security and Performance with Red Hat & Intel

July 26, 2012

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Advanced Encryption Standard (AES)

What is it?

AES is a Federal Information Processing Standards (FIPS) approved cryptography algorithm (FIPS PUB 197). It is a symmetric-key algorithm. It uses the same cryptographic key for both encryption and decryption. Furthermore, it is a block cipher.

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