Jazz Performance – A Guide to Better Performance

Note: I have had a tremendous response to this article, and the attached PDF.  I also received some great feedback which I am incorporating into the document.

  • 2/13/2013 – updated the document based on comments and feedback.
  • 2/14/2013 – updated the PDF document based on additional feedback.  Added content on reporting and weekly administrative tasks.

A lot of my time has been spent working on Jazz performance over the past year.  As I worked with different customers, I saw a lot of different approaches and a lot of different performance issues.  As the year has rolled on, I have tried to capture things that I have learned, and share them in my blog series on Jazz performance (see Jazz Performance Part 1 – Is My Network Causing Me Pain?).  I have also been capturing a lot of the best practices and explanations about Jazz performance.  I have compiled all of this information, and checked with the experts, and put it all into one place.

Last year, some of my IBM friends also mentioned the concept of a performance guide to our customers.  They called this guide a “Purple Book”.  What you see attached here is the initial version of that “purple book”.  Why am I releasing this right now, on my blog?  Why isn’t this on the “official IBM site” or up on Jazz.net?  This is an early copy of that “Purple Book”, but there is enough good information in here that it may be worthwhile for a lot of our customers.  It still needs more information, more refinement and more review, before it can get released on Jazz.net.  This information will actually become the foundation of a Deployment wiki site which should go live later this year.  I expect the information to be updated and expanded upon in that deployment wiki.  This document is a “point in time” view of Jazz performance.  I know that it will improve and change over time, as new tools and techniques for monitoring and improving Jazz performance are uncovered.  Please feel free to provide comments (and even content!) for this guide.

So what is this guide about?  It has sections on what impacts the performance of a Jazz solution, with some basic explanation of why performance is impacted.  It has a guide on monitoring your Jazz implementation, and then finally ends with a section of troubleshooting advice and tips.   Here is a link to the Jazz Performance Guide, please give it a read and let me know what you think.

6 thoughts on “Jazz Performance – A Guide to Better Performance

  1. Marty Duchow

    Dan – Thank you so much for this great piece of work. It’s a very solid foundation for the comprehensive performance guide information we’ve been struggling to assemble from so many disparate IBM resources.

    A few comments, suggestions, wishes…
    · Regarding browsers – I know IBM tends to softshoe around the browser wars and as such shies away from deep dive analysis and endorsement of one browser vs. another. While I understand their position, it’s an uphill battle for many large corporate environments to move beyond IE, particularly IE8. Even references to raw data benchmarks with the CLM tools would be very helpful in making the case for alternate browsers in my environment.
    · I would like to see mention of the performance impact (memory, cpu, threads, etc.) of running the data collection jobs. These are typically meant to be run during off-peak times, but we have pressure to run these multiple times during a 24-hr cycle so both on-shore and off-shore see fresh data, as well as on-demand requests for special runs during the daytime.
    · Related to the previous item, it would be nice to see mention of RRDI or other warehousing solutions mentioned. Our RRDI WAS JVM is on a separate box – but it’s a separate virtual box. Should it be on a separate VM host as well? Similar question for the database side. Plus any other reporting considerations would be helpful.
    · Based on how we configure our WAS environment, our architecture is significantly different than what you recommend. Specifically, we run all our JVMs on one large VM (32GB directly allocated memory with 24GB of that dedicated to the various JVMs). I realize you can’t address every possible configuration, but a broader discussion of how to properly size such an alternate environment and the limitations of it would be great as we don’t have much choice but to live within our enterprise standards.


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