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Tuesday, August 23, 2011

CMG'11 papers about non-statistical ways to capture outliers/anomalies and trends

from  The CMG'11 Abstract report  :

Monitoring Performance QoS using Outliers
Eugene Margulis, Telus
Commonly used Performance Metrics often measure technical parameters that the end user neither knows nor cares about. The statistical nature of these metrics assumes a known underlying distribution when in reality such distributions are also unknown. We propose a QoS metric that is based on counting the outliers - events when the user is clearly “dis”-satisfied based on his/her expectation at the moment. We use outliers to track long term trends and changes in performance of individual transactions as well as to track system-wide freeze events that indicate system-wide resource exhaustion.

BTW I have already tried to "count" outliers  ; see my 
2005 paper listed here: http://itrubin.blogspot.com/2007/06/system-management-by-exception.html

I used the SEDS database to count and analyze exceptions:

Introduction to Wavelets and their Application for Computer Performance Trend and Anomaly Detection: 
Introduction to wavelets and their application for computer performance analysis. Wavelets are a set of waveforms that can be used to match a signal or noise. There are various families of wavelets unlike Fourier Analysis. Wavelets are stretched(scaled) in time AND frequency and correlated with the signal. The correlation in time and frequency is displayed as a heat map. The color is the intensity, the X axis is the time and the Y axis is the frequency. The heat map shows the time the trends or anamoly starts and when it repeats(frequency).

CMG'11 Abstract Report shows my virtual presence

The CMG'11 agenda is online now. The Abstract report shows the following paper related to this blog subject:

1. A Real-World Application of Dynamic Thresholds for Performance Management by Jonathan B Gladstone

He published some material on this blog that most likly is included in his CMG paper: 

Feb 17, 2011
Jonathan Gladstone has worked with a team to implement pro-active Mainframe CPU usage monitoring, basing his design partly on presentations and conversations with Igor Trubin (currently of IBM) and Boris Ginis (of BMC Software).

Here is the abstract form the Abstract report:
The author describes a real application of dynamic thresholds as developed at BMO Financial Group. The case shown uses performance management data from IBM mainframes, but the method would work equally well for detecting deviations from normal patterns in any time-series data including resource utilization in distributed systems, storage, networks or even in non-IT applications such as traffic or health management. This owes much to previous work by well-regarded CMG participants Igor Trubin (currently at IBM), Boris Zibitsker (BEZ Systems) and Boris Ginis (BMC Software).

2. Automatic Daily Monitoring of Continuous Processes in Theory and Practice by Frank Bereznay

    Monitoring large numbers of processes for potential issues before they become problematic can be time consuming and resource intensive. A number of statistical methods have been used to identify change due to a discernable cause and separate it from the fluctuations that are part of normal activity. This session provides a case study of creating a system to track and report these types of changes. Determining the best level of data summarization, control limits, and charting options will be examined as well as all of the SAS code needed to implement the process and extend its functionality.

I believe that paper is based on the presentation he did at Southern CA CMG this year, which I have already mentioned in my following post: "The Master of MASF"

I have not written any paper for this year (1st time for the last 10 years!) but I glad that the technology I have been promoting for years still have presented in this year CMG conference with some references to my work!

Tuesday, August 16, 2011

"The Master of MASF"

The following paper has been recently presented at  Southern California CMG (SCCMG)

Automatic Daily Monitoring of Continuous Processes
Theory and Practice


MP Welch – Merrill Consultants
Frank Bereznay - IBM
That is another great paper that promotes the MASF approach in System performance monitoring, which is actually the main subject of this blog. Most likely that paper will be presented again and publish at the international  CMG'11 conference.

I am very proud that I was called "The Master of MASF" at that presentation! Thank you, Frank!
Here is the link to the presentation file I have found via google, which has the following pages referencing my work and also this blog:

Automatic Daily Monitoring of Continuous Processes Theory and Practice

The paper also has good references to Ron Kaminski and  Dima Seliverstov work. Both authors as well as Frank  Bereznay have already  been mentioned in this blog already: 

See the following posts for Frank  Bereznay work:

Aug 13, 2007
2006 Best Paper Award paper: Did Something Change? Using Statistical Techniques to Interpret Service and Resource Metrics. Frank M. Bereznay, Kaiser Permanente LINK: http://cmg.org/conference/cmg2006/awards/6139.pdf ...

Nov 05, 2010
Brian Barnett, Perry Gibson, and Frank Bereznay. That paper has a deep discussion about normality of performance data, showing examples where MASF approach does not work. The Survival Analysis that does not require any knowledge of how...

For Ron Kaminski work:

Jan 24, 2009
and ron kaminski who expressed some interest in my ev algorithm to capture recent bad trends as that solves some problems of workload pathology recognition on which he has been working recently. so you want to manage your z-series mips?

And for Dima Seliverstov work:

Dec 10, 2010
At CMG'10 conference I met BMC software specialist Dima Seliverstrov and he mentioned of referencing my 1st CMG'01 paper in his CMG presentation (scheduled to be presented TODAY!). I looked at his paper "Application of Stock Market...