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Wednesday, September 27, 2017

I am nominated (and now ELECTED) again for CMG 2018/2019 #BoardOfDirectors - #CMGnews

October 2017 update: I have been elected on the next 2 years term.
_____
I have been working as the director for CMG for almost 2 years.
Sitting on the Board of Directors (www.CMG.org)

Here is my previous nomination statement:

CMG Board of Directors Nomination


My term in CMG BOD comes to the end soon and the work was very interesting and exciting!
So I decided to nominate myself for the next term as I believe after gathering so great experiences as a CMG director now I can serve much more productive!

Below is my updated nomination statement:
Professional Work Experience: I have over 30 years of experience in the IT field. I have started my career in 1979 as an IBM 370 system engineer. In 1986, I received my PhD. in Robotics at St. Petersburg Technical University (Russia), where I then taught full-time such subjects as CAD/CAM, Robotics and Computer Science for about 12 years. For that period, I have published more than 30 papers and made several presentations for different international conferences related to the Robotics, Artificial Intelligence and Computer fields. In 1999, I moved to the US and worked at Capital One bank as a Capacity Planner. My first CMG paper was written and presented in 2001. The next one, "Global and Application Level Exception Detection System Based on MASF Technique," won a Best Paper award at CMG’02 and was presented again at UKCMG’03 in Oxford, England. My CMG papers were republished in the IBM z/Series Expo and in CIS Jornal. I also presented my papers in Central Europe CMG conference (Austria) and at numerous US regional meetings including workshops. After working more than 2 years as the Capacity Management team lead for IBM, I had worked for SunTrust Bank for 3 years and then got back to IBM holding for 2+ years Sr. IT Architect position (Certified IT Specialist). Currently I work for Capital One bank as IT Manager for IT Capacity Management group.
Major accomplishments: SETDS ML Anomaly detection methodology; Model Factory (patent pending). The current list of my publications consists of 14 items. I have an entrepreneurship experience as I have recently formed my small business for developing cloud based mobile apps and services (TRUTECH development, LLC)
Since 2005 I have worked as SouthernCMG vice-chair covering vendors’ connections.
In 2015 I have been elected to the CMG (http://www.cmg.org) board of directors. Major achievements as a CMG Director are: working in publication committee I have prototyped and put into CMG.org  site the CMG blog and published there a few initial posts; I was the MeasureIT editor and also helped to reestablish CMG journal. Found Suggested some good invited speakers for conference (e.g. Kevin McLaughlin from Capital One); brought 4 vendors as potential partners and also work in CMG regions committee. Has started organizing the DC area CMG meet-up (former NCACMG)

Willingness to Serve: CMG has been an extremely valuable part of my professional life for the past 15th years. Because of CMG, I became a known specialist in IT Capacity Management discipline! I have already worked at the regional CMG  level to support the organization and would like to serve on CMG's Board of Directors to continue promoting the organization throughout the IT community. My company and family members support my involvement with and commitment to CMG.

Candidate Statement: I believe that I am uniquely qualified and motivated to serve CMG and its future development, as the IT landscape dramatically changes. As my major accomplishment lays in the area of Machine Learning, Predictive analytics and Anomaly detection (e.g. SETDS method) I would like to be sure that CMG content reflects this and other bleeding edge technology including cloud computing and big data. Being experienced blogger/vlogger (System Management by Exception/ iTrubin on YouTube), I would leverage social networks to bring more members to CMG. Also I would like to leverage my success in establishing the vendors’ connection to bring more partners and sponsors. So my position as a Capacity Management expert and my dedication to the CMG organization will allow me to contribute in substantial ways. I further believe that my teaching experience could enhance CMG’s training and educational services for technical community. If elected, I will diligently pursue innovative ways to strengthen the organization’s membership. I will continue the CMG’s dedicated tradition of volunteerism and will actively seek ways to support and improve CMG's commitment to supporting its members.

ME: 





Friday, September 15, 2017

I invite you to register for the #cmgimPACt conference and save 15%!

Dear Friends,
Hope you are well! As you know I am a part of the Board of Directors for Computer Measurement Group (CMG). This November we are hosting our 43rd annual imPACt conference November 6th-9th in New Orleans, Louisiana.
I think that this conference – which will host a variety of speakers from companies such as Netflix and Capital One – is something you should consider participating in. The networking and knowledge exchange opportunities are plentiful, and it should be a good time as well!
My friends and colleagues can register for the conference and save 15% using the code CMGBOD during the registration process.
I hope to see you there!
www.cmgimpact.com for more information


Rich Galan of Rubicon Project: The Need for Real-Time Anomaly Detection


Thursday, September 7, 2017

#imPACt 2017 conference program is published. 4. "Applying Artificial Intelligence for Performance Engineering" (#CMGnews)

See the full program HERE

 Applying Artificial Intelligence for Performance Engineering 
EMT
Environments become very complex thanks to new technology and architectures. Change happens more rapidly. Performance Engineering is either part of the pipeline or happens in production. This work cant be done by looking at static dashboards any longer and drawing conclusions based on years of experience. Performance Engineering has to leverage new approaches such as anomaly detection, machine learning and artificial intelligence. In this session I talk about how Dynatrace leverages AI to scale and automate many of the performance engineering tasks
Presenter bio: Andreas has been working in software quality for the past 15 years helping companies from small startup to large enterprise figuring out why their current application falls short on quality and how to prevent quality issues for future development. He is a regular speaker at international conferences, meetups & user groups. He has done DevOps Boston, Velocity Santa Clara, Agile Testing Days, Star West or STPCon in the recent years. Besides being excited about software quality he is also an enthusiastic salsa dancer
Andreas Grabner

Monday, August 28, 2017

#imPACt 2017 conference program is published. 3. "Rules of Thumb for Response Time Percentiles" (#CMGnews):

See the full program HERE


Again Percentiles! My anomaly detection tool (SonR) now has option to use percentiles to calculate UCL and LCL (Control Limits).



Let's go a listen about  percentiles at the following CMG international conference session:
 Rules of Thumb for Response Time Percentiles: How Risky are they? 
PERF
Whether externally mandated or internally tracked, the enterprise relies on governance of application service response time objectives. In many cases, achieving service requirements in terms of the average response time may not deliver an experience that delights the consumer. The consumer may request a deeper level of governance. Service providers want to achieve the promised objectives and, on the other hand, avoid over-provisioning. This paper explores rules of thumb that can be applied to estimate 90th or 95th percentiles for service response times, based on the measured or predicted mean. The risk assessment behind these recommendations is described in the paper. Various types of networks were modeled and analyzed. Even though classical queueing models rely on strict assumptions (and rarely met in the real world), it was found that the classical M/M/1 model provided a useful upper bound. Another function was evaluated for tighter accuracy.
Presenter bio: Dr. Salsburg is an independent consultant. Previously, Dr. Salsburg was a Distinguished Engineer and Chief Architect for Unisys Technology Products. He was founder and president of Performance & Modeling, Inc. Dr. Salsburg has been awarded three international patents in the area of infrastructure performance modeling algorithms and software. In addition, he has published over 70 papers and has lectured world-wide on the topics of Real-Time Infrastructure, Cloud Computing and Infrastructure Optimization. In 2010, the Computer Measurement Group awarded Dr. Salsburg the A. A. Michelson Award.
Presenter bio: Co-founder and Chief Scientist, BGS Systems, 1975 - 1998

#imPACt 2017 conference program is published. 2. "The Curse of P90..." (#CMGnews):

See the full program HERE

I love Percentiles! My anomaly detection tool (SonR) now has option to use percentiles to calculate UCL and LCL (Control Limits).

Let's go a listen about  percentiles at the following CMG international conference session:

The Curse of P90: An Elegant Way to Overcome it Without Magic 
CAP
Over the decades of development of methodologies and metrics for IT capacity planning and performance analysis, percentile terminology has become the lingua franca of the field. It makes sense: percentiles are easy to interpret, not sensitive to outliers, and directly usable for approximating the distribution of the variable being measured for stochastic simulations. However, depending on which percentile is used, we can miss important information, like multimodality of the metric's distribution. Another, less obvious, downside of relying on percentiles comes into play when we size infrastructure for a high percentile of demand (e.g., p90). Given that it takes time to order, manufacture, receive, and install infrastructure, this means that we need to answer the statistically nontrivial question, "what will this percentile of demand be in one to three years?" This paper discusses the issues that arise in answering it and proposes an elegant way of resolving them.
Presenter bio: Alexander Gilgur is a Data Scientist and Systems Analyst with over 20 years of experience in a wide variety of domains - Control Systems, Chemical Industry, Aviation, Semiconductor manufacturing, Information Technologies, and Networking - and a solid track record of implementing his innovations in production. He has authored and co-authored a number of know-hows, publications, and patents. Alex enjoys applying the beauty of Math and Statistics to solving capacity and performance problems and is interested in non-stationary processes, which make the core of IT problems today. Presently, he is a Network Data Scientist at Facebook and an occasional faculty member at UC Berkeley's MIDS program. He is also a father, a husband, a skier, a soccer player, a sport psychologist, a licensed soccer coach, a licensed professional engineer (PE), and a music aficionado. Alex's technical blog is at http://alexonsimanddata.blogspot.com.