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Technology

Webcast – Free predictive Analytics For Microsoft System Center

By | Business Manager, Event Management, Microsoft Operations Management Suite, Process Owner, Service Owner, Subject Matter Expert, System Center Operations Manager | No Comments

Approved Consulting and Opslogix arranged a webinar to demonstrate the strength of implementing IT Service Analytics for your operational data in this recorded webcast. About IT Service Analytics IT Service Analytics is a free plug ´n play business intelligence and process support platform for Microsoft System Center. IT Service Analytics enables your IT organization(s) to make qualified decisions based on intelligent and accurate information gathered throughout your IT landscape. By optimizing and combining data from System Center Operations Manager, Microsoft OMS and System Center Service Manager into one holistic data model you are able to put the IT service in focus. This allows you to extract, correlate and predict information about IT Service Management processes. Download the presentation deck here IT Service Analytics.pdf. About the speaker Jonas Lenntun is the founder of Approved Consulting AB and has a long experience with Microsoft products and IT monitoring. After working in this area for over 15 years, Jonas has developed a broad knowledge of the entire Microsoft product range, with a personal focus on ITIL and System Center. His experience as CEO and former CIO with an understanding of IT challenges, combined with deep knowledge of Microsoft System Center, ITIL and Analytics is what led…

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Machine Learning algorithms together with SCOM for correlations between performance,  alerts and events data

By | Event Management, Subject Matter Expert, System Center Operations Manager | No Comments

Introduction This summer we had the benefit to do some research with the new features built in SQL Server and the more advanced analytical part of SQL Server 2016 such as R. The research intends to explore the possibility to find correlation between certain events, such as broken hardware or server unavailability, and deviations in performance data from related computer systems. The main purpose and final goal is to be able to automatically find the most probable causes to certain events, especially where there may not be any obvious connections and/or the number of considerable causes is far too many for manual analysis. The analysis has taken place in a smaller environment containing simulated errors. Performance, alerts and events data has been collected from a period of 30 days. Performance data from each point in time has been compared with other data from the same entity to measure its deviation. Its deviation ratio has been used to find patterns by filtering out data considered as “not deviating”.Some filtered data has appeared to have patterns similar to the patterns from some alerts and events. Calculating deviations from 30 days (7.7 million observations) has been possible in less than 3 minutes. The method should therefore be applicable on larger environments with decent…

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Predictive Analytics for System Center and OMS – The missing piece of the puzzle!

By | Event Management, Microsoft Operations Management Suite, Subject Matter Expert, System Center Operations Manager, System Center Service Manager | No Comments

World of IT is changing and so are the IT organizations. The cloud era has begun and it is now being widely adopted. As a result of this, new technologies and products are evolving rapidly, and many of them powered by the cloud platform. While it’s appealing to look into and explore all the new capabilities of all these new technologies, it’s easy to forget that most organizations in the real world are still managing or partially managing their datacenters on-premise. And more important for this article, many of them are managed with products from the Microsoft System Center Suite. In this article I will talk about combining and analyzing the result sets from different technologies, such as agent based monitoring from Microsoft System Center Operations Manager (SCOM), but also some rather new technologies, such as log analytics with Microsoft Operations Management Suite (OMS). In addition, I’ll address some of the concerns and requests we get from our customers throughout the industry such as service modeling, security considerations and wish for a holistic perspective of the whole IT Service delivery supported by their processes.

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The release of Predictive Analytics for Microsoft System Center

By | Business Manager, Change Management, Incident Management, Microsoft Operations Management Suite, Problem Management, Process Owner, Service Owner, Subject Matter Expert, System Center Operations Manager, System Center Service Manager | No Comments

Today we are proud to announce IT Service Analytics (www.itserviceanalytics.com), a plug ´n play business intelligence platform for Microsoft System Center. With your IT services in focus this toolset is built on IT Service Management (ITSM). It allows you to combine IT process data such as incidents-, change-, problem management with operational data from Microsoft System Center Operations Manager (SCOM) and log analytics from Microsoft Operations Management Suite (OMS). Make qualified decisions based on intelligent and accurate information thanks to a 360 end-to-end view of operations management and the ability to extract, correlate and predict information about IT Service Management processes. By implementing advanced analytics and statistical capabilities from data already collected, IT Service Analytics will turn your data into knowledge. IT Service Analytics is a comprehensive toolset to keep you one step ahead of the business demands while delivering high quality IT services.    

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Intercepting failures with time pattern recognition

By | Event Management, Subject Matter Expert, System Center Operations Manager | No Comments

You have both hourly and daily data for service component availability, performance, events and alerts gathered in SCOM. Since it is just heaps of data, it can be difficult to get an understanding whether any of the logged events occur according to some kind of time pattern and when any of them relate to one another. Recognizing reocurrences is very beneficial when managing sparse and at first sight unrelated events. After grouping and filtering all events by an identified time pattern we are able to find correlations and (hopefully) causations of specific happenings. In this blog post we will review the built-in SCOM reports for analyzing this kind of data and will also show you how adding some extra capabilities makes life much easier.  

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