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Webcast - Free predictive Analytics For Microsoft System Center

Approved Consulting and Opslogix arranged a webinar to demonstrate the strength of implementing IT Service Analytics for your operational data in this recorded webcast.

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

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.

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Continual Service Improvement - and how to become better!

CSI, or Continual Service Improvement, is one of the more important processes when working with IT Service Management. To achieve good results when implementing IT Service Management you need to be able to measure, follow up and evaluate complete processes and not just separate parts at a time.

Showing a holistic picture of how functional your IT Services are yet another challenge while using System Center products. They are all sold under one System Center flag and yet are completely separate entities. Thus making your life hard once you realize that all of the separate bits and pieces are actually a part of one big puzzle.

Here is how we help our clients overcome the System Center segregation issue and enable them to have full visibility of their IT Service Delivery.

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

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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Automated analysis - the shortcut to proactive monitoring

The transition from reactive to proactive monitoring can in some cases be a real challenge for IT organizations. This usually involves a lot of tuning of thresholds and alerts to give an early indication if a resource might fail. It can also increase the alert noise in your environment and to succeed with the proactive initiative, more IT staff might be required to work with all the new alerts and indications to prevent a possible service failure.

To deliver a successful implementation of proactive monitoring with the increased amount of events generated from growing numbers of devices each year, another approach needs to be considered.

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The release of Predictive Analytics for Microsoft System Center

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Intercepting failures with time pattern recognition

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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Detecting abnormal behavior with baseline filtering

I bet we would all agree that the ultimate goal of IT monitoring is to prevent IT service outages. But admit, even with all the monitors set up in System Center Operations Manager and alerts configured to notify admins when vital thresholds have been reached, we are still not being efficient enough in solving (not to mention preventing) critical issues on time.

Dealing with alerts generated in SCOM has multiple complications. Too many alerts being generated and no clear priority system are a few examples, leading administrators into 'alert ignorance'.

In this article we are going to look at a different approach to identifying upcoming issues in your IT environment which will introduce clarity and guidance into the assorted jungle of alerts and capacity issues.

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Forecasting System Center Operations Manager data

With the massive amount of data collected in the System Center Operations Manager from all servers and other monitored equipment, IT Operations departments are sitting on a gold mine of data just begging to be used. One of the areas that can benefit from such internal data capital is forecasting.

By implementing forecasting processes you can predict the behavior of managed objects some months into the future. This knowledge enables you to act in advance in order to prevent service failures and service level breaches.

Most business areas use some kind of forecasting methods when planning new investments, calculating yearly budgets etc. We believe that IT organizations should be no different and start using operational data to gain insights and learn from the past while planning their future.

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Querying Distributed Application data from SCOM Data Warehouse

Operations Manager is good at monitoring performance of separate software components.It also has an interface to bundle them together into groups in order to be able to understand what the health state of the whole as a group is.

In SCOM context this is called a Distributed Application. At Approved we treat this (with addition of Live Maps Unity from Savision) as an interface for managing IT Services.

As in most cases after getting data into SCOM and then into SCOM Data Warehouse, some day we want to extract and analyze this data or, better yet, use it as a base to predict future outcomes and deal with issues before users even notice them.

And, as in most cases, extracting and querying SCOM DW Distributed Application data is not really straightforward. Lets start with finding the 'services' themselves.

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