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Understanding the Virtualization and Cloud Management Puzzle

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Edit Note: This is the second of a three-part post. In the first post Sanna summed up the history of enterprise IT consolidation initiatives based on server virtualization, and how those initiatives hit a brick wall at about 30 percent based on management complexity and concern over application performance in virtualized environments.

Since virtualization has created a dynamic management environment that defies human analysis, it stands to reason that any new solution will need to be much more advanced than any approach requiring human interpretation and/or manual processes. The answer lies in advanced mathematics and automation found in “behavior learning” technology and predictive IT analytic applications as a new approach to managing virtualization and cloud environments.

These predictive analytic approaches for IT leverage advanced mathematical and statistical engines that Gartner defines as Behavior Learning technologies to perform real-time data analysis, capacity management and ensure performance of a heterogeneous IT environment automatically.

Recently categorized by Gartner as “transformational,” behavior learning technologies are emerging as a key advancement in solving performance and visibility issues connected with virtualization management. While behavior learning technologies have been around for a few years, allowing enterprises to massively automate manual and rules based processes for physical environments, it was not until the advent of virtualization where the technology found its calling.

Companies such as CA, Microsoft, (s msft) BMC,(s BMC) HP (s hpq), and VMware (s vmw), provide basic analytic capabilities, such as dynamic baselining, within their flagship solutions. Netuitive is a company that specializes in predictive analytics with a software platform that sits on top of the enterprise IT infrastructure stack where it collects analyzes and correlates data in real-time from all of the existing IT monitoring tools including those mentioned above. This enables automated end-to-end monitoring and management of complex infrastructures.

This new framework replaces manual, rules-based approaches to performance management with an analytics-based approach that automatically correlates and self-learns the behavior of the entire IT environment to identify, forecast and resolve IT problems before they impact quality of service. By taking this holistic approach, it provides coveted visibility across platforms and vendors that until now has been lacking. And because its learning is adaptive, this approach excels in dynamic, virtualized infrastructure environments. This is what effective virtualization and cloud management is all about — visibility across all layers of the IT stack, automated problem diagnostics and predictive analytics enabling organizations to manage their performance and capacity proactively.

Early adopters of behavior learning are some of the smartest and largest production deployments of VMware in the world. For example, Netuitive users include seven of the top 10 banks and two telco giants who are now able to predict degradations and avoid outages for their most critical applications. One global telco reported that it is using a behavior learning platform to analyze more than a million metrics simultaneously allowing it to eliminate 3,480 hours annually in service degradation representing a business savings of $18 million.

That’s management in a virtualized enterprise environment, but what about the cloud?

This is second post in a three-part series. The third post will run Sunday.

Nicola Sanna is chief executive officer of Netuitive, and has held the role since 2002. Netuitive enables enterprises to proactively manage the performance and capacity of their IT infrastructures – physical, virtual and cloud.

Image courtesy of Flickr user Adam_T4.

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