Daniel Heimlich, Vice President, Netuitive (www.netuitive.com), says:

Predictive analytics has been around for a while and is applicable in several forms, most notably in business intelligence or BI where you see it applied in areas such as web trends and consumer data analysis. What we’re talking about is predictive analytics “for IT.” Predictive analytics for IT is about understanding vast amounts of real-time data to forecast IT performance issues before they affect customers and users. Our predictive analytics software is powered by what Gartner calls “behavior learning” technology, a math-based approach that involves advanced statistical analysis and algorithms to self-learn how an IT environment is performing.

Large scale virtualization and private cloud infrastructures are far more complex and difficult to manage than anything a data center manager could have envisioned even a few years ago. While virtualization and cloud may simplify service provisioning, the underlying infrastructure has many more interrelated, moving parts to oversee. In such environments, with optimized resources, there will be little room for error. In such a complex environments, it is inconceivable that you would continue to try to monitor performance of the IT infrastructure and applications via manual rules-based processes. This is where a performance and capacity management platform based on behavior learning technology leveraging advanced statistical analysis and predictive analytics becomes essential.

Using our patented Behavior Learning EngineTM, Netuitive replaces manual, rules-based methods for performance monitoring with automated statistical analysis that correlates and self-learns the operational behavior of IT systems and applications. It allows large enterprises to resolve IT performance problems as quickly as possible by isolating root cause and, in some cases, forecast problems and prevent them from happening altogether. Netuitive excels in virtualized and cloud environments and provides a holistic view of the entire virtual data center architecture.

Netuitive, which has nine Behavior Learning technology patents, is a predictive analytics software platform. It sits on top of the enterprise IT infrastructure stack where it collects and analyzes data in real-time from existing IT monitoring tools such as BMC, IBM, NetApp, CA, HP, VMware, Microsoft, Oracle, Compuware, and others. This provides the coveted holistic view across enterprise platforms, vendors and users enabling it to proactively manage IT performance and capacity of complex infrastructures with a very small footprint in terms of storage and computing resources.

The emergence of predictive analytics in virtualization and cloud management is central to an enterprise ITs ability to innovate. The core premise of cloud computing is the ability to interchange components and resources at will based on demand. Innovation in IT goes only as far as the flexibility of the management layer allows. Netuitive’s technology-agnostic approach across virtual, cloud and physical environments enables a holistic view across silos, platforms, vendors and users. Under this approach, innovation is limitless and is validated by big early adopters of virtualization and cloud computing including 8 of the world’s 10 largest banks and several global telecommunications companies who have deployed it as part of strategic virtualization management and cloud infrastructure initiatives.

A predictive analytics-based approach to virtualization and cloud management is a precursor to making sure that the environment is production-ready for mission critical applications. This is being validated by big early adopters in financial services and telecommunications who are some of the largest and most demanding deployments of virtualization in the world. Netuitive customers include eight of the top 10 banks and two telco giants who are now able to predict degradations and avoid outages for their most critical applications. Gartner reported how a global telco is using predictive analytics powered by a behavior learning engine 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.

As predictive analytic approaches continue to take root in these large virtualization management and cloud infrastructure initiatives, IT leaders are starting to realize the promise of the cloud by serving line of business owners more efficiently, CFOs are realizing lower hardware costs and energy bills from right-sized infrastructures, and application owners are beginning to confidently deploy and change resources in minutes, not weeks. This is what effective virtualization and cloud management is all about — service-level visibility, automated problem diagnostics and predictive analytics enabling organizations to manage their performance and capacity proactively and end-to-end.