New Behavior Learning Tools Solving Cloud and Virtualization Management Problems

New Behavior Learning Tools Solving Cloud and Virtualization Management Problems

08/24/2010

Leading Analyst Firm Categorizes Behavior Learning as “Transformational” in Two New Hype Cycle Reports



The adoption of Behavior Learning tools is being driven by the emergence of virtualization and the need to gain a holistic understanding of the virtual IT infrastructure state (e.g., the ability to understand the health of a dynamic virtual server environment based on behavior patterns and not static thresholds), according to the new Gartner Hype Cycle for IT Operations Management, 2010.

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In addition, two new Gartner Hype Cycles list Behavior Learning tools and categorize it as “transformational” in both.

The Gartner Hype Cycles are reports that provide information and advice including a graphical way to track multiple technologies within an IT domain or technology portfolio. Gartner's Hype Cycles characterize the typical progression of an emerging technology, from over enthusiasm through a period of disillusionment to an eventual understanding of the technologies relevance and role in a market or domain. Each technology or listing on the Hype Cycle receives a benefit rating from Gartner ranging from “low” all the way up to “transformational.”

In July, Gartner published the Hype Cycle for IT Operations Management, 2010(1) and the Hype Cycle for Real Time Infrastructure, 2010(2). Behavior Learning was listed and was categorized as transformational in both reports and was the only technology to achieve a transformational categorization in the Hype Cycle for IT Operations Management, 2010.

As defined by Gartner, “Behavior learning tools use a statistical process method to solve data analysis problems, collecting data from multiple performance and event sources, and establishing a set of behavioral patterns. Once patterns of normalcy are established, the behavior learning tool looks for deviations from normal behavior, interpreting the symptoms for diagnosis and appropriate alerting. Depending on the behavior learning tool, the data sources can be behavior learning tool agents, existing performance and event monitoring tools, log files or a combination of all these sources.”

Regarding the position, adoption speed and justification for behavior learning tools, the Gartner Hype Cycle for IT Operations Management, 2010 cited, “When using existing IT operations availability and performance management tools, many IT organizations continue to struggle to deliver a proactive monitoring capability due to the vast amount of disparate data that needs to be collected, analyzed and correlated.

Behavior learning tools gather event and performance data from a wide range of sources, identifying behavioral irregularities, allowing IT operations to understand the state of the IT infrastructure in a more holistic way. Behavior learning tools can detect subtle deviations from normal activity issues that can be identified before having a potentially negative impact on IT services.

The adoption of behavior learning tools is being driven by the emergence of virtualization and the need to gain a holistic understanding of the virtual IT infrastructure state (e.g., the ability to understand the health of a dynamic virtual server environment based on behavior patterns and not static thresholds). In addition, IT behavior learning tools are being adopted by forward-thinking IT organizations that seek a way to consolidate availability and performance data to aid in root cause analysis.”

According to Gartner analyst David Williams, “Behavior learning tools have the potential to massively improve business service performance and availability by establishing normal behavior patterns, allowing subtle deviations of IT normalcy to be detected before the individual availability and performance tool thresholds are exceeded. This capability is focused on IT services and applications, and ensures that potential issues can be investigated and remediated before they impact the business — a key requirement when moving toward a real-time infrastructure (RTI) state. IT organizations with increasingly dynamic virtual IT environments will benefit from behavior learning tools, especially when there are many performance and event sources to track and understand, as they provide IT operations with a new way to comprehend the overall state of the IT infrastructure.”

Netuitive is a leading provider of self-learning performance management software that leverages Behavior Learning technology at its core and was named as a sample vendor in the Gartner Hype Cycle for IT Operations, 2010, and the Gartner Hype Cycle for Real Time Infrastructure 2010.

Netuitive CEO Nicola Sanna commented, “We believe the Gartner reports reflect what we are already seeing among our customers. Cloud and virtualized environments have created management nightmares that can only be solved by replacing human guesswork with automated statistical analysis and predictive analytics that excel in optimizing virtualized environments.”

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