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The Missing Link Between Virtualization and APM
Actionable Intelligence with Predictive Analytics for IT
Do you have “intelligence” about how your applications perform – even in virtualized infrastructure? Or do you just have “information”? What’s the difference? And why does it matter?
For years, application performance management has been about monitoring the availability of servers by focusing on performance metrics or “information” from CPU, disk and memory. But things aren’t so simple anymore.
For one thing, the advent of server virtualization adds the need to examine performance metrics from an ever growing number of storage and the network components, which grows complexity. On top of this, the behavior of all the components is becoming much more unpredictable, creating uncharted territory for even the smartest engineer, let alone a typical administrator.
Meanwhile, application performance management emerged as the “right” way to monitor applications. This added even more “information”, including different types of performance metrics and instrumentation – from transactions, to user experience, to deep monitoring of software object behavior.
So now we have even more information to really make the engineers’ job of analyzing the data even more difficult. We have complexity upon complexity – and it’s become impossible for IT support staff to process all this information and really understand how applications are performing, and the dependencies to the performance of the underlying infrastructure.
How much information are we talking about? Industry estimates now show enterprises collecting 300% more performance metrics yet they continue to struggle with antiquated approaches based on setting thresholds and creating rules and relationships to try to model inter-dependent behavior of all the components. And while there are a growing number of application performance management (APM) tools, they lack the analytics muscle or “intelligence” to help users make sense of all the data. And this is crucial to be able to correlate application performance to the behavior of the underlying infrastructure and resolve or even prevent service outages and degradations. In fact, Gartner estimates that by 2015, more than 50% of enterprises will need capabilities beyond those delivered by the current APM tools to manage a complex and dynamic infrastructure and application environment.
But a solution is now emerging in the form of advanced predictive IT analytics software, powered by what Gartner refers to as Behavior Learning technologies. The new approach automates the management process and provides holistic analysis and visibility enabling cross-domain insight and is serving as the “brains” or “intelligence” for large scale application performance management (APM) solutions leveraging existing APM tools.
These predictive IT analytics software solutions can analyze and correlate real-time performance and application data from tools like CA Wily Introscope as well as all underlying physical, virtual and cloud infrastructure. They automate the monitoring, analysis, and correlation of millions of performance data metrics consolidating them down to only meaningful alerts. They are mathematically accurate and unbiased, enabling you to proactively identify and resolve application performance problems before users are affected.
The result is an enterprise-class APM solution delivering intelligent, cross-domain insight required for managing voluminous data being generated by a growing number of application performance management tools. It ensures quality of service and quality of experience for critical business applications to protect revenue opportunities, end-user productivity, and customer satisfaction.
Early adopters include some of the world’s largest banks and telcos who rely on Behavior Learning and IT analytics to predict degradations and avoid outages for their most critical applications i.e. online banking and global payments. Demand is now taking off with Gartner predicting that 40% of the Global 2000 will have deployed Behavior Learning technology by 2014, up from 10% in 2010.
Below are are two examples of how enterprises view critical application performance. Typical APM tools provide a myriad of information on specific application performance. Enterprises seeking a more holistic approach can utilize open, technology-agnostic IT analytics platforms, such as Netuitive, that offer standard integrations with all the leading APM and monitoring platforms to provide a holistic view of critical application performance in large, heterogeneous IT environments.
The two dashboards below illustrate the difference between “information” and “intelligence”. On the one hand, you have a lot of data from an APM dashboard, which an expert could certainly analyze to try to tell you how an application is performing. Of course this might only represent a fraction of the charts that the user could be looking at.
On the other hand, you have Netuitive’s service or application dashboard, allows your experts to take all the relevant metrics that define application performance – from IT, end-user experience, or business metrics – and presents the results in simplified health, workload, and (where applicable) capacity indices. Once all the potential stakeholders in a company understand the analytics behind the dashboard, anyone can tell – at a glance – how even the most complex application or service is performing.
Information-Centric Monitoring Dashboard
Netuitive Predictive Analytics Dashboard, providing simple, powerful “intelligence” on how applications are performing
So does all of the old “information” go away? Of course not. Once a problem has been isolated to a specific area or IT silo, you still need to look at the performance metric timelines to figure out how to resolve the problem. And it doesn’t matter if you analyze that data in Netuitive, or in the interface of the source monitoring system. The point is – this self-learning, predictive analytics is the only way you are going to be able to manage all the information you know have to digest for virtualization and application performance management.
So ask yourself: with all the money you've spent on tools to collect data on applications and infrastructure, is the result just “information” overload, or analytics that provide actionable “intelligence”?
About Graham Gillen
Graham Gillen is the Sr. Product Marketing Manager for Netuitive. He currently leads Netuitive’s initiatives to market solutions in the areas of virtualization and capacity management, systems management, and applications performance management. Before joining Netuitive in 2008, Graham was a Sr. Solutions Marketing Manager at VeriSign, and Sr. Product Manager at webMethods. Graham recently completed his Certificate in Marketing from the University of Virginia Darden School of Business. He also received a Master of Science degree in Operations Research from Georgia Tech and a Bachelor of Science degree in Engineering from the University of Virginia.
