Using Analytics to Detect Application Performance Anomalies
March 04, 2014
Charley Rich
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IT organizations are under more pressure to deliver exceptional business performance than ever. Further complicating the challenge is the evolving nature of Information Technology (IT). The rise of Big Data, mobile, cloud, and BYOD have added complexity, making it ever more challenging for IT to acquire the visibility they need to detect anomalies.

Today, an organization’s application infrastructure typically includes Web components, messaging middleware and mainframes. Application performance is impacted by many factors coming from multiple sources—application servers, messaging protocols, virtualized systems, capacity issues and many more. Inevitably, failures in one or more of these systems occur — and IT is left to deal with the result.

Such situations are why Application Performance Management (APM) solutions exist. To be effective, APM must deliver three major benefits:

- Gain enough visibility to see an entire system

- Track activities through the infrastructure chain as they occur

- Correlate events—many of which might seem unrelated—in order to spot developing trends before users are impacted.

Surprisingly, a number of APM platforms miss on one or more of these key functions.

Monitoring is Not Enough

To be sure, most APM solutions do a good job of monitoring individual applications. But, monitoring is not enough. When problems arise, especially in today's complex topologies, the failure of a single application is rarely the culprit. Performance threats usually are the result of multiple issues — and many of these, if caught early in the process using real-time analytics, could prevent much larger failures from occurring. Evading cascading failures is essential. Ideally, IT Specialists should avoid being in the position of putting out fires — they should be able to make sure the fire never starts. But, without the necessary visibility, this is no simple task.

To properly manage today's application environment, organizations must be able to analyze the entire application chain from end to end, understanding the dependencies between the links in the chain. It must also be able to focus on early detection of abnormalities, differentiating symptom from cause rather than simply reacting to an outage. The combination of these two factors provides the level of assurance IT needs in its key mission: to reduce the frequency and duration of outages.

End-to-end performance monitoring and analysis must embrace the entire IT environment, from .NET to mainframes. It must cover a wide range of components from J2EE application servers, Web Services to middleware messaging, brokers and even legacy applications. It must also be elastic, having the ability to transparently scale to meet unexpected surges in demand.

Analyzing Situations with Complex Event Processing

Accomplishing the second requirement — proactive analytics, rather than reactive response — requires a sophisticated technology, one example being Complex Event Processing (CEP). CEP engines, along with business policies, analyze situations or "business views" comprised of multiple events and key performance indicators.

Instead of alerts based on individual events passing a threshold, the analytical approach is analyzing situations. It compares application behavior against your norms, looking for anomalies that indicate potential problems. Norms are established dynamically using statistical functions such as Bollinger bands, momentum oscillators, standard deviation, velocity, fluctuation and rates of change.

This approach ensures that real problems — not just transient variations, a.k.a. "false alarms" — are identified and ensures true readings of real-time performance.

With CEP-based analytics, IT Specialists are assisted in quickly identifying root causes, instead of merely chasing symptoms. By dynamically analyzing event streams, the CEP approach can differentiate symptoms from cause — even inferring an explanation where there is signal loss.

APM solutions using real-time anomaly detection have the ability to maintain SLAs in the most high-demand deployments including payments, EFT, trading, settlement, compliance patient data, claims processing and retail order management. They not only bring developing situations to the attention of IT staff before users are aware, but also assist in diagnosing and correcting the underlying causes quickly and efficiently.

In an era when business functions are more sophisticated, diverse, integrated and immediate than ever, analytical Application Performance Management plays an essential role for IT professionals and their customers.

Charley Rich is VP Product Management and Marketing at Nastel Technologies.

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