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Using Analytics to Detect Application Performance Anomalies

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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Using Analytics to Detect Application Performance Anomalies

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.

Hot Topics

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...