2013 AnIntegratedFrameworkforOptimiz

• (Tang et al., 2013) ⇒ Liang Tang, Tao Li, Larisa Shwartz, Florian Pinel, and Genady Ya Grabarnik. (2013). “An Integrated Framework for Optimizing Automatic Monitoring Systems in Large IT Infrastructures.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2488209

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Cited By

• http://scholar.google.com/scholar?q=%222013%22+An+Integrated+Framework+for+Optimizing+Automatic+Monitoring+Systems+in+Large+IT+Infrastructures
• http://dl.acm.org/citation.cfm?id=2487575.2488209&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; system monitoring; ticket analysis

Abstract

The competitive business climate and the complexity of IT environments dictate efficient and cost-effective service delivery and support of IT services. These are largely achieved by automating routine maintenance procedures, including problem detection, determination and resolution. System monitoring provides an effective and reliable means for problem detection. Coupled with automated ticket creation, it ensures that a degradation of the vital signs, defined by acceptable thresholds or monitoring conditions, is flagged as a problem candidate and sent to supporting personnel as an incident ticket. This paper describes an integrated framework for minimizing false positive tickets and maximizing the monitoring coverage for system faults.

In particular, the integrated framework defines monitoring conditions and the optimal corresponding delay times based on an off-line analysis of historical alerts and incident tickets. Potential monitoring conditions are built on a set of predictive rules which are automatically generated by a rule-based learning algorithm with coverage, confidence and rule complexity criteria. These conditions and delay times are propagated as configurations into run-time monitoring systems. Moreover, a part of misconfigured monitoring conditions can be corrected according to false negative tickets that are discovered by another text classification algorithm in this framework. This paper also provides implementation details of a program product that uses this framework and shows some illustrative examples of successful results.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 AnIntegratedFrameworkforOptimiz	Tao Li Liang Tang Larisa Shwartz Florian Pinel Genady Ya Grabarnik			An Integrated Framework for Optimizing Automatic Monitoring Systems in Large IT Infrastructures				10.1145/2487575.2488209		2013