Automatic determination of high significance alert...

Data processing: measuring – calibrating – or testing – Measurement system – Statistical measurement

Reexamination Certificate

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C700S026000

Reexamination Certificate

active

11173525

ABSTRACT:
A computer is programmed to fit exponential models to upper percentile subsets of observed measurements for performance metrics collected as attributes of a computer system. The subsets are defined from sets chosen to reduce model bias due to expected variations in system performance, e.g. those resulting from temporal usage patterns induced by end users and/or workload scheduling. Measurement levels corresponding to high cumulative probability, indicative of likely performance anomalies, are extrapolated from the fitted models generated from measurements of lower cumulative probability. These levels are used to establish and to automatically set warning and alert thresholds which signal to (human) administrators when performance anomalies are observed.

REFERENCES:
patent: 6675128 (2004-01-01), Hellerstein
patent: 2006/0243055 (2006-11-01), Sundermeyer et al.
Don Burleson, “Oracle 10g Predictive Modeling”, Burleson Consulting, (Prior to Jun. 30, 2005), pp. 1-6.
Randall C. Kennedy, “APM gets smart with ProactiveNet's latest”, InfoWorld, Oct. 1, 2004, pp. 1-3.
David Comer & Mike Fobor (Product Managers), “Capabilities and Value of AppManger® Performance Profiler”, NetConnect 2005, netiQ, pp. 1-15.

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