Computer performance estimation system configured to take expected events into consideration
First Claim
16. In or for an computer performance estimation system operable for receiving input values for successive time trials and, for each time trial, computing output values based on the input values and learned parameters and updating the learned parameters to reflect relationships observed among the input and output values, a method comprising the steps of:
- identifying expected events including scheduled events;
provisioning the estimation system with learned parameters for the expected events;
initializing the learned parameters for the expected events; and
running the estimation system to forecast performance of the computer system as effected by the scheduled events while updating the learned parameters including the learned parameters for the scheduled events.
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Abstract
The present invention may be embodied as expected event scheduler and processor in an application performance monitoring (APM) services. The expected event scheduler and processor allows the APM system to take scheduled events into account when performing the performance forecasting for the host system. The learned parameters may be based on measured input values including internal measurements, such as data from monitoring agents located within the host computer system, as well as external measurements relating to factors such as computer backup runs, monthly payroll runs, quarterly financial reporting runs, weekends, holidays, weather data, traffic data, advertisements run by the operator of the system or others, promotional events, product releases, news announcements, elections and other natural and demographic factors. The expected events may overlap in time, and the expected event scheduler and processor learns weighing factors for the simultaneously occurring expected events by updating the learned parameters over successive time trials.
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Citations
31 Claims
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16. In or for an computer performance estimation system operable for receiving input values for successive time trials and, for each time trial, computing output values based on the input values and learned parameters and updating the learned parameters to reflect relationships observed among the input and output values, a method comprising the steps of:
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identifying expected events including scheduled events;
provisioning the estimation system with learned parameters for the expected events;
initializing the learned parameters for the expected events; and
running the estimation system to forecast performance of the computer system as effected by the scheduled events while updating the learned parameters including the learned parameters for the scheduled events. - View Dependent Claims (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 26, 27, 28, 30)
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17-1. The method of claim 16, wherein the expected events further seasonal events including weekends and holidays.
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21. In or for an computer performance estimation system operable for receiving input values for successive time trials and, for each time trial, computing output values based on the input values and learned parameters and updating the learned parameters to reflect relationships observed among the input and output values, a method comprising the steps of:
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identifying expected events including scheduled events;
provisioning the estimation system with learned parameters for the expected events;
initializing the learned parameters for the expected events;
running the estimation system to forecast performance of the computer system as effected by the scheduled events while updating the learned parameters including the learned parameters for the scheduled events; and
wherein the step of running the computer performance estimation system comprises the steps of (a) receiving measured data from corresponding to operation of the computer system for a current time trial, the measured data including date received from one or more monitoring agents deployed within the computer system;
(b) estimating operation of the computer system for the current time trial using imputed learned parameters;
(c) predicting operation of the computer system for future time trial using forecasted learned parameters;
(d) updating the learned parameters based on the measured data received for the current time trial; and
repeating the steps (a) through (d) for a number of successive time trials. - View Dependent Claims (22, 23, 24, 25, 29, 31)
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Specification