Method to Optimize Prediction of Threshold Violations Using Baselines

• US 20110161048A1
• Filed: 03/30/2010
• Published: 06/30/2011
• Est. Priority Date: 12/31/2009
• Status: Abandoned Application

• Current Assignee: BMC Software Incorporated (KKR & Co., Inc.)
• Original Assignee: BMC Software Incorporated (KKR & Co., Inc.)
• Inventors: Scarpelli, Joe, Dang, Derek, Lefaive, Alex, Sodem, Sridhar
• Application Number:
  US12/750,347
• Publication Number:
  US 20110161048A1
• Time in Patent Office: Days
• US Class Current: 702/181
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 2201/81 Threshold

Abstract

A baseline technique allows reducing the number of threshold violation predictions that need to be generated in a performance monitoring system. One or more baselines may be calculated based on long-term trends in a monitored metric. If the metric is within the baseline, then predictions regarding short-term trends in the metric may be omitted. If the metric is outside the baseline, then short-term trends may be analyzed to predict possible threshold violations.

Claims

1. A method comprising:

collecting data by a computer-implemented performance monitoring system corresponding to a metric of an information technology system;

setting a threshold value corresponding to the metric;

generating a baseline corresponding to the metric; and

generating a prediction that the metric will violate the threshold only if at least some of the data corresponding to the metric are outside of the baseline.

2. The method of claim 1, wherein the act of generating a baseline comprises:

generating a first baseline value for a measurement period corresponding to a first condition; and

generating a second baseline value for the measurement period corresponding to a second condition, wherein the first baseline value and the second baseline value define a baseline range for the measurement period.

3. The method of claim 1, wherein the act of generating a prediction that the metric will violate the threshold only if the data corresponding to the metric is outside of the baseline comprises:

generating a prediction that the metric will violate the threshold only if a statistically significant number of data values collected during a measurement period corresponding to the metric are outside of the baseline.

4. The method of claim 1, wherein the act of generating a baseline corresponding to the metric comprises:

calculating a baseline using an exponentially weighted moving average of the metric.

5. The method of claim 1, wherein the act of generating a baseline corresponding to the metric comprises:

condensing data values collected during a first measurement period into a first condensed value having a first relationship to the data values collected during the first measurement period; and

calculating a first baseline value for a second measurement period using a first baseline value for the first measurement period and the first condensed value.

6. The method of claim 5, wherein the act of condensing data values comprises:

calculating a first condensed value as a first percentile of the data values collected during the first measurement period.

7. The method of claim 5, wherein the act of calculating a first baseline value comprises:

calculating a first baseline value for a second measurement period occurring at the same time a following day as the first measurement period.

8. The method of claim 5, wherein the act of calculating a first baseline value comprises:

calculating a first baseline value for a second measurement period occurring at the same time a following weekend day as the first measurement period.

9. The method of claim 5, wherein the act of generating a baseline corresponding to the metric further comprises:

condensing data values collected during the first measurement period into a second condensed value having a second relationship to the data values collected during the first measurement period; and

calculating a second baseline value for the second measurement period using a second baseline value for the first measurement period and the second condensed value.

10. The method of claim 9, wherein the act of condensing data values collected during the first measurement period into a second condensed value having a second relationship to the data values collected during the first measurement period comprises:

calculating a second condensed value as a second percentile of the data values collected during the first measurement period.

11. The method of claim 1, wherein the act of generating a prediction that the metric will violate the threshold only if the data corresponding to the metric is outside of the baseline comprises:

calculating a trend of the data corresponding to the metric collected during a measurement period; and

generating a prediction that the metric will violate the threshold only if the data corresponding to the metric is outside of the baseline and the trend is toward the threshold.

12. A performance monitoring system, comprising:

a processor;

an operator display, coupled to the processor;

a storage subsystem, coupled to the processor; and

a software, stored by the storage subsystem, comprising instructions that when executed by the processor cause the processor to perform the method of claim 1.

13. A non-transitory computer readable medium with instructions for a programmable control device stored thereon wherein the instructions cause a programmable control device to perform the method of claim 1.

14. A networked computer system comprising:

a plurality of computers communicatively coupled, at least one of the plurality of computers programmed to perform at least a portion of the method of claim 1 wherein the entire method of claim 1 is performed collectively by the plurality of computers.

15. A method, comprising:

collecting data by a computer-implemented performance monitoring system corresponding to a metric of an information technology system during a first measurement period;

setting a threshold value corresponding to the metric;

generating a first baseline value for the first measurement period corresponding to a first condition;

generating a second baseline value for the first measurement period corresponding to a second condition, wherein the first baseline value and the second baseline value define a baseline range for the first measurement period;

calculating a trend of the data corresponding to the metric collected during a measurement period; and

generating a prediction that the metric will violate the threshold only if a statistically significant number of data values collected during the first measurement period corresponding to the metric are outside of the baseline range and the trend is toward the threshold.

16. The method of claim 15, further comprising:

condensing data values collected during the first measurement period into a first condensed value calculated as a first percentile of the data values collected during the first measurement period;

condensing data values collected during the first measurement period into a second condensed value calculated as a second percentile of the data values collected during the first measurement period;

calculating a third baseline value for a second measurement period using the first baseline value for the first measurement period and the first condensed value; and

calculating a fourth baseline value for the second measurement period using the second baseline value for the first measurement period and the second condensed value.

17. The method of claim 16, wherein the act of calculating a third baseline value and the act of calculating a fourth baseline value are performed for a second measurement period that is at the same time as the first measurement period on a following day.

18. A method, comprising:

collecting data by a computer-implemented performance monitoring system corresponding to a metric of an information technology system during a first measurement period;

generating a first baseline value for the first measurement period corresponding to a first condition;

generating a second baseline value for the first measurement period corresponding to a second condition, wherein the first baseline value and the second baseline value define a baseline range for the first measurement period;

calculating a third baseline value for a second measurement period responsive to the first baseline value for the first measurement period and the data collected during the first measurement period; and

calculating a fourth baseline value for the second measurement period responsive to the second baseline value for the first measurement period and data collected during the first measurement period.

19. The method of claim 18, wherein the act of calculating a third baseline value comprises:

calculating a third baseline value for a second measurement period as an exponentially weighted moving average of the first baseline value for the first measurement period and a first percentile of the data values collected during the first measurement period.

20. The method of claim 18, further comprising:

setting a threshold value corresponding to the metric;

calculating a trend of the data corresponding to the metric collected during the first measurement period; and

generating a prediction that the metric will violate the threshold only if a statistically significant number of data values collected during the first measurement period corresponding to the metric are outside of the baseline range and the trend is toward the threshold.