Cross-correlation of metrics for anomaly root cause identification

Patent metadata

Field	Value
Publication number	US-11886285-B2
Application number	US-202217843198-A
Country	US
Kind code	B2
Filing date	Jun 17, 2022
Priority date	Mar 15, 2019
Publication date	Jan 30, 2024
Grant date	Jan 30, 2024

Abstract

Technologies are disclosed herein for cross-correlating metrics for anomaly root cause detection. Primary and secondary metrics associated with an anomaly are cross-correlated by first using the derivative of an interpolant of data points of the primary metric to identify a time window for analysis. Impact scores for the secondary metrics can be then be generated by computing the standard deviation of a derivative of data points of the secondary metrics during the identified time window. The impact scores can be utilized to collect data relating to the secondary metrics most likely to have caused the anomaly. Remedial action can then be taken based upon the collected data in order to address the root cause of the anomaly.

First claim

What is claimed is:

1. A method comprising:
retrieving a primary dataset and a plurality of secondary datasets, the primary dataset comprising data points for a primary metric, and the plurality of secondary datasets comprising data points for a plurality of secondary metrics;
identifying a time window based on the primary dataset;
computing an interpolant for data points in the time window for one or more of the plurality of secondary datasets, the interpolant corresponding to an anomaly impacting operation of one or more components of a computing system; and
performing, on the one or more components, a remedial action for the anomaly, the remedial action restoring the operation of the one or more components.

2. The method of claim 1 , further comprising computing an impact score for each of the plurality of secondary metrics based on the interpolant.

3. The method of claim 2 , wherein the impact score comprises a standard deviation of derivatives of the interpolant during the time window.

4. The method of claim 2 , further comprising selecting a set of secondary metrics from the plurality of secondary metrics based on respective impact scores.

5. The method of claim 1 , further comprising identifying a cause of the anomaly impacting operation of the one or more components.

6. The method of claim 5 , wherein the remedial action addresses the cause of the anomaly.

7. The method of claim 1 , wherein the remedial action includes one or more of restoring, rebooting, reconfiguring, or initializing the computing system.

8. The method of claim 1 , wherein the remedial action includes restoring, rebooting, initializing, or reconfiguring the one or more components.

9. The method of claim 1 , further comprising transmitting an alert to an associated administrator of the computing system.

10. The method of claim 1 , further comprising:
receiving an indication of the anomaly at the computing system; and
retrieving the primary dataset and the plurality of secondary datasets based on the indication.

11. A computing system, comprising:
one or more processors; and
a computer-readable storage medium having computer-executable instructions stored thereupon which, when executed by the one or more processors, cause the one or more processors to:
retrieve a primary dataset and a plurality of secondary datasets, the primary dataset comprising data points for a primary metric, and the plurality of secondary datasets comprising data points for a plurality of secondary metrics;
identify a time window based on the primary dataset;
compute an interpolant for data points in the time window for each of the plurality of secondary datasets, one or more of the interpolants corresponding to an anomaly impacting operation of one or more components of the computing system; and
perform, on the one or more components, a remedial action for the anomaly, the remedial action restoring the operation of the one or more components.

12. The computing system of claim 11 , further comprising computing an interpolant for the data points in the primary dataset by fitting a cubic polynomial through the data points for the primary metric.

13. The computing system of claim 11 , wherein the interpolant for the data points in the time window for each of the plurality of secondary datasets are computed by fitting a cubic polynomial through the data points for the plurality of secondary metrics.

14. The computing system of claim 11 , wherein identifying the time window comprises evaluating roots of a derivative of an interpolant for the data points in the primary dataset.

15. The computing system of claim 11 , wherein the data points for the primary metric and the data points for the plurality of secondary metrics are collected during a time period corresponding to the anomaly detected at the computing system.

16. The computing system of claim 11 , further comprising computing an impact score for each of the plurality of secondary metrics based on the interpolant for each of the plurality of secondary datasets.

17. A computer-readable storage medium having computer-executable instructions stored thereupon which, when executed by a processor, cause the processor to:
retrieve a primary dataset and a plurality of secondary datasets, the primary dataset comprising data points for a primary metric, and the plurality of secondary datasets comprising data points for a plurality of secondary metrics;
identify a time window based on the primary dataset;
compute a secondary interpolant for data points in the time window for each of the plurality of secondary datasets, one or more of the secondary interpolants corresponding to an anomaly impacting operation of one or more components of a computing system; and
perform, on the one or more components, a remedial action for the anomaly, the remedial action restoring the operation of the one or more components.

18. The computer-readable storage medium of claim 17 , wherein the time window is identified by evaluating roots of a derivative of an interpolant for the primary dataset.

19. The computer-readable storage medium of claim 17 , wherein the data points for the primary metric and the data points for the plurality of secondary metrics are collected during a time period corresponding to the anomaly detected at the computing system.

20. The computer-readable storage medium of claim 17 , wherein the remedial action includes restoring, rebooting, initializing, or reconfiguring the one or more components.

Assignees

• Ebay Inc

Inventors

• Poole Maxwell Henry
• Sambasivan Satish
• Kaushik Vivek Siva

Classifications

• G06F11/0793 Primary

  Remedial or corrective actions (recovery from an exception in an instruction pipeline G06F9/3861; by retry G06F11/1402; for recovering from a failure of a protocol instance or entity H04L69/40) · CPC title

• G06F11/0706

  the processing taking place on a specific hardware platform or in a specific software environment · CPC title

• G06F17/18 Primary

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06F11/079

  Root cause analysis, i.e. error or fault diagnosis (in a hardware test environment G06F11/22; in a software test environment G06F11/36) · CPC title

• G06F11/1441

  Resetting or repowering · CPC title