The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 13, 2021

Filed:

Feb. 19, 2019
Applicant:

Vmware, Inc., Palo Alto, CA (US);

Inventors:

Ashot Nshan Harutyunyan, Yerevan, AM;

Naira Movses Grigoryan, Yerevan, AM;

Arnak Poghosyan, Yerevan, AM;

Nicholas Kushmerick, Seattle, WA (US);

Assignee:

VMware, Inc., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 12/24 (2006.01); G06F 11/30 (2006.01); G06F 11/34 (2006.01); G06N 20/00 (2019.01); G06F 17/16 (2006.01); H04L 12/26 (2006.01);
U.S. Cl.
CPC ...
G06F 11/3452 (2013.01); G06F 11/3419 (2013.01); G06F 11/3495 (2013.01); G06F 17/16 (2013.01); G06N 20/00 (2019.01); H04L 41/142 (2013.01); H04L 43/067 (2013.01); G06F 11/3006 (2013.01); G06F 2201/835 (2013.01);
Abstract

Computational processes and systems are directed to detecting abnormally behaving objects of a distributed computing system. An object can be a physical or a virtual object, such as a server computer, application, VM, virtual network device, or container. Processes and systems identify a set of metrics associated with an object and compute an indicator metric from the set of metrics. The indicator metric is used to label time stamps that correspond to outlier metric values of the set of metrics. The metrics and outlier time stamps are used to compute rules by machine learning. Each rule corresponds to a subset or combination of metrics and represents specific threshold conditions for metric values. The rules are applied to run-time metric data of the metrics to detect run-time abnormal behavior of the object.


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