US 12,007,865 B2
Machine learning for rule evaluation
Raja Kommula, Cupertino, CA (US); Ganesh Byagoti Matad Sunkada, Bengaluru (IN); Prashanth K, Bengaluru (IN); Thayumanavan Sridhar, Sunnyvale, CA (US); and Raj Yavatkar, Los Gatos, CA (US)
Assigned to Juniper Networks, Inc., Sunnyvale, CA (US)
Filed by Juniper Networks, Inc., Sunnyvale, CA (US)
Filed on Jun. 30, 2022, as Appl. No. 17/810,167.
Claims priority of application No. 202241022566 (IN), filed on Apr. 16, 2022.
Prior Publication US 2023/0336408 A1, Oct. 19, 2023
Int. Cl. G06F 11/34 (2006.01); G06F 11/32 (2006.01); H04L 41/0604 (2022.01); H04L 41/0681 (2022.01); H04L 41/16 (2022.01); H04L 43/024 (2022.01); H04L 43/04 (2022.01); H04L 43/08 (2022.01)
CPC G06F 11/3409 (2013.01) [G06F 11/327 (2013.01); H04L 41/0604 (2013.01); H04L 41/0609 (2013.01); H04L 41/0681 (2013.01); H04L 41/16 (2013.01); H04L 43/024 (2013.01); H04L 43/04 (2013.01); H04L 43/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
collecting, by a performance monitoring system, telemetry data comprising metrics related to a network of computing devices, wherein, for each metric, metric values associated with a corresponding metric name are collected at each of a plurality of times;
evaluating, by the performance monitoring system, alert rules using the collected telemetry data, wherein evaluating a first rule includes comparing metric values associated with a corresponding metric name of the first rule to a corresponding threshold value of the first rule at each of a plurality of rule evaluation times based on a first evaluation interval to generate a rule evaluation attribute;
determining, by the performance monitoring system, a predicted rule weight for the first rule based on the rule evaluation attribute; and
determining, by the performance monitoring system, a second evaluation interval for the first rule based on the predicted rule weight and the first evaluation interval.