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기록

REAL-TIME ADAPTIVE OPERATIONS PERFORMANCE MANAGEMENT SYSTEM

발명심사 중
20청구항 · 3 독립항
§ Ⅰ

개요

발명자

Justin David Kearns; Ophir Ronen; Laura Ann Zuchlewski

IPC 분류

G6Q 10/637G6F 16/355G6N 20/

CPC 분류

G6Q10/637G6F16/355G6N20/

Operations events received from different monitoring systems are transformed into a common event format having standardized fields including a source origin identifier, a source component identifier, a creation time, and event data. Frequency-time analysis is performed on the transformed Operations events by segmenting time-domain data into time bins and determining source origin counts for each time bin. Event clusters are identified based on time-frequency-space envelopes determined from the frequency-time analysis. Each event cluster is associated with resolution metrics including a time-to-resolve value and a number of responders required for resolution. A predictive model is trained using the event clusters and their associated resolution metrics. New incoming Operations events are grouped into a new event cluster. The trained predictive model is applied to the new event cluster to predict resolution requirements, and a remediation action is initiated based on the predicted resolution requirements.

원문 (중국어)

Operations events received from different monitoring systems are transformed into a common event format having standardized fields including a source origin identifier, a source component identifier, a creation time, and event data. Frequency-time analysis is performed on the transformed Operations events by segmenting time-domain data into time bins and determining source origin counts for each time bin. Event clusters are identified based on time-frequency-space envelopes determined from the frequency-time analysis. Each event cluster is associated with resolution metrics including a time-to-resolve value and a number of responders required for resolution. A predictive model is trained using the event clusters and their associated resolution metrics. New incoming Operations events are grouped into a new event cluster. The trained predictive model is applied to the new event cluster to predict resolution requirements, and a remediation action is initiated based on the predicted resolution requirements.