Invention Grant
- Patent Title: Multi-layered computing system attribute dependency
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Application No.: US16866893Application Date: 2020-05-05
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Publication No.: US11269753B2Publication Date: 2022-03-08
- Inventor: Shashidhar Sastry , Rahul Chenny , Debasisha Padhi
- Applicant: Kyndryl, Inc.
- Applicant Address: US NY New York
- Assignee: Kyndryl, Inc.
- Current Assignee: Kyndryl, Inc.
- Current Assignee Address: US NY New York
- Agency: Heslin Rothenberg Farley & Mesiti P.C.
- Agent Michael A. Petrocelli, Esq.
- Main IPC: G06F11/34
- IPC: G06F11/34 ; G06K9/62 ; G06N20/00

Abstract:
A method, computer program product, and a system where a processor(s) obtains, from a data source, a list of objects at different layers of a computing system. The processor(s) generates exploration lists from the list (each exploration list with objects for a layer). The processor(s) identifies updated and new data at the layers associated with the objects on the list; the identified data comprises attributes for each layer. The processor(s) applies machine learning algorithm(s) to enrich the data by identifying dependencies between the attributes for each layer as influencers for one or more key performance indicators of the computing system. The processor(s) generates, from the enriched data, a hierarchy matrix. The processor(s) determines, based on the hierarchy matrix that an event associated with one or more computing resources of the computing system will influence a particular key performance indicator.
Public/Granted literature
- US20210349802A1 MULTI-LAYERED COMPUTING SYSTEM ATTRIBUTE DEPENDENCY Public/Granted day:2021-11-11
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