Invention Grant
- Patent Title: Machine learning system for workload failover in a converged infrastructure
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Application No.: US16043297Application Date: 2018-07-24
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Publication No.: US10585775B2Publication Date: 2020-03-10
- Inventor: Aalap Desai , Anant Agarwal , Alaa Shaabana , Ravi Cherukupalli , Sourav Kumar , Vikram Nair
- Applicant: VMware, Inc.
- Applicant Address: US CA Palo Alto
- Assignee: VMware, Inc.
- Current Assignee: VMware, Inc.
- Current Assignee Address: US CA Palo Alto
- Agency: Thomas | Horstemeyer, LLP
- Main IPC: G06F11/34
- IPC: G06F11/34 ; G06F9/455 ; G06K9/62 ; G06N20/00

Abstract:
Systems and methods for analyzing a customer deployment in a converged or hyper-converged infrastructure are disclosed. A machine learning model is trained based upon historical usage data of other customer deployments. A k-means clustering is performed to generate a prediction as to whether a deployment is configured for optimal failover. Recommendations to improve failover performance can also be generated.
Public/Granted literature
- US20200034270A1 MACHINE LEARNING SYSTEM FOR WORKLOAD FAILOVER IN A CONVERGED INFRASTRUCTURE Public/Granted day:2020-01-30
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