US 11,868,227 B2
Unification of disparate cloud resources using machine learning
Leonid Kuperman, Tarzana, CA (US); and Laurent Gil, Miami, FL (US)
Assigned to CAST AI Group, Inc., North Miami Beach, FL (US)
Filed by CAST AI Group, Inc., North Miami Beach, FL (US)
Filed on May 17, 2021, as Appl. No. 17/321,856.
Claims priority of provisional application 63/029,104, filed on May 22, 2020.
Prior Publication US 2021/0365348 A1, Nov. 25, 2021
Int. Cl. G06F 11/34 (2006.01); G06F 11/32 (2006.01); G06N 20/00 (2019.01); G06F 11/30 (2006.01)
CPC G06F 11/3428 (2013.01) [G06F 11/3006 (2013.01); G06F 11/3075 (2013.01); G06F 11/328 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory computer-readable medium comprising instructions encoded thereon that, when executed by at least one processor, cause the at least one processor to:
launch a respective instance on each respective cloud service provider (CSP) of a plurality of CSPs, the plurality of CSPs including two or more distinct CSPs;
receive, from each respective instance, performance benchmark data for each CSP shape of the respective CSP on which the respective instance is launched;
input the performance benchmark data from each respective instance into a model;
receive, as output from the model, a determination of, for each CSP shape, group of a plurality of groups to which the CSP shape belongs;
rank each group based on a parameter; and
provide for display to a user a recommended CSP shape based on the ranking, the recommended CSP shape implemented using one of the two or more distinct CSPs.