US 12,248,820 B2
Adaptive hybrid cloud resource management
Gandhi Sivakumar, Bentleigh (AU); Kushal S. Patel, Pune (IN); Luke Peter Macura, Lucas (AU); and Sarvesh S. Patel, Pune (IN)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Oct. 28, 2021, as Appl. No. 17/513,522.
Prior Publication US 2023/0138597 A1, May 4, 2023
Int. Cl. G06F 9/50 (2006.01); G06F 9/48 (2006.01); G06F 12/02 (2006.01)
CPC G06F 9/5083 (2013.01) [G06F 9/4862 (2013.01); G06F 12/0238 (2013.01); G06F 2212/202 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A method comprising:
collecting, by one or more processors of a computer system, digestive capabilities for Input Output Queues (IOQs) of infrastructure components in a hybrid cloud infrastructure;
allocating, by the one or more processors of the computer system, nonvolatile memory express (NVMe) storage cloud resources for the hybrid cloud infrastructure based on the collected digestive capabilities for IOQs of the infrastructure components;
collecting, by the one or more processors of the computer system, infrastructure and IOQ capacity information of a computing instance in the hybrid cloud infrastructure;
adding, by the one or more processors of the computer system, the infrastructure and IOQ capacity information from the computing instance to a model space, the model space configured to provide computational insights as to the digestive capabilities of the computing instance based on the collected information;
collecting, by the one or more processors of the computer system, infrastructure and IOQ capacity information of a target subsystem in the hybrid cloud infrastructure;
adding, by the one or more processors of the computer system, the infrastructure and IOQ capacity information of the target subsystem to the model space, the model space configured to provide computational insights as to the digestive capabilities of the target subsystem based on the collected information;
determining, by the one or more processors of the computer system, end-to-end digestive capability for IOQs in the hybrid cloud infrastructure from the collected infrastructure and IOQ capacity information of the computing instance and the target subsystem;
collecting, by the one or more processors of the computer system, digestive capabilities for IOQs of applications running in the computing instance in the hybrid cloud infrastructure; and
tuning, by the one or more processors of the computer system, application level IOQs of the computing instance in the hybrid cloud infrastructure using the end-to-end digestive capability for IOQs in the hybrid cloud infrastructure and the collected digestive capabilities for IOQs of applications running in the computing instance in the hybrid cloud infrastructure.