US 12,293,233 B2
Automated methods and systems that provide resource recommendations for virtual machines
Nitu Sharaff, Palo Alto, CA (US); and Yanislav Yankov, Palo Alto, CA (US)
Assigned to VMWare LLC, Palo Alto, CA (US)
Filed by VMware LLC, Palo Alto, CA (US)
Filed on Oct. 5, 2021, as Appl. No. 17/494,699.
Prior Publication US 2023/0106318 A1, Apr. 6, 2023
Int. Cl. G06F 9/50 (2006.01); G06N 20/00 (2019.01)
CPC G06F 9/5077 (2013.01) [G06F 9/5016 (2013.01); G06F 9/5027 (2013.01); G06N 20/00 (2019.01); G06F 2209/503 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
one or more processors;
one or more memories;
one or more data-storage devices; and
computer instructions that, when executed by one or more of the one or more processors, controls the system to
store a plurality of computational-resource-consumption datasets collected during each hosting of each of multiple virtual machines by one or more distributed-computer-system-based hosting platforms, each computational-resource-consumption dataset comprising a memory consumption and a processing-bandwidth consumption of a respective virtual machine during a respective hosting,
generate, for each of the computational-resource-consumption datasets, a corresponding resource value,
generate a decision tree using the generated resource values and virtual machine characterizations corresponding to the multiple virtual machines associated with the computational-resource-consumption datasets, the decision tree comprising multiple nodes associated with multiple rules, wherein each rule is associated with a corresponding entropy gain, wherein a rule having the best entropy gain is associated with two datasets of the plurality of computational-resource-consumption datasets,
receive a request for a computational-resource specification for a virtual machine of the multiple virtual machines,
input a virtual machine characterization of the virtual machine characterizations for the virtual machine to the decision tree;
generate a response to the received request containing
the computational-resource specification generated from output of the decision tree; and
execute the virtual machine using an allocated computational hardware resource based at least on the response.