US 11,775,655 B2
Risk assessment of a container build
Abhishek Malvankar, White Plains, NY (US); John M. Ganci, Jr., Raleigh, NC (US); Carlos A. Fonseca, LaGrangeville, NY (US); and Charles E. Beller, Baltimore, MD (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on May 11, 2021, as Appl. No. 17/317,043.
Prior Publication US 2022/0366055 A1, Nov. 17, 2022
Int. Cl. G06F 9/455 (2018.01); G06F 21/57 (2013.01); G06N 3/08 (2023.01); G06F 9/54 (2006.01)
CPC G06F 21/577 (2013.01) [G06F 9/45558 (2013.01); G06F 9/541 (2013.01); G06N 3/08 (2013.01); G06F 2009/45587 (2013.01); G06F 2221/033 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer system comprising:
a processor operatively coupled to memory; and
an artificial intelligence (AI) platform in communication with the processor and the memory, the AI platform comprising:
a representation manager configured to employ natural language processing (NLP) to convert a received metadata file associated with provisioning into one or more vector representations;
a neural network manager configured to identify a subject of the provisioning and selectively leverage a first artificial neural network (ANN) responsive to the identified subject, the selective leverage including the first ANN to assign a first score to each of the one or more vector representations, the first score to convey a compliance factor corresponding to operability of the one or more vector representations;
the neural network manager configured to selectively leverage a second ANN responsive to the first score assignment from the first ANN, the second ANN configured to assign a second score to the received metadata file, wherein the second score corresponds to provisioning efficiency; and
the processor to selectively provision a container or virtual machine (VM) responsive to the second score.