公开(公告)号：US20230028934A1

公开(公告)日：2023-01-26

申请号：US17458618

申请日：2021-08-27

Applicant: VMWARE, INC.

Inventor： VAMSHIK SHETTY ,  Madan Mohan Singhal ,  Seena Ann Sabu

IPC: H04L29/08 ,  G06K9/62 ,  G06N5/04 ,  G06F9/50

Abstract: The current document is directed to methods and systems that automatically instantiate complex distributed applications by deploying distributed-application instances across the computational resources of one or more distributed computer systems and that automatically manage instantiated distributed applications. Automatic deployment of multiple instances of a distributed application across computational resources, such as distribution of microservices of a microservice-based application across one or more distributed computer systems, and scaling of instantiated distributed applications are computationally difficult optimization problems that are not amenable to traditional centralized approaches. The current document discloses decentralized, distributed automated methods and systems that instantiate and manage distributed applications. Reinforcement-learning-based agents are installed within the computational resources of one or more distributed computer systems. Distributed-application instances are initially distributed to one or more agents. The agents then exchange distributed-application instances among themselves in order to locally optimize the set of distributed-application instances that they each manage.

公开(公告)号：US20240168790A1

公开(公告)日：2024-05-23

申请号：US18097526

申请日：2023-01-17

Applicant: VMWARE, INC.

Inventor： VAMSHIK SHETTY ,  Maarten Wiggers ,  Jobin George

IPC: G06F9/455

CPC classification number: G06F9/45558 ,  G06F2009/4557

Abstract: System and computer-implemented method for recommending guidelines for managed objects for a computing environment uses a transductive embedding technique on a graph of the computing environment to generate initial embeddings for the nodes of the graph. An inductive embedding technique is then applied on the initial embeddings and features of the nodes of the graph to produce final embeddings for the nodes of the graph, which are used to execute a link classification operation on the final embeddings for at least some nodes of the graph to select a recommended guideline for a target managed object.