公开(公告)号：US12200008B2

公开(公告)日：2025-01-14

申请号：US17381001

申请日：2021-07-20

Applicant: VMware LLC

Inventor： Narasimhan Gomatam Mandeyam ,  Sambit Kumar Das ,  Shyam Sundar Govindaraj

IPC: H04L9/40 ,  H04L61/4511

Abstract: The method of some embodiments assigns a client to a particular datacenter from among multiple datacenters. The method is performed at a first datacenter, starting when it receives security data associated with a second datacenter. Then the method receives a DNS request from the client. Based on the received security data, the method sends a DNS reply assigning the client to the particular datacenter instead of the second datacenter. The receiving and sending is performed by a DNS cluster of the datacenter in some embodiments. The particular datacenter includes a set of servers implementing an application for the client in some embodiments. The datacenter to which the client gets assigned can be the first datacenter or a third datacenter.

公开(公告)号：US12255950B2

公开(公告)日：2025-03-18

申请号：US18369809

申请日：2023-09-18

Applicant: VMware LLC

Inventor： Saurav Suri ,  Sambit Kumar Das ,  Shyam Sundar Govindaraj ,  Sumit Kalra

IPC: H04L67/1017 ,  H04L61/4511

Abstract: Some embodiments provide a method of performing load balancing for a group of machines that are distributed across several physical sites. The method of some embodiments iteratively computes (1) first and second sets of load values respectively for first and second sets of machines that are respectively located at first and second physical sites, and (2) uses the computed first and second sets of load values to distribute received data messages that the group of machines needs to process, among the machines in the first and second physical sites. The iterative computations entail repeated calculations of first and second sets of weight values that are respectively used to combine first and second load metric values for the first and second sets of machines to repeatedly produce the first and second sets of load values for the first and second sets of machines. The repeated calculation of the weight values automatedly and dynamically adjusts the load prediction at each site without user adjustment of these weight values. As it is difficult for a user to gauge the effect of each load metric on the overall load, some embodiments use machine learned technique to automatedly adjust these weight values.