公开(公告)号：US11025495B1

公开(公告)日：2021-06-01

申请号：US16802591

申请日：2020-02-27

Applicant: VMWARE, INC.

Inventor： Yash Bhatnagar ,  Hemani Katyal ,  Chandrashekhar Jha ,  Mageshwaran Rajendran ,  Ritesh Jha

IPC: H04L12/24 ,  G06F9/50 ,  G06F11/34

Abstract: Example methods and apparatus to determine container priorities in virtualized computing environments are disclosed herein. Examples include: a cluster controller to classify a first container into a cluster based on the first container having a number of distinct allocated resources within a threshold number of distinct allocated resources corresponding to a second container; a container ranking generator to: determine resource utilization rank values for a resource usage type of a number of distinct allocated resources, the resource utilization rank values indicative that the first container utilizes the resource usage type more than the second container; determine an aggregated resource utilization rank value for the first container based on aggregating ones of the resource utilization rank values corresponding to the first container; and a container priority controller to generate a priority class for the first container based on the aggregated resource utilization rank value.

公开(公告)号：US20190317873A1

公开(公告)日：2019-10-17

申请号：US15952824

申请日：2018-04-13

Applicant: VMware, Inc.

Inventor： Aditya Gopisetti ,  Chandrashekhar Jha ,  Jobin Raju George ,  Kumar Gaurav ,  Jusvinder Singh

IPC: G06F11/34 ,  G06F9/455 ,  G06F11/30

Abstract: The detection of idle virtual machines through usage pattern analysis is described. In one example, a computing device can collect utilization metrics from a virtual machine over time. The utilization metrics can be related to one or more processing usage, disk usage, network usage, and memory usage metrics, among others. The utilization metrics can be separated into a set of training metrics and a set of validation metrics, and a number of clusters can be determined based on the set of training metrics. The clusters can be used to organize the set of validation metrics into groups. Depending upon the number or overall percentage of the utilization metrics assigned to individual ones of the plurality of clusters, it is possible to determine whether or not the virtual machine is an idle virtual machine. Once identified, idle virtual machines can be shut down to conserve processing resources and costs.

公开(公告)号：US20240202171A1

公开(公告)日：2024-06-20

申请号：US18107038

申请日：2023-02-08

Applicant: VMWare, Inc.

Inventor： Chandrashekhar Jha ,  Mervin Nirmal John M W

IPC: G06F16/215 ,  G06F9/455 ,  G06F16/22

CPC classification number: G06F16/215 ,  G06F9/45558 ,  G06F16/2246 ,  G06F2009/45591

Abstract: A request to load a content pack can be received. A first duplicity check between the content pack and a previously loaded content pack can be performed. A second duplicity check between the content pack and the previously loaded content pack can be performed responsive to a determination that the content pack passed the first duplicity check. The content pack can be loaded responsive to a determination that the content pack passed the second duplicity check.

公开(公告)号：US11848821B2

公开(公告)日：2023-12-19

申请号：US18160464

申请日：2023-01-27

Applicant: VMWARE, INC.

Inventor： Yash Bhatnagar ,  Hemani Katyal ,  Chandrashekhar Jha ,  Mageshwaran Rajendran ,  Ritesh Jha

IPC: H04L41/0893 ,  G06F9/50 ,  G06F11/34

CPC classification number: H04L41/0893 ,  G06F9/5038 ,  G06F9/5077 ,  G06F9/5083 ,  G06F11/34

Abstract: An example system includes memory, programmable circuitry, and machine readable instructions to program the programmable circuitry to: obtain utilization metric information corresponding to utilization metrics collected over a time interval, the utilization metrics corresponding to allocated resources utilized by containers, the containers associated with a cluster, obtain a request to generate priority classes for the containers in the cluster, the priority classes indicative of which containers have a greater priority in the cluster, and generate the priority classes for the containers based on the utilization metric information and a count of network interactions corresponding to the containers for the time interval.

公开(公告)号：US11797501B2

公开(公告)日：2023-10-24

申请号：US17174378

申请日：2021-02-12

Applicant: VMWARE, INC.

Inventor： Chandrashekhar Jha ,  Navya Sree Tirunagari ,  Yash Bhatnagar ,  Ritesh Jha

IPC: G06F16/21 ,  G06F16/23 ,  G06F16/242 ,  G06F16/25 ,  G06F11/34 ,  G06F11/07 ,  G06F16/2458

CPC classification number: G06F16/217 ,  G06F11/079 ,  G06F11/3419 ,  G06F16/2358 ,  G06F16/244 ,  G06F16/2477 ,  G06F16/256

Abstract: Methods and systems described herein are directed to aggregating and querying log messages. Methods and systems determine event types of log message generated by event sources of the distributed computing system. The event types are aggregated into aggregated records for a shortest time unit and event types are aggregated into aggregated records for longer time units based on the aggregated records associated with the shortest time unit. In response to a query regarding occurrences of an event type in a query time interval, the query time interval is split into subintervals with time lengths that range from the shortest time unit to a longest time unit that lie within the query time interval. The method determines a total event count of occurrences of the event type in the query time interval based on the aggregated records with time stamps in the subintervals. The event count in the query time interval may be used to detect abnormal behavior of the event sources.

公开(公告)号：US11595266B2

公开(公告)日：2023-02-28

申请号：US16654051

申请日：2019-10-16

Applicant: VMware, Inc.

Inventor： Santoshkumar Kavadimatti ,  Chandrashekhar Jha ,  Gerin Jacob ,  Naveen Mudnal ,  Rajat Garg

IPC: H04L41/14 ,  G06F9/455 ,  H04L67/10 ,  H04L41/0806 ,  G06F9/54

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to detect drift in a hybrid cloud environment. An example apparatus to detect drift in a hybrid cloud environment includes a configuration model determiner to, after deployment of a blueprint in the hybrid cloud environment, generate a first model including first relationships of a first plurality of resources corresponding to the blueprint, the blueprint including a plurality of properties in which at least one of the plurality of properties is agnostic of type of cloud, an inventor model determiner to generate a second model including second relationships of a second plurality of resources as deployed in the hybrid cloud environment based on the blueprint, and a drift determiner to determine a drift value based on the first relationships and the second relationships, the drift value representative of a difference between the first relationships and the second relationships.

公开(公告)号：US11562299B2

公开(公告)日：2023-01-24

申请号：US16444190

申请日：2019-06-18

Applicant: VMware, Inc.

Inventor： Chandrashekhar Jha ,  Ritesh Jha ,  Yash Bhatnagar ,  Rajat Garg ,  Rachil Chandran

IPC: G06F15/16 ,  G06N20/10 ,  G06F9/455

Abstract: Disclosed are various embodiments for automating the prediction of workload tenures in datacenter environments. In some embodiments, parameters are identified for a plurality of workloads of a software defined data center. A machine learning model is trained to determine a predicted tenure based on parameters of the workloads. A workload for the software defined data center is configured to include at least one workload parameter. The workload is processed using the trained machine learning model to determine the predicted tenure. An input to the machine learning model includes the at least one workload parameter.

公开(公告)号：US11188439B2

公开(公告)日：2021-11-30

申请号：US15952824

申请日：2018-04-13

Applicant: VMware, Inc.

Inventor： Aditya Gopisetti ,  Chandrashekhar Jha ,  Jobin Raju George ,  Kumar Gaurav ,  Jusvinder Singh

IPC: G06F9/455 ,  G06F11/34 ,  G06F11/30

Abstract: The detection of idle virtual machines through usage pattern analysis is described. In one example, a computing device can collect utilization metrics from a virtual machine over time. The utilization metrics can be related to one or more processing usage, disk usage, network usage, and memory usage metrics, among others. The utilization metrics can be separated into a set of training metrics and a set of validation metrics, and a number of clusters can be determined based on the set of training metrics. The clusters can be used to organize the set of validation metrics into groups. Depending upon the number or overall percentage of the utilization metrics assigned to individual ones of the plurality of clusters, it is possible to determine whether or not the virtual machine is an idle virtual machine. Once identified, idle virtual machines can be shut down to conserve processing resources and costs.

公开(公告)号：US20210103617A1

公开(公告)日：2021-04-08

申请号：US17122893

申请日：2020-12-15

Applicant: VMware, Inc.

Inventor： Chandrashekhar Jha ,  Kumar Gaurav ,  Sushil Verma ,  Vishal Gupta ,  Aditya Gopisetti

IPC: G06F16/904 ,  G06F16/28 ,  G06F16/901

Abstract: A system can provide a visual representation of an inventory of data entities for a distributed computing system. Inventory data including cost and operational data for data entities such as data centers, servers, and virtual machines, can be converted into a format file. The format file can be used to create a tree of nodes and node summaries corresponding to the data entities. A user interface can display hierarchical and isolated views of the tree revealing parent child relationships between data entities within a computing system infrastructure. Node summaries including cost and utilization data can be displayed to reveal how specific sub-costs such as labor and licensing, are driven by data entities in one level of the infrastructure and pushed to respective parent or child data entities in other levels. Views of the tree can be used to determine areas of inefficiency or reduced value within the computing system.

公开(公告)号：US10719363B2

公开(公告)日：2020-07-21

申请号：US15876244

申请日：2018-01-22

Applicant: VMWARE, INC.

Inventor： Chandrashekhar Jha ,  Dattathreya Sathyamurthy ,  Swarnalatha Pasupuleti ,  Ritesh Jha ,  Soumya Panigrahi

IPC: G06F9/50 ,  G06N20/00

Abstract: Techniques for optimizing resource claims for containers is described. In one example, resource utilization data associated with at least one container may be obtained for a period. A set of forecasting models may be trained based on the resource utilization data associated with a portion of the period. Resource utilization of the at least one container may be predicted for a remaining portion of the period using the set of trained forecasting models. The predicted resource utilization may be compared with the obtained resource utilization data for the remaining portion of the period. A forecasting model may be determined from the set of trained forecasting models based on the comparison to optimize resource claims for the at least one container.