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：US20220374292A1

公开(公告)日：2022-11-24

申请号：US17326169

申请日：2021-05-20

Applicant: VMware, Inc.

Inventor： Ritesh Jha ,  Jobin Raju George ,  Pushkar Patil ,  Vaidic Joshi ,  Nikhil Jaiswal

IPC: G06F9/54 ,  G06F9/50 ,  G06F16/18

Abstract: The current document is directed to methods and systems that efficiently process and store log/event messages generated within distributed computer facilities. Various different types of initial processing steps may be applied to a stream of log/event messages received by a message-collector system or a message-ingestion-and-processing subsystem. The currently disclosed methods and systems employ additional pre-processing steps to identify the types of received log/event messages, monitor event-type-associated log/event-message-usage-delay histories, and employ time-series-analysis-based and/or neural-network-based estimation of event-type-associated log/event-message usage to efficiently store log/event-messages in low-cost and low-latency storage facilities.

公开(公告)号：US20220318202A1

公开(公告)日：2022-10-06

申请号：US17222050

申请日：2021-04-05

Applicant: VMware, Inc.

Inventor： Ritesh Jha ,  Vaidic Joshi ,  Jobin Raju George ,  Nikhil Jaiswal ,  Pushkar Patil

IPC: G06F16/17 ,  G06F16/18 ,  G06F16/9035 ,  G06F16/9038 ,  G06F9/30 ,  G06F9/54

Abstract: The current document is directed to methods and subsystems within distributed log-analytics systems that automatically and autonomously generate indications of log sources for log/event messages received by the distributed log-analytics systems. The log-source indications can be incorporated in tags associated with received log/event messages to facilitate use of log/event-message information and log/event-message-processing tools contained in content packs provided by designers, manufacturers, and vendors of computational entities by log/event-message systems that collect, process, and store large volumes of log/event messages generated by many different types of computational entities within distributed computer systems. Log-source indications are generated by a combination of using currently available log-source indications associated with log/event messages, event-type-clustering based event-type-to-log source mapping, and machine-learning-based event-type-to-log source mapping.

公开(公告)号：US11151478B2

公开(公告)日：2021-10-19

申请号：US16423201

申请日：2019-05-28

Applicant: VMWARE, INC.

Inventor： Ritesh Jha ,  Priyank Agarwal ,  Vaidic Joshi ,  Suchit Dhakate ,  Jasmine Ejner

IPC: G06N20/00 ,  G06F40/40 ,  G06F9/455

Abstract: The present disclosure provides an approach for training a machine learning model by first training the model on a generic dataset and then iteratively training the model on “easy” domain specific training data before moving on to “difficult” domain specific training data. Inputs of a domain-specific dataset are run on the generically-trained model to determine which inputs generate an accuracy score above a threshold. The inputs with an accuracy score above a threshold are used to retrain the model, along with the corresponding outputs. The retraining continues until all domain specific dataset has been used to train the model, or until no remaining inputs of the domain specific dataset generate an accuracy score, when run on the model, that is above a threshold.

公开(公告)号：US20210182297A1

公开(公告)日：2021-06-17

申请号：US16807187

申请日：2020-03-03

Applicant: VMWARE, INC.

Inventor： Karthik Seshadri ,  Siddartha Laxman Karibhimanvar ,  Ritesh Jha ,  Radhakrishnan Devarajan ,  Chaitanya Krishna Mullangi

IPC: G06F16/2455 ,  G06F16/23 ,  G06F16/26 ,  G06F16/27 ,  G06F16/25

Abstract: This disclosure describes how data supporting real-time reporting services can be cached during a log intake process. In particular, instead of caching all the log data being generated by an operational system, only the log data relevant to existing queries associated with the real-time reporting services are cached. In some embodiments, only particular metrics contained within the log data are stored for rapid access by the real-time reporting services.

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.