公开(公告)号：US20220283924A1

公开(公告)日：2022-09-08

申请号：US17367490

申请日：2021-07-05

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan ,  Clement Pang ,  George Oganesyan ,  Karen Avagyan

IPC: G06F11/34 ,  G06F11/07

Abstract: Computer-implemented methods and systems described herein perform intelligent sampling of application traces generated by an application. Computer-implemented methods and systems determine different sampling rates based on frequency of occurrence of trace types and/or frequency of occurrence of durations of the traces. Each sampling rate corresponds to a different trace type and/or different duration. The sampling rates for low frequency trace types and durations are larger than the sampling rates for high frequency trace types and durations. The relatively larger sampling rates for low frequency trace types and low frequency durations ensures that low frequency trace types and low frequency durations are sampled in sufficient numbers and are not passed over during sampling of the application traces. The set of sampled traces are stored in a data storage device.

公开(公告)号：US11500829B2

公开(公告)日：2022-11-15

申请号：US16517297

申请日：2019-07-19

Applicant: VMware, Inc.

Inventor： Clement Pang

IPC: G06F16/21 ,  G06F16/22 ,  G06F16/28

Abstract: In a computer-implemented method for adapting time series database schema of a time series database, time series data ingested into a time series database according to a time series database schema is accessed over a time period, wherein time series data comprises a plurality of dimensions. The time series data of the time period is analyzed to determine a data shape of the time series data of the time period. It is determined whether to adapt the time series database schema based at least in part on the data shape of the time series data of the time period. In some embodiments, the time series database schema is adapted based at least in part on the data shape of the time series data of the time period. Time series data is then ingested into the time series database according to the adapted time series database schema.

公开(公告)号：US11321284B2

公开(公告)日：2022-05-03

申请号：US16517309

申请日：2019-07-19

Applicant: VMware, Inc.

Inventor： Clement Pang

IPC: G06F16/00 ,  G06F16/21 ,  G06F16/28 ,  G06F16/2458

Abstract: In a computer-implemented method for adapting time series database schema, a plurality of queries to a time series database received over a time period is accessed, wherein time series data is ingested into the time series database according to a time series database schema, wherein time series data comprises a plurality of dimensions. The plurality of queries of the time period is analyzed to determine a relative frequency of the plurality of dimensions within the plurality of queries over the time period. It is determined whether to adapt the time series database schema based at least in part on the relative frequency of the plurality of dimensions within the plurality of queries over the time period.

公开(公告)号：US20210216860A1

公开(公告)日：2021-07-15

申请号：US16742594

申请日：2020-01-14

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Narek Hovhannisyan ,  Sirak Ghazaryan ,  George Oganesyan ,  Clement Pang ,  Ashot Nshan Harutyunyan ,  Naira Movses Grioryan

IPC: G06N3/08 ,  G06F16/2458 ,  G06N3/04

Abstract: The current document is directed to methods and systems that generate forecasts based on input time-series data using a forecasting neural network or other machine-learning-based forecasting subsystem. In various implementations, an input time series is first classified and then transformed, based on the classification, to a corresponding stationary time series. The corresponding stationary time series is then submitted to a neural network or other machine-learning-based forecasting subsystem to generate an initial forecast for future time points. The initial forecast is then inverse transformed, based on the input-time-series classification, to generate a final, output forecast.

公开(公告)号：US11023353B2

公开(公告)日：2021-06-01

申请号：US16250831

申请日：2019-01-17

Applicant: VMware, Inc.

Inventor： Arnak Poghosyan ,  Clement Pang ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan

IPC: G06F15/173 ,  G06F11/34 ,  G06F11/30 ,  G06F11/07 ,  H04L12/24 ,  G06F16/2458 ,  G06F17/18 ,  G06N3/02

Abstract: Computational processes and systems are directed to forecasting time series data and detection of anomalous behaving resources of a distributed computing system data. Processes and systems comprise off-line and on-line modes that accelerate the forecasting process and identification of anomalous behaving resources. In the off-line mode, recurrent neural network (“RNN”) is continuously trained using time series data associated with various resources of the distributed computing system. In the on-line mode, the latest RNN is used to forecast time series data for resources in a forecast time window and confidence bounds are computed over the forecast time window. The forecast time series data characterizes expected resource usage over the forecast time window so that usage of the resource may be adjusted. The confidence bounds may be used to detect anomalous behaving resources. Remedial measures may then be executed to correct problems indicated by the anomalous behavior.

公开(公告)号：US11416364B2

公开(公告)日：2022-08-16

申请号：US17119462

申请日：2020-12-11

Applicant: VMware, Inc.

Inventor： Naira Movses Grigoryan ,  Arnak Poghosyan ,  Ashot Nshan Harutyunyan ,  Clement Pang ,  Dev Nag

IPC: G06F11/30 ,  G06F11/34 ,  G06F11/32

Abstract: The current document is directed to methods and systems that employ distributed-computer-system metrics collected by one or more distributed-computer-system metrics-collection services, call traces collected by one or more call-trace services, and attribute values for distributed-computer-system components to identify attribute dimensions related to anomalous behavior of distributed-computer-system components. In a described implementation, nodes correspond to particular types of system components and node instances are individual components of the component type corresponding to a node. Node instances are associated with attribute values and node are associated with attribute-value spaces defined by attribute dimensions. A set of call traces is partitioned, by clustering. Using attribute values and call traces, attribute dimensions that are likely related to particular anomalous behaviors of distributed-computer-system components are determined by decision-tree-related analyses for each partition and are reported to one or more computational entities to facilitate resolution of the anomalous behaviors.

公开(公告)号：US20220058073A1

公开(公告)日：2022-02-24

申请号：US17492099

申请日：2021-10-01

Applicant: VMware, Inc.

Inventor： Amak Poghosyan ,  Ashot Nshan Harutyunyan ,  Naira Movses Grigoryan ,  Clement Pang ,  George Oganesyan ,  Davit Baghdasaryan

IPC: G06F11/07 ,  G06F11/34 ,  G06K9/62

Abstract: The current document is directed to methods and systems that employ call traces collected by one or more call-trace services to generate call-trace-classification rules to facilitate root-cause analysis of distributed-application operational problems and failures. In a described implementation, a set of automatically labeled call traces is partitioned by the generated call-trace-classification rules. Call-trace-classification-rule generation is constrained to produce relatively simple rules with greater-than-threshold confidences and coverages. The call-trace-classification rules may point to particular services and service failures, which provides useful information to distributed-application and distributed-computer-system managers and administrators attempting to diagnose operational problems and failures that arise during execution of distributed applications within distributed computer systems. A first dataset is collected during normal distributed-application operation and a second dataset is collected during problem-associated or failure-associated operation of the distributed application. The first and second datasets are used to generate noise-subtracted call-trace-classification rules and/or diagnostic suggestions.

公开(公告)号：US10789233B2

公开(公告)日：2020-09-29

申请号：US15952090

申请日：2018-04-12

Applicant: VMware, Inc.

Inventor： Clement Pang

IPC: G06F7/00 ,  G06F16/22 ,  G06F16/2455 ,  G06F16/2458 ,  G06F16/2453

Abstract: In a method for dynamic refresh of an index during query path generation for time series data, a query for time series data is received. During generation of a query plan based on the query, operations in a stage for a plurality of paths of execution are determined based at least in part on elements of the query, wherein execution of the stage comprises accessing an index of a plurality of indices. It is determined whether to refresh indices of a plurality of indices based on a potential usefulness of the indices in reducing a solution set for the stage of a path of execution of the plurality of paths of execution. The indices are selectively refreshed based on the potential usefulness of the indices in reducing a solution set for the stage of a path of execution of the plurality of paths of execution.

公开(公告)号：US10789232B2

公开(公告)日：2020-09-29

申请号：US15952066

申请日：2018-04-12

Applicant: VMware, Inc.

Inventor： Clement Pang

IPC: G06F7/00 ,  G06F16/22 ,  G06F16/2455 ,  G06F16/2458 ,  G06F16/2453

Abstract: In a method for generating a query plan for time series data, a query for time series data is received, the query including elements. The query is parsed to identify the elements and operators between the elements. First stages for a plurality of paths of execution are determined based at least in part on the elements and the operators. At least a first stage for the plurality of paths of execution is executed. The plurality of paths of execution is evaluated after completion of the first stage. Based on the evaluating, a subset of paths of execution is selected for continued execution and evaluation.

公开(公告)号：US11609885B2

公开(公告)日：2023-03-21

申请号：US16517353

申请日：2019-07-19

Applicant: VMware, Inc.

Inventor： Clement Pang

IPC: G06F7/00 ,  G06F16/21 ,  G06F16/28 ,  G06F16/2458

Abstract: In a computer-implemented method for maintaining a time series database including a plurality of time series database schemas, time series data including data points are received at an ingestion node of a time series database, the data points comprising a plurality of dimensions. A plurality of time series database schemas of the time series database is determined for storing the time series data. The time series data is ingested according to the plurality of time series database schemas, wherein each data point is stored according to each time series database schema of the plurality of time series database schemas, such that the time series database comprises multiple instances of each data point.