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公开(公告)号：US20250130871A1
公开(公告)日：2025-04-24
申请号：US18381520
申请日：2023-10-18
Applicant: VMware, Inc.
Inventor： Ashot Nshan Harutyunyan , Arnak Poghosyan , Tigran Bunarjyan , Andranik Haroyan , Marine Harutyunyan , Litit Harutyunyan , Ashot Baghdasaryan
Abstract: This disclosure is directed to automated computer-implemented methods for application discovery from log messages generated by event sources of applications executing in a cloud infrastructure. The methods are executed by an operations manager that constructs a data frame of probability distributions of event types of the log messages generated by the event sources in a time period. The operations manager executes clustering techniques that are used to form clusters of the probability distributions in the data frame, where each of the clusters corresponds to one of the applications. The operations manager displays the clusters of the probability distributions in a two-dimensional map of applications in a graphical user interface that enables a user to select one of the clusters in the map of applications that corresponds to one of the applications and launch clustering of probability distributions of the user-selected cluster to discover two or more instances of the application.
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公开(公告)号：US20240419530A1
公开(公告)日：2024-12-19
申请号：US18336799
申请日：2023-06-16
Applicant: VMware, Inc.
Inventor： Ashot Nshan Harutyunyan , Arnak Poghosyan , Artur Grigoryan , Vahan Tadevosyan , Vahe Mikayelyan
IPC: G06F11/07
Abstract: Automated computer-implemented methods and systems for discovering incidents occurring with objects running in a data center and executing remedial measures that correct the incidents are described herein. The methods and systems discover clusters of alerts in a stream of alerts triggered by a stream of events occurring with objects in the data center. User feedback is used to identify alerts with related event types in each cluster of alerts that corresponds to separate incidents occurring in the data center. The methods and system compare a set of runtime alerts to each incident to determine one or more similar incidents to the set of runtime alerts. The one or more similar incidents and corresponding remedial measures are displayed in a GUI with each remedial measure selectable to launch an operation that corrects one of the problems represented by the one or more similar incidents.
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公开(公告)号：US20240028955A1
公开(公告)日：2024-01-25
申请号：US18100159
申请日：2023-01-23
Applicant: VMware, Inc.
Inventor： Ashot Nshan Harutyunyan , Arnak Poghosyan , Lilit Harutyunyan , Nelli Aghajanyan , Tigran Bunarjyan , Marine Harutyunyan , Sam Israelyan
Abstract: Automated, computer-implemented methods and systems describe herein resolve performance problems with objects executing in a data center. The operations manager uses machine learning to train an inference model that relates probability distributions of event types of log messages of the object to a key performance indicator (“KPI”) of the object. The operations manager monitors the KPI for run-time KPI values that violates a KPI threshold. When the KPI violates the threshold, the operations manager determines probabilities of event types of log messages recorded in a run-time interval and uses the inference model to determine event types of the probabilities of event types of log messages in the run-time interval to determine a root cause of the performance problem. The inference models can be used to identify log messages of event types that correspond to potential performance problems with data center objects and execute appropriate remedial measures to avoid the problems.
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公开(公告)号：US20240028442A1
公开(公告)日：2024-01-25
申请号：US17871080
申请日：2022-07-22
Applicant: VMware, Inc.
Inventor： Ashot Nshan Harutyunyan , Arnak Poghosyan , Lilit Harutyunyan , Nelli Aghajanyan , Tigran Bunarjyan , Marine Harutyunyan , Sam Israelyan
IPC: G06F11/07
CPC classification number: G06F11/079 , G06F11/0769
Abstract: Automated, computer-implemented methods and systems for resolving performance problems with objects executing in a data center are described. The automated methods use machine learning to train a model that comprises rules defining relationships between probabilities of event types of in log messages and values of a key performance indictor (“KPI”) of the object over a historical time period. When a KPI violates a corresponding threshold, the rules are used to evaluate run time log messages that describe the probable root cause of the performance problem. An alert identifying the KPI threshold violation, and the log messages are displayed in a graphical user interface of an electronic display device.
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公开(公告)号：US20230099001A1
公开(公告)日：2023-03-30
申请号：US17490340
申请日：2021-09-30
Applicant: VMware, Inc.
Inventor： Ashot Nshan Harutyunyan , Arnak Poghosyan
Abstract: Automated processes and systems troubleshoot and optimize performance of applications running in distributed computing systems. An automated computer-implemented processes train an inference model for an application based on metrics associated with the application and a key performance indicator (“KPI”) of the application. When a run-time performance problem is detected in run-time KPI values of KPI, the trained inference model is applied to run-time metrics and run-time KPI values to identify relevant run-time metrics that can be used to identify the root cause of the performance problem. The root cause of the performance problem can be used to generate a recommendation for correcting the performance problem. An alert identifying the root cause of the performance problem and the recommendation for correcting the performance problem are displayed on an interface of a display, thereby enabling correction of the performance problem and optimization of the application.
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Patent Agency Ranking
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
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.
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7.发明申请公开(公告)号：US20220027249A1
公开(公告)日：2022-01-27
申请号：US16936565
申请日：2020-07-23
Applicant: VMware, Inc.
Inventor： Sunny Dua , Bonnie Zhang , Karen Aghajanyan , Hovhannes Antonyan , Ashot Nshan Harutyunyan , Arnak Poghosyan , Naira Movses Grigoryan
Abstract: Methods and systems described herein automate various aspects of troubleshooting a problem in a distributed computing system for various forms of object information regarding objects of the distributed computing system. In one aspect, the object information includes metrics, log messages, properties, network flows, events, and application traces. Methods and systems learn interesting patterns contained in the object information. The interesting patterns include change points in metrics and network flows, changes in the types of log messages, broken correlations between events, anomalous event transactions, atypical histogram distributions of metrics, and atypical histogram distributions of span durations in application traces. The interesting patterns are displayed in a graphical user interface (“GUI”) that enables a user to assign a label identifying a problem associated with the interesting patterns.
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公开(公告)号：US11055382B2
公开(公告)日：2021-07-06
申请号：US14701217
申请日：2015-04-30
Applicant: VMware, Inc.
Abstract: Methods and systems that estimate a degree of abnormality of a complex system based on historical time-series data representative of the complex system's past behavior and using the historical degree of abnormality to determine whether or not a degree of abnormality determined from current time-series data representative of the same complex system's current behavior is worthy of attention. The time-series data may be metric data that represents behavior of a complex system as a result of successive measurements of the complex system made over time or in a time interval. A degree of abnormality represents the amount by which the time-series data violates a threshold. The larger the degree of abnormality of the current time-series data is from the historical degree of abnormality, the larger the violation of the thresholds and the greater the probability the violation in the current time-series data is worthy of attention.
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公开(公告)号：US20200341832A1
公开(公告)日：2020-10-29
申请号：US16391702
申请日：2019-04-23
Applicant: VMware, Inc.
Inventor： Arnak Poghosyan , Ashot Nshan Harutyunyan , Naira Movses Grigoryan
Abstract: Automated processes and systems that determine a state of a complex computational system of a distributed computing system are described. The processes and systems determine outlier and normal metric values of metrics associated with a complex computational system. A total outlier metric is constructed based on the outlier and normal metric values of the metrics. Time stamps of outlier and normal total outlier metric values of the total outlier metric are labeled. Each time-stamp label identifies a normal or abnormal state of the complex computation system. One or more rules for classifying normal and abnormal states of the complex computational system are computed based on the time-stamp labels. The rules are applied to run-time metric values to determine a state of the complex computational system and generate an alert when the state is abnormal. The type of alert and corresponding abnormal state may be used to execute remedial measures.
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公开(公告)号：US10394612B2
公开(公告)日：2019-08-27
申请号：US15190678
申请日：2016-06-23
Applicant: VMware, Inc.
Inventor： Naira Movses Grigoryan , Vahan Tadevosyan , Nina Karapetyan , Ashot Nshan Harutyunyan , Arnak Poghosyan
IPC: G06F9/50
Abstract: Methods and systems to evaluate data center performance and prioritize data center objects and anomalies for remedial actions are described. Methods rank data center objects and determine object performance trends. Methods calculate an object rank of each object of the data center over a period of time and calculate an object trend of each object of the data center based on relative frequencies of alerts at different times. The objects may be prioritized for remedial actions based on the object ranks and object trends.
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