Patents by Inventor Uri Shaft

Uri Shaft has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20200327708
    Abstract: Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.
    Type: Application
    Filed: April 27, 2020
    Publication date: October 15, 2020
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Uri Shaft, Lik Wong, Maria Kaval
  • Patent number: 10789065
    Abstract: Techniques for analyzing, understanding, and remediating differences in configurations among many software resources are described herein. Machine learning processes are applied to determine a small feature set of parameters from among the complete set of parameters configured for each software resource. The feature set of parameters is selected to optimally cluster configuration instances for each of the software resources. Once clustered based on the values of the feature set of parameters, a graph is generated for each cluster of configuration instances that depicts the differences among the configuration instances within the cluster. An interactive visualization tool renders the graph in a user interface, and a management tool allows changes to the graph and changes to the configuration of one or more software resources.
    Type: Grant
    Filed: May 7, 2018
    Date of Patent: September 29, 2020
    Assignee: Oracle lnternational Corporation
    Inventors: Dustin Garvey, Amit Ganesh, Timothy Mark Frazier, Shriram Krishnan, Sr., Uri Shaft, Prasad Ravuri, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan
  • Patent number: 10747642
    Abstract: Systems and methods are described for efficiently detecting an optimal number of behaviors to model software system performance data and the aspects of the software systems that best separate the behaviors. The behaviors may be ranked according to how well fitting functions partition the performance data.
    Type: Grant
    Filed: October 20, 2018
    Date of Patent: August 18, 2020
    Assignee: Oracle International Corporation
    Inventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Brent Arthur Enck, Timothy Mark Frazier, Sumathi Gopalakrishnan, Eric L. Sutton
  • Publication number: 20200258005
    Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.
    Type: Application
    Filed: April 29, 2020
    Publication date: August 13, 2020
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Uri Shaft, Lik Wong
  • Publication number: 20200249931
    Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.
    Type: Application
    Filed: April 21, 2020
    Publication date: August 6, 2020
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Amit Ganesh, Uri Shaft, Prasad Ravuri, Long Yang, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan, Timothy Mark Frazier, Shriram Krishnan
  • Patent number: 10733528
    Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.
    Type: Grant
    Filed: February 29, 2016
    Date of Patent: August 4, 2020
    Assignee: Oracle International Corporation
    Inventors: Dustin Garvey, Uri Shaft, Lik Wong
  • Patent number: 10699211
    Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal. Based on the noise signal, a first classification is generated for a plurality of seasonal instances within the set of time series data, where each respective instance of the plurality of instances corresponds to a respective sub-period within the season and the first classification associates a first set of one or more instances from the plurality of instances with a particular class of seasonal pattern. Based on the dense signal, a second classification is generated that associates a second set of one or more instances with the particular class. Based on the first classification and the second classification, a third classification is generated, where the third classification associates a third set of one or more instances with the particular class.
    Type: Grant
    Filed: February 29, 2016
    Date of Patent: June 30, 2020
    Assignee: Oracle International Corporation
    Inventors: Dustin Garvey, Uri Shaft, Lik Wong
  • Patent number: 10692255
    Abstract: Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.
    Type: Grant
    Filed: September 27, 2018
    Date of Patent: June 23, 2020
    Assignee: Oracle International Corporation
    Inventors: Dustin Garvey, Uri Shaft, Lik Wong, Maria Kaval
  • Patent number: 10664264
    Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.
    Type: Grant
    Filed: July 23, 2018
    Date of Patent: May 26, 2020
    Assignee: Oracle International Corporation
    Inventors: Dustin Garvey, Amit Ganesh, Uri Shaft, Prasad Ravuri, Long Yang, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan, Timothy Mark Frazier, Shriram Krishnan
  • Patent number: 10635563
    Abstract: Systems and methods for performing unsupervised baselining and anomaly detection using time-series data are described. In one or more embodiments, a baselining and anomaly detection system receives a set of time-series data. Based on the set of time-series, the system generates a first interval that represents a first distribution of sample values associated with the first seasonal pattern and a second interval that represents a second distribution of sample values associated with the second seasonal pattern. The system then monitors a time-series signals using the first interval during a first time period and the second interval during a second time period. In response to detecting an anomaly in the first seasonal pattern or the second seasonal pattern, the system generates an alert.
    Type: Grant
    Filed: May 31, 2017
    Date of Patent: April 28, 2020
    Assignee: Oracle International Corporation
    Inventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Maria Kaval
  • Publication number: 20200125471
    Abstract: Techniques for training and evaluating seasonal forecasting models are disclosed. In some embodiments, a network service generates, in memory, a set of data structures that separate sample values by season type and season space. The set of data structures may include a first set of clusters corresponding to different season types in the first season space and a second set of clusters corresponding to different season types in the second season space. The network service merges two or more clusters the first set and/or second set of clusters. Clusters from the first set are not merged with clusters from the second set. After merging the clusters, the network serves determines a trend pattern for each of the remaining clusters in the first and second set of clusters. The network service then generates a forecast for a metric of a computing resource based on the trend patterns for each remaining cluster.
    Type: Application
    Filed: October 23, 2018
    Publication date: April 23, 2020
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Sumathi Gopalakrishnan
  • Publication number: 20200125601
    Abstract: Generating persistent multifaceted statistical distributions of event data associated with computing nodes is disclosed. From a data stream, events are identified that occur during a first time interval. Characteristics associated with the events are determined. Based on a primary characteristic, it is determined that an event corresponds to an event cluster. The event count for that cluster is incremented. It is determined that the characteristics correspond to an event descriptor of events in the cluster. Responsive to requests to view the event cluster, information about descriptors from the cluster are displayed indicating events having a particular event descriptor, or a summary of characteristics that distinguish the descriptor from other event descriptors.
    Type: Application
    Filed: April 12, 2019
    Publication date: April 23, 2020
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Brent Arthur Enck, Sampanna Shahaji Salunke, Uri Shaft, John Branson Bley, Timothy Mark Frazier, Sumathi Gopalakrishnan
  • Publication number: 20200125988
    Abstract: Techniques for machine-learning of long-term seasonal patterns are disclosed. In some embodiments, a network service receives a set of time-series data that tracks metric values of at least one computing resource over time. Responsive to receiving the time-series data, the network service detects a subset of metric values that are outliers and associated with a plurality of timestamps. The network service maps the plurality of timestamps to one or more encodings of at least one encoding space that defines a plurality of encodings for different seasonal patterns. Based on the mapped encodings, the network service generates a representation of a seasonal pattern. Based on the representation of the seasonal pattern, the network service may perform one or more operations in association with the at least one computing resource.
    Type: Application
    Filed: October 23, 2018
    Publication date: April 23, 2020
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Sumathi Gopalakrishnan
  • Publication number: 20200125474
    Abstract: Systems and methods are described for efficiently detecting an optimal number of behaviors to model software system performance data and the aspects of the software systems that best separate the behaviors. The behaviors may be ranked according to how well fitting functions partition the performance data.
    Type: Application
    Filed: October 20, 2018
    Publication date: April 23, 2020
    Applicant: Oracle International Corporation
    Inventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Brent Arthur Enck, Timothy Mark Frazier, Sumathi Gopalakrishnan, Eric L. Sutton
  • Patent number: 10592230
    Abstract: Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on the plurality of parameter sets such that the signature vectors have equal lengths. A signature vector may map to one or more parameter sets of the plurality of parameter sets. A plurality of clusters are generated based on the similarity between signature vectors. Operations may be performed on a target resource based on one or more nodes in the plurality of clusters.
    Type: Grant
    Filed: August 7, 2019
    Date of Patent: March 17, 2020
    Assignee: Oracle International Corporation
    Inventors: Dustin Garvey, Timothy Mark Frazier, Shriram Krishnan, Uri Shaft, Amit Ganesh, Prasad Ravuri, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan
  • Publication number: 20200004860
    Abstract: Techniques for analyzing an execution of a query statement based on a random archive are disclosed. A plurality of query statements that are executed during a particular time period are identified. A random sampling function is executed to randomly select a set of query statements from the plurality of query statements. Execution plans and/or performance metrics associated with each execution of the randomly-selected query statements are stored into a random archive. Responsive to determining that a performance metric for a current execution of a particular query statement does not satisfy a performance criteria, information associated with the particular query statement from the random archive is analyzed. A model plan characteristic associated with an execution of the particular query statement stored in the random archive is determined. An execution plan associated with the model plan characteristic is determined for another execution of the particular query statement.
    Type: Application
    Filed: July 1, 2018
    Publication date: January 2, 2020
    Applicant: Oracle International Corporation
    Inventors: Arvind Kumar Maheshwari, Uri Shaft, Karl Dias, Vishwanath Karra, Stephen Wexler, Anil Kumar Kothuri
  • Publication number: 20190370115
    Abstract: Techniques for generating distribution approximations with low memory footprints are disclosed. In some embodiments, a system receives a first set of values that measure one or more metrics of at least one computing resource. A set of clusters are generated, within volatile or non-volatile memory, that approximate a distribution of the first set of values measuring the one or more metrics of the at least one computing resource. The set of clusters is transformed, within volatile or non-volatile memory, to a piecewise approximation of a function for the first set of values.
    Type: Application
    Filed: June 5, 2018
    Publication date: December 5, 2019
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Brent Arthur Enck, Sumathi Gopalakrishnan
  • Publication number: 20190373007
    Abstract: Systems and methods for performing unsupervised baselining and anomaly detection using time-series data are described. In one or more embodiments, a baselining and anomaly detection system receives a set of time-series data. Based on the set of time-series, the system generates a first interval that represents a first distribution of sample values associated with the first seasonal pattern and a second interval that represents a second distribution of sample values associated with the second seasonal pattern. The system then monitors a time-series signals using the first interval during a first time period and the second interval during a second time period. In response to detecting an anomaly in the first seasonal pattern or the second seasonal pattern, the system performs a responsive action, such as generating an alert.
    Type: Application
    Filed: July 27, 2019
    Publication date: December 5, 2019
    Applicant: Oracle International Corporation
    Inventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Maria Kaval
  • Publication number: 20190370677
    Abstract: Techniques for efficiently generating aggregate distribution approximations are disclosed. In some embodiments, a system receives a plurality of piecewise approximations that represent different distributions of a set of values on at least one computing resource. Based on the plurality of piecewise approximations, a set of clusters are generated, within volatile or non-volatile memory, that approximate an aggregate distribution of the set of metric values on the at least one computing resource. The set of clusters is transformed, within volatile or non-volatile memory, to an aggregate piecewise approximation of a function for the set of metric values on the at least one computing resource.
    Type: Application
    Filed: June 5, 2018
    Publication date: December 5, 2019
    Applicant: Oracle International Corporation
    Inventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Brent Arthur Enck, Sumathi Gopalakrishnan
  • Patent number: 10496396
    Abstract: Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on the plurality of parameter sets such that the signature vectors have equal lengths. A signature vector may map to one or more parameter sets of the plurality of parameter sets. A plurality of clusters are generated based on the similarity between signature vectors. Operations may be performed on a target resource based on one or more nodes in the plurality of clusters.
    Type: Grant
    Filed: July 20, 2018
    Date of Patent: December 3, 2019
    Assignee: Oracle International Corporation
    Inventors: Dustin Garvey, Timothy Mark Frazier, Shriram Krishnan, Uri Shaft, Amit Ganesh, Prasad Ravuri, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan