Patents by Inventor Brent Arthur Enck
Brent Arthur Enck 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).
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Patent number: 11675851Abstract: 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: GrantFiled: September 20, 2021Date of Patent: June 13, 2023Assignee: Oracle International CorporationInventors: Dustin Garvey, Brent Arthur Enck, Sampanna Shahaji Salunke, Uri Shaft, John Branson Bley, Timothy Mark Frazier, Sumathi Gopalakrishnan
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Publication number: 20220004579Abstract: 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: ApplicationFiled: September 20, 2021Publication date: January 6, 2022Applicant: Oracle International CorporationInventors: Dustin Garvey, Brent Arthur Enck, Sampanna Shahaji Salunke, Uri Shaft, John Branson Bley, Timothy Mark Frazier, Sumathi Gopalakrishnan
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Patent number: 11126667Abstract: 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: GrantFiled: April 12, 2019Date of Patent: September 21, 2021Assignee: Oracle International CorporationInventors: Dustin Garvey, Brent Arthur Enck, Sampanna Shahaji Salunke, Uri Shaft, John Branson Bley, Timothy Mark Frazier, Sumathi Gopalakrishnan
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Patent number: 11048612Abstract: 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: GrantFiled: August 17, 2020Date of Patent: June 29, 2021Assignee: Oracle International CorporationInventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Brent Arthur Enck, Timothy Mark Frazier, Sumathi Gopalakrishnan, Eric L. Sutton
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Patent number: 10997517Abstract: 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: GrantFiled: June 5, 2018Date of Patent: May 4, 2021Assignee: Oracle International CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Brent Arthur Enck, Sumathi Gopalakrishnan
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Patent number: 10963346Abstract: 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: GrantFiled: June 5, 2018Date of Patent: March 30, 2021Assignee: Oracle international CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Brent Arthur Enck, Sumathi Gopalakrishnan
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Publication number: 20200379882Abstract: 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: ApplicationFiled: August 17, 2020Publication date: December 3, 2020Applicant: Oracle International CorporationInventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Brent Arthur Enck, Timothy Mark Frazier, Sumathi Gopalakrishnan, Eric L. Sutton
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Patent number: 10855548Abstract: Techniques are disclosed for summarizing, diagnosing, and correcting the cause of anomalous behavior in computing systems. In some embodiments, a system identifies a plurality of time series that track different metrics over time for a set of one or more computing resources. The system detects a first set of anomalies in a first time series that tracks a first metric and assigns a different respective range of time to each anomaly. The system determines whether the respective range of time assigned to an anomaly overlaps with timestamps or ranges of time associated with anomalies from one or more other time series. The system generates at least one cluster that groups metrics based on how many anomalies have respective ranges of time and/or timestamps that overlap. The system may preform, based on the cluster, one or more automated actions for diagnosing or correcting a cause of anomalous behavior.Type: GrantFiled: February 15, 2019Date of Patent: December 1, 2020Assignee: Oracle International CorporationInventors: Dustin Garvey, Neil Goodman, Sampanna Shahaji Salunke, Brent Arthur Enck, Sumathi Gopalakrishnan, Amit Ganesh, Timothy Mark Frazier
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Publication number: 20200267057Abstract: Techniques are disclosed for summarizing, diagnosing, and correcting the cause of anomalous behavior in computing systems. In some embodiments, a system identifies a plurality of time series that track different metrics over time for a set of one or more computing resources. The system detects a first set of anomalies in a first time series that tracks a first metric and assigns a different respective range of time to each anomaly. The system determines whether the respective range of time assigned to an anomaly overlaps with timestamps or ranges of time associated with anomalies from one or more other time series. The system generates at least one cluster that groups metrics based on how many anomalies have respective ranges of time and/or timestamps that overlap. The system may preform, based on the cluster, one or more automated actions for diagnosing or correcting a cause of anomalous behavior.Type: ApplicationFiled: February 15, 2019Publication date: August 20, 2020Applicant: Oracle International CorporationInventors: Dustin Garvey, Neil Goodman, Sampanna Shahaji Salunke, Brent Arthur Enck, Sumathi Gopalakrishnan, Amit Ganesh, Timothy Mark Frazier
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Patent number: 10747642Abstract: 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: GrantFiled: October 20, 2018Date of Patent: August 18, 2020Assignee: Oracle International CorporationInventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Brent Arthur Enck, Timothy Mark Frazier, Sumathi Gopalakrishnan, Eric L. Sutton
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Publication number: 20200125474Abstract: 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: ApplicationFiled: October 20, 2018Publication date: April 23, 2020Applicant: Oracle International CorporationInventors: Sampanna Shahaji Salunke, Dustin Garvey, Uri Shaft, Brent Arthur Enck, Timothy Mark Frazier, Sumathi Gopalakrishnan, Eric L. Sutton
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Publication number: 20200125601Abstract: 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: ApplicationFiled: April 12, 2019Publication date: April 23, 2020Applicant: Oracle International CorporationInventors: Dustin Garvey, Brent Arthur Enck, Sampanna Shahaji Salunke, Uri Shaft, John Branson Bley, Timothy Mark Frazier, Sumathi Gopalakrishnan
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Publication number: 20190370677Abstract: 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: ApplicationFiled: June 5, 2018Publication date: December 5, 2019Applicant: Oracle International CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Brent Arthur Enck, Sumathi Gopalakrishnan
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Publication number: 20190370115Abstract: 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: ApplicationFiled: June 5, 2018Publication date: December 5, 2019Applicant: Oracle International CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Brent Arthur Enck, Sumathi Gopalakrishnan