-
公开(公告)号：US20200351283A1
公开(公告)日：2020-11-05
申请号：US16400392
申请日：2019-05-01
Applicant: Oracle International Corporation
Inventor： Sampanna Shahaji Salunke , Dario Bahena Tapia , Dustin Garvey , Sumathi Gopalakrishnan , Neil Goodman
Abstract: 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.
-
Patent Agency Ranking
公开(公告)号：US20230075486A1
公开(公告)日：2023-03-09
申请号：US18055773
申请日：2022-11-15
Applicant: Oracle International Corporation
Inventor： Sampanna Shahaji Salunke , Dario Bahena Tapia , Dustin Garvey , Sumathi Gopalakrishnan , Neil Goodman
Abstract: 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.
-
公开(公告)号：US11949703B2
公开(公告)日：2024-04-02
申请号：US18055773
申请日：2022-11-15
Applicant: Oracle International Corporation
Inventor： Sampanna Shahaji Salunke , Dario Bahena Tapia , Dustin Garvey , Sumathi Gopalakrishnan , Neil Goodman
IPC: H04L29/06 , G06F18/2411 , G06N20/10 , H04L9/40
CPC classification number: H04L63/1425 , G06F18/2411 , G06N20/10
Abstract: 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.
-
公开(公告)号：US11533326B2
公开(公告)日：2022-12-20
申请号：US16400392
申请日：2019-05-01
Applicant: Oracle International Corporation
Inventor： Sampanna Shahaji Salunke , Dario Bahena Tapia , Dustin Garvey , Sumathi Gopalakrishnan , Neil Goodman
Abstract: 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.
-
5.发明授权公开(公告)号：US10855548B2
公开(公告)日：2020-12-01
申请号：US16277012
申请日：2019-02-15
Applicant: Oracle International Corporation
Inventor： Dustin Garvey , Neil Goodman , Sampanna Shahaji Salunke , Brent Arthur Enck , Sumathi Gopalakrishnan , Amit Ganesh , Timothy Mark Frazier
Abstract: 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.
-
6.发明申请公开(公告)号：US20200267057A1
公开(公告)日：2020-08-20
申请号：US16277012
申请日：2019-02-15
Applicant: Oracle International Corporation
Inventor： Dustin Garvey , Neil Goodman , Sampanna Shahaji Salunke , Brent Arthur Enck , Sumathi Gopalakrishnan , Amit Ganesh , Timothy Mark Frazier
Abstract: 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.
-
-
-
-
-
Search Results
6
records
(took 0.015 seconds)
