公开(公告)号：US10445907B2

公开(公告)日：2019-10-15

申请号：US15379106

申请日：2016-12-14

Applicant: Oracle International Corporation

Inventor： Kusumaharanadh Poduri ,  Arvind Kumar Maheshwari ,  Raghav Ravichandran

IPC: G06T11/20 ,  H04L12/26

Abstract: Techniques for selecting an anomaly based on a context are disclosed. A set of metrics corresponding to communications with nodes of a computer system are identified. A set of insights are generated based on the set of metrics. A context for determining a primary anomaly is determined. A subset of metrics associated with the context are identified. A subset of insights that are generated based on the subset of metrics are identified. An insight is selected from the subset of insights as the primary anomaly. A visualization associated with the primary anomaly is presented at a user interface. One or more secondary anomalies may be concurrently presented with the visualization. Additionally, the primary anomaly, the selected visualization, and/or the secondary anomaly is used to determine a new context for selecting another primary anomaly. Hence, a series of primary anomalies may be selected, each primary anomaly being related to each other.

公开(公告)号：US20170364851A1

公开(公告)日：2017-12-21

申请号：US15186938

申请日：2016-06-20

Applicant: Oracle International Corporation

Inventor： Arvind Kumar Maheshwari ,  Raghav Ravichandran ,  Vladimir Volchegursky ,  Tse-Han Huang

IPC: G06Q10/06

CPC classification number: G06Q10/06315 ,  G06Q10/06314

Abstract: Techniques are described herein for seasonal pattern determination and validation. In one or more embodiments, a set of time-series data is received to analyze for seasonal behavior. In response a plurality of patterns may be generated, including a first pattern and a second pattern, such that each of the first pattern and the second pattern approximate data points that represent a same sub-period of multiple instances of a season within the set of time-series data. One or more other instances of the season may then be analyzed to determine whether at least part of the first pattern or the second pattern is detected. Based at least in part on determining that the at least part of the first pattern is detected in the at least part of the same sub-period, a responsive action that is associated with the first pattern may be performed.

公开(公告)号：US20210004998A1

公开(公告)日：2021-01-07

申请号：US17029743

申请日：2020-09-23

Applicant: Oracle International Corporation

Inventor： Kusumaharanadh Poduri ,  Arvind Kumar Maheshwari ,  Raghav Ravichandran

IPC: G06T11/20 ,  H04L12/26

Abstract: Techniques for selecting an anomaly based on a context are disclosed. A set of metrics corresponding to communications with nodes of a computer system are identified. A set of insights are generated based on the set of metrics. A context for determining a primary anomaly is determined. A subset of metrics associated with the context are identified. A subset of insights that are generated based on the subset of metrics are identified. An insight is selected from the subset of insights as the primary anomaly. A visualization associated with the primary anomaly is presented at a user interface. One or more secondary anomalies may be concurrently presented with the visualization. Additionally, the primary anomaly, the selected visualization, and/or the secondary anomaly is used to determine a new context for selecting another primary anomaly. Hence, a series of primary anomalies may be selected, each primary anomaly being related to each other.

公开(公告)号：US20190378313A1

公开(公告)日：2019-12-12

申请号：US16549390

申请日：2019-08-23

Applicant: Oracle International Corporation

Inventor： Kusumaharanadh Poduri ,  Arvind Kumar Maheshwari ,  Raghav Ravichandran

IPC: G06T11/20 ,  H04L12/26

Abstract: Techniques for selecting an anomaly based on a context are disclosed. A set of metrics corresponding to communications with nodes of a computer system are identified. A set of insights are generated based on the set of metrics. A context for determining a primary anomaly is determined. A subset of metrics associated with the context are identified. A subset of insights that are generated based on the subset of metrics are identified. An insight is selected from the subset of insights as the primary anomaly. A visualization associated with the primary anomaly is presented at a user interface. One or more secondary anomalies may be concurrently presented with the visualization. Additionally, the primary anomaly, the selected visualization, and/or the secondary anomaly is used to determine a new context for selecting another primary anomaly. Hence, a series of primary anomalies may be selected, each primary anomaly being related to each other.

公开(公告)号：US10970893B2

公开(公告)日：2021-04-06

申请号：US17029743

申请日：2020-09-23

Applicant: Oracle International Corporation

Inventor： Kusumaharanadh Poduri ,  Arvind Kumar Maheshwari ,  Raghav Ravichandran

IPC: G06T11/20 ,  H04L12/26

Abstract: Techniques for selecting an anomaly based on a context are disclosed. A set of metrics corresponding to communications with nodes of a computer system are identified. A set of insights are generated based on the set of metrics. A context for determining a primary anomaly is determined. A subset of metrics associated with the context are identified. A subset of insights that are generated based on the subset of metrics are identified. An insight is selected from the subset of insights as the primary anomaly. A visualization associated with the primary anomaly is presented at a user interface. One or more secondary anomalies may be concurrently presented with the visualization. Additionally, the primary anomaly, the selected visualization, and/or the secondary anomaly is used to determine a new context for selecting another primary anomaly. Hence, a series of primary anomalies may be selected, each primary anomaly being related to each other.

公开(公告)号：US10818052B2

公开(公告)日：2020-10-27

申请号：US16549390

申请日：2019-08-23

Applicant: Oracle International Corporation

Inventor： Kusumaharanadh Poduri ,  Arvind Kumar Maheshwari ,  Raghav Ravichandran

IPC: G06T11/20 ,  H04L12/26

Abstract: Techniques for selecting an anomaly based on a context are disclosed. A set of metrics corresponding to communications with nodes of a computer system are identified. A set of insights are generated based on the set of metrics. A context for determining a primary anomaly is determined. A subset of metrics associated with the context are identified. A subset of insights that are generated based on the subset of metrics are identified. An insight is selected from the subset of insights as the primary anomaly. A visualization associated with the primary anomaly is presented at a user interface. One or more secondary anomalies may be concurrently presented with the visualization. Additionally, the primary anomaly, the selected visualization, and/or the secondary anomaly is used to determine a new context for selecting another primary anomaly. Hence, a series of primary anomalies may be selected, each primary anomaly being related to each other.

公开(公告)号：US11263566B2

公开(公告)日：2022-03-01

申请号：US15186938

申请日：2016-06-20

Applicant: Oracle International Corporation

Inventor： Arvind Kumar Maheshwari ,  Raghav Ravichandran ,  Vladimir Volchegursky ,  Tse-Han Huang

IPC: G06Q10/06 ,  G06F8/65 ,  G06F9/50

Abstract: Techniques are described herein for seasonal pattern determination and validation. In one or more embodiments, a set of time-series data is received to analyze for seasonal behavior. In response a plurality of patterns may be generated, including a first pattern and a second pattern, such that each of the first pattern and the second pattern approximate data points that represent a same sub-period of multiple instances of a season within the set of time-series data. One or more other instances of the season may then be analyzed to determine whether at least part of the first pattern or the second pattern is detected. Based at least in part on determining that the at least part of the first pattern is detected in the at least part of the same sub-period, a responsive action that is associated with the first pattern may be performed.

公开(公告)号：US20180082449A1

公开(公告)日：2018-03-22

申请号：US15379106

申请日：2016-12-14

Applicant: Oracle International Corporation

Inventor： Kusumaharanadh Poduri ,  Arvind Kumar Maheshwari ,  Raghav Ravichandran

IPC: G06T11/20 ,  H04L12/26 ,  G06F3/0484

CPC classification number: G06T11/206 ,  H04L43/045

Abstract: Techniques for selecting an anomaly based on a context are disclosed. A set of metrics corresponding to communications with nodes of a computer system are identified. A set of insights are generated based on the set of metrics. A context for determining a primary anomaly is determined. A subset of metrics associated with the context are identified. A subset of insights that are generated based on the subset of metrics are identified. An insight is selected from the subset of insights as the primary anomaly. A visualization associated with the primary anomaly is presented at a user interface. One or more secondary anomalies may be concurrently presented with the visualization. Additionally, the primary anomaly, the selected visualization, and/or the secondary anomaly is used to determine a new context for selecting another primary anomaly. Hence, a series of primary anomalies may be selected, each primary anomaly being related to each other.