公开(公告)号：US11971778B1

公开(公告)日：2024-04-30

申请号：US18299469

申请日：2023-04-12

Applicant: Splunk Inc.

Inventor： Jacob Barton Leverich ,  Shang Cai ,  Hongyang Zhang ,  Mihai Ganea ,  Alex Cruise

IPC: G06F11/07

CPC classification number: G06F11/079 ,  G06F11/0709 ,  G06F11/0793

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

公开(公告)号：US10558516B2

公开(公告)日：2020-02-11

申请号：US16176186

申请日：2018-10-31

Applicant: SPLUNK INC.

Inventor： Jacob Barton Leverich ,  Shang Cai ,  Hongyang Zhang ,  Mihai Ganea ,  Alex Cruise

IPC: G06F11/00 ,  G06F11/07

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

公开(公告)号：US11632383B2

公开(公告)日：2023-04-18

申请号：US17075928

申请日：2020-10-21

Applicant: SPLUNK INC.

Inventor： Adam Jamison Oliner ,  Jonathan La ,  Colleen Kinross ,  Hongyang Zhang ,  Jacob Leverich ,  Shang Cai ,  Mihai Ganea ,  Alex Cruise ,  Toufic Boubez ,  Manish Sainani

IPC: G06F21/00 ,  H04L9/40 ,  G06N3/08 ,  G06N5/00 ,  G06N3/04

Abstract: In some implementations, sequences of time series values determined from machine data are obtained. Each sequence corresponds to a respective time series. A plurality of predictive models is generated for a first time series from the sequences of time series values. Each predictive model is to generate predicted values associated with the first time series using values of a second time series. For each of the plurality of predictive models, an error is determined between the corresponding predicted values and values associated with the first time series. A predictive model is selected for anomaly detection based on the determined error of the predictive model. Transmission is caused of an indication of an anomaly detected using the selected predictive model.

公开(公告)号：US20190065298A1

公开(公告)日：2019-02-28

申请号：US16176186

申请日：2018-10-31

Applicant: SPLUNK INC.

Inventor： Jacob Barton Leverich ,  Shang Cai ,  Hongyang Zhang ,  Mihai Ganea ,  Alex Cruise

IPC: G06F11/07

CPC classification number: G06F11/079

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

公开(公告)号：US11537951B2

公开(公告)日：2022-12-27

申请号：US17146339

申请日：2021-01-11

Applicant: SPLUNK INC.

Inventor： Lin Ma ,  Jacob Leverich ,  Adam Oliner ,  Alex Cruise ,  Hongyang Zhang

IPC: G06F7/08 ,  G06N20/00 ,  H04L67/10 ,  H04L9/40 ,  G06F16/28 ,  G06F16/951 ,  G06F16/2455 ,  G06F16/903 ,  H04L41/14

Abstract: Embodiments of the present invention are directed to facilitating distributed data processing for machine learning. In accordance with aspects of the present disclosure, a set of commands in a query to process at an external computing service is identified. For each command in the set of commands, at least one compute unit including at least one operation to perform at the external computing service is identified. Each of the at least one compute unit associated with each command is analyzed to identify an optimized manner in which to execute the set of commands at the external computing service. An indication of the optimized manner in which to execute the set of commands and a corresponding set of data is provided to the external computing service to utilize for executing the set of commands at the external computing service.

公开(公告)号：US10992560B2

公开(公告)日：2021-04-27

申请号：US16227248

申请日：2018-12-20

Applicant: SPLUNK INC.

Inventor： Jacob Barton Leverich ,  Shang Cai ,  Hongyang Zhang ,  Mihai Ganea ,  Alex Cruise

IPC: H04L12/24 ,  H04L12/26 ,  H04L29/08 ,  H04L29/06

Abstract: An anomaly detection system includes a plurality of signals. Each of the signals is associated with an anomaly detection procedure that will be used to identify anomalies within the signal. Anomaly detection is performed by applying the anomaly detection procedure to a sequential set of data points of a signal. The signals are updated based on incoming data streams. The data streams are analyzed, and the sequential set of data points for each signal is updated based on data points extracted from the data streams.

公开(公告)号：US10146609B1

公开(公告)日：2018-12-04

申请号：US15206126

申请日：2016-07-08

Applicant: Splunk, Inc.

Inventor： Jacob Barton Leverich ,  Shang Cai ,  Hongyang Zhang ,  Mihai Ganea ,  Alex Cruise

IPC: G06F11/00 ,  G06F11/07

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

公开(公告)号：US11669382B2

公开(公告)日：2023-06-06

申请号：US16722673

申请日：2019-12-20

Applicant: SPLUNK INC.

Inventor： Jacob Barton Leverich ,  Shang Cai ,  Hongyang Zhang ,  Mihai Ganea ,  Alex Cruise

IPC: G06F11/07

CPC classification number: G06F11/079 ,  G06F11/0709 ,  G06F11/0793

Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.

公开(公告)号：US10922625B2

公开(公告)日：2021-02-16

申请号：US15885395

申请日：2018-01-31

Applicant: Splunk Inc.

Inventor： Lin Ma ,  Jacob Leverich ,  Adam Oliner ,  Alex Cruise ,  Hongyang Zhang

IPC: G06F17/00 ,  G06N20/00 ,  G06F7/08 ,  H04L29/08 ,  H04L29/06 ,  G06F16/28 ,  G06F16/951 ,  G06F16/2455 ,  G06F16/903 ,  H04L12/24

Abstract: Embodiments of the present invention are directed to facilitating distributed data processing for machine learning. In accordance with aspects of the present disclosure, a set of commands in a query to process at an external computing service is identified. For each command in the set of commands, at least one compute unit including at least one operation to perform at the external computing service is identified. Each of the at least one compute unit associated with each command is analyzed to identify an optimized manner in which to execute the set of commands at the external computing service. An indication of the optimized manner in which to execute the set of commands and a corresponding set of data is provided to the external computing service to utilize for executing the set of commands at the external computing service.

公开(公告)号：US10375098B2

公开(公告)日：2019-08-06

申请号：US15420737

申请日：2017-01-31

Applicant: SPLUNK INC.

Inventor： Adam Jamison Oliner ,  Jonathan La ,  Colleen Kinross ,  Hongyang Zhang ,  Jacob Leverich ,  Shang Cai ,  Mihai Ganea ,  Alex Cruise ,  Toufic Boubez ,  Manish Sainani

IPC: H04L29/06 ,  G06N3/04 ,  G06N3/08

Abstract: In some implementations, sequences of time series values determined from machine data are obtained. Each sequence corresponds to a respective time series. A plurality of predictive models is generated for a first time series from the sequences of time series values. Each predictive model is to generate predicted values associated with the first time series using values of a second time series. For each of the plurality of predictive models, an error is determined between the corresponding predicted values and values associated with the first time series. A predictive model is selected for anomaly detection based on the determined error of the predictive model. Transmission is caused of an indication of an anomaly detected using the selected predictive model.