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公开(公告)号：US11916764B1
公开(公告)日：2024-02-27
申请号：US18152027
申请日：2023-01-09
Applicant: SPLUNK INC.
Inventor： Pradeep Baliganapalli Nagaraju , Adam Jamison Oliner , Brian Matthew Gilmore , Erick Anthony Dean , Jiahan Wang
IPC: G06F15/177 , H04L43/028 , H04L41/14 , G06N20/00 , G06F16/901 , G06F16/9038 , H04L43/08 , G06F16/2458 , G06N5/047
CPC classification number: H04L43/028 , G06F16/2477 , G06F16/901 , G06F16/9038 , G06N20/00 , H04L41/14 , H04L43/08 , G06N5/047
Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.
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公开(公告)号：US11132373B1
公开(公告)日：2021-09-28
申请号：US16400001
申请日：2019-04-30
Applicant: Splunk Inc.
IPC: G06F16/24 , G06F16/248 , G06F16/2455 , G06F16/23 , G06F11/30 , G06F11/32 , G06F11/34 , G06F16/25 , G06F3/0482
Abstract: An asset monitoring and reporting system (AMRS) implements decoupled update cycle and disparate search frequency dispatch for dynamic elements of an asset monitoring and reporting system. The AMRS identifies occurrence of an update to a visualization of a client dashboarding component of an AMRS, the visualization comprising dynamic elements and corresponding dynamic element searches that are each associated with a search query to be submitted for execution to obtain a value of a metric of an asset node associated with a respective dynamic element. The AMRS further sends a request indicative of the dynamic elements to a server component of the AMRS, receives dynamic element objects for the dynamic elements, the dynamic element objects specifying search queries corresponding to the dynamic elements, modifies dynamic element searches of the dashboarding component in accordance with the search queries, and stores a definition of the visualization as control information.
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公开(公告)号：US11809439B1
公开(公告)日：2023-11-07
申请号：US17473415
申请日：2021-09-13
Applicant: Splunk Inc.
IPC: G06F16/24 , G06F16/248 , G06F16/2455 , G06F11/30 , G06F16/23 , G06F11/34 , G06F11/32 , G06F16/25 , G06F3/0482
CPC classification number: G06F16/248 , G06F11/3006 , G06F11/323 , G06F11/3495 , G06F16/2379 , G06F16/2455 , G06F16/252 , G06F3/0482
Abstract: An example method of updating a client dashboarding component of an asset monitoring and reporting system comprises: identifying an update of a client dashboarding component of an asset monitoring and reporting system (AMRS), the client dashboarding component comprising one or more dynamic elements, each dynamic element associated with an asset node; receiving one or more search queries, each search query corresponding to a dynamic element of the one or more dynamic elements; modifying one or more dynamic elements of the client dashboarding component in accordance with the one or more search queries; and updating the client dashboarding component to reflect metric values associated with the modified dynamic elements.
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公开(公告)号：US11610156B1
公开(公告)日：2023-03-21
申请号：US17397919
申请日：2021-08-09
Applicant: SPLUNK INC.
Inventor： Pradeep Baliganapalli Nagaraju , Steve Zhang , Jiahan Wang , Adam Jamison Oliner , Erick Anthony Dean
Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.
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Patent Agency Ranking
公开(公告)号：US20200012966A1
公开(公告)日：2020-01-09
申请号：US16573745
申请日：2019-09-17
Applicant: Splunk Inc.
Inventor： Pradeep Baliganapalli Nagaraju , Adam Jamison Oliner , Brian Matthew Gilmore , Erick Anthony Dean , Jiahan Wang
IPC: G06N20/00
Abstract: Disclosed is a technique that can be performed by an electronic device. The electronic device can generate time-stamped events, extract training data from the time-stamped events, and sending the training data over a network to a remote computer. The electronic device can receive model data generated by the remote computer from the training data by use of a machine learning process, update a local model of the electronic device based on the received model data, and generate an output by processing locally sourced data of the electronic device with the updated local model.
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公开(公告)号：US12086451B1
公开(公告)日：2024-09-10
申请号：US17661464
申请日：2022-04-29
Applicant: SPLUNK INC.
IPC: G06F3/06
CPC classification number: G06F3/065 , G06F3/0611 , G06F3/0626 , G06F3/0679
Abstract: A process for facilitating downscaling of datastores (e.g., in a stateful system) is described herein. In embodiments, a set of metrics associated with a set of data stores of a stateful service is obtained. The set of metrics may indicate a utilization of each of the data stores of the set of data stores. Based on the set of metrics indicating underutilization associated with at least a portion of the set of data stores, a determination is made to initiate a downscaling of the set of data stores. Thereafter, a downscaler is deployed to perform downscaling operations to downscale the set of data stores. The downscaler communicates with a first data store to replicate data of the first data store onto a second data store. Based on identifying that the downscaler has completed the downscaling operations to downscale the set of data stores, the downscaler is terminated.
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公开(公告)号：US11836579B2
公开(公告)日：2023-12-05
申请号：US16573745
申请日：2019-09-17
Applicant: Splunk Inc.
Inventor： Pradeep Baliganapalli Nagaraju , Adam Jamison Oliner , Brian Matthew Gilmore , Erick Anthony Dean , Jiahan Wang
Abstract: Disclosed is a technique that can be performed by an electronic device. The electronic device can generate time-stamped events, extract training data from the time-stamped events, and send the training data over a network to a remote computer. The electronic device can receive model data generated by the remote computer from the training data by use of a machine learning process, update a local model of the electronic device based on the received model data, and generate an output by processing locally sourced data of the electronic device with the updated local model.
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公开(公告)号：US12184744B1
公开(公告)日：2024-12-31
申请号：US17958082
申请日：2022-09-30
Applicant: SPLUNK INC.
Inventor： Christopher Kellogg , Pradeep Baliganapalli Nagaraju
IPC: H04L67/562 , G06F21/62
Abstract: A process for providing requests to a management application in a multi-tenant environment is described herein. In embodiments, a broker client is deployed within a tenant execution environment executed by a server computer system. In embodiments, the broker client is configured to communicate with a broker responsible for managing the tenant execution environment based on configuration information. Furthermore, in various embodiments, request to perform operations associated with the tenant execution environment are transmitted to the broker client over a connection and the broker client provides the request to the broker for execution.
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公开(公告)号：US11087236B2
公开(公告)日：2021-08-10
申请号：US15660897
申请日：2017-07-26
Applicant: Splunk Inc.
Inventor： Pradeep Baliganapalli Nagaraju , Steve Zhang , Jiahan Wang , Adam Jamison Oliner , Erick Anthony Dean
Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.
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