Data visualization in an extended reality environment

    公开(公告)号:US11644940B1

    公开(公告)日:2023-05-09

    申请号:US16264529

    申请日:2019-01-31

    Applicant: SPLUNK INC.

    CPC classification number: G06F3/04815 G06F3/0482 G06F3/04842 G06F9/451

    Abstract: A device that includes an extended reality application is employed by a user to access an extended reality environment. A selection of a first subset of dashboard panels included in a plurality of dashboard panels is received via an input device associated with the extended reality environment. Each dashboard panel included in the plurality of dashboard panels includes a visual representation of data. The first subset of dashboard panels is displayed in a foreground area of a workspace of the XR environment. A second subset of dashboard panels included in the plurality of dashboard panels is displayed in a background area of the workspace of the XR environment.

    User interface for customizing data streams

    公开(公告)号:US11636116B2

    公开(公告)日:2023-04-25

    申请号:US17243156

    申请日:2021-04-28

    Applicant: SPLUNK Inc.

    Abstract: Systems and methods are described for customizable data streams in a streaming data processing system. Routing criteria for the customizable data streams are defined by a user, an automated process, or any other process. The routing criteria can be defined using graphical controls. The streaming data processing system uses the routing criteria to determine data that should be used to populate a particular data stream. Further, processing pipelines are customized such that a particular processing pipeline can obtain data from a particular user defined data stream and write data to a particular user defined data stream. Data is routed through the user defined data streams and customized processing pipelines based on a data route. A data route for a set of data may include multiple user defined data streams and multiple processing pipelines. The data route can include a loop of processing pipelines and data streams.

    Supporting graph data structure transformations in graphs generated from a query to event data

    公开(公告)号:US11625394B1

    公开(公告)日:2023-04-11

    申请号:US17653626

    申请日:2022-03-04

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for supporting transformations of a graph generated from a query to event data. The event data may be unstructured event data, from which instances of a journey can be identified that represent sequences of related events describing actions performed in a computing environment. When evaluating journey instances, it can be helpful to visualize the instances as a graph. Depending on the instances viewed, a user may desire different modifications to the graph. While such modifications can be made when initially building instances from the unstructured event data, this can limit reuse of the resulting instances (since the modification would also be present when evaluating other subsets). To address this, embodiments of the present disclosure enable graph modifications to be applied to subsets of journey instances after building those instances from unstructured event data, increasing reuse of instances built from a query against the unstructured data.

    Identifying threat indicators by processing multiple anomalies

    公开(公告)号:US11606379B1

    公开(公告)日:2023-03-14

    申请号:US17236890

    申请日:2021-04-21

    Applicant: Splunk Inc.

    Abstract: Techniques are described for processing anomalies detected using user-specified rules with anomalies detected using machine-learning based behavioral analysis models to identify threat indicators and security threats to a computer network. In an embodiment, anomalies are detected based on processing event data at a network security system that used rules-based anomaly detection. These rules-based detected anomalies are acquired by a network security system that uses machine-learning based anomaly detection. The rules-based detected anomalies are processed along with machine learning detected anomalies to detect threat indicators or security threats to the computer network. The threat indicators and security threats are output as alerts to the network security system that used rules-based anomaly detection.

    Expediting processing of selected events on a time-limited basis

    公开(公告)号:US11593477B1

    公开(公告)日:2023-02-28

    申请号:US16779465

    申请日:2020-01-31

    Applicant: Splunk Inc.

    Abstract: Techniques are described that enable an IT and security operations application to prioritize the processing of selected events for a defined period of time. Data is obtained reflecting activity within an IT environment, wherein the data includes a plurality of events each representing an occurrence of activity within the IT environment. A severity level is assigned to each event of the plurality of events, where the events are processed by the IT and security operations application in an order that is based at least in part on the severity level assigned to each event. Input is received identifying at least one event of the plurality of events for expedited processing to obtain a set of expedited events, and the identified events are processed by the IT and security operations application before processing events that are not in the set of expedited events.

    Bucket data distribution for exporting data to worker nodes

    公开(公告)号:US11580107B2

    公开(公告)日:2023-02-14

    申请号:US16398038

    申请日:2019-04-29

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described for exporting bucket data from one or more buckets to one or more worker nodes. The system can identify data from different bucket data from buckets stored in a data intake and query system that is to be processed by one or more worker nodes. The system can allocate one or more execution resources, such as a processing pipeline, to process and export the bucket data from the buckets. The system can assign bucket data corresponding to individual buckets to the execution resource based on a bucket distribution policy. The indexer can export the bucket data to the worker nodes for further processing based on the bucket data-execution resource assignment.

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