Splunk Inc.

Ricky Gene Burnett

Steven Shaun McIntyre

Dipock Das

Darrell Sano

Troy Elliott Molander

Arthur Foelsche

Alexander Douglas James

Joseph Gabriel Echeverria

Ran Xie

Daniel Ferstay

Bei Li

Ganesh Jothikumar

Salih Ammar Wajih Zainulabdeen

Amy Joanna Sutedja

Ankur Dalsukhbhai Bambharoliya

Anush Kumar Jayaraman

Max Feng

Eric Prokop

Jeremiah Reichardt

Troy Elliot Molander

Systems and methods are described for a implementing a streaming data processing system that includes a pool of pre-configured resources and a pool of dedicated resources. The streaming data processing system can implement a processing pipeline using compute resources. The pool of pre-configured resources can support previews of processing pipelines for a plurality of users and the pool of dedicated resources can support full deployments of processing pipelines for a particular user. The streaming data processing system can implement a preview of a processing pipeline using a pre-configured resource of the pool of pre-configured resources. Further, the streaming data processing system can implement the processing pipeline using a dedicated resource of the pool of dedicated resources. The streaming data processing system can provision the dedicated resource and deploy the processing pipeline using the dedicated resource.

Implementation of a data processing pipeline using assignable resources and pre-configured resources

Systems and methods are described for providing previews of deployment of data stream processing instructions sets, sometimes called pipelines, to a stream data processing system. Rather than deploying such an instruction set, which may cause detrimental side effects, previews can be facilitated by conversion of a data stream processing instructions set to a batch query that is applied to an existing data set. An output of the batch query can then be provided to an end user as a preview of output of the data stream processing instructions set, when implemented.

Data stream processing instruction set previews using batch conversion

The disclosure includes methods and systems that perform operations of identifying a behavior of a metric, where the metric is associated with a node of included within a nodal graph displayed on a graphical user interface. Additionally, a root cause of the behavior is determined through automated, computerized analytics, which may include execution of a search query associated with the node, and a notification of the root cause may be provided via the graphical user interface. Additionally, the graphical user interface may be configured to receive user input that results in the generation of a nodal graph, where the user input includes placement of nodes on a display screen and edges representing a connection between two nodes, where the edges may represent a dependency between the nodes.

Computerized monitoring of a metric through execution of a search query, determining a root cause of the behavior, and providing a notification thereof

Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in training of a machine learning model according to the user interaction, the machine learning model configured to determine a prediction, classification or clustering of a result of a first search query by utilizing a result of at least a second search query as input to the machine learning model.

Real-time measurement and system monitoring based on generated dependency graph models of system components

Systems and methods are disclosed for implementing dual textual/graphical programming interfaces for programming streaming data processing pipelines. A user interface is provided that enables a user to author a processing pipeline as a query in a query language, and to request conversion of that query language into a graph data structure representation of the pipeline, which can be visualized in the interface. The interface further enables modification of the graph via interaction with the visualization. On request, the modified graph can be converted back into the query language, with the querying being modified to reflect the modifications to the graph.

Dual textual/graphical programming interfaces for streaming data processing pipelines

Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in automatic changes to control information reflected in the computer storage model that directs the processing of various monitoring functions associated with the metrics.

System monitoring driven by automatically determined operational parameters of dependency graph model with user interface

One or more embodiments related to a method that includes querying a data store for current interaction data between call center personnel and customers. The call center personnel are grouped into call center groups. The method further includes determining, for at least some call center groups, a current interaction metric specific to the call center group. The current interaction method is provided for each of the at least some call center groups.

Monitoring framework

Framework for group monitoring using pipeline commands

Framework for supporting a call center

Call center analysis

Growing community of inventors

Davis, CA, United States of America

Ricky Gene Burnett