Model driven state machine transitions to configure an installation of a software program

    公开(公告)号:US11237813B1

    公开(公告)日:2022-02-01

    申请号:US17163135

    申请日:2021-01-29

    Applicant: Splunk Inc.

    Abstract: Disclosed are embodiments of a installed software program that receive a model from a product management system. The model is trained to select one of a plurality of predefined states based on operational parameter values of the installation of the software program. Each of the plurality of predefined states define configuration values of the installation of the software program. The defined configuration values indicate, in some embodiments, updates to operational parameter values of the installation of the software program.

    Model driven state machine transitions to configure an installation of a software program

    公开(公告)号:US11579860B2

    公开(公告)日:2023-02-14

    申请号:US17563598

    申请日:2021-12-28

    Applicant: Splunk Inc.

    Abstract: Disclosed are embodiments of a installed software program that receive a model from a product management system. The model is trained to select one of a plurality of predefined states based on operational parameter values of the installation of the software program. Each of the plurality of predefined states define configuration values of the installation of the software program. The defined configuration values indicate, in some embodiments, updates to operational parameter values of the installation of the software program.

    MODEL DRIVEN STATE MACHINE TRANSITIONS TO CONFIGURE AN INSTALLATION OF A SOFTWARE PROGRAM

    公开(公告)号:US20220244934A1

    公开(公告)日:2022-08-04

    申请号:US17563598

    申请日:2021-12-28

    Applicant: Splunk Inc.

    Abstract: Disclosed are embodiments of a installed software program that receive a model from a product management system. The model is trained to select one of a plurality of predefined states based on operational parameter values of the installation of the software program. Each of the plurality of predefined states define configuration values of the installation of the software program. The defined configuration values indicate, in some embodiments, updates to operational parameter values of the installation of the software program.

    Machine learning modeling of candidate models for software installation usage

    公开(公告)号:US12181999B1

    公开(公告)日:2024-12-31

    申请号:US17589534

    申请日:2022-01-31

    Applicant: Splunk Inc.

    Abstract: This document discloses methods and systems for modeling product usage. In one practical application, the systems and methods may be utilized to model product usage based on large volume, machine generated product usage data to optimize product pricing and operations. Specifically, the systems and methods described herein may utilize methods with key components to select the maximum number of dimensions that can be modeled based on the number of data points, use a logarithm kernel function to normalize machine data with long-tailed statistical distributions on different numerical scales, compare a large number of candidate models with different candidate dimensions and different structures, and quantify the amount of change and drift in models over time.

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