Normalization of discovery models using machine learning

  • Release version: Washingtondc
  • Updated February 1, 2024
  • 3 minutes to read
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    Summary of Normalization of Discovery Models Using Machine Learning

    The normalization of discovery models in ServiceNow's Software Asset Management utilizes machine learning to enhance the recognition and classification of discovered software in real-time. By employing machine learning, users can improve their normalization rates for unrecognized software, which is crucial for effective software asset management.

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    Key Features

    • Machine learning predicts version, full version, and edition of discovered software.
    • Activation of the machine learning normalization plugin is required to enable these features.
    • Normalization occurs daily through scheduled jobs, with options for content service rules or machine learning predictions.
    • Machine learning results are reflected in specific columns of the Software Discovery Model table, providing insights into prediction values and normalization status.
    • Status indicators include 'ML normalized', 'Reverted', and 'Content overridden' to track the normalization process.

    Key Outcomes

    By implementing machine learning normalization, customers can expect:

    • Enhanced accuracy in software recognition and classification.
    • Real-time updates on the normalization status and predictions.
    • Automatic updates to normalization based on content service rules, prioritizing content predictions over machine learning when necessary.
    • The ability to manually revert normalizations if needed, with clear differentiation between machine learning and content rule effects.

    Use machine learning to improve your normalization rates in real time by normalizing your unrecognized discovered software.

    The Software Asset Management application uses machine learning to improve normalization of discovery models. The prediction values currently supported by machine learning are version, full version, and edition.

    Opt in for machine learning normalization by activating the Software Asset Management – Machine Learning Normalization (com.sn_sam_ml_normalization) plugin.

    Once the plugin is activated, ensure that the Enable ML Normalization for discovered software (com.snc.samp.enable.ml_normalization) property is selected. For more details on this property, see Software Asset Management properties. You can opt out of machine learning normalization by disabling this property. If you opt out, normalization of discovery models only takes place against the content service rules.

    The scheduled job, SAM-Normalize discovery models using content library rules, triggers on a daily basis and normalizes the discovery models based on the content rules. This scheduled job runs irrespective of whether the Software Asset Management – Machine Learning Normalization plugin is activated or not. If this plugin is activated, then the partially normalized discovery models are picked up by another scheduled job, SAM-Normalize discovery models using machine learning. The scheduled job, SAM-Normalize discovery models using content library rules is enhanced to invoke the on-demand scheduled job, SAM-Normalize discovery models using machine learning and also validates machine learning predictions.

    Once the scheduled job, SAM-Normalize discovery models using machine learning is complete, you can view the updated values in the following machine learning based columns in the Software Discovery Model [cmdb_sam_sw_discovery_model] table:
    • ML prediction values: Indicates the predicted values for the attributes.
    • ML model version: Indicates the model version that was used for predicting the attributes.
    • ML normalization status: Indicates the status of machine learning normalization. Values for this column include:
      • ML normalized: Discovery model is normalized by machine learning
      • Reverted: Discovery model is normalized by machine learning but the user reverted the normalized values
      • Content overridden: Machine learning predictions over-written by new content rules
    Note:
    The status of the scheduled job, SAM-Normalize discovery models using machine learning is tracked in the Software Asset Job Result [samp_job_log] table.
    As the content rules are always getting updated, the weekly scheduled job SAM-Normalize discovery models using content library rules picks up the discovery models normalized by machine learning and tries to normalize these models with the latest content rules. If the predicted values of machine learning differ from the predictive values of the content service, the machine learning predictions are overwritten with the content service values. The content service prediction values always get precedence over the machine learning prediction values.
    Note:
    For details on the normalization rules for the predictive values, refer to tables titled Normalization rules for licensed products andNormalization rules for non licensed products.
    You can manually normalize a discovery model by reverting the normalization values. When you revert normalizations in the Software Discovery Model form, all the normalized values, got from content and machine learning, are removed. The discovery model reverts to a status of Match not Found.
    Note:
    When you revert a discovery model normalized by machine learning, the content rules are not deactivated. However, if a discovery model is normalized only by content rules, then the content rules are deactivated.
    Table 1. Normalization rules for licensed products
    Fields Normalization status
    All fields are normalized
    Note:
    All the fields include publisher, product, version, edition, and full version.
    		 Normalized
    Only the publisher is normalized Publisher normalized
    If none of the fields are normalized: publisher, product, version, edition, full version Match not found
    Only product and publisher are normalized. Partially normalized
    Table 2. Normalization rules for non licensed products
    Fields Normalization status
    If only publisher and product are normalized Normalized
    Only the publisher is normalized Publisher normalized
    If none of the fields are normalized: publisher, product, version, edition, full version Match not found