Normalization of discovery models using machine learning
Summarize
Summary of Normalization of discovery models using machine learning
ServiceNow’s Software Asset Management (SAM) application leverages machine learning (ML) to enhance the normalization of discovery models by improving recognition of discovered software attributes like version, full version, and edition in real time. This capability increases normalization rates beyond traditional content service rules, facilitating more accurate and up-to-date software asset data.
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Activation and Configuration
- Enable ML normalization by activating the Software Asset Management – Machine Learning Normalization plugin (com.snsammlnormalization).
- Ensure the property Enable ML Normalization for discovered software (com.snc.samp.enable.mlnormalization) is selected to use ML-based normalization.
- Disabling this property opts out of ML normalization, reverting normalization to use only content service rules.
Normalization Process and Scheduled Jobs
- The daily scheduled job SAM-Normalize discovery models using content library rules runs regardless of ML plugin activation and normalizes discovery models using content rules.
- If ML normalization is enabled, this job triggers another job, SAM-Normalize discovery models using machine learning, which applies ML predictions to partially normalized models.
- A weekly job re-applies content rules to discovery models normalized by ML, ensuring content service predictions override ML if discrepancies occur, as content rules take precedence.
- The status of these jobs is tracked in the Software Asset Job Result [sampjoblog] table.
Machine Learning Normalization Details
- Normalized values and ML prediction details are stored in the Software Discovery Model [cmdbsamswdiscoverymodel] table, including:
- ML prediction values: Predicted software attributes.
- ML model version: Version of the ML model used.
- ML normalization status: Status such as ML normalized, reverted by user, or overridden by content rules.
- Users can manually revert ML or content normalization, which resets the discovery model status to Match not Found. Reverting ML normalization does not disable content rules, but reverting normalization done only by content rules does disable those rules.
Normalization Rules
Normalization status depends on which fields are normalized for licensed and non-licensed products:
| Fields Normalized | Status |
|---|---|
| All fields (publisher, product, version, edition, full version) | Normalized |
| Only publisher normalized | Publisher normalized |
| Only product and publisher normalized | Partially normalized |
| None of the fields normalized | Match not found |
| Fields Normalized | Status |
|---|---|
| Publisher and product normalized | Normalized |
| Only publisher normalized | Publisher normalized |
| None of the fields normalized | Match not found |
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.
- 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
| 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 |
| 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 |