Synchronized Databricks AI Catalog data

After the synchronization, the assets are available in the specified domain.

Warning Do not move the assets to another domain. Doing so may lead to errors during future synchronizations.

Asset status

By default, the assets are shown in a plain list, but you can enable a multi-path hierarchy to show it in a tree structure.

The status of assets depends on the selected value in the Default Asset Status field in the capability.

  • If No Status is selected, newly created assets receive the first status listed in your Operating Model statuses, and existing assets keep their assigned status.
  • If Implemented is selected, all assets receive the "Implemented" status.
Note For more information about AI Model Version asset statuses, go to Configure the lifecycle stages of AI Governance assets.

Synchronized metadata

Important considerations:

  • We always integrate the latest version of a model.
  • The integrated attributes depend on training run type.
  • If you don't see the listed synchronized metadata, you can add characteristics to the layout on the asset type page.

Asset type

Synchronized metadata

 Public ID
AI Base Model Description Description
Model Name ModelName
Version Version
Model Lifecycle Status ModelLifecycleStatus
Creation Date in Source CreationDateInSource
Retirement Date in Source RetirementDateInSource
Content Filter ContentFilter
AI System Provider AISystemProvider
Databricks AI Model Version

Description from source system

 DescriptionFromSourceSystem
Model Accuracy ModelAccuracy
Model Precision ModelPrecision
Mean Squared Error MeanSquaredError
Mean Absolute Error MeanAbsoluteError
Feature Importance Feature Importance
Version Version

Any custom metrics defined via the configuration. If you use custom metrics, ensure that you add them to the assignment and layout on the asset type page.

  • accuracy_score,
  • exact_match
  • example_count
  • f1_score
  • f1_score_micro
  • f1_score_macro
  • false_negatives
  • false_positives
  • log_loss
  • max_error
  • mean_absolute_error
  • mean_absolute_percentage_error
  • mean_on_target
  • mean_squared_error
  • precision
  • precision_recall_auc
  • r2_score
  • recall
  • roc_auc
  • root_mean_squared_error
  • sum_on_target
  • token_count
  • true_negatives
  • true_positives
  
AI Model Deployment Description from Source DescriptionFromSourceSystem
Initiating User in Source InitiatingUserInSource
Creation Date in Source CreationDateInSource
Modification Date in Source ModificationDateInSource
Retirement Date in Source RetirementDateInSource
Implemented Content Filtering ImplementedContentFiltering
Compute Configuration ComputeConfiguration
AI Endpoint Access Method AccessMethod
Access Instructions AccessInstructions
Traffic Split TrafficSplit
AI Monitor Data Drift Detection Enabled DataDriftDetection
Prediction Drift Detection Enabled PredictionDriftDetection
Schedule Schedule
Alert Configuration AlertConfiguration