Synchronize Google Vertex AI

Synchronizing Gemini Enterprise Agent Platform (formerly Vertex AI) is the process of integrating metadata from Google Vertex AI and making the data available in Collibra Platform.

You can synchronize manually or automate the process by adding a synchronization schedule.

Prerequisites

In your Collibra environment:

Steps

  1. On the main toolbar, click Products icon → Catalog.
    The Catalog homepage opens.
  2. Click Integrations.
    The Integrations page opens.
  3. Click the Integration configuration tab.
  4. In the Connection name column, locate the GCP connection that you used when you added the Google Vertex AI capability and click the link in the Capabilities column.
    The Synchronization page opens.
  5. In the Synchronization configuration section, click Add configuration.
  6. Complete the fields as needed.
    7. Field Action
    Domain

    Select the domain asset in which you want to add the Vertex AI assets.

    Important Ensure that you select a domain of the type Technology Asset Domain.
    Project IDs

    To add a Project ID where Vertex AI is enabled, click Add Project Id. You can add multiple Project IDs. The capability will search in the specified projects.
    Vertex AI Locations
    Optionally, when a new location is added in Vertex AI and not yet supported by the integration, you can add the location in Vertex AI Locations. When you add locations in this field, the integration ingests Vertex AI assets only from the specified locations.
    Do you want to ingest input and output assets?

    Optionally, select Do you want to ingest input and output assets? to ingest datasets, such as database, schema, table, column, file assets, or storage container, and create them as assets with relations to the AI Model Deployment asset. For more information, go to AI model traceability: automatic linking of AI Governance assets.
    Systems

    In System, select the System asset in which you want to link the Vertex AI assets.
    Custom Label Mappings

    Optionally, in Custom Label Mappings, define the Vertex AI resource labels you want to integrate. You do this by adding a mapping between a Vertex AI label and a Collibra attribute. You can add multiple label mappings. Label mappings apply across various asset types that the integration creates.

    After you synchronize the capability, the values of the specified Vertex AI resource labels are mapped to the corresponding attributes.

    To add a custom label mapping:

    1. Click Add Custom Label Mappings.
    2. In Label, select the label from the list of available Vertex AI labels.
    3. In Attribute, select the attribute in which you want to see the value. Make sure the attribute is assigned to the asset type you want to enrich.
    Custom AI Metrics Mappings

    Optionally, in Custom AI Metrics Mappings, define the Vertex AI model-evaluation metrics that you want to integrate. You do this by adding a mapping between a metric and a Collibra attribute. You can add multiple metric mappings. The available metrics are a fixed set of model-evaluation metrics, such as accuracy and precision, and apply to model versions only.

    After you synchronize the capability, the values of the specified Vertex AI metrics are mapped to the corresponding attributes.

    Important 

    If you use this feature, add any custom attributes/characteristics, as needed, to the asset type assignment.

    To add a custom AI metric mapping:

    1. Click Add Custom AI Metrics Mappings.
    2. In Metric, select the metric from the list of available Vertex AI metrics.
    3. In Attribute, select the attribute in which you want to see the value.
      Make sure to select an attribute that is included in the Vertex AI Model asset type assignment.
  7. Click Save.
  8. Click Synchronize.
    A notification indicates the synchronization has started.
  1. On the main toolbar, click Products icon → Catalog.
    The Catalog homepage opens.
  2. Click Integrations.
    The Integrations page opens.
  3. Click the Integration configuration tab.
  4. In the Connection name column, locate the GCP connection that you used when you added the Google Vertex AI capability and click the link in the Capabilities column.
    The Synchronization page opens.
  5. In the Synchronization configuration section, click Add configuration.
  6. Complete the fields as needed.
    7. Field Action
    Domain

    Select the domain asset in which you want to add the Vertex AI assets.

    Important Ensure that you select a domain of the type Technology Asset Domain.
    Project IDs

    To add a Project ID where Vertex AI is enabled, click Add Project Id. You can add multiple Project IDs. The capability will search in the specified projects.
    Vertex AI Locations
    Optionally, when a new location is added in Vertex AI and not yet supported by the integration, you can add the location in Vertex AI Locations. When you add locations in this field, the integration ingests Vertex AI assets only from the specified locations.
    Do you want to ingest input and output assets?

    Optionally, select Do you want to ingest input and output assets? to ingest datasets, such as database, schema, table, column, file assets, or storage container, and create them as assets with relations to the AI Model Deployment asset. For more information, go to AI model traceability: automatic linking of AI Governance assets.
    Systems

    In System, select the System asset in which you want to link the Vertex AI assets.
    Custom Label Mappings

    Optionally, in Custom Label Mappings, define the Vertex AI resource labels you want to integrate. You do this by adding a mapping between a Vertex AI label and a Collibra attribute. You can add multiple label mappings. Label mappings apply across various asset types that the integration creates.

    After you synchronize the capability, the values of the specified Vertex AI resource labels are mapped to the corresponding attributes.

    To add a custom label mapping:

    1. Click Add Custom Label Mappings.
    2. In Label, select the label from the list of available Vertex AI labels.
    3. In Attribute, select the attribute in which you want to see the value. Make sure the attribute is assigned to the asset type you want to enrich.
    Custom AI Metrics Mappings

    Optionally, in Custom AI Metrics Mappings, define the Vertex AI model-evaluation metrics that you want to integrate. You do this by adding a mapping between a metric and a Collibra attribute. You can add multiple metric mappings. The available metrics are a fixed set of model-evaluation metrics, such as accuracy and precision, and apply to model versions only.

    After you synchronize the capability, the values of the specified Vertex AI metrics are mapped to the corresponding attributes.

    Important 

    If you use this feature, add any custom attributes/characteristics, as needed, to the asset type assignment.

    To add a custom AI metric mapping:

    1. Click Add Custom AI Metrics Mappings.
    2. In Metric, select the metric from the list of available Vertex AI metrics.
    3. In Attribute, select the attribute in which you want to see the value.
      Make sure to select an attribute that is included in the Vertex AI Model asset type assignment.
  7. Click Save.
  8. In the Synchronization Schedule section, click Add schedule.
  9. Enter the required information and click Save:
    FieldDescription
    RepeatThe interval when you want to synchronize automatically. The possible values are: Daily, Weekly, Monthly, and Cron expression.
    Cron

    The Quartz Cron expression that determines when the synchronization takes place.

    This field is only visible if you select Cron expression in the Repeat field.

    Every

    The day on which you want to synchronize, for example, Sunday.

    This field is only visible if you select Weekly in the Repeat field.

    Every first

    The day of the month on which you want to synchronize, for example, Tuesday.

    This field is only visible if you select Monthly in the Repeat field.

    At

    The time at which you want to synchronize automatically, for example, 14:00.

    • You can only schedule on the hour. For example, you can add a synchronization schedule at 8:00, but not at 8:45.
    • This field is only visible if you select Daily, Weekly, or Monthly in the Repeat field.
    Time zoneThe time zone for the schedule.

What's next

The synchronization job synchronizes the Google Vertex AI data.
After the synchronization:

Helpful resources

Check out the A human-centered intro to AI integrations course in Collibra University.