Synchronize Google Vertex AI

Synchronizing Google 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 you can automate it by adding a synchronization schedule.

Before you begin

You have created a GCP connection.
You have added the Google Vertex AI capability to the GCP connection.

Required permissions

You have a resource role with the Configure external system resource permission, for example, Owner.
You have a global role with the Catalog global permission, for example, Catalog Author.
You have a global role with the View Edge connections and capabilities global permission, for example, Edge integration engineer. For example, Edge integration engineer.

Steps

Manually synchronize Google Vertex AI
Add a synchronization schedule

On the main toolbar, click → Catalog.
The Data Catalog Home opens.
On the main toolbar, click .
The Create dialog box appears.
In the Register with Edge section of the Create dialog box, click Integration Configuration.
The Integration Configuration page opens.
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.
In the Synchronization Configuration section, click Add Configuration.
In Domain, select the Domain asset in which you want to add the Google Vertex AI assets.
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 these projects.
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.
Optionally, in Custom AI Label Mappings, define which custom Google Vertex AI Model labels you want to integrate. You do this by adding the mapping between the custom model label and the Collibra attribute. The attribute list contains all attribute types that are assigned to the Vertex AI Model asset type.
After you synchronize the capability, the specified custom Vertex AI Model labels are mapped to the corresponding attributes.
Show me how
Important
If you use this feature, make sure to add any custom attributes/characteristics, as needed, to the asset type assignment.
1. Click Add Custom AI Label Mapping.
2. In Label, type the name of the custom label manually.
  Use the exact label name as in the Google Vertex AI platform.
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.
Click Save.
Click Synchronize.
A notification indicates the synchronization has started.

On the main toolbar, click → Catalog.
The Data Catalog Home opens.
On the main toolbar, click .
The Create dialog box appears.
In the Register with Edge section of the Create dialog box, click Integration Configuration.
The Integration Configuration page opens.
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.
In the Synchronization Configuration section, click Add Configuration.
In Domain, select the Domain asset in which you want to add the Google Vertex AI assets.
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 these projects.
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.
Optionally, in Custom AI Label Mappings, define which custom Google Vertex AI Model labels you want to integrate. You do this by adding the mapping between the custom model label and the Collibra attribute. The attribute list contains all attribute types that are assigned to the Vertex AI Model asset type.
After you synchronize the capability, the specified custom Vertex AI Model labels are mapped to the corresponding attributes.
Show me how
Important
If you use this feature, make sure to add any custom attributes/characteristics, as needed, to the asset type assignment.
1. Click Add Custom AI Label Mapping.
2. In Label, type the name of the custom label manually.
  Use the exact label name as in the Google Vertex AI platform.
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.
Click Save.
In the Synchronization Schedule section, click Add schedule.

Enter the required information and click Save:

Field	Description
Repeat	The 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 zone	The time zone for the schedule.

What's next?

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

You can view a summary of the results from the Activities list.
The resulting assets get a relation to the Domain that you selected.
For information on the integrated data, go to Synchronized Google Vertex AI data.