AI Service Graph Connector for GCP Vertex AI
Summarize
Summary of AI Service Graph Connector for GCP Vertex AI
The AI Service Graph Connector for GCP Vertex AI enables ServiceNow customers to seamlessly discover and import AI assets from their Google Cloud Platform (GCP) environment into the ServiceNow AI Control Tower. This integration catalogs AI systems, agents, models, tools, and prompts, while automatically collecting usage data to populate the AI Control Tower value dashboard. This provides comprehensive visibility and governance over AI operations within ServiceNow.
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Supported Versions and Roles
- The connector is supported on ServiceNow releases: Australia, Zurich, and Yokohama.
- Required user roles include snaidisc.discoveryadmin and sncmdbintutil.sgcadmin to configure and manage the connector.
Setup and Prerequisites
Initial configuration requires several key setup steps:
- ServiceNow Prerequisites: Enable write permissions on the Data Source table by selecting appropriate access rights (create, update, delete) and clear cached data for the Data Source and Tables using a background script to ensure proper data refresh.
- GCP Vertex AI Prerequisites: Create a dedicated GCP service account with least-privilege access and assign necessary Vertex AI roles at project or organization level. Enable required APIs in GCP. A JSON key file is needed for authentication; if available, JKS file creation can be skipped.
- Cloud Trace Service: Must be enabled in GCP to capture detailed AI data such as prompts, tools, models, and sub-agents. Without it, only top-level agent names are discoverable. Agents must be redeployed after enabling Cloud Trace for full discovery.
- Register the connector within the ServiceNow instance following detailed setup instructions to complete integration.
Data Mapping and Integration
The connector organizes discovered AI data into staging and target tables within ServiceNow’s CMDB and related classes to maintain structured asset management. Key data sources and their mapped tables include:
- Execution Data: Stored in AI usage tables.
- AI Systems: Mapped to CMDB AI system components, product models, and digital asset tables.
- Models, Tools, and Prompts: Stored in respective AI model, tool, and prompt product model and digital asset tables.
- System Subcomponents: Managed via many-to-many relationship tables for AI system subcomponents.
What This Enables for ServiceNow Customers
By implementing this connector, customers gain automated and comprehensive discovery of their GCP Vertex AI assets directly within ServiceNow. This enhances AI governance by providing visibility into AI models, agents, and usage, supporting better management, compliance, and optimization of AI resources across their enterprise IT environment.
The AI Service Graph Connector for GCP Vertex AI enables you to discover and import AI assets from your Google Cloud environment into ServiceNow AI Control Tower.
The connector integrates with your Google Cloud Platform account to catalog AI systems, agents, models, and prompts. Usage data is automatically collected and populated into the AI Control Tower value dashboard, providing comprehensive visibility and governance of your AI operations.
Download apps from the Store
Visit the ServiceNow store website to download the AI Service Graph Connector for GCP Vertex AI application.
Supported ServiceNow versions
This connector is supported on the following ServiceNow releases:
| Release | Status |
|---|---|
| Australia | Supported |
| Zurich | Supported |
| Yokohama | Supported |
User Roles
You must have one of the following roles assigned.
| Required Roles |
|---|
| sn_ai_disc.discovery_admin |
| sn_cmdb_int_util.sgc_admin |
ServiceNow Prerequisites
Complete the following setup steps once when configuring the connector for the first time.
The connector requires write permissions to the Data Source table to create data sources.
- Select Global from the application picker.
- Navigate to Application Access.
- Select the Can create, Can update, and Can delete check boxes.
- Select Update.
- Switch to the connector application scope.
Clear the cached data for the Data Source and Tables.
- Navigate to .
- Enter the following script in the Run Script text box:
GlideTableManager.invalidateTable('sys_data_source'); GlideCacheManager.flushTable('sys_data_source'); GlideTableManager.invalidateTable('sys_db_object'); GlideCacheManager.flushTable('sys_db_object'); - Select Run Script.Note:The script might take several minutes to complete. After completion, switch to the connector application scope.
- After completion, switch to the connector application scope.
GCP Vertex AI Prerequisites
Follow the setup instructions to create a service account, assign roles, bind roles to the service account, and enable APIs. To create a JKS file, a JSON file is required. If a JSON file is available, skip the JKS file creation step. After completing setup, register the connector in your ServiceNow instance. For setup instructions and API details, see the Service Graph connector for GCP Vertex AI- Setup Instructions [KB2731256] KB article.
Cloud trace service is required to capture details like prompts, tools, models, and sub-agents. These are discovered only after they have been executed at least once.
If Cloud trace service is not enabled. You must enable cloud trace service and redeploy the agents to properly discover AI agents, tools, models, prompts and sub-agents.
Service Account and Role Configuration
Create a dedicated GCP service account with least-privilege access. The connector requires permissions to query Vertex AI agents and observability data.
The service account requires the following:
- A service account created in your GCP project with the appropriate Vertex AI roles.
- Roles bound to the service account at the project or organization level.
- Required APIs are enabled in your GCP project.
Data Mapping
The following table lists the data sources, the staging tables, and the target tables CMDB CI classes and non-CMDB classes where data is stored for a GCP Vertex AI project.
| Data source | Staging table | Target tables |
|---|---|---|
| SG-GCPVertexAI-Execution | sn_ai_disc_gcp_sgc_sg_gcp_execution | sn_ai_disc_ai_usage |
| SG-GCPVertexAI-System | sn_ai_disc_gcp_sgc_sg_gcp_ai_system | cmdb_ai_system_component_product_model alm_ai_system_digital_asset cmdb_ci_function_ai cmdb_rel_asset_ci |
| SG-GCPVertexAI-Model | sn_ai_disc_gcp_sgc_sg_gcp_ai_model | cmdb_ai_model_product_model alm_ai_model_digital_asset |
| SG-GCPVertexAI-Tool | sn_ai_disc_gcp_sgc_sg_gcp_ai_tool | sn_ent_ai_tool |
| SG-GCPVertexAI-Prompt | sn_ai_disc_gcp_sgc_sg_gcp_ai_prompt | cmdb_ai_prompt_product_model alm_ai_prompt_digital_asset |
| SG-GCPVertexAI-System Subcomponent M2M | sn_ai_disc_gcp_sgc_sg_gcp_ai_system_subcomponent_m2m | sn_ent_ai_system_subcomponent_m2m |