AI Service Graph Connector for Databricks
Summarize
Summary of AI Service Graph Connector for Databricks
The AI Service Graph Connector for Databricks enables ServiceNow customers to discover, import, and govern AI assets from their Databricks environment into the ServiceNow AI Control Tower. It integrates directly with Databricks accounts to catalog AI systems, agents, models, and prompts, and automatically collects usage data. This data populates the AI Control Tower’s value dashboard, providing comprehensive visibility and governance over AI operations.
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Key Features
- AI Asset Discovery and Import: Automatically imports AI assets such as models, agents, and prompts from Databricks into the ServiceNow Configuration Management Database (CMDB).
- Usage Data Collection: Collects and integrates usage metrics to track AI system utilization and performance within ServiceNow.
- Comprehensive Data Mapping: Maps Databricks data fields to corresponding ServiceNow tables for AI systems, models, tools, and usage, ensuring accurate data representation and management.
- Multi-Cloud Support: Compatible with Databricks workspaces on Azure, AWS, and GCP.
- Role-Based Access Control: Requires specific ServiceNow roles (discoveryadmin and sgcadmin) to manage the connector and data sources securely.
Practical Setup Requirements
- ServiceNow Setup: Requires updating data source permissions to enable creation, update, and deletion, plus clearing cache via background scripts to refresh data sources and tables.
- Databricks Setup: Requires an active workspace with administrative access and OAuth credentials configured with sufficient scopes for metadata reading.
- Permissions: The service principal or user must have admin or workspace access, with specific permissions for clusters, Unity Catalog, and SQL Warehouses to enable complete data synchronization.
Data Mapping Essentials
The connector maps several key fields between Databricks and ServiceNow to maintain data integrity:
- Agents: Include model IDs, agent IDs, versions, status, quantity, vendor, and company information mapped to AI system product model tables.
- AI Models: Includes model category, external references, state, provider, vendor, source system, and quantity mapped to AI model digital asset tables.
- AI Tools: Maps tool name, type, description, source information, and vendor details to the AI Tool table.
- Usage Data: Tracks user, timestamp, session ID, invocation count, AI system, and type to correlate AI system and model utilization.
Supported Versions and Roles
- Supported on ServiceNow Australia and Zurich releases.
- Requires users to have the snaidisc.discoveryadmin and sncmdbintutil.sgcadmin roles for management and configuration.
Benefits for ServiceNow Customers
By leveraging this connector, customers gain automated, up-to-date visibility into their AI assets hosted on Databricks, enabling better governance, compliance, and operational insights through ServiceNow AI Control Tower dashboards. The integration streamlines AI asset management and usage tracking, facilitating informed decision-making and enhanced AI lifecycle oversight.
The AI Service Graph Connector for Databricks enables you to discover and import AI assets from your Databricks environment into ServiceNow AI Control Tower.
The connector integrates with your Databricks 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 Databricks application.
Supported ServiceNow versions
This connector is supported on the following ServiceNow releases:
| Release | Status |
|---|---|
| Australia | Supported |
| Zurich | 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 checkboxes.
- Select Update.
- Switch to the connector application scope.
Clear the cached data for the Data Source and Tables.
- Navigate to System Definition > Background Scripts
- Paste the following script into 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 may take several minutes to complete.
- After completion, switch to the connector application scope.
Databricks Prerequisites
The Al Service Graph Connector for Databricks automatically imports data from your Databricks into the ServiceNow CMDB. This playbook will guide you through configuring the connection and credentials.
Before proceeding, verify you have:
Databricks Workspace: An active workspace (Azure, AWS, or GCP) with administrative access to the resources you intend to sync.
Authentication Method: A valid OAuth credentials with sufficient scopes to read workspace metadata.
These permissions are managed via the Databricks Admin console or Account console under the User Management or Service Principal sections:
Service Principal / User Access: The identity used for the connection must have the Admin or Workspace Access entitlement.
Compute/Clusters: Can View permissions for all clusters to be imported.
Unity Catalog: USE CATALOG and USE SCHEMA permissions if importing data lineage or metadata from the Unity Catalog.
SQL Warehouses: Can Use permissions if tracking SQL endpoint utilization.
For information on Databricks resources to generate credentials and configure workspace access, see Databricks- Configure OAuth for Service Principals and https://docs.databricks.com/aws/en/admin/users-groups
Data Mapping
Agents: alm_ai_system_digital_asset -> Model table (cmdb_ai_system_component_product_model)| Required Fields | ServiceNow (Target) | Databricks (Staging) |
| Model ID | Model | ai_system_product_model |
| Agent ID | Product instance identifier | agent_id |
| Version | External record reference | u_id |
| Status | State (install_status) | install_status |
| Quantity | Quantity | quantity |
| Vendor | Vendor | vendor_ref |
| Company | Company | cleansed_manufacturer_ref |
| AI Models | ai_models | |
| Source System | Source System | vendor_name |
| Asset Type | Model Category | asset_type |
| Required Fields | ServiceNow (Target) | Databricks (Model Staging) |
| Model Category | asset_type | |
| External record reference | u_id | |
| Model Id | Model | ai_product_model |
| State | install_status | |
| Provider | Company | cleanse_manufacturer_ref |
| Vendor | Vendor | vendor_ref |
| Source System | vendor_name | |
| Quantity | quantity |
| Required Fields | ServiceNow | Databricks |
| Name | Name | Tool Name |
| Type | Tool Type | |
| Description | Description | Tool Description |
| Source Information | Source Information | Vendor Name |
| Required Fields | ServiceNow (Target) | Databricks (Staging) |
| User | User | User ID |
| Time | Time | Timestamp |
| Parent ID | Session ID | Session ID |
| Total Invocations | Count | Invocation count |
| AI system | AI system | Agent ID |
| Type | Type |