AI Service Graph Connector for Databricks

  • Release version: Australia
  • Updated May 3, 2026
  • 2 minutes to read
    • Summarize
    Summarized using AI
    This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.

    Summary of AI Service Graph Connector for Databricks

    The AI Service Graph Connector for Databricks enables ServiceNow customers to discover and import AI assets from their Databricks environment directly into the ServiceNow AI Control Tower. This integration catalogs AI systems, agents, models, and prompts from Databricks, automatically collecting usage data and populating it into the AI Control Tower value dashboard. This provides comprehensive visibility and governance over AI operations within the ServiceNow platform.

    Show full answer Show less

    Key Features

    • Seamless Integration: Connects ServiceNow with Databricks workspaces (Azure, AWS, or GCP) for importing AI assets.
    • Automated Data Import: Imports AI systems, agents, models, and prompts along with usage data into the ServiceNow CMDB.
    • Governance and Visibility: Usage data is displayed in AI Control Tower, enabling monitoring and management of AI operations.
    • Support for Multiple ServiceNow Versions: Compatible with Australia and Zurich releases.
    • Role-Based Access: Requires roles such as snaidisc.discoveryadmin or sncmdbintutil.sgcadmin for setup and operation.
    • Data Mapping: Detailed mapping of Databricks AI assets to ServiceNow tables, including AI models, agents, tools, and usage metrics.

    Setup and Configuration

    ServiceNow customers must perform specific prerequisites and configurations to enable the connector:

    • ServiceNow Prerequisites: Grant write permissions to the Data Source table, update application access settings, and clear cache using provided scripts to ensure proper data handling.
    • Databricks Prerequisites: An active Databricks workspace with administrative access and OAuth credentials with necessary scopes are required.
    • Permissions: The connecting identity must have Admin or Workspace Access entitlement, and specific permissions on clusters, Unity Catalog, and SQL warehouses depending on the data imported.

    Data Mapping and Required Fields

    The connector maps key AI asset data from Databricks staging tables to ServiceNow target tables, ensuring accurate synchronization of:

    • AI Models: Fields such as model ID, version, status, vendor, and quantity are synchronized between Databricks and ServiceNow.
    • AI Agents: Agent IDs and related metadata are mapped to the ServiceNow model tables.
    • AI Tools: Essential details like tool name, type, description, and vendor information are imported into the AI Tool table.
    • Usage Data: Tracks user activity, timestamps, invocation counts, and session details to monitor AI system utilization.

    Benefits for ServiceNow Customers

    By implementing the AI Service Graph Connector for Databricks, customers gain a unified view of their AI landscape within ServiceNow, enabling:

    • Improved governance and compliance through centralized AI asset management.
    • Enhanced operational insights via automatic usage tracking and reporting.
    • Streamlined AI asset discovery and lifecycle management integrated with existing ServiceNow processes.

    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.

    Note:
    Updating data source access and clear cache is a prerequisite that needs to be completed only once, when setting up a new instance for the first time.
    Update Data Source Access

    The connector requires write permissions to the Data Source table to create data sources.

    To enable data source creation:
    1. Select Global from the application picker.
    2. Navigate to Application Access.
    3. Select the Can create, Can update, and Can delete checkboxes.
    4. Select Update.
    5. Switch to the connector application scope.
    Clear cache

    Clear the cached data for the Data Source and Tables.

    To clear the cache:
    1. Navigate to System Definition > Background Scripts
    2. 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');
    3. Select Run Script.
      Note:
      The script may take several minutes to complete.
    4. 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.

    Required Permissions

    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.

    Resource-Specific Permissions

    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
    Models: AI Model Digital Asset (alm_ai_model_digital_asset):
    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
    Tools: AI Tool (sn_ent_ai_tool)
    Required Fields ServiceNow Databricks
    Name Name Tool Name
     Type Tool Type
    Description  Description Tool Description
    Source Information  Source Information Vendor Name
    AI Agents Usage: sn_ai_disc_ai_usage -> AI system/Model table (alm_ai_system_digital_asset)
    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