Multi-instance Setup

  • Release version: Australia
  • Updated March 12, 2026
  • 2 minutes to read
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    Summary of Multi-instance Setup

    The Multi-instance Setup feature in AI Control Tower allows a production (prod) instance, referred to as the manager, to control, manage, and communicate with multiple sub-production (sub-prod) instances, known as managed instances. This setup facilitates synchronization across instances, streamlining AI asset review and management processes.

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    Key Features

    • AI Asset Synchronization: Utilizes the multi-instance framework to synchronize AI assets such as systems, models, prompts, datasets, and, starting from the September 2025 release, AI agents from sub-prod instances to the prod instance. This accelerates the review process by centralizing asset information.
    • Version Compatibility: From May 2026 onward, both prod and sub-prod instances must run at least AI Control Tower core version 6.2.4 to ensure proper multi-instance framework functionality. When upgrading sub-prod instances to version 6.2.4, it is recommended to upgrade the prod instance accordingly.
    • AI Inventory Information Synchronization: The prod instance reflects the true production state of AI assets. Asset states such as models or datasets are only marked as deployed when activated in production, regardless of their active status in sub-prod environments, which are considered under development.
    • Data Sharing Preference: Customers can enable a data sharing preference where the prod instance’s data sharing settings automatically apply to all sub-prod instances. This preference is off by default.
    • Data Overflow Processing and Bursting Preference: Similar to data sharing, enabling this preference applies the prod instance’s overflow processing and bursting settings to all sub-prod instances. This setting is also off by default.
    • Read-Only Preferences in Sub-prod Instances: When multi-instance management is configured and enabled, preferences related to data sharing, overflow processing, and bursting in sub-prod instances become read-only, ensuring consistency with the prod instance settings.

    Practical Implications for ServiceNow Customers

    Implementing the Multi-instance Setup enables ServiceNow customers to centrally manage AI assets across multiple environments, ensuring synchronization and consistency while maintaining clear lifecycle states for assets. This setup supports faster and more efficient AI asset reviews and deployment processes by consolidating asset information in the production instance.

    Customers should ensure version alignment across instances for smooth operation and can manage data sharing and processing preferences centrally, reducing administrative overhead and potential configuration discrepancies across environments.

    The multi-instance setup enables a prod (manager) instance to control, manage, and communicate with multiple sub-prod (managed) instances for AI Control Tower.

    AI asset Synchronization

    Multi-instance setup uses the multi-instance framework, which helps the user to synchronize assets from sub-prod instances to prod instances for a faster review process.

    Multi-instance setup synchronizes rules for the sub-prod instances from the prod instance.

    Note:
    Starting with the May 2026 release, confirm that both the prod and sub-prod instances are running the same AI Control Tower core version (6.2.4), which is the minimum supported version.

    If there’s any upgrade to version 6.2.4 in a sub-prod, then it’s advisable to upgrade the prod instance to 6.2.4 to confirm Multi-instance framework functions correctly.

    AI inventory information
    You can include the sub-prod instances that you want to synchronize with the prod instance. This synchronizes AI inventory information between the instances.

    When configured, the scheduled job starts synchronizing AI systems, AI models, prompts, and datasets. From the September (2025) release, the job has been enhanced to include synchronizing AI agents as well.

    Note:
    State of the assets while configuring Multi-instance management.

    The AI inventory in production reflects the true state of your assets like models, datasets, or skills from a production standpoint. Even if a model or dataset is active in a sub prod (lower) environment, it's still considered as under development from a prod perspective, since it's being tested and not yet live.

    For this reason, you don’t synchronize asset states across environments. An asset’s state changes to deployed only when the asset and its related records are activated in the production system.

    In summary, the state represents the overall lifecycle of the asset, not its local status in a specific environment.

    Data sharing preference
    You have the option to enable the data sharing preference, when it is enabled the preferences of the data sharing from the production will be applied to all sub-prod instances. By default, the data sharing preference is turned off.
    Data overflow processing and bursting preference
    You have the option to enable the data overflow processing and bursting preferences, when it is enabled the preferences of the data overflow and bursting from the production will be applied to all sub-prod instances. By default, data overflow processing and bursting is turned off.
    Note:
    All the preferences mentioned earlier for a sub-prod instance are available in read-only mode, when Multi-instance is configured and enabled.

    For information about configuring Multi-instance management for AI Control Tower, see Configure Multi-instance management for AI Control Tower

    For information about Data section, see Data sharing, processing, and security in AI Control Tower