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 in AI Control Tower enables a production (prod) manager instance to control, manage, and communicate with multiple sub-production (sub-prod) managed instances. This setup uses the multi-instance framework to synchronize AI assets, rules, and inventory information across instances, streamlining review and deployment processes.

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    Key Features

    • AI Asset Synchronization: Synchronizes assets such as AI systems, models, prompts, datasets, and from September 2025 onwards, AI agents, from sub-prod instances to the prod instance to facilitate faster reviews.
    • Rule Synchronization: Synchronizes operational rules from the prod instance to sub-prod instances to maintain consistency.
    • Version Compatibility: Both prod and sub-prod instances must run the same AI Control Tower core version (minimum 6.2.4 as of May 2026) to ensure proper multi-instance framework functioning.
    • AI Inventory Information: The prod instance reflects the true production state of assets. Asset states are not synchronized directly; assets in sub-prod remain under development until activated in prod.
    • Data Sharing Preference: Optionally apply prod instance data sharing preferences to all sub-prod instances. This setting is off by default.
    • Data Overflow Processing and Bursting Preference: Optionally apply prod instance preferences for data overflow processing and bursting to sub-prod instances. This is also off by default.
    • Read-only Preferences on Sub-prod: When multi-instance management is enabled, preferences on sub-prod instances are read-only to maintain centralized control.

    Practical Benefits for ServiceNow Customers

    This setup allows ServiceNow customers using AI Control Tower to centrally manage multiple environments, ensuring consistency and control over AI asset deployment and lifecycle. Customers can expect synchronized AI assets and rules, streamlined review processes, and consistent data handling across their AI environments.

    By enforcing version compatibility and centralized preference management, it reduces configuration errors and operational discrepancies between production and sub-production instances.

    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, Data overflow processing, and Security & privacy in AI Control Tower