> For the complete documentation index, see [llms.txt](https://docs.verge.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.verge.io/run-the-platform/system-administration/service-containers.md). # Service Containers Overview of VergeOS service containers, lightweight environments used to run internal system services such as AI modules, providing modularity, isolation, and efficient resource usage. The Service Containers section provides visibility into the lightweight environments used to run specific internal VergeOS services, such as AI modules and other system-level components. These containers operate independently to ensure modularity, isolation, and efficient resource usage within the virtual data center. While this section is not typically relevant for day-to-day administration, it is available under Infrastructure > Service Containers for informational and debugging purposes. Users may occasionally reference this area to verify container status or assist with support diagnostics, but direct interaction is rarely required. This section exists primarily to support internal operations and future extensibility. No configuration or management actions are expected from administrators at this time *** **Version Compatibility**: This functionality is available in VergeOS 26.0 and later. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.verge.io/run-the-platform/system-administration/service-containers.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.