> For the complete documentation index, see [llms.txt](https://docs.fabricplan.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.fabricplan.com/documentation/readme/known-limitations-in-plan-preview.md). # Known Limitations in Plan (Preview) Review the following known issues and limitations before you begin working with plan (preview). ### B2B user support Plan doesn't support Microsoft Entra B2B IDs. ### Private link support Plan items aren’t supported in workspaces or tenants that use private links. ### Semantic model * You must have *Admin* or *Build* permissions on the semantic model. * Semantic models in Direct Lake mode require additional configuration. * Semantic model connections support only OAuth-based and service principal–based authentication. * Semantic models published in *My workspace* aren't supported. ### Capacities supported Power BI Pro and Power BI Premium Per User (PPU) aren't supported for Plan scenarios that use XMLA endpoints and embed tokens. Similarly, lower-capacity SKUs that do not support XMLA endpoints are also unsupported. ### Workspace permissions * Users with the *Contributor* role can't create or share cloud connections. * Users with lower-level workspace roles, such as *Contributor*, can't create Plan artifacts that require embed token generation. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.fabricplan.com/documentation/readme/known-limitations-in-plan-preview.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.