Retrieval-Augmented Generation (RAG) has emerged as a trusted solution for large organizations to enhance their Language Model-powered applications, especially those with diverse users. As these applications grow, implementing a multi-tenancy framework becomes essential. Multi-tenancy provides secure, isolated access to data for different user groups, ensuring user trust, meeting regulatory standards, and improving operational efficiency. Milvus is an open-source vector database built to handle high-dimensional vector data and is an indispensable infrastructure component of RAG, storing and retrieving contextual information for LLMs from external sources. Milvus offers flexible multi-tenancy strategies for various needs, including database-level, collection-level, and partition-level multi-tenancy.