---
title: "How to Manage your LLM Teams using MLflow's Role-Based Access Control"
url: https://daily.dev/posts/how-to-manage-your-llm-teams-using-mlflow-s-role-based-access-control-cfsel5htk
source_url: https://mlflow.org/blog/rbac-feature
type: article
source: "mlflow"
published: 2026-06-18T07:24:25.890Z
updated: 2026-06-18T07:24:48.718Z
tags: ["machine-learning", "python", "llm"]
reading_time: 8
upvotes: 1
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# How to Manage your LLM Teams using MLflow's Role-Based Access Control

**[mlflow](https://daily.dev/sources/MLflow)** · 8 min read · 1 upvotes · 0 comments

## Summary

MLflow 3.13 introduces Role-Based Access Control (RBAC) to address permission management challenges in LLM teams. Instead of per-resource explicit permission calls, teams can now define reusable roles with resource patterns (e.g., EDIT on all prompts), assign users to roles, and isolate teams using workspaces. Four permission levels exist: READ, USE, EDIT, and MANAGE. The system supports three user tiers: Platform Admin, Workspace Manager, and Regular User. Legacy per-resource permissions from pre-3.13 are removed, with DB migration handling backfill. Direct per-resource grants remain available for one-off scenarios. The post includes a full AuthServiceClient API reference and setup walkthrough.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://mlflow.org/blog/rbac-feature>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#llm](https://daily.dev/tags/llm)

[View this post on daily.dev](https://daily.dev/posts/how-to-manage-your-llm-teams-using-mlflow-s-role-based-access-control-cfsel5htk)