Databricks-ML-Assoc Databricks Machine Learning Practice Question
A data scientist has registered a model in the Databricks Model Registry. They want to transition the model from 'Staging' to 'Production' but need to ensure that only specific users can perform this transition. Which Databricks feature should they use to enforce this access control?
⚠ Common exam trap
Many candidates confuse cluster or data access controls with model registry permissions, assuming that broader workspace permissions automatically apply to model stages.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Model Registry permissions with stage-level access control.
The Model Registry provides granular permissions at the model level, including the ability to restrict stage transitions. By configuring stage-level access control, administrators can ensure that only authorized users can move a model to Production. Other features like cluster ACLs, secret scopes, and volume permissions do not govern model registry operations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cluster access control lists (ACLs).
Why it's wrong here
Cluster ACLs control who can attach to or manage clusters, not model registry operations. They do not govern permissions on models or their stages. Using cluster ACLs would not prevent unauthorized users from transitioning a model, as model registry permissions are separate and must be configured independently.
- ✗
Unity Catalog volume permissions.
Why it's wrong here
Unity Catalog volumes are used for storing and accessing files, not for managing model registry permissions. Volume permissions control data access, not model stage transitions. Even if models are stored in Unity Catalog, stage transition permissions are handled by the Model Registry's own permission model, not volume ACLs.
- ✗
Workspace-level secret scopes.
Why it's wrong here
Secret scopes are used to manage secrets for authentication, not to control access to model registry stages. They do not provide any mechanism to restrict who can transition models. While secrets are important for secure access to external systems, they are unrelated to model stage permissions.
- ✓
Model Registry permissions with stage-level access control.
Why this is correct
Databricks Model Registry supports stage-level permissions, allowing you to grant users or groups the ability to transition models to specific stages. By setting permissions on the model, you can restrict who can move a model to Production. This is the correct feature to enforce access control for model stage transitions.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
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