Databricks-GenAI-Assoc Assembling and Deploying Apps Practice Question
Exhibit
Error: Model serving endpoint update failed. Reason: 'INSUFFICIENT_PERMISSIONS' - The service principal does not have access to the model in the Unity Catalog.
Refer to the exhibit. An engineer is automating the deployment of a model to an endpoint using the Databricks CLI. Based on the error log provided, what is the most appropriate action to resolve this deployment failure?
⚠ Common exam trap
Candidates often try to resolve permission errors by checking workspace-level settings rather than focusing on the specific hierarchical grants (catalog, schema, model) required by Unity Catalog.
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
✓
Grant the service principal 'USE' and 'READ' permissions on the catalog, schema, and model.
Deployment failures due to 'INSUFFICIENT_PERMISSIONS' often stem from the service principal used by the CI/CD pipeline lacking the necessary grants on the registered model in Unity Catalog. The engineer must ensure the principal has 'USE CATALOG', 'USE SCHEMA', and 'READ' permissions on the model version. Addressing this at the Unity Catalog level is the standard procedure for cross-service authorization in Databricks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Upgrade the model serving endpoint to a higher capacity cluster size.
Why it's wrong here
Increasing cluster capacity only affects compute resource limits, not security or authorization policies. The error clearly indicates an authorization failure, meaning that compute resources are irrelevant until the identity used for deployment is granted the required permissions to access the specified model registry object.
- ✓
Grant the service principal 'USE' and 'READ' permissions on the catalog, schema, and model.
Why this is correct
Unity Catalog requires explicit grants for service principals to access assets. The error indicates that the service principal lacks the necessary permissions to read the model metadata or download the model artifacts. Granting these specific privileges allows the serving infrastructure to access the model during deployment.
- ✗
Delete the model serving endpoint and recreate it using a personal access token.
Why it's wrong here
Using a personal access token is discouraged for automated CI/CD deployments as tokens are linked to individual users and expire. Recreating the endpoint does not address the underlying permission issue, as the service principal will continue to lack access to the model regardless of how the endpoint is created.
- ✗
Restart the Databricks workspace to force an update of the internal permission cache.
Why it's wrong here
Permission errors in Unity Catalog are evaluated in real-time by the access control service. Restarting the workspace does not clear or refresh permissions. The issue is a missing grant, which requires a deliberate administrative action to update the security policy associated with the specific service principal account.
Visual reference
About these practice questions
This Databricks-GenAI-Assoc question is part of Courseiva's 330-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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
This Databricks-GenAI-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-GenAI-Assoc exam.