PMLE Collaborating to manage data and models Practice Question
A team wants to share a trained model with other teams within the organization. They need to provide access to the model artifact in Vertex AI Model Registry and ensure that only authorized teams can deploy the model. What should they do?
⚠ Common exam trap
Google Cloud often tests the misconception that sharing the storage bucket or encryption key is sufficient for controlled deployment, when in fact IAM roles on the model resource are required to enforce deployment authorization.
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
✓
Use IAM to grant the 'aiplatform.models.deploy' role to the other teams on the model resource
Vertex AI Model Registry uses IAM to control access to model resources. By granting the 'aiplatform.models.deploy' role on the specific model resource, you ensure that only authorized teams can deploy the model, while other operations (like viewing or updating) remain restricted. This follows the principle of least privilege and avoids exposing the model artifact broadly.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Grant the other teams access to the Cloud Storage bucket where the model is stored
Why it's wrong here
This bypasses Vertex AI's access control and may expose other artifacts.
- ✗
Set the model to public in Vertex AI Model Registry
Why it's wrong here
Public access is insecure and unnecessary.
- ✗
Use Cloud Key Management Service to encrypt the model and share the decryption key
Why it's wrong here
KMS does not control deployment permissions.
- ✓
Use IAM to grant the 'aiplatform.models.deploy' role to the other teams on the model resource
Why this is correct
IAM roles provide fine-grained access control within Vertex AI.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.