The answer is to use IAM to grant the 'aiplatform.models.deploy' permission on the specific model resource. This is correct because Vertex AI Model Registry enforces fine-grained access control through IAM roles, and the 'aiplatform.models.deploy' permission is the precise authorization needed to deploy a model from the registry, while leaving other actions like viewing or updating the model artifact restricted. On the Google Professional Machine Learning Engineer exam, this tests your understanding of resource-level IAM policies versus project-level roles—a common trap is granting broader roles like 'aiplatform.user' or 'editor', which would over-permission the team. The key is to apply the principle of least privilege by scoping the deploy permission directly to the model resource in the registry. Memory tip: think "deploy on the model, not the project"—the permission must be tied to the specific model artifact, not the entire Vertex AI service.
PMLE Collaborating to manage data and models Practice Question
This PMLE practice question tests your understanding of collaborating to manage data and models. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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
Option D is correct because 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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
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.
Detailed technical explanation
How to think about this question
Vertex AI Model Registry integrates with IAM to provide fine-grained access control at the model resource level. The 'aiplatform.models.deploy' permission is a custom role that allows a principal to create a deployment (endpoint) from the model, but does not grant read access to the model artifact in Cloud Storage. This separation ensures that even if a team has the model artifact, they cannot deploy it without the IAM permission, and vice versa. In practice, organizations often combine this with VPC-SC perimeters to further restrict access.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Collaborating to manage data and models — This question tests Collaborating to manage data and models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use IAM to grant the 'aiplatform.models.deploy' role to the other teams on the model resource — Option D is correct because 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.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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