The answer is `aiplatform.endpoints.predict`. This permission is required because Vertex AI endpoint online prediction involves sending a request to a deployed model’s endpoint, and IAM enforces resource-level access control—meaning the identity must have the predict permission specifically scoped to that endpoint resource to invoke the model. On the Google Cloud Generative AI Leader exam, this question tests your understanding of how IAM permissions map to specific Vertex AI actions, often appearing as a scenario where a developer receives a permission denied error despite having broader roles. A common trap is confusing this with `aiplatform.models.predict` (which applies to raw model resources, not endpoints) or assuming a generic role like Vertex AI User covers all actions. Remember: endpoints are the gateways for online predictions, so the permission must match the resource type. Memory tip: think “Endpoint = Predict,” as in “EP” for Endpoint Predict.
Generative AI Leader Fundamentals of Generative AI Practice Question
This Generative AI Leader practice question tests your understanding of fundamentals of generative ai. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Exhibit
Error: 403 Permission 'aiplatform.endpoints.predict' denied on resource 'projects/my-project/locations/us-central1/endpoints/my-endpoint'.
Refer to the exhibit. A developer sees this error when trying to call a Vertex AI endpoint for online prediction. What permission does the requesting identity need to be granted?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
aiplatform.endpoints.predict
The error occurs when calling a Vertex AI endpoint for online prediction, which requires the `aiplatform.endpoints.predict` permission. This permission is specifically scoped to the endpoint resource, allowing the identity to send prediction requests to a deployed model endpoint. The correct IAM role binding must include this permission for the requesting identity to successfully invoke the endpoint.
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.
✗
aiplatform.prediction.predict
Why it's wrong here
This is not a standard Vertex AI permission; the correct one is aiplatform.endpoints.predict.
✓
aiplatform.endpoints.predict
Why this is correct
The error explicitly states this permission is required.
Related concept
Read the scenario before looking for a memorised answer.
✗
aiplatform.endpoints.use
Why it's wrong here
No such permission exists; the correct permission is predict.
✗
aiplatform.models.predict
Why it's wrong here
This permission is for predicting using a model directly, not through an endpoint.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between permissions scoped to endpoints versus models, and candidates mistakenly choose `aiplatform.models.predict` because they think prediction is always tied to the model, not the endpoint serving it.
Detailed technical explanation
How to think about this question
Vertex AI endpoints act as a managed serving layer that routes prediction requests to a deployed model. The `aiplatform.endpoints.predict` permission is part of the `roles/aiplatform.user` or custom roles, and it controls access to the `predict` method on the endpoint resource. Under the hood, this permission is checked by the IAM policy attached to the endpoint resource, and missing it results in a 403 Forbidden error, even if the identity has permissions on the underlying model.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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.
What does this Generative AI Leader question test?
Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: aiplatform.endpoints.predict — The error occurs when calling a Vertex AI endpoint for online prediction, which requires the `aiplatform.endpoints.predict` permission. This permission is specifically scoped to the endpoint resource, allowing the identity to send prediction requests to a deployed model endpoint. The correct IAM role binding must include this permission for the requesting identity to successfully invoke the endpoint.
What should I do if I get this Generative AI Leader 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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