PROFESSIONAL-CLOUD-ARCHITECT · Question #347
Your team plans to use Vertex AI to develop and deploy machine learning models for various use cases for fraud detection, product recommendations, and customer churn prediction. You want to enhance…
The correct answer is D. Create a service perimeter and include aiplatform.googleapis.com and notebooks.googleapis.com. Creating a service perimeter with VPC Service Controls around Vertex AI and Workbench prevents unauthorized data movement outside trusted networks. Including the Vertex AI and Workbench APIs ensures that model training, deployment, and notebook access are restricted to…
Question
Options
- AEnable Private Google Access for the VPC network to allow Vertex AI services to access public
- BEnable VPC Flow Logs to monitor network traffic to and from Vertex AI services and to identify
- CCreate a service perimeter and include ml.googleapis.com and document.googleapis.com as
- DCreate a service perimeter and include aiplatform.googleapis.com and notebooks.googleapis.com
How the community answered
(44 responses)- A2% (1)
- B14% (6)
- C7% (3)
- D77% (34)
Explanation
Creating a service perimeter with VPC Service Controls around Vertex AI and Workbench prevents unauthorized data movement outside trusted networks. Including the Vertex AI and Workbench APIs ensures that model training, deployment, and notebook access are restricted to resources within the perimeter, effectively mitigating the risk of data exfiltration.
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