Google Cloud Professional Machine Learning Engineer — Question 318

You are a lead ML architect at a small company that is migrating from on-premises to Google Cloud. Your company has limited resources and expertise in cloud infrastructure. You want to serve your models from Google Cloud as soon as possible. You want to use a scalable, reliable, and cost-effective solution that requires no additional resources. What should you do?

Answer options

• A. Configure Compute Engine VMs to host your models.
• B. Create a Cloud Run function to deploy your models as serverless functions.
• C. Create a managed cluster on Google Kubernetes Engine (GKE), and deploy your models as containers.
• D. Deploy your models on Vertex AI endpoints.

Correct answer: D

Explanation

The correct answer is D because Vertex AI endpoints provide a fully managed service specifically designed for serving machine learning models, ensuring scalability, reliability, and ease of use without requiring additional infrastructure management. Options A and C involve managing virtual machines and Kubernetes clusters, which require more resources and expertise. Option B, while serverless, may not offer the same level of integration and optimization for ML models as Vertex AI does.