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?

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.