Deploying ViT on Vertex AI with Model Registry and Endpoints

AI Impact Summary

The article outlines deploying a Vision Transformer (ViT) model from TensorFlow as a SavedModel on Vertex AI, using Model Registry and Endpoint for a production-ready lifecycle. It describes uploading the model to Vertex AI, provisioning an Endpoint, and deploying a deployed_model with dedicated resources and a 100% traffic split, enabling versioned deployments and traffic routing. The approach leverages the tf2-gpu serving image and the google-cloud-aiplatform SDK to minimize custom infra, streamline scaling, and support monitoring and rollback capabilities for ViT inference in production.