Deploy ViT on Vertex AI with Model Registry and Endpoint using TF2.8 GPU image

AI Impact Summary

This guide walks through deploying a ViT model from TensorFlow as a SavedModel to Vertex AI using the google-cloud-aiplatform SDK. It covers uploading the artifact to a GCS bucket, registering the model in Vertex AI Model Registry, creating an Endpoint, and deploying with GPU-accelerated resources and a 100% traffic split. The approach leverages Vertex AI pre-built TF serving images (tf2-gpu.2-8) and demonstrates how to wire ModelServiceClient, EndpointServiceClient, and PredictionServiceClient to manage lifecycle. This enables production-ready inference with versioning, traffic routing, and monitoring while reducing custom deployment boilerplate.