You are in the process of building an ML model that analyzes segmented frames extracted from a video feed and generates bounding boxes around specific objects. Your goal is to automate various stages of your training pipeline, which include data ingestion and preprocessing from Cloud Storage, training the object model along with hyperparameter tuning using Vertex AI jobs, and ultimately deploying the model to an endpoint. To orchestrate the entire pipeline while minimizing the need for cluster management, which approach should you adopt?