You are building an MLOps pipeline to retrain tree-based models in production. The pipeline must include components for data ingestion, data processing, model training, model evaluation, and model deployment. Your organization primarily uses PySpark for data preprocessing, and you want to minimize infrastructure management. How should you architect this pipeline?