Machine Learning Model Versioning and Deployment Pipeline

Create a comprehensive MLOps pipeline script that manages machine learning model versioning, validation, and automated deployment. Develop a system that tracks model performance metrics, compares new models against production baselines, automatically rolls back if performance degrades, and supports A/B testing configurations. Implement robust logging, model registry with semantic versioning, and integration with cloud deployment platforms like Kubernetes.