Distributed Machine Learning Model Deployment Framework

Create a Kubernetes-native deployment framework for machine learning models used in financial predictive analytics. Design a custom Helm chart that supports model versioning, A/B testing, and seamless model swapping for price prediction, fraud detection, and credit scoring models. Implement a custom Python operator that manages model lifecycle, including automated retraining, performance monitoring, and drift detection. Include comprehensive logging, metrics collection using Prometheus, and integration with MLflow for experiment tracking.