Seldon Core Deployment Configuration

Prepare the necessary `Seldon Core` deployment configuration (YAML files) to serve your trained anomaly detection model as a real-time inference endpoint on a Kubernetes cluster. Your configuration should define a custom `SeldonDeployment` that incorporates your pre-trained model and the `Featuretools` pipeline for real-time feature extraction. Consider how to pass the raw sensor input to your model and receive anomaly predictions. Provide a Dockerfile if a custom runtime environment is needed beyond standard Seldon wrappers.