Machine Learning Pipeline Observability Framework

Create an end-to-end observability solution for machine learning model training and deployment pipelines. Design a system that tracks model performance metrics, resource utilization, data drift, and inference latency across multiple Kubernetes clusters. Implement custom Prometheus exporters, generate automated alerting for performance degradation, and develop a centralized dashboard showing model health, training lineage, and deployment status.