What tools or techniques are commonly used for monitoring machine learning models in production?

Common tools and techniques for monitoring machine learning models in production include Prometheus for real-time metrics collection, Grafana for visualization, and ELK Stack (Elasticsearch, Logstash, Kibana) for log analysis. Other specialized tools like Seldon and MLflow provide capabilities for model performance tracking and comparison. Techniques may involve setting up alerts based on key performance indicators (KPIs), analyzing user feedback, and employing techniques like A/B testing and shadow deployments to evaluate model efficacy and stability over time.