How can you monitor latency for machine learning models in production?

To monitor latency for ML models in production, you can implement logging mechanisms within your serving architecture that record the time taken for inference requests. Metrics can be collected using monitoring tools like Prometheus or Grafana, which can visualize latency trends, including average, median, and 95th percentile latencies. It’s also beneficial to set up alerts for latency anomalies by defining thresholds. Additionally, employing A/B testing can help compare latencies between different model versions.