Monitoring tracks model accuracy, latency and user feedback once an LLM is in production. Observability dives deeper into the logs and traces that explain why outputs change. Together they ensure reliable behaviour under load and help catch regressions quickly.
Teams typically combine automated alerts with manual review. Usage analytics reveal where prompts fail, while red teams probe for dangerous responses. Continuous evaluation closes the loop so models can improve over time.