Observability, Monitoring & Telemetry: Keeping AI Systems Healthy

Deploying an AI system is the start of a responsibility, not the end of one. Once a model or agent is live, you need to know what it is doing and why. Terms covered: - Observability: understanding what is happening inside a system from what it produces. A design property, built in rather than added later. - Monitoring: tracking defined metrics over time and alerting when something crosses a threshold - Model Monitoring: prediction accuracy, confidence scores, output distributions, latency - Agent Monitoring: what actions agents take, how they use tools, and whether they stay within their boundaries - Telemetry: the continuous collection of logs, traces and metrics that feeds all of it Without telemetry, monitoring is blind. Without monitoring, observability has nothing to analyze. — AI Fundamentals Glossary | H2O.ai University Full playlist: https://www.youtube.com/playlist?list=PLAWKlIKS-66E Free courses and certifications: https://h2o.ai/university #AIObservability #Monitoring #MLOps #AIGlossary #H2Oai