Monitoring AI-Ready Infrastructure with Azure Monitor

AI workloads demand highly resilient and observable environments to run efficiently. To keep these systems healthy, cloud administrators must understand how to track system health, analyze logs, and respond to issues before they impact performance. This text-based course guides you through the foundational concepts of modern cloud observability. You will learn how to collect vital metrics, analyze system behavior, and establish robust alerting systems specifically tailored for AI-ready infrastructure. What you'll learn: - Understand core cloud observability concepts, telemetry types, and monitoring architecture. - Configure metrics collection and design functional dashboards to visualize system health. - Write KQL (Kusto Query Language) queries to analyze complex log data and perform root-cause analysis. - Set up alert and processing rules to automatically detect anomalies and notify team members. - Apply modern observability practices to track resource consumption for AI and machine learning workloads. The course begins with foundational monitoring definitions before moving into practical log querying, dashboard creation, and alert configuration. You will progress through written explanations and conceptual scenarios that build real-world troubleshooting skills. This course is designed for beginner cloud administrators, system engineers, and IT professionals new to cloud observability, with no prior monitoring experience required. Start reading today to build a reliable foundation for monitoring modern AI infrastructure.