Detecting Workload Anomalies with Prometheus and Machine Learning

Learn how to implement anomaly detection in workload monitoring through a comprehensive conference talk that combines Prometheus monitoring with machine learning techniques. Explore practical approaches to identifying unusual patterns and potential issues in system workloads using time-series data analysis. Discover how to leverage Prometheus's powerful monitoring capabilities alongside machine learning algorithms to create effective anomaly detection systems. Gain insights into setting up automated alerts, understanding workload patterns, and implementing predictive monitoring strategies that can help maintain system reliability and performance. The presentation, delivered by Anthony Nocentino at the PowerShell Summit, provides hands-on demonstrations and real-world examples of integrating these technologies for improved system observability and proactive issue detection.