AI-Driven Anomaly Detection on IBM i Operational Data: DB2 Statistical Baselines, Python in PASE, Isolation Forest, and Automated Alerting in 2026
Build AI-driven anomaly detection for IBM i operational data in 2026: query QSYS2 system views for job and performance metrics, establish DB2 statistical baselines with SQL window functions, install Python and scikit-learn in PASE, train an Isolation Forest model on historical IBM i data, detect real-time anomalies, and trigger automated alerts via email or data queue when anomalies are found.