cluster administration

Explores how AI augments Kubernetes administration: using ML for predictive autoscaling, anomaly detection, self-healing, and policy automation. Covers AIOps toolchains, observability data, GitOps/MLOps integration, security and cost optimization, and SLO-driven operations, while noting challenges like data quality, model drift, bias, and governance.