joao-aires/operations-platforms

Reduce Azure Kubernetes Service (AKS) spending: pod rightsizing, VPA-driven recommendations, cluster-autoscaler tuning, spot node pools, namespace-level cost visibility, and cost-anomaly detection. WHEN: rightsize pods, VPA recommendations, idle nodes, scale-down, autoscaler profile, spot nodes, cheaper compute, cost add-on, namespace cost breakdown, spending anomaly, 'my AKS bill is too high', 'is my app consuming what it requests', resource requests vs actual usage, over-provisioned workloads, spot vs on-demand, per-namespace or per-team cost allocation, 'who's spending what and why'. DO NOT USE FOR: GPU / inference cost and idle GPU pools (use aks-gpu-inference); autoscaler that is failing to scale up during an incident (use aks-troubleshooting); choosing SKUs at cluster-creation time (use aks-cluster-setup).

Measure and improve application/infrastructure resource efficiency, JVM memory and GC, startup/shutdown, autoscaling, scheduling and resilience during setup, feature changes or recurring optimization reviews.

Design, generate, review and maintain Kubernetes application/infrastructure resources, Helm charts and Kustomize overlays with secure defaults, reliable lifecycle, controller ownership and rendered validation.