AKS Cluster Autoscaler (CAS)

Enable and tune the Cluster Autoscaler to automatically scale down idle nodes.

Check CAS Status

az aks show \
  --name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --query "agentPoolProfiles[].{name:name, casEnabled:enableAutoScaling, min:minCount, max:maxCount, count:count}" \
  -o table

az aks show \
  --name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --query "autoScalerProfile" -o json

Check Node Utilization (7 days)

Follow the metrics discovery steps in azure-aks-rightsizing.md to list available metric definitions and query node CPU utilization. Use metric names such as node_cpu_usage_percentage or cpuUsagePercentage depending on what's available on the cluster.

Enable CAS

# Cluster-level
az aks update \
  --name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --enable-cluster-autoscaler \
  --min-count <MIN_NODES> --max-count <MAX_NODES>

# Specific node pool
az aks nodepool update \
  --cluster-name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --name "<NODEPOOL_NAME>" \
  --enable-cluster-autoscaler \
  --min-count <MIN_NODES> --max-count <MAX_NODES>

Recommended min/max Defaults

Scenario	min-count	max-count
Dev/test	1	current_count
Production (web/API)	2	current_count * 3
Production (batch)	0	current_count * 5

Risk: Low. CAS only scales down when pods can be safely rescheduled. Set min-count >= 2 for production HA.

Tune CAS Profile

Apply when CAS is already on but idle nodes persist:

⚠️ Warning: Setting skip-nodes-with-system-pods=false allows CAS to evict system pods. Ensure all system pods in kube-system have PodDisruptionBudgets before enabling this.

az aks update \
  --name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --cluster-autoscaler-profile \
    scale-down-delay-after-add=10m \
    scale-down-unneeded-time=10m \
    scale-down-utilization-threshold=0.5 \
    max-graceful-termination-sec=600 \
    skip-nodes-with-system-pods=false

To roll back to CAS defaults:

az aks update \
  --name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --cluster-autoscaler-profile ""

Profile Comparison

Profile	scale-down-delay-after-add	scale-down-unneeded-time	utilization-threshold	Best For
Default	10m	10m	0.5	General workloads
Cost-Optimized	5m	5m	0.5	Cost-sensitive, non-critical
Conservative	30m	30m	0.7	Stateful / production
Aggressive	2m	2m	0.4	Dev/test, batch

Risk: High for aggressive tuning. Ensure PodDisruptionBudgets (PDBs) are set on critical workloads before tuning. Always confirm with user before applying.

Check existing PDBs before tuning:

kubectl get pdb --all-namespaces