Agent skill

aks-automatic-2025

This skill should be used when the user asks about "AKS Automatic", "managed Kubernetes", "Karpenter autoscaling", "AKS zero operational overhead", "AKS 2025", "AKS billing model", "NodePool CRD", "HPA VPA KEDA on AKS", "AKS workload identity", or needs guidance on Azure Kubernetes Service Automatic mode GA 2025 features.

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SKILL.md

AKS Automatic - 2025 GA Features

Complete knowledge base for Azure Kubernetes Service Automatic mode (GA October 2025).

Overview

AKS Automatic is a fully-managed Kubernetes offering that eliminates operational overhead through intelligent automation and built-in best practices.

Key Features (GA October 2025)

1. Zero Operational Overhead

  • Fully-managed control plane and worker nodes
  • Automatic OS patching and security updates
  • Built-in monitoring and diagnostics
  • Integrated security and compliance

2. Karpenter Integration

  • Dynamic node provisioning based on real-time demand
  • Intelligent bin-packing for cost optimization
  • Automatic node consolidation and deprovisioning
  • Support for multiple node pools and instance types

3. Auto-Scaling (Enabled by Default)

  • Horizontal Pod Autoscaler (HPA): Scale pods based on CPU/memory
  • Vertical Pod Autoscaler (VPA): Adjust pod resource requests/limits
  • KEDA: Event-driven autoscaling for external triggers

4. Enhanced Security

  • Microsoft Entra ID integration for authentication
  • Azure RBAC for Kubernetes authorization
  • Network policies enabled by default
  • Automatic security patches
  • Workload identity for pod-level authentication

5. Advanced Networking

  • Azure CNI Overlay for efficient IP usage
  • Cilium dataplane for high-performance networking
  • Network policies for microsegmentation
  • Private clusters supported

6. New Billing Model (Effective October 19, 2025)

  • Hosted control plane fee: $0.16/cluster/hour
  • Compute charges based on actual node usage
  • No separate cluster management fee
  • Cost savings from Karpenter optimization

7. Node Operating System

  • Ubuntu 22.04 for Kubernetes < 1.34
  • Ubuntu 24.04 for Kubernetes >= 1.34
  • Automatic OS upgrades with node image channel

Creating AKS Automatic Cluster

Basic Creation

bash
az aks create \
  --resource-group MyRG \
  --name MyAKSAutomatic \
  --sku automatic \
  --kubernetes-version 1.34 \
  --location eastus

Production-Ready Configuration

bash
az aks create \
  --resource-group MyRG \
  --name MyAKSAutomatic \
  --location eastus \
  --sku automatic \
  --tier standard \
  \
  # Kubernetes version
  --kubernetes-version 1.34 \
  \
  # Karpenter (default in automatic mode)
  --enable-karpenter \
  \
  # Networking
  --network-plugin azure \
  --network-plugin-mode overlay \
  --network-dataplane cilium \
  --service-cidr 10.0.0.0/16 \
  --dns-service-ip 10.0.0.10 \
  --load-balancer-sku standard \
  \
  # Use custom VNet (optional)
  --vnet-subnet-id /subscriptions/<sub-id>/resourceGroups/MyRG/providers/Microsoft.Network/virtualNetworks/MyVNet/subnets/AKSSubnet \
  \
  # Availability zones
  --zones 1 2 3 \
  \
  # Authentication and authorization
  --enable-managed-identity \
  --enable-aad \
  --enable-azure-rbac \
  --aad-admin-group-object-ids <group-object-id> \
  \
  # Auto-upgrade
  --auto-upgrade-channel stable \
  --node-os-upgrade-channel NodeImage \
  \
  # Security
  --enable-defender \
  --enable-workload-identity \
  --enable-oidc-issuer \
  \
  # Monitoring
  --enable-addons monitoring \
  --workspace-resource-id /subscriptions/<sub-id>/resourceGroups/MyRG/providers/Microsoft.OperationalInsights/workspaces/MyWorkspace \
  \
  # Tags
  --tags Environment=Production ManagedBy=AKSAutomatic

With Azure Policy Add-on

bash
az aks create \
  --resource-group MyRG \
  --name MyAKSAutomatic \
  --sku automatic \
  --enable-addons azure-policy \
  --kubernetes-version 1.34

Karpenter Configuration

AKS Automatic uses Karpenter for intelligent node provisioning. Customize node provisioning with AKSNodeClass and NodePool CRDs.

Default AKSNodeClass

yaml
apiVersion: karpenter.azure.com/v1alpha1
kind: AKSNodeClass
metadata:
  name: default
spec:
  # OS Image - Ubuntu 24.04 for K8s 1.34+
  osImage:
    sku: Ubuntu
    version: "24.04"

  # VM Series
  vmSeries:
    - Standard_D
    - Standard_E

  # Max pods per node
  maxPodsPerNode: 110

  # Security
  securityProfile:
    sshAccess: Disabled
    securityType: Standard

Custom NodePool

yaml
apiVersion: karpenter.sh/v1
kind: NodePool
metadata:
  name: general-purpose
spec:
  # Constraints
  template:
    spec:
      requirements:
        - key: kubernetes.io/arch
          operator: In
          values: ["amd64"]
        - key: karpenter.sh/capacity-type
          operator: In
          values: ["on-demand"]
        - key: kubernetes.azure.com/agentpool
          operator: In
          values: ["general"]

      # Node labels
      labels:
        workload-type: general

      # Taints (optional)
      taints:
        - key: "dedicated"
          value: "general"
          effect: "NoSchedule"

      # NodeClass reference
      nodeClassRef:
        group: karpenter.azure.com
        kind: AKSNodeClass
        name: default

  # Limits
  limits:
    cpu: "1000"
    memory: 4000Gi

  # Disruption budget
  disruption:
    consolidationPolicy: WhenEmpty
    consolidateAfter: 30s
    expireAfter: 720h # 30 days
    budgets:
      - nodes: "10%"
        duration: 5m

GPU NodePool for AI Workloads

yaml
apiVersion: karpenter.sh/v1
kind: NodePool
metadata:
  name: gpu-workloads
spec:
  template:
    spec:
      requirements:
        - key: kubernetes.io/arch
          operator: In
          values: ["amd64"]
        - key: karpenter.sh/capacity-type
          operator: In
          values: ["on-demand"]
        - key: node.kubernetes.io/instance-type
          operator: In
          values: ["Standard_NC6s_v3", "Standard_NC12s_v3", "Standard_NC24s_v3"]

      labels:
        workload-type: gpu
        gpu-type: nvidia-v100

      taints:
        - key: "nvidia.com/gpu"
          value: "true"
          effect: "NoSchedule"

      nodeClassRef:
        group: karpenter.azure.com
        kind: AKSNodeClass
        name: gpu-nodeclass

  limits:
    cpu: "200"
    memory: 800Gi
    nvidia.com/gpu: "16"

  disruption:
    consolidationPolicy: WhenEmpty
    consolidateAfter: 300s

Autoscaling with HPA, VPA, and KEDA

Horizontal Pod Autoscaler (HPA)

yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: myapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  minReplicas: 2
  maxReplicas: 50
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70
    - type: Resource
      resource:
        name: memory
        target:
          type: Utilization
          averageUtilization: 80
  behavior:
    scaleUp:
      stabilizationWindowSeconds: 0
      policies:
        - type: Percent
          value: 100
          periodSeconds: 15
        - type: Pods
          value: 4
          periodSeconds: 15
      selectPolicy: Max
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
        - type: Percent
          value: 50
          periodSeconds: 15

Vertical Pod Autoscaler (VPA)

yaml
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
  name: myapp-vpa
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  updatePolicy:
    updateMode: "Auto"  # Auto, Recreate, Initial, Off
  resourcePolicy:
    containerPolicies:
      - containerName: "*"
        minAllowed:
          cpu: 100m
          memory: 128Mi
        maxAllowed:
          cpu: 4
          memory: 8Gi
        controlledResources: ["cpu", "memory"]
        controlledValues: RequestsAndLimits

KEDA ScaledObject (Event-Driven)

yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: myapp-queue-scaler
spec:
  scaleTargetRef:
    name: myapp
  minReplicaCount: 0  # Scale to zero
  maxReplicaCount: 100
  pollingInterval: 30
  cooldownPeriod: 300
  triggers:
    # Azure Service Bus Queue
    - type: azure-servicebus
      metadata:
        queueName: myqueue
        namespace: myservicebus
        messageCount: "5"
      authenticationRef:
        name: azure-servicebus-auth

    # Azure Storage Queue
    - type: azure-queue
      metadata:
        queueName: myqueue
        queueLength: "10"
        accountName: mystorageaccount
      authenticationRef:
        name: azure-storage-auth

    # Prometheus metrics
    - type: prometheus
      metadata:
        serverAddress: http://prometheus.monitoring.svc.cluster.local:9090
        metricName: http_requests_per_second
        threshold: "100"
        query: sum(rate(http_requests_total[2m]))

Workload Identity (Replaces AAD Pod Identity)

Setup

bash
# Workload identity is enabled by default in AKS Automatic

# Create managed identity
az identity create \
  --name myapp-identity \
  --resource-group MyRG

# Get identity details
export IDENTITY_CLIENT_ID=$(az identity show -g MyRG -n myapp-identity --query clientId -o tsv)
export IDENTITY_OBJECT_ID=$(az identity show -g MyRG -n myapp-identity --query principalId -o tsv)

# Assign role to identity
az role assignment create \
  --assignee $IDENTITY_OBJECT_ID \
  --role "Storage Blob Data Contributor" \
  --scope /subscriptions/<sub-id>/resourceGroups/MyRG/providers/Microsoft.Storage/storageAccounts/mystorage

# Create federated credential
export AKS_OIDC_ISSUER=$(az aks show -g MyRG -n MyAKSAutomatic --query oidcIssuerProfile.issuerUrl -o tsv)

az identity federated-credential create \
  --name myapp-federated-credential \
  --identity-name myapp-identity \
  --resource-group MyRG \
  --issuer $AKS_OIDC_ISSUER \
  --subject system:serviceaccount:default:myapp-sa

Kubernetes Resources

yaml
# Service Account
apiVersion: v1
kind: ServiceAccount
metadata:
  name: myapp-sa
  namespace: default
  annotations:
    azure.workload.identity/client-id: "<IDENTITY_CLIENT_ID>"

---
# Deployment using workload identity
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 2
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
        azure.workload.identity/use: "true"  # Enable workload identity
    spec:
      serviceAccountName: myapp-sa
      containers:
        - name: myapp
          image: myregistry.azurecr.io/myapp:latest
          env:
            - name: AZURE_CLIENT_ID
              value: "<IDENTITY_CLIENT_ID>"
            - name: AZURE_TENANT_ID
              value: "<TENANT_ID>"
            - name: AZURE_FEDERATED_TOKEN_FILE
              value: /var/run/secrets/azure/tokens/azure-identity-token
          volumeMounts:
            - name: azure-identity-token
              mountPath: /var/run/secrets/azure/tokens
              readOnly: true
      volumes:
        - name: azure-identity-token
          projected:
            sources:
              - serviceAccountToken:
                  path: azure-identity-token
                  expirationSeconds: 3600
                  audience: api://AzureADTokenExchange

Monitoring and Observability

Enable Container Insights

bash
# Already enabled with --enable-addons monitoring
# Query logs using Azure Monitor

# Get cluster logs
az monitor log-analytics query \
  --workspace <workspace-id> \
  --analytics-query "KubePodInventory | where ClusterName == 'MyAKSAutomatic' | take 10" \
  --output table

# Get Karpenter logs
kubectl logs -n kube-system -l app.kubernetes.io/name=karpenter

Prometheus and Grafana

bash
# Enable managed Prometheus
az aks update \
  --resource-group MyRG \
  --name MyAKSAutomatic \
  --enable-azure-monitor-metrics

# Access Grafana dashboards through Azure Portal

Cost Optimization

Billing Model (October 2025)

  • Control plane: $0.16/hour per cluster
  • Compute: Pay for actual node usage
  • Karpenter: Automatic bin-packing and consolidation
  • Scale-to-zero: Possible with KEDA and Karpenter

Cost-Saving Tips

  1. Use Spot Instances for Non-Critical Workloads
yaml
- key: karpenter.sh/capacity-type
  operator: In
  values: ["spot"]
  1. Configure Aggressive Consolidation
yaml
disruption:
  consolidationPolicy: WhenUnderutilized
  consolidateAfter: 30s
  1. Implement Pod Disruption Budgets
yaml
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  name: myapp-pdb
spec:
  minAvailable: 1
  selector:
    matchLabels:
      app: myapp
  1. Use VPA for Right-Sizing
  • VPA automatically adjusts resource requests based on actual usage

Migration from Standard AKS to Automatic

AKS Automatic is a new cluster mode - in-place migration is not supported. Follow these steps:

  1. Create new AKS Automatic cluster
  2. Install workloads in new cluster
  3. Validate functionality
  4. Switch traffic (DNS, load balancer)
  5. Decommission old cluster

Best Practices

✓ Use AKS Automatic for new production clusters ✓ Enable workload identity for pod authentication ✓ Configure custom NodePools for specific workload types ✓ Implement HPA, VPA, and KEDA for comprehensive scaling ✓ Use spot instances for batch and fault-tolerant workloads ✓ Enable Container Insights and Managed Prometheus ✓ Configure Pod Disruption Budgets for critical apps ✓ Use network policies for microsegmentation ✓ Enable Azure Policy add-on for compliance ✓ Implement GitOps with Flux or Argo CD

Troubleshooting

Check Karpenter Status

bash
kubectl logs -n kube-system -l app.kubernetes.io/name=karpenter --tail=100
kubectl get nodepools
kubectl get nodeclaims

View Node Provisioning Events

bash
kubectl get events --field-selector involvedObject.kind=NodePool -A

Debug Workload Identity Issues

bash
# Check service account annotation
kubectl get sa myapp-sa -o yaml

# Check pod labels
kubectl get pod <pod-name> -o yaml | grep azure.workload.identity

# Check federated credential
az identity federated-credential show \
  --identity-name myapp-identity \
  --resource-group MyRG \
  --name myapp-federated-credential

References

AKS Automatic represents the future of managed Kubernetes on Azure - zero operational overhead with maximum automation!

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