azure-aks

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• SKILL.md

SKILL.md (first lines)

# Azure Kubernetes Service

Deploy and manage production-grade Kubernetes clusters on Azure with AKS. Covers cluster creation, node pool management, networking, ingress controllers, monitoring, security, and Terraform-based provisioning.

## When to Use

- You need managed Kubernetes without maintaining control plane infrastructure.
- Your workloads require container orchestration with auto-scaling.
- You need tight integration with Azure AD, Key Vault, and Container Registry.
- You are running microservices that require service mesh, ingress, or network policies.
- You need GPU or spot node pools for specialized or cost-optimized workloads.

Confirm subscription, cluster/context, budget, quotas, region/zone/SKU support and rollback before mutations. Examples are partial and version-sensitive: inspect current AKS and AzureRM provider schemas, supported Kubernetes upgrade paths and pod-disruption budgets. `get-credentials` changes local kubeconfig/current context. Do not manually scale an autoscaler-controlled pool without coordinating the autoscaler. Use existing secret references for Grafana credentials, not command-line values.

## Prerequisites

```bash
# Install Azure CLI and kubectl
# Prerequisite: organization-approved Azure CLI installed from a verified signed package.
az version
az aks install-cli

# Login and set subscription
az login
az account set --subscription "my-subscription-id"

# Register required providers
az provider register --namespace Microsoft.ContainerService
az provider register --namespace Microsoft.OperationsManagement

# Verify kubectl
kubectl version --client
```

## Cluster Creation

### Illustrative Cluster Configuration

```bash
# Create resource group
az group create --name myapp-rg --location eastus

# Create AKS cluster with best-practice defaults
az aks create \
  --resource-group myapp-rg \
  --name myapp-aks \
  --node-count 3 \
  --node-vm-size Standard_D4s_v5 \
  --enable-managed-identity \
  --enable-cluster-autoscaler \
  --min-count 2 \
  --max-count 10 \
  --network-plugin azure \
  --network-policy calico \
  --service-cidr 10.1.0.0/16 \
  --dns-service-ip 10.1.0.10 \
  --vnet-subnet-id "/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.Network/virtualNetworks/{vnet}/subnets/{subnet}" \
  --enable-aad \
  --aad-admin-group-object-ids "{aad-group-id}" \
  --enable-azure-rbac \
  --zones 1 2 3 \
  --generate-ssh-keys \
  --tags environment=prod team=platform

# Get cluster credentials
az aks get-credentials --resource-group myapp-rg --name myapp-aks

# Verify cluster access
kubectl get nodes -o wide
kubectl cluster-info
```

### Private Cluster

```bash
az aks create \
  --resource-group myapp-rg \
  --name myapp-private-aks \
  --node-count 3 \
  --node-vm-size Standard_D4s_v5 \
  --enable-managed-identity \
  --enable-private-cluster \
  --private-dns-zone system \
  --network-plugin azure \
  --vnet-subnet-id "/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.Network/virtualNetworks/{vnet}/subnets/{subnet}" \
  --generate-ssh-keys
```

## Node Pool Management

```bash
# Add a user node pool for application workloads
az aks nodepool add \
  --resource-group myapp-rg \
  --cluster-name myapp-aks \
  --name apppool \
  --node-count 3 \
  --node-vm-size Standard_D8s_v5 \
  --mode User \
  --enable-cluster-autoscaler \
  --min-count 2 \
  --max-count 15 \
  --zones 1 2 3 \
  --labels workload=app tier=frontend \
  --node-taints dedicated=app:NoSchedule \
  --max-pods 50

# Add GPU node pool for ML workloads
az aks nodepool add \
  --resource-group myapp-rg \
  --cluster-name myapp-aks \
  --name gpupool \
  --node-count 1 \
  --node-vm-size Standard_NC6s_v3 \
  --mode User \
  --enable-cluster-autoscaler \
  --min-count 0 \
  --max-count 4 \
  --node-taints sku=gpu:NoSchedule \

From sickn33/agentic-awesome-skills, MIT.

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