Azure Container Instances

# Run an Nginx container accessible from the internet
az container create \
  --name my-nginx \
  --resource-group MyRG \
  --image nginx:latest \
  --cpu 1 \
  --memory 1 \
  --dns-name-label my-nginx-demo \
  --ports 80

# Access at: http://my-nginx-demo.<region>.azurecontainer.io

# Pass regular and secure environment variables
az container create \
  --name my-app \
  --resource-group MyRG \
  --image mycontainerregistry.azurecr.io/myapp:v1.0 \
  --environment-variables APP_ENV=production \
  --secure-environment-variables \
    DATABASE_PASSWORD='super-secret-password' \
    API_KEY='my-api-key'

# View logs from the running container
az container logs --name my-app --resource-group MyRG

# Small: 0.5 CPU, 0.5 GB memory
az container create --name small-task --resource-group MyRG \
  --image my-batch-image:latest --cpu 0.5 --memory 0.5 \
  --restart-policy Never  # Don't restart after completion

# Large: 4 CPU, 16 GB memory for intensive tasks
az container create --name ml-inference --resource-group MyRG \
  --image ml-model:latest --cpu 4 --memory 16

# Batch job: run once, never restart
az container create \
  --name data-processor \
  --resource-group MyRG \
  --image my-batch-image:latest \
  --restart-policy Never \
  --environment-variables BATCH_DATE=2025-01-01

# Check the container's final state
az container show \
  --name data-processor \
  --resource-group MyRG \
  --query '{state:instanceView.state, exitCode:instanceView.currentState.exitCode}'

# multi-container.yaml
apiVersion: '2021-09-01'
location: eastus
name: my-container-group
properties:
  containers:
  - name: app
    properties:
      image: myapp:v1.0
      ports: [{port: 80}]
      resources: {requests: {cpu: 1, memoryInGb: 1}}
  - name: log-forwarder
    properties:
      image: fluent-bit:latest
      resources: {requests: {cpu: 0.5, memoryInGb: 0.5}}
  osType: Linux
  restartPolicy: Always
type: Microsoft.ContainerInstance/containerGroups

# Deploy from YAML
# az container create --resource-group MyRG --file multi-container.yaml

# Mount an Azure Files share for persistent storage
az container create \
  --name stateful-app \
  --resource-group MyRG \
  --image myapp:v1.0 \
  --azure-file-volume-account-name mystorageaccount \
  --azure-file-volume-account-key '<storage-account-key>' \
  --azure-file-volume-share-name myfileshare \
  --azure-file-volume-mount-path /data

# Data written to /data persists in the Azure Files share

# Create a GPU-enabled container instance
az container create \
  --name gpu-inference \
  --resource-group MyRG \
  --image my-ml-model:latest \
  --gpu-count 1 \
  --gpu-sku V100 \
  --cpu 4 \
  --memory 16 \
  --os-type Linux

# Create an ACI container in a VNet
az container create \
  --name private-task \
  --resource-group MyRG \
  --image myapp:v1.0 \
  --vnet MyVNet \
  --subnet ContainerSubnet \
  --restart-policy Never

# The container gets a private IP from the subnet CIDR
# It can reach VNet resources (SQL, Redis, VMs) on private IPs

# Enable virtual nodes on an AKS cluster
az aks enable-addons \
  --name myAKSCluster \
  --resource-group MyRG \
  --addons virtual-node \
  --subnet-name VirtualNodeSubnet

# Schedule a burst pod on ACI via node selector
# spec:
#   nodeSelector:
#     kubernetes.io/role: agent
#     beta.kubernetes.io/os: linux
#     type: virtual-kubelet
#   tolerations:
#   - key: virtual-kubelet.io/provider
#     operator: Exists