Advanced Azure CLI Automation: Loops, Dynamic Tagging, and Large-Scale Workflows

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After writing my first Azure CLI automation scripts, I realized the real power comes when you start automating at scale. Instead of managing a single VM or resource group, you can handle dozens or hundreds of resources, loop through them, apply dynamic tags, and implement conditional logic to prevent mistakes. In this post, I’ll show you how I do it.

Scenario

In this advanced guide, we’ll:

  1. Loop through multiple virtual machines and resource groups.
  2. Apply dynamic tags based on environment or owner.
  3. Implement conditional logic to skip resources that already exist.
  4. Log everything for troubleshooting.
  5. Combine all steps into a large-scale automation workflow.

Step 1 – Looping Through Multiple Resources

I often need to create or manage multiple VMs at once. Bash loops make this easy:

bash

RESOURCE_GROUP="AutoRG"
LOCATION="EastUS"
VM_LIST=("VM1" "VM2" "VM3")
ADMIN_USER="azureuser"

for VM_NAME in "${VM_LIST[@]}"
do
    echo "Creating $VM_NAME in $RESOURCE_GROUP..."
    az vm create \
        --resource-group $RESOURCE_GROUP \
        --name $VM_NAME \
        --image UbuntuLTS \
        --admin-username $ADMIN_USER \
        --generate-ssh-keys
done

Pro tip: Using arrays makes scaling your automation straightforward. You can read VM names from a file if you need hundreds.

Step 2 – Dynamic Tagging

Instead of hardcoding tags, I use variables or even a CSV file to dynamically apply tags:

bash

declare -A TAGS
TAGS=( ["VM1"]="Dev" ["VM2"]="Test" ["VM3"]="Prod" )

for VM_NAME in "${!TAGS[@]}"
do
    ENV=${TAGS[$VM_NAME]}
    az resource tag \
        --tags Owner="Admin" Environment="$ENV" \
        --name $VM_NAME \
        --resource-group $RESOURCE_GROUP \
        --resource-type "Microsoft.Compute/virtualMachines"
done

This ensures each VM gets the correct environment tag automatically—no manual edits.

Step 3 – Conditional Logic for Safety

Sometimes you want to skip creating a VM if it already exists:

bash

for VM_NAME in "${VM_LIST[@]}"
do
    if az vm show --name $VM_NAME --resource-group $RESOURCE_GROUP &>/dev/null; then
        echo "$VM_NAME already exists, skipping..."
    else
        echo "Creating $VM_NAME..."
        az vm create \
            --resource-group $RESOURCE_GROUP \
            --name $VM_NAME \
            --image UbuntuLTS \
            --admin-username $ADMIN_USER \
            --generate-ssh-keys
    fi
done

Lesson learned: Conditional checks prevent your scripts from failing or accidentally overwriting resources.

Step 4 – Logging Everything

When running large-scale scripts, logging is crucial:

bash

LOG_FILE="automation.log"

{
  echo "Script started: $(date)"
  # Include your loops and commands here
} >> $LOG_FILE 2>&1

Logging allows you to review what happened, troubleshoot errors, and ensure compliance for audits.

Step 5 – Combining Everything into a Scalable Workflow

Once loops, dynamic tagging, and conditional checks are in place, you can automate entire projects. For example:

  1. Create multiple resource groups for different environments.
  2. Deploy VMs in each resource group.
  3. Apply dynamic tags.
  4. Schedule backups.
  5. Log output to a centralized file.

This workflow is what I use when managing labs or production environments—it saves hours of manual work and eliminates human errors.

Step 6 – Scheduling Large-Scale Automation

I combine this with:

  • Cron Jobs (Linux/macOS)
  • Task Scheduler (Windows)
  • Azure Automation Runbooks for cloud-native scheduling

Microsoft Learn’s sandbox environment is perfect for testing large-scale scripts safely before deploying to your real subscription.

Step 7 – Next-Level Tips

  • Parameterize everything: VM size, location, subscription, etc.
  • Use external config files for arrays and tags—makes your scripts easier to maintain.
  • Add error handling for each step—especially loops with multiple resources.
  • Version control your scripts using Git.

Conclusion

Once you start combining loops, dynamic tagging, and conditional logic, Azure CLI automation becomes a powerful tool for large-scale cloud administration. You can manage multiple VMs, resource groups, and backups efficiently, with minimal human intervention.

Pro Tip: Experiment with the Microsoft Learn Sandbox for advanced automation exercises. You can safely practice looping through dozens of VMs, testing conditional logic, and logging workflows—all for free.

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