If you prefer to run CLI reference commands locally, install the Azure CLI. If you're running on Windows or macOS, consider running Azure CLI in a Docker container. For more information, see How to run the Azure CLI in a Docker container.
If you're using a local installation, sign in to the Azure CLI by using the az login command. To finish the authentication process, follow the steps displayed in your terminal. For other sign-in options, see Sign in with the Azure CLI.
When you're prompted, install the Azure CLI extension on first use. For more information about extensions, see Use extensions with the Azure CLI.
Run az version to find the version and dependent libraries that are installed. To upgrade to the latest version, run az upgrade.
Sample script
Launch Azure Cloud Shell
The Azure Cloud Shell is a free interactive shell that you can use to run the steps in this article. It has common Azure tools preinstalled and configured to use with your account.
To open the Cloud Shell, just select Try it from the upper right corner of a code block. You can also launch Cloud Shell in a separate browser tab by going to https://shell.azure.com.
When Cloud Shell opens, verify that Bash is selected for your environment. Subsequent sessions will use Azure CLI in a Bash environment, Select Copy to copy the blocks of code, paste it into the Cloud Shell, and press Enter to run it.
Sign in to Azure
Cloud Shell is automatically authenticated under the initial account signed-in with. Use the following script to sign in using a different subscription, replacing subscriptionId with your Azure subscription ID.
# Run a job and tasks with Azure Batch# Variable block
let "randomIdentifier=$RANDOM*$RANDOM"location="East US"
[[ "$RESOURCE_GROUP" == '']] && resourceGroup="msdocs-batch-rg-$randomIdentifier" || resourceGroup="${RESOURCE_GROUP}"tag="run-job"storageAccount="msdocsstorage$randomIdentifier"batchAccount="msdocsbatch$randomIdentifier"# Create a resource group.
echo "Creating $resourceGroup in "$location"..."az group create --name$resourceGroup--location"$location"--tag$tag# Create a general-purpose storage account in your resource group.
echo "Creating $storageAccount"az storage account create --resource-group$resourceGroup--name$storageAccount--location"$location"--sku Standard_LRS
# Create a Batch account.
echo "Creating $batchAccount"az batch account create --name$batchAccount--storage-account$storageAccount--resource-group$resourceGroup--location"$location"# Authenticate against the account directly for further CLI interaction.az batch account login --name$batchAccount--resource-group$resourceGroup--shared-key-auth# Create a new Linux pool with a virtual machine configuration. az batch pool create --id mypool --vm-size Standard_A1 --target-dedicated2--image canonical:ubuntuserver:18_04-lts-gen2 --node-agent-sku-id"batch.node.ubuntu 18.04"# Create a new job to encapsulate the tasks that are added.az batch job create --id myjob --pool-id mypool
# Add tasks to the job. Here the task is a basic shell command.az batch task create --job-id myjob --task-id task1 --command-line"/bin/bash -c 'printenv AZ_BATCH_TASK_WORKING_DIR'"
az batch task create \
--job-id myjob \
--json-file tasks.json
To update the job
Update the job so that it is automatically marked as completed once all the tasks are finished.
Azure CLI
az batch job set \
--job-id myjob \
--on-all-tasks-complete terminatejob
To monitor the status of the job
Azure CLI
az batch job show --job-id myjob
To monitor the status of a task
Azure CLI
az batch task show \
--job-id myjob \
--task-id task1
Clean up resources
Use the following command to remove the resource group and all resources associated with it using the az group delete command - unless you have an ongoing need for these resources. Some of these resources may take a while to create, as well as to delete.
Azure CLI
az group delete --name$resourceGroup
Sample reference
This script uses the following commands. Each command in the table links to command-specific documentation.
Find out about the Azure Batch capabilities designed to help you efficiently run large-scale parallel and high-performance computing applications in the cloud.