Managing Azure Batch with Terraform

Azure Batch helps you run large-scale parallel and high-performance computing (HPC) applications efficiently in the cloud. In this guide, we’ll explore how to manage Azure Batch using Terraform.

Prerequisites

• Azure subscription
• Terraform installed
• Azure CLI installed

Basic Configuration

Here’s a basic example of setting up an Azure Batch account:

resource "azurerm_resource_group" "batch_rg" {
  name     = "batch-resources"
  location = "eastus"
}

resource "azurerm_storage_account" "batch_storage" {
  name                     = "batchstorage"
  resource_group_name      = azurerm_resource_group.batch_rg.name
  location                 = azurerm_resource_group.batch_rg.location
  account_tier             = "Standard"
  account_replication_type = "LRS"
}

resource "azurerm_batch_account" "batch_account" {
  name                = "batchaccount"
  resource_group_name = azurerm_resource_group.batch_rg.name
  location           = azurerm_resource_group.batch_rg.location
  storage_account_id = azurerm_storage_account.batch_storage.id
  
  pool_allocation_mode = "BatchService"
}

resource "azurerm_batch_pool" "batch_pool" {
  name                = "batchpool"
  resource_group_name = azurerm_resource_group.batch_rg.name
  account_name        = azurerm_batch_account.batch_account.name
  display_name        = "Batch Pool"
  vm_size            = "Standard_D2s_v3"
  node_agent_sku_id  = "batch.node.ubuntu 20.04"

  fixed_scale {
    target_dedicated_nodes = 2
  }

  storage_image_reference {
    publisher = "Canonical"
    offer     = "UbuntuServer"
    sku       = "20.04-LTS"
    version   = "latest"
  }
}

Advanced Features

Auto-scaling

Configure auto-scaling for your Batch pool:

resource "azurerm_batch_pool" "batch_pool" {
  # ... other configurations ...

  auto_scale {
    evaluation_interval = "PT15M"
    formula            = <<EOF
      startingNumberOfVMs = 1;
      maxNumberofVMs = 25;
      pendingTaskSamplePercent = $PendingTasks.GetSamplePercent(180 * TimeInterval_Second);
      pendingTaskSamples = pendingTaskSamplePercent < 70 ? startingNumberOfVMs : avg($PendingTasks.GetSample(180 * TimeInterval_Second));
      $TargetDedicatedNodes=min(maxNumberofVMs, pendingTaskSamples);
    EOF
  }
}

Container Support

Enable container support in your Batch pool:

resource "azurerm_batch_pool" "batch_pool" {
  # ... other configurations ...

  container_configuration {
    type = "DockerCompatible"
    container_registries {
      registry_server = "myregistry.azurecr.io"
      user_name      = "username"
      password       = "password"
    }
  }
}

Best Practices

1. Always use auto-scaling to optimize costs
2. Implement proper monitoring and logging
3. Use managed identities for enhanced security
4. Regularly update node agent and VM images
5. Implement proper error handling and retry logic

Security Considerations

1. Use Azure Key Vault to store sensitive information
2. Implement network security groups
3. Use managed identities instead of service principals
4. Enable Azure Monitor for monitoring and alerting
5. Regularly audit access and permissions

Monitoring and Logging

Configure monitoring for your Batch account:

resource "azurerm_monitor_diagnostic_setting" "batch_diagnostics" {
  name                       = "batch-diagnostics"
  target_resource_id        = azurerm_batch_account.batch_account.id
  log_analytics_workspace_id = azurerm_log_analytics_workspace.workspace.id

  log {
    category = "ServiceLog"
    enabled  = true
  }

  metric {
    category = "AllMetrics"
    enabled  = true
  }
}

Conclusion

Azure Batch with Terraform provides a powerful way to manage large-scale computing workloads. By following these best practices and configurations, you can create efficient and secure batch processing environments.