Allocating Public IP Addresses for Azure VMs Hosting AI Workloads

Question

Pulumi · Accepted Answer

Allocating public IP addresses for Azure VMs is a common task when setting up infrastructure for AI workloads that need to be accessible over the internet. In Azure, Public IP addresses can be used to communicate with your VMs from outside the Azure network.

Here we will create a Pulumi program in Python that allocates a static public IP address and associates it with an Azure VM. We are going to use two main resources for this task:

- `PublicIPAddress` from the `azure-native` package, which creates a public IP address.
- `NetworkInterface` from the `azure-native` package, which creates a network interface.

First, we need to install the necessary Pulumi Azure Native SDK. This can be done by running `pip install pulumi-azure-native`.

Now, let's write the Pulumi program:

```python
import pulumi
from pulumi_azure_native import resources, network, compute

# Configuring a new resource group
resource_group = resources.ResourceGroup("resource_group")

# Creating a public IP address
public_ip = network.PublicIPAddress(
    "public_ip",
    resource_group_name=resource_group.name,
    location=resource_group.location,
    public_ip_allocation_method=network.IPAllocationMethod.STATIC,
    sku=network.PublicIPAddressSkuArgs(
        name=network.PublicIPAddressSkuName.STANDARD,
    ),
    tags={"purpose": "ai_workloads"}
)

# Creating a network interface for the VM
net_interface = network.NetworkInterface(
    "net_interface",
    resource_group_name=resource_group.name,
    location=resource_group.location,
    ip_configurations=[network.NetworkInterfaceIPConfigurationArgs(
        name='ipconfig1',
        subnet=network.SubnetArgs(id=subnet_id),  # Replace 'subnet_id' with the actual subnet ID
        private_ip_allocation_method=network.IPAllocationMethod.DYNAMIC,
        public_ip_address=network.PublicIPAddressArgs(id=public_ip.id)
    )]
)

# Creating the VM
vm = compute.VirtualMachine(
    "vm",
    resource_group_name=resource_group.name,
    location=resource_group.location,
    network_profile=compute.NetworkProfileArgs(
        network_interfaces=[
            compute.NetworkInterfaceReferenceArgs(
                id=net_interface.id,
                primary=True,
            )
        ]
    ),
    # Other required VM properties like OS profile, Hardware profile, etc. need to be defined here
)

# Expose the public IP address as a stack output
pulumi.export('public_ip_address', public_ip.ip_address)
```

In this program:

1. We create a new resource group for our resources called `resource_group`.
2. We allocate a new public IP with `PublicIPAddress`, specifying it to use the STATIC allocation method. For production AI workloads, you typically use a static IP.
3. We define a network interface by creating a `NetworkInterface` with a dynamic private IP and associating the previously created public IP to it.
4. We create an Azure VM and associate it with the network interface created in the previous step.
5. Finally, we export the public IP address so that it can be easily retrieved after deployment.

In a real-world scenario, you'd require a pre-existing virtual network and subnet to which the network interface will attach. You would replace `subnet_id` with the ID of your existing subnet. Additionally, more details would be needed to fully define the Virtual Machine, such as the OS profile and hardware profile.

Remember to fill in the required parameters for the VM that have been omitted in this example (such as `os_profile`, `storage_profile`, `hardware_profile`, etc.), according to the specific requirements of your AI workloads.

Ensure that your Pulumi program aligns with your compliance and security standards, including appropriate tagging and naming conventions.