1. Isolated Network Group for AI Research with Private DNS


    To achieve an isolated network group designed for AI research with a private DNS, you can use Pulumi to orchestrate cloud resources that support creating virtual networks with restricted access and private naming resolution. The primary components you would need for such a setup include:

    1. A virtual network (VNet) to create an isolated network space in which your AI research can be conducted without exposure to the public internet.
    2. Subnets within the VNet to further divide and organize your network into segments based on the different components of your AI research workloads.
    3. Network security groups (NSGs) for each subnet to define inbound and outbound security rules that control traffic flow to and from resources in the subnet.
    4. A private DNS zone to manage and resolve domain names within the isolated network without registering these domains in the public DNS system.

    Assuming you're using Azure for hosting your infrastructure, you can use the azure-native Pulumi Python SDK to create these resources. Here, we're building the necessary infrastructure within Azure:

    • azure-native.network.VirtualNetwork: Creates a new virtual network.
    • azure-native.network.Subnet: Defines subnets within the virtual network.
    • azure-native.network.NetworkSecurityGroup: Establishes network security groups.
    • azure-native.network.PrivateZone: Sets up a private DNS zone.

    Here's a Pulumi program written in Python that illustrates how to create an isolated network group with a private DNS for your AI research:

    import pulumi import pulumi_azure_native.network as network # Initialize resource group resource_group = network.ResourceGroup("ai_research_resource_group") # Create a virtual network virtual_network = network.VirtualNetwork( "ai_research_vnet", resource_group_name=resource_group.name, address_space=network.AddressSpaceArgs( address_prefixes=[""] ) ) # Create a subnet for the AI research workloads ai_research_subnet = network.Subnet( "ai_research_subnet", resource_group_name=resource_group.name, virtual_network_name=virtual_network.name, address_prefix="" ) # Create a network security group for the AI research subnet ai_research_nsg = network.NetworkSecurityGroup( "ai_research_nsg", resource_group_name=resource_group.name, security_rules=[network.SecurityRuleArgs( name="AllowSSH", priority=100, access="Allow", direction="Inbound", protocol="Tcp", source_port_range="*", destination_port_range="22", source_address_prefix="VirtualNetwork", destination_address_prefix="*" )] ) # Associate the network security group with the AI research subnet ai_research_subnet_nsg_association = network.SubnetNetworkSecurityGroupAssociation( "ai_research_subnet_nsg_association", subnet_name=ai_research_subnet.name, network_security_group_id=ai_research_nsg.id, resource_group_name=resource_group.name, virtual_network_name=virtual_network.name, ) # Create a private DNS zone, which will not be accessible outside of the VNet private_dns_zone = network.PrivateZone( "ai_research_dns_zone", resource_group_name=resource_group.name, location="global", private_zone_name="research.ai.internal" ) # Output the resource ids pulumi.export("resource_group_id", resource_group.id) pulumi.export("virtual_network_id", virtual_network.id) pulumi.export("ai_research_subnet_id", ai_research_subnet.id) pulumi.export("ai_research_nsg_id", ai_research_nsg.id) pulumi.export("private_dns_zone_id", private_dns_zone.id)

    This program initializes a resource group, which is a container that holds related resources for an Azure solution. Inside the resource group, we create a virtual network that provides a private IP space for your resources.

    Subnets are created within the VNet to organize your services, and each subnet can be associated with a network security group to control traffic flow. The network security group created in this program contains an inbound rule allowing SSH access only from within the virtual network, thereby limiting access to resources located in the subnet.

    A private DNS zone is also provisioned to allow for the resolution of domain names within the VNet. This lets you use friendly domain names instead of IP addresses to communicate between services in your AI research environment.

    The resulting infrastructure is a well-isolated network suitable for sensitive AI research, protected from public internet access and with private DNS ensuring secure and private name resolution.