OCI Route Tables for Secure AI Model Training Data Paths

Question

Pulumi · Accepted Answer

In Oracle Cloud Infrastructure (OCI), route tables are used to route network traffic from one subnet to other destinations. When setting up a secure path for AI model training data, you'll want to ensure that your route tables are configured properly to direct traffic to the correct services while maintaining security and privacy.

To implement route tables in OCI using Pulumi, you would use the `oci.Core.RouteTable` resource, which allows you to define routing rules for your virtual cloud network (VCN). These routing rules can direct the traffic from your subnet to services like NAT gateways, internet gateways, or other specialized services required for your AI data paths.

Below, we will write a Pulumi program that configures a VCN with a subnet and an associated route table. I'll include comments throughout the code to explain what each section does:

```python
import pulumi_oci as oci

# Create an OCI Virtual Cloud Network (VCN)
vcn = oci.core.VirtualNetwork(
    "aiTrainingVCN",
    cidr_block="10.0.0.0/16",  # This will be the IP range for the VCN
    compartment_id="ocid1.compartment.oc1..exampleuniqueID"  # Replace with your compartment OCID
)

# Create a Subnet within the VCN
subnet = oci.core.Subnet(
    "aiTrainingSubnet",
    vcn_id=vcn.id,
    cidr_block="10.0.1.0/24",  # Subnet range within the VCN. Must be a subset of the VCN CIDR.
    compartment_id=vcn.compartment_id,
)

# Define a route rule to direct traffic to a NAT Gateway for secure internet access
# Internet access might be required for downloading dependencies, AI models, or data sets.
nat_gateway = oci.core.NatGateway(
    "aiTrainingNAT",
    vcn_id=vcn.id,
    compartment_id=vcn.compartment_id,
)

# Create a route table with a rule to route traffic through the NAT Gateway
route_table = oci.core.RouteTable(
    "aiTrainingRouteTable",
    vcn_id=vcn.id,
    route_rules=[{
        # Assuming all traffic should be routed through the NAT Gateway
        'destination': "0.0.0.0/0",
        'destination_type': "CIDR_BLOCK",
        'network_entity_id': nat_gateway.id,
    }],
    compartment_id=vcn.compartment_id,
)

# Associate the route table with the subnet
oci.core.SubnetRouteTableAttachment(
    "aiTrainingSubnetRouteTableAttachment",
    subnet_id=subnet.id,
    route_table_id=route_table.id,
)

# The following lines export the VCN and Subnet IDs so they can be used in other parts of the program or reference
pulumi.export('vcn_id', vcn.id)
pulumi.export('subnet_id', subnet.id)
```

In this piece of code, we:

1. Create a VCN that will contain all the network resources.
2. Inside the VCN, we define a subnet where our AI training workloads would run.
3. We set up a NAT Gateway which allows resources that have private IP addresses in the VCN to access the internet without being directly exposed.
4. A route table is configured with a rule that directs all outbound traffic (`0.0.0.0/0`) through the NAT Gateway, providing controlled internet access to instances in the subnet.
5. Finally, we create a `SubnetRouteTableAttachment` which associates the route table with our subnet, ensuring that the defined routes are used by the subnet.

To use this code, make sure to replace the placeholder values with real values from your OCI environment, such as your Compartment ID, and customize the CIDR blocks and rules as per your actual network layout and security requirements.

After running this program using Pulumi CLI, your cloud environment will include a network setup supporting secure paths for your AI training data traffic. Remember to adhere to security best practices by whitelisting only required traffic and keeping the rest of the paths restricted.