Associating Resolver Rules for Large Model Training Clusters

Question

Pulumi · Accepted Answer

## Pulumi and AWS Route53 Resolver Rules

When working with large model training clusters in the cloud, domain name resolution within a virtual private cloud (VPC) is a common requirement. Training clusters often need to resolve domain names to internal services or to endpoints outside of the VPC. AWS provides a service called Route 53 Resolver which allows you to configure how DNS queries are resolved for your VPC.

Route 53 Resolver Rules are custom DNS rules that determine how DNS queries are routed. They can be used to forward queries to resolvers in your on-premises networks or to forward queries between VPCs. By associating these rules with your VPC, you instruct AWS on how to handle DNS resolution.

In a scenario where you have a large model training cluster, you might need these Resolver Rules to ensure that your machine learning application can access the necessary datasets and services, whether they are located within AWS or elsewhere.

Let's use Pulumi to create and associate a Route 53 Resolver Rule with a VPC. We'll be using the `pulumi_aws` SDK for this.

### Program Explanation and Setup

Here's what we are going to do:

1. **Create a VPC**: Our resources will live in this VPC.
2. **Create a Route 53 Resolver Rule**: This specifies how certain DNS queries are handled.
3. **Associate the Resolver Rule with the VPC**: This applies our rule to the VPC.

We'll start by setting up the necessary environment and importing the required packages. Then, we'll define our resources.

```python
import pulumi
import pulumi_aws as aws

# Assume that we have an existing VPC or create a new one
vpc = aws.ec2.Vpc.get("existing-vpc", "vpc-123456")  # Replace with your VPC ID

# Create a Resolver Rule that specifies the DNS queries for a specific domain
# (e.g., internal.example.com) to be resolved via custom IP addresses
resolver_rule = aws.route53.ResolverRule("trainingClusterResolverRule",
    domain_name="internal.example.com",   # The domain name to be resolved
    rule_type="FORWARD",                  # Forward the queries to another resolver
    target_ips=[                          # The IPs to forward the queries to
        aws.route53.types.ResolverRuleTargetIp(ip="123.45.67.89"),  
        # Add additional resolver IPs if needed
    ],
    resolver_endpoint_id="rslvr-out-f1234567890abcdef0",  # The resolver to use (get this from your AWS console or another Pulumi resource)
)

# Associate the Resolver Rule with our VPC
rule_association = aws.route53.ResolverRuleAssociation("trainingClusterRuleAssoc",
    resolver_rule_id=resolver_rule.id,
    vpc_id=vpc.id,  # Associate with our VPC
)
```

In the `resolver_rule` variable, we create a new DNS resolver rule. We specify the domain name to forward and the IP addresses of the DNS resolvers to which we want to forward the queries. In this example, we set `rule_type` to `"FORWARD"` indicating that we're forwarding DNS queries. The `target_ips` is a list that can include multiple custom resolver IP addresses.

You also need a Resolver Endpoint, which is represented by `resolver_endpoint_id`. The endpoint contains the IP addresses the Resolver uses to query outward. It must exist beforehand or be created in a separate step.

Finally, we use the `aws.route53.ResolverRuleAssociation` to link our resolver rule to the VPC. We pass it the ID of the resolver rule we just created (`resolver_rule.id`) and the ID of our VPC.

After setting up this configuration, when an instance in the associated VPC makes a DNS query for `internal.example.com`, it will be forwarded to the provided IP addresses for resolution.

To apply these changes to your AWS environment, save this program in a Python file, then run `pulumi up` using the Pulumi CLI. Pulumi will communicate with AWS to create and configure these resources for you.