Traefik as API Gateway for Kubernetes-hosted LLMs

Question

Pulumi · Accepted Answer

To set up Traefik as an API Gateway for Kubernetes-hosted Language Model services (LLMs), you'll need to have a Kubernetes cluster running and then deploy Traefik within that cluster to handle the ingress traffic and route it to your services.

Here's a step-by-step guide to achieve this using Pulumi to define your infrastructure as code. We'll be using Pulumi with the Kubernetes provider, which will allow us to create and manage Kubernetes resources such as deployments, services, and ingresses.

To start, you need to install Pulumi CLI and configure Kubernetes as a provider. Ensure that you're logged into your Kubernetes cluster where you want to deploy Traefik.

Below is a Pulumi program that will:
- Create a namespace for Traefik.
- Deploy Traefik as a deployment within that namespace.
- Expose Traefik so it can receive external traffic.
- Set up an Ingress resource so that Traefik can route requests based on hostnames to different LLM services.

```python
import pulumi
from pulumi_kubernetes.apps.v1 import Deployment
from pulumi_kubernetes.core.v1 import Namespace, Service
from pulumi_kubernetes.networking.v1 import Ingress
from pulumi_kubernetes.networking.v1beta1 import IngressBackend, IngressRule
from pulumi_kubernetes.helm.v3 import Chart, ChartOpts

# Create a Kubernetes namespace specifically for Traefik resources.
traefik_namespace = Namespace("traefik-namespace", metadata={"name": "traefik"})

# Deploy Traefik using the Helm chart.
# We leverage Pulumi's Helm support which allows us to deploy existing Helm charts.
traefik_chart = Chart(
    "traefik-chart",
    config=ChartOpts(
        chart="traefik",
        version="9.18.2",
        fetch_opts={"repo": "https://helm.traefik.io/traefik"},
        namespace=traefik_namespace.metadata["name"],
        # Values from the chart's values.yaml can be overridden here.
        # For example, we might want to expose Traefik on a LoadBalancer service.
        values={
            "service": {
                "type": "LoadBalancer"
            }
        }
    ),
    opts=pulumi.ResourceOptions(namespace=traefik_namespace.metadata["name"])
)

# Expose Traefik via a LoadBalancer service.
traefik_service = Service(
    "traefik-service",
    metadata={
        "name": "traefik",
        "namespace": traefik_namespace.metadata["name"],
    },
    spec={
        "type": "LoadBalancer",
        "selector": {
            "app.kubernetes.io/name": "traefik"  # Match labels used by the Helm Chart for Traefik.
        },
        "ports": [
            {"protocol": "TCP", "port": 80},
            {"protocol": "TCP", "port": 443}
        ],
    }
)

# Define an Ingress for routing traffic to LLM services.
# This example assumes you have services named `llm-service-1` and `llm-service-2`,
# running in the namespaces `llm-namespace-1` and `llm-namespace-2`.
llm_ingress = Ingress(
    "llm-ingress",
    metadata={
        "name": "llm-ingress",
        "namespace": traefik_namespace.metadata["name"],
        "annotations": {
            # Traefik-specific annotations can be added here.
            "kubernetes.io/ingress.class": "traefik",
        },
    },
    spec={
        "rules": [
            IngressRule(
                host="llm-service-1.example.com",
                http={ "paths": [ { "path": "/", "backend": IngressBackend(service_name="llm-service-1", service_port=80) } ] }
            ),
            IngressRule(
                host="llm-service-2.example.com",
                http={ "paths": [ { "path": "/", "backend": IngressBackend(service_name="llm-service-2", service_port=80) } ] }
            )
        ]
    },
    opts=pulumi.ResourceOptions(namespace=traefik_namespace.metadata["name"])
)

# Export the external IP assigned to Traefik so we can easily access it.
pulumi.export("traefik_external_ip", traefik_service.status["load_balancer"]["ingress"][0]["ip"])
```

This code does the following:
- It sets up a namespace for Traefik for organizational purposes.
- It then uses the Helm Chart for Traefik to simplify its deployment on Kubernetes.
- It then creates a service of type `LoadBalancer` to expose Traefik to external traffic.
- Lastly, it sets up an `Ingress` resource that specifies how incoming requests to different hostnames (like those for your LLM services) should be routed to the appropriate Kubernetes services.

You'll need to tweak the `llm_ingress` resource to point to your actual LLM service names and namespaces. The assumption here is that you've already deployed your Language Model services within the Kubernetes cluster and they're accessible via services within their own namespaces.

Also, note that you might need to configure DNS records to point to the external IP address exposed by Traefik for hostname routing to work properly. The `pulumi.export` statement at the end of the program is used to output the external IP address of the Traefik service so that it can be easily retrieved.

After you write this script to a file (e.g., `traefik.py`), you can use the `pulumi up` command to provision these resources on your cluster. This program manages the setup of Traefik as your API gateway, providing a point of entry for traffic into your Kubernetes-hosted services.