Alauda AI

Configure External Access for Inference Services

TOC

Introduction

This document provides a step-by-step guide on how to configure external access for your inference services, including checking external access addresses, creating domains, setting up load balancers, and verifying the configuration.

Steps

1. View External Access Address of the Inference Service

You can:

  1. Navigate to the service details page and copy the address from the Access Method card, or
  2. View the address in the YAML card under status.url.

2. Create a Domain

In the Administrator Console, go to Network > Domains, and then click Create Domain.

  • In the Domain field, enter the external access address of your inference service.
  • For Allocated To (Cluster), select the cluster where your service is located.
  • For Allocated Projects, choose the project where your inference service resides.

3. Create a Load Balancer

(One load balancer can be shared by multiple projects; create a new one only if necessary.)

In the Administrator Console, go to Network > Load Balancers, and then click Create Load Balancer. For detailed help documentation, please refer to .

4. Configure the Load Balancer

In the Alauda Container Platform Console, navigate to Network > Load Balancers, then click the name of the load balancer you just created to enter its configuration page.

4.1 Add Listener Frontend Resources

Add listening ports: HTTP protocol on port 80, and HTTPS protocol on port 443. You can add more as needed.

4.2 Add Forwarding Rules Resources

  • Domains: Select the domain you created in the previous step.
  • ServiceGroup (Kubernetes Service): Select knative-ingressgateway in the istio-system namespace and choose port 80.

For more detailed parameter configurations, you can refer to .

5. Verify Access to the Inference Service via External Address

To verify that your inference service is accessible externally, use the curl command below. Remember to replace the placeholders with your actual load balancer IP address, port, and inference service address.

# For HTTP
curl -v --resolve "your-inference-service-domain.com:your-port:your-load-balancer-ip" \
    http://your-inference-service-domain.com/v1/models

# For HTTPS (skip `-k` if you have a valid certificate)
curl -vk --resolve "your-inference-service-domain.com:443:your-load-balancer-ip" \
    https://your-inference-service-domain.com/v1/models

Here's what each part of the command means and what you need to replace:

  • your-inference-service-domain.com: This should be the domain name you created for your inference service (e.g., qwen2-0b5-kubeflow-admin-cpaas-io.my-company.com).
  • your-port: This is the port your load balancer is listening on for HTTP traffic (commonly 80).
  • your-load-balancer-ip: This is the actual IP address of your load balancer (e.g., 192.168.137.21).

If the request successfully returns the model list, your configuration is complete! If it fails, double-check your load balancer settings or review the inference service logs to pinpoint the problem.