inference-gateway-routing

Configure multi-tiered inference gateway routing for LLM providers on EKS.

18|4|Updated Apr 29, 2026
One-click install
npx skills add https://github.com/aws-samples/sample-oh-my-aidlcops --skill inference-gateway-routing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: inference-gateway-routing
Source: https://github.com/aws-samples/sample-oh-my-aidlcops/tree/main/plugins/ai-infra/skills/inference-gateway-routing
Command: npx skills add https://github.com/aws-samples/sample-oh-my-aidlcops --skill inference-gateway-routing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires kubectl, kgateway, bifrost, langfuse, otel-collector, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill configures and routes traffic through a two-tier inference gateway on EKS, integrating multiple LLM providers, and ensuring efficient inference with cascading and semantic routing.

Core Features & Use Cases

  • Cascading Routing: Implements a cascade of LLM providers to provide fallback options.
  • Semantic Routing: Allows the selection of models based on the intent detected.
  • HTTPRoute with Trace Propagation: Manages traffic routing to a Langfuse endpoint while enabling OpenTelemetry for trace propagation.
  • Use Case: An e-commerce company using multiple LLM providers wants to integrate them into a unified endpoint while ensuring the best cost-performance and maintaining traces for auditing.

Quick Start

Create a routing configuration to route requests to LLM providers using 'kubectl apply -f path/to/config.yaml'

Frequently Asked Questions about inference-gateway-routing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I configure cascading routing for multiple LLM providers on EKS?▼

To configure cascading routing for LLM providers on EKS, you can use this Skill to set up a multi-tiered inference gateway with Kubernetes Gateway API, providing automated fallback options across providers. It applies configurations via kubectl.

What is semantic routing for LLM inference and how does it work?▼

Semantic routing for LLM inference allows the dynamic selection of models based on the intent detected in the request. This Skill implements semantic routing within a multi-tiered gateway to direct requests to the appropriate provider.

How do I propagate OpenTelemetry traces through an inference gateway to Langfuse?▼

You propagate OpenTelemetry traces by configuring HTTPRoute resources to manage traffic routing to a Langfuse endpoint. This Skill sets up the necessary OTel trace propagation within the EKS inference gateway for auditing.

Do I need a pre-existing EKS cluster to set up a Kubernetes Gateway API for LLM traffic?▼

Yes, you need a pre-existing EKS cluster to use this Skill. It assumes you already have a Kubernetes and EKS environment deployed, and requires dependencies like kubectl, kgateway, and Bifrost to configure the gateway.

Can I unify multiple LLM providers into a single endpoint while maintaining cost-performance?▼

Yes, you can unify multiple LLM providers into a single endpoint while optimizing cost-performance. This Skill uses cascading and semantic routing to route traffic efficiently, which is ideal for e-commerce companies needing integrated LLM infrastructure.