Multi-Tenant LLM Hosting

Host many teams/customers on shared inference infrastructure without sacrificing security, performance, or cost governance.

When to Use This Skill

• Building an internal LLM platform shared by multiple teams
• Hosting LLM inference for external customers with isolation requirements
• Implementing per-tenant quotas, billing, and rate limiting
• Designing request routing for multi-model, multi-tenant environments
• Preventing noisy-neighbor issues on shared GPU infrastructure

Prerequisites

• Kubernetes cluster with GPU node pools
• API gateway or LLM gateway (LiteLLM, Envoy, Kong)
• Prometheus + Grafana for per-tenant observability
• Redis or equivalent for rate limiting state
• Billing system or cost attribution database