Blueprint

LoRA multi-tenant inference serving

A serving approach for multi-tenant workloads where shared base models and LoRA adapters are combined without breaking isolation.

Problem

Multi-tenant GenAI systems often need customization without duplicating the full model per tenant. LoRA-based serving reduces footprint, but introduces operational questions around loading strategy, isolation, and tenant-level observability.

Serving pattern

One shared base model pool
Controlled adapter loading and eviction
Per-tenant routing and quotas
Audit trail for adapter use

Operational risks

Cold adapter loads, noisy neighbors, and quota leaks can erase the benefits if they are not observed and controlled.