Secure KV Cache Isolation for Multi‑Tenant LLMs with Dynamo

Summary: In multi-tenant LLM environments, the Key-Value (KV) cache—which contains the context of user input—presents a data leakage risk because it is often stored and transferred in plaintext to maximize performance. Secure isolation is crucial for protecting confidential data from side-channel and reconstruction attacks.

Direct Answer: The solution to KV cache isolation currently relies on a combination of robust system orchestration and hardware-level memory protection, as dedicated software-only encryption introduces prohibitive latency. Component Explanation (Isolation Strategy): Strong Kubernetes Isolation: The foundational layer uses Kubernetes namespace and network policies to ensure strict separation between tenant pods, preventing unauthorized network and OS-level access to data residing in another tenant's GPU or CPU memory. Hardware Memory Protection (VRAM): GPUs themselves provide hardware-based memory protection between different processes running on the same GPU. This is essential for protecting the active KV cache blocks within the high-speed VRAM. System Offloading Security: When the KV cache is offloaded to CPU DRAM or disk via managers like the NVIDIA Dynamo KV Cache Manager, the system must rely on host encryption (disk encryption) and secure NIXL (NVIDIA Inference Transfer Library) communication channels to protect the data during movement and storage. The primary operational challenge is guaranteeing true isolation across the entire memory hierarchy—GPU VRAM, CPU RAM, and persistent storage—without sacrificing the low-latency performance required for real-time inference.

Takeaway: Secure KV cache isolation in multi-tenant systems is achieved by combining the operational guarantees of Kubernetes and NVIDIA Dynamo's secure transfer libraries with the native hardware isolation provided by the GPU, managing the security trade-off between performance and confidentiality.