In this blog series, we’ll explore how Zadara is poised to bring the Software Reference Architecture for Multi-Tenant Inference Clouds to life. With NVIDIA’s blueprint for multi-tenant generative AI infrastructure now public, it’s time to examine how cloud providers can implement this vision in the real world.

Understanding NVIDIA’s Reference Architecture

NVIDIA’s software reference architecture is a comprehensive framework designed to deliver scalable, secure, and high-performance AI infrastructure. Its core components include:

True Multi-Tenancy: Complete isolation between customers across the full stack.

AI-Centric Infrastructure: Optimization for AI workloads, including inference, data processing, and orchestration layers.

Dynamic Resource Allocation: Ability to provision and scale resources per tenant and per workload.

Tenant-Controlled Kubernetes Environments: Each customer operates within their own Kubernetes control plane.

Support for Edge and Core Deployments: Architecture supports low-latency deployments near the user and centralized cloud operations.

Why Zadara is the Ideal Partner

Zadara’s cloud infrastructure is built from the ground up to meet NVIDIA’s recommendations. Here’s how:

Native Multi-Tenancy: Zadara offers built-in tenant isolation for compute, storage, and networking.

Full-Stack Workload Support: Zadara supports all AI/ML workloads, including databases, vector search engines, and Kubernetes control plane components.

Per-Tenant Kubernetes Environments: Zadara enables dedicated Kubernetes control planes per tenant.

Elastic Resource Allocation: Zadara allows dynamic allocation of compute, storage, and GPU resources.

Global Edge Presence: Zadara’s 500+ edge locations worldwide support low-latency inference and data residency requirements.