NVIDIA DSX OS

NVIDIA DSX OS

Open, modular software for AI factory operations.

Overview

The Operating Layer for AI Factories

Bringing an AI factory into production requires infrastructure and platform teams to connect hardware provisioning, networking, Kubernetes, GPU management, workload scheduling, inference services, security, monitoring, and recovery. Building and operating each layer separately can slow deployment, leave valuable capacity underused, and make failures harder to resolve.

NVIDIA DSX OS™ brings these capabilities together through an open, modular software portfolio. It helps operators bring infrastructure online, maintain a consistent runtime, improve GPU utilization, automate fleet health, and deliver production AI services reliably at scale.

Adopt the components that address immediate requirements, integrate them with your existing environment, and expand as your infrastructure and services grow.

Features

One Modular Software Portfolio for AI Factory Operations

DSX OS provides modular capabilities for bringing accelerated infrastructure online, running AI workloads, and maintaining productive capacity through day-two operations.

Provision and Manage AI Infrastructure

Automate bare-metal lifecycle operations and manage networking, DPUs, switches, and rack-level systems across multi-tenant GPU environments.

Detect, Remediate, and Recover

Validate cluster readiness, monitor fleet health, isolate affected nodes, automate remediation, and return infrastructure to service.

Establish a Consistent Cluster Runtime

Deploy and maintain a validated NVIDIA-accelerated Kubernetes foundation with operators for GPU and networking resources and visibility into physical cluster topology.

Orchestrate AI Workloads and Services

Allocate GPU resources, place distributed workloads, and deploy scalable AI services across accelerated Kubernetes clusters.

Benefits

Improve the Economics of Operating AI Factories

DSX OS helps providers bring infrastructure online faster, increase productive use of accelerated capacity, and operate AI services reliably across multi-tenant environments.

Accelerate Time to Revenue

Reuse modular infrastructure and platform software instead of rebuilding foundational operating capabilities for every environment.

Bring clusters online, validate readiness, and begin delivering AI services faster.

Make More Productive Use of GPU Capacity

Match GPU capacity to workload demand through intelligent scheduling, resource allocation, topology-aware placement, and service orchestration.

Increase Reliability and Resiliency

Maintain runtime consistency, monitor fleet health, identify failures, protect workloads, automate remediation, and return affected capacity to service.

Move operations from reactive alerting toward an automated health-and-recovery lifecycle

Scale Secure Multi-Tenant Operations

Manage infrastructure lifecycles, verify platform integrity, orchestrate resources, and deliver AI services across tenants and clusters.

Adopt individual components or combine capabilities as operational requirements grow.

Starting Options

Start With the Capability Your AI Factory Needs

DSX OS is designed for incremental adoption. Begin with a focused operational requirement and expand over time.

Bring Infrastructure Online

Use NVIDIA Infra Controller and related infrastructure-management software to provision and manage multi-tenant GPU infrastructure.

Establish a Validated Runtime

Use AI Cluster Runtime, NVIDIA GPU Operator, NVIDIA Network Operator, Topograph, and NVIDIA Cluster Readiness Engine to create and validate an accelerated Kubernetes foundation.

Improve Fleet Health and Recovery

Use NVIDIA Fleet Intelligence, NVSentinel, and NVIDIA Cluster Readiness Engine to monitor infrastructure health, detect faults, and automate remediation.

Deploy Distributed Inference

Use NVIDIA Dynamo, Grove, and NVIDIA Cloud Functions to deploy and scale production inference services across accelerated infrastructure.

Resources

The Latest From the NVIDIA DSX Ecosystem

Next Steps

Start Building With DSX OS

Explore the complete portfolio, choose the capabilities that match your environment, and follow the linked documentation and open source projects to begin evaluating DSX OS.

Build an AI-Ready Foundation

Use NVIDIA AI Cluster Runtime as a validated foundation for accelerated Kubernetes, and then add the GPU and network operators, cluster readiness validation, and health automation your environment needs.

Deploy Production Inference

Use NVIDIA Dynamo to build and scale modular distributed inference services on Kubernetes.

FAQs

NVIDIA DSX OS™ is an open, modular software portfolio for building, operating, and scaling multi-tenant AI factory infrastructure. It includes open-source components and related NVIDIA technologies for platform and infrastructure operations.

Bringing an AI factory into production requires infrastructure and platform teams to coordinate hardware provisioning, networking, Kubernetes, GPU management, workload scheduling, inference services, security, monitoring, and recovery. Operating these layers separately can slow deployment, leave capacity underused, and complicate failure recovery. DSX OS provides modular technologies that can be integrated into existing platforms and software stacks.

DSX OS is modular and designed for incremental adoption. Organizations can start with the components that address their immediate operational requirements, integrate them with existing software stacks, and add capabilities as their infrastructure and services grow.

DSX OS platform software includes KAI Scheduler, Karta, NVIDIA Run:ai, NVIDIA Cloud Functions (NVCF), Grove, and NVIDIA Dynamo. These components support workload scheduling and GPU orchestration, service orchestration, and distributed inference.

DSX OS infrastructure software includes NVIDIA GPU Operator, NVIDIA Network Operator, Topograph, NVIDIA AI Cluster Runtime, NVIDIA Infra Controller (NICo), NVIDIA DOCA Platform Framework (DPF), NVIDIA Switch Infrastructure - Config Manager, and NVIDIA Rack Management Service. Together, these components support cluster runtime, topology awareness, bare-metal provisioning, multi-tenant lifecycle operations, and rack and network infrastructure management.

NVIDIA Cluster Readiness Engine supports cluster burn-in certification, orchestrated benchmarking, and hardware-failure detection. NVIDIA Fleet Intelligence provides real-time insights into GPU fleet health and integrity. NVIDIA NVSentinel provides Kubernetes-native GPU monitoring and fault remediation.

Implementation guidance, quick starts, reference designs, and links to open-source projects are available in the NVIDIA DSX documentation.