NVIDIA Network Operator v25.7.0

Quick Start Guide for Kubernetes

Before deploying the NVIDIA Network Operator, ensure you have the following:

Prerequisites

  1. Kubernetes Cluster: A running Kubernetes cluster (v1.19+) with nodes that have NVIDIA NICs.

  2. CLI Tools: Install kubectl and helm on your client machine:

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    $ curl -fsSL -o get_helm.sh https://raw.githubusercontent.com/helm/helm/master/scripts/get-helm-3 \ && chmod 700 get_helm.sh \ && ./get_helm.sh

  3. Container Runtime: Nodes must be configured with a container engine such as CRI-O or containerd.

Add the NVIDIA NGC Helm repository:

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helm repo add nvidia https://helm.ngc.nvidia.com/nvidia helm repo update

Install the Network Operator:

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helm install network-operator nvidia/network-operator \ -n nvidia-network-operator \ --create-namespace \ --version v25.7.0 \ --set sriovNetworkOperator.enabled=true \ --wait

Verify the installation:

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kubectl -n nvidia-network-operator get pods

This quick start guide covers five essential networking configurations for different computational requirements:


Use Case

Purpose

Performance Requirements

Applications

SR-IOV Network with RDMA High-performance networking with hardware acceleration
  • >10 Gbps throughput
  • <1μs latency
  • Dedicated VF resources
HPC simulations, distributed ML training, financial trading Keywords: SR-IOV, RDMA, HPC, low-latency, VF isolation
Host Device Network with RDMA Direct hardware access for legacy applications
  • Raw device control
  • Exclusive hardware access
  • Minimal CPU overhead
Legacy HPC codes, specialized protocols, DPDK applications Keywords: host-device, PCI-passthrough, direct-access, exclusive-access
IP over InfiniBand with RDMA Shared Device InfiniBand networking with shared RDMA resources
  • >50 Gbps bandwidth
  • Parallel I/O workloads
  • Shared device efficiency
Distributed storage, data analytics, scientific computing Keywords: InfiniBand, IPoIB, shared-device, high-bandwidth
MacVLAN Network with RDMA Shared Device Network isolation with shared RDMA capabilities
  • Multi-tenant segmentation
  • 10+ pods per node
  • Moderate throughput
Cloud-native HPC, microservices, multi-tenant ML Keywords: MacVLAN, multi-tenant, network-segmentation, resource-sharing
SR-IOV InfiniBand Network with RDMA Virtualized InfiniBand with hardware acceleration
  • >100 Gbps bandwidth
  • Hardware acceleration
  • Isolated IB partitions
Large-scale HPC clusters, AI/ML training, research computing Keywords: SR-IOV, InfiniBand, hardware-acceleration, ultra-high-bandwidth
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© Copyright 2025, NVIDIA. Last updated on Aug 26, 2025.