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Technology Preview for DPF deployment with NVIDIA DOCA SNAP service

Created on May 29, 2025

Scope

This Technology Preview (TP) guide offers comprehensive instructions for deploying the NVIDIA DOCA SNAP service within a Kubernetes cluster using the DOCA Platform Framework. It details the step-by-step process for configuring the NVIDIA DOCA SNAP service over both TCP and RDMA transports on NVIDIA BlueField-3 DPUs.

This guide is designed for experienced system administrators, system engineers, and solution architects looking to provision Kubernetes pods with emulated PCIe block devices backed by networked storage. We will take full advantage of NVIDIA DPU hardware acceleration and offload capabilities, maximizing datacenter workload efficiency and performance.

Note

This reference implementation, as the name implies, is a specific, opiniated deployment example designed to address the usecase described above.
While other approaches may exist to implement similar solutions, this document provides a detailed guide for this particular method.

Abbreviations and Acronyms

Term	Definition	Term	Definition
BFB	BlueField Bootstream	OVN	Open Virtual Network
BGP	Border Gateway Protocol	PVC	Persistent Volume Claim
CNI	Container Network Interface	RDG	Reference Deployment Guide
CRD	Custom Resource Definition	RDMA	Remote Direct Memory Access
CSI	Container Storage Interface	SF	Scalable Function
DOCA	Data Center Infrastructure-on-a-Chip Architecture	SFC	Service Function Chaining
DOCA SNAP	NVIDIA® DOCA™ Storage-Defined Network Accelerated Processing	SPDK	Storage Performance Development Kit
DPF	DOCA Platform Framework	SR-IOV	Single Root Input/Output Virtualization
DPU	Data Processing Unit	TOR	Top of Rack
DTS	DOCA Telemetry Service	VF	Virtual Function
GENEVE	Generic Network Virtualization Encapsulation	VLAN	Virtual LAN (Local Area Network)
HBN	Host Based Networking	VRR	Virtual Router Redundancy
IPAM	IP Address Management	VTEP	Virtual Tunnel End Point
K8S	Kubernetes	VXLAN	Virtual Extensible LAN
MAAS	Metal as a Service

Introduction

The NVIDIA BlueField-3 Data Processing Unit is a powerful infrastructure compute platform designed for high-speed processing of software-defined networking, storage, and cybersecurity. With a capacity of 400 Gb/s, BlueField-3 combines robust computing, high-speed networking, and extensive programmability to deliver hardware-accelerated, software-defined solutions for demanding workloads.

Deploying and managing DPUs and their associated DOCA services, especially at scale, can be quite challenging. Without a proper provisioning and orchestration system, handling the DPU lifecycle and configuring DOCA services place a heavy operational burden on system administrators. The NVIDIA DOCA Platform Foundation addresses this challenge by streamlining and automating the lifecycle management of DOCA services.

NVIDIA DOCA unlocks the full potential of the BlueField platform, enabling rapid development of applications and services that offload, accelerate, and isolate data center workloads. One such example is NVIDIA DOCA SNAP, a DPU storage service that is designed to accelerate and optimize storage protocol by leveraging the capabilities of NVIDIA's BlueField DPUs. NVIDIA DOCA SNAP technology encompasses a family of services that enable hardware-accelerated virtualization of local storage running on NVIDIA BlueField products. The SNAP services present networked storage as local block devices to the host, emulating local drives on the PCIe bus. At its core, DOCA SNAP enables high-performance, low-latency access to storage by allowing applications to interact directly with raw block devices - bypassing traditional filesystem overhead. As part of the DPF deployment model, the DOCA SNAP solution is composed of multiple functional components packaged into containers, which are deployed across both the x86 and DPU Kubernetes clusters.

This guide is similar to the RDG for DPF with OVN-Kubernetes and HBN Services document, which covers K8s cluster deployment with NVIDIA DOCA Host-Based Networking Service and OVN-Kubernetes CNI network plugin. In this guide, HBN enables the routing of OVN accelerated workload traffic together with storage protocol traffic on the server side by using BlueField as a BGP router.

This reference implementation leverages open-source components, and provides an end-to-end walkthrough of the deployment process, including:

Infrastructure provisioning with MAAS
Integration with NVIDIA’s DPF
Deployment and orchestration of DPU-based services inside the Kubernetes cluster
Configuration of BlueField devices with enabled NVMe emulation for DOCA SNAP service
Management of DPU resources and workloads using Kubernetes-native constructs

This guide provides a comprehensive, practical example of installing the DPF system with NVIDIA DOCA SNAP service on a Kubernetes cluster according to the "Storage Development Guide".

Info

In our guide we used the Storage Performance Development Kit (SPDK) as an example of storage backend service.

This storage backend service is used only for demonstration purposes and is not intended or supported for production usecases.

References

Solution Architecture

Key Components and Technologies

NVIDIA BlueField® Data Processing Unit (DPU)
The NVIDIA® BlueField® data processing unit (DPU) ignites unprecedented innovation for modern data centers and supercomputing clusters. With its robust compute power and integrated software-defined hardware accelerators for networking, storage, and security, BlueField creates a secure and accelerated infrastructure for any workload in any environment, ushering in a new era of accelerated computing and AI.

NVIDIA DOCA Software Framework
NVIDIA DOCA™ unlocks the potential of the NVIDIA® BlueField® networking platform. By harnessing the power of BlueField DPUs and SuperNICs, DOCA enables the rapid creation of applications and services that offload, accelerate, and isolate data center workloads. It lets developers create software-defined, cloud-native, DPU- and SuperNIC-accelerated services with zero-trust protection, addressing the performance and security demands of modern data centers.

NVIDIA ConnectX SmartNICs
10/25/40/50/100/200 and 400G Ethernet Network Adapters
The industry-leading NVIDIA® ConnectX® family of smart network interface cards (SmartNICs) offer advanced hardware offloads and accelerations.
NVIDIA Ethernet adapters enable the highest ROI and lowest Total Cost of Ownership for hyperscale, public and private clouds, storage, machine learning, AI, big data, and telco platforms.

NVIDIA LinkX Cables
The NVIDIA® LinkX® product family of cables and transceivers provides the industry’s most complete line of 10, 25, 40, 50, 100, 200, and 400GbE in Ethernet and 100, 200 and 400Gb/s InfiniBand products for Cloud, HPC, hyperscale, Enterprise, telco, storage and artificial intelligence, data center applications.

NVIDIA Spectrum Ethernet Switches
Flexible form-factors with 16 to 128 physical ports, supporting 1GbE through 400GbE speeds.
Based on a ground-breaking silicon technology optimized for performance and scalability, NVIDIA Spectrum switches are ideal for building high-performance, cost-effective, and efficient Cloud Data Center Networks, Ethernet Storage Fabric, and Deep Learning Interconnects.
NVIDIA combines the benefits of NVIDIA Spectrum^™ switches, based on an industry-leading application-specific integrated circuit (ASIC) technology, with a wide variety of modern network operating system choices, including NVIDIA Cumulus^® Linux , SONiC and NVIDIA Onyx^®.

NVIDIA Cumulus Linux
NVIDIA® Cumulus® Linux is the industry's most innovative open network operating system that allows you to automate, customize, and scale your data center network like no other.

NVIDIA Network Operator
The NVIDIA Network Operator simplifies the provisioning and management of NVIDIA networking resources in a Kubernetes cluster. The operator automatically installs the required host networking software - bringing together all the needed components to provide high-speed network connectivity. These components include the NVIDIA networking driver, Kubernetes device plugin, CNI plugins, IP address management (IPAM) plugin and others. The NVIDIA Network Operator works in conjunction with the NVIDIA GPU Operator to deliver high-throughput, low-latency networking for scale-out, GPU computing clusters.

Kubernetes
Kubernetes is an open-source container orchestration platform for deployment automation, scaling, and management of containerized applications.

Kubespray
Kubespray is a composition of Ansible playbooks, inventory, provisioning tools, and domain knowledge for generic OS/Kubernetes clusters configuration management tasks and provides:
- A highly available cluster
- Composable attributes
- Support for most popular Linux distributions

OVN-Kubernetes
OVN-Kubernetes (Open Virtual Networking - Kubernetes) is an open-source project that provides a robust networking solution for Kubernetes clusters with OVN (Open Virtual Networking) and Open vSwitch (Open Virtual Switch) at its core. It is a Kubernetes networking conformant plugin written according to the CNI (Container Network Interface) specifications.

RDMA
RDMA is a technology that allows computers in a network to exchange data without involving the processor, cache or operating system of either computer.
Like locally based DMA, RDMA improves throughput and performance and frees up compute resources.

Solution Design

Solution Logical Design

The logical design includes the following components:

1 x Hypervisor node (KVM based) with ConnectX-7
- 1 x Firewall VM
- 1 x Jump VM
- 1 x MAAS VM
- 3 x VMs running all K8s management components for Host/DPU clusters
2 x Worker nodes, each with a 1 x BlueField-3 NIC
Storage Target Node with ConnectX-7 and SPDK target apps
Single 200 GbE High-Speed (HS) switch
1 GbE Host Management network

image-2025-5-27_18-43-28-version-1-modificationdate-1748360607113-api-v2.png

SFC Logical Diagram

The DOCA Platform Framework simplifies DPU management by providing orchestration through a K8s API. It handles the provisioning and lifecycle management of DPUs, orchestrates specialized DPU services, and automates service function chaining (SFC) tasks. This ensures seamless deployment of NVIDIA DOCA services and OVN-Kubernetes CNI, allowing traffic to be efficiently offloaded and routed through HBN's data plane. The SFC logical diagram implemented in this guide is shown below.

image-2025-5-25_15-0-2-version-1-modificationdate-1748174402680-api-v2.png

Disk Emulation Logical Diagram

The following logical diagram demonstrates the main components involved in a disk mount procedure to tenant workload pod.

Upon receiving a new request for an emulated NVMe drive, DOCA SNAP components bring a block device (BDEV) via NVMe-oF using either RDMA or TCP storage protocols to the required K8s worker node. The DPU then emulates it as a block device on the x86 host via the "BlueField NVMe SNAP Controller" .

image-2025-5-25_15-22-19-version-1-modificationdate-1748175739603-api-v2.png

Firewall Design

The pfSense firewall in this solution serves a dual purpose:

Firewall – Provides an isolated environment for the DPF system, ensuring secure operations
Router – Enables internet access and connectivity between the host management network and the high-speed network

Port-forwarding rules for SSH and RDP are configured on the firewall to route traffic to the jump node’s IP address in the host management network. From the jump node, administrators can manage and access various devices in the setup, as well as handle the deployment of the Kubernetes (K8s) cluster and DPF components.
The following diagram illustrates the firewall design used in this solution:

image-2025-5-6_11-12-39-1-version-1-modificationdate-1746519159413-api-v2.png

Software Stack Components

image-2025-5-27_18-25-38-1-version-1-modificationdate-1748359537010-api-v2.png

Warning

Make sure to use the exact same versions for the software stack as described above.

Bill of Materials

image-2025-5-25_15-47-1-1-version-1-modificationdate-1748177221630-api-v2.png

Deployment and Configuration

Node and Switch Definitions

These are the definitions and parameters used for deploying the demonstrated fabric:

Switch Port Usage
`mgmt-switch`	1	swp1-4
`hs-switch`	1	swp1,11-14,32

Hosts
Rack	Server Type	Server Name	Switch Port	IP and NICs	Default Gateway
Rack1	Hypervisor Node	`hypervisor`	mgmt-switch: `swp1` hs-switch: `swp1`	lab-br (interface eno1): Trusted LAN IP mgmt-br (interface eno2): - hs-br (interface ens2f0np0):	Trusted LAN GW
Rack1	Storage Target Node	`target`	mgmt-switch: `swp4` hs-switch: `swp32`	enp1s0f0: 10.0.110.25/24 enp144s0f0np0: 10.0.124.1/24	10.0.110.254
Rack1	Worker Node	`worker1`	mgmt-switch: `swp2` hs-switch: `swp11`-`swp12`	ens15f0: 10.0.110.21/24 ens5f0np0/ens5f1np1: 10.0.120.0/22	10.0.110.254
Rack1	Worker Node	`worker2`	mgmt-switch: `swp3` hs-switch: `swp13`-`swp14`	ens15f0: 10.0.110.22/24 ens5f0np0/ens5f1np1: 10.0.120.0/22	10.0.110.254
Rack1	Firewall (Virtual)	`fw`	-	WAN (lab-br): Trusted LAN IP LAN (mgmt-br): 10.0.110.254/24 OPT1 (hs-br): 172.169.50.1/30	Trusted LAN GW
Rack1	Jump Node (Virtual)	`jump`	-	enp1s0: 10.0.110.253/24	10.0.110.254
Rack1	MAAS (Virtual)	`maas`	-	enp1s0: 10.0.110.252/24	10.0.110.254
Rack1	Master Node (Virtual)	`master1`	-	enp1s0: 10.0.110.1/24	10.0.110.254
Rack1	Master Node (Virtual)	`master2`	-	enp1s0: 10.0.110.2/24	10.0.110.254
Rack1	Master Node (Virtual)	`master3`	-	enp1s0: 10.0.110.3/24	10.0.110.254

Wiring

Hypervisor Node

image-2025-6-8_15-6-14-1-version-1-modificationdate-1749384373477-api-v2.png

K8s Worker Node

image-2025-6-8_15-5-2-1-version-1-modificationdate-1749384300957-api-v2.png

Storage Target Node

image-2025-6-8_15-5-42-1-version-1-modificationdate-1749384341380-api-v2.png

Fabric Configuration

Updating Cumulus Linux

As a best practice, make sure to use the latest released Cumulus Linux NOS version.

For information on how to upgrade Cumulus Linux, refer to the Cumulus Linux User Guide.

Configuring the Cumulus Linux Switch

The SN3700 switch (hs-switch), is configured as follows:

Info

The following commands configure BGP unnumbered on hs-switch.
Cumulus Linux enables the BGP equal-cost multipathing (ECMP) option by default.

SN3700 Switch Console

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            nv set bridge domain br_default vlan 10 vni 10
nv set evpn enable on
nv set interface lo ip address 11.0.0.101/32
nv set interface lo type loopback
nv set interface swp1 ip address 172.169.50.2/30
nv set interface swp1 link speed auto
nv set interface swp1-32 type swp
nv set interface swp32 bridge domain br_default access 10
nv set nve vxlan enable on
nv set nve vxlan source address 11.0.0.101
nv set qos roce enable on
nv set qos roce mode lossless
nv set router bgp autonomous-system 65001
nv set router bgp enable on
nv set router bgp graceful-restart mode full
nv set router bgp router-id 11.0.0.101
nv set system hostname hs-switch
nv set vrf default router bgp address-family ipv4-unicast enable on
nv set vrf default router bgp address-family ipv4-unicast redistribute connected enable on
nv set vrf default router bgp address-family ipv4-unicast redistribute static enable on
nv set vrf default router bgp address-family ipv6-unicast enable on
nv set vrf default router bgp address-family ipv6-unicast redistribute connected enable on
nv set vrf default router bgp address-family l2vpn-evpn enable on
nv set vrf default router bgp enable on
nv set vrf default router bgp neighbor swp11 peer-group hbn
nv set vrf default router bgp neighbor swp11 type unnumbered
nv set vrf default router bgp neighbor swp12 peer-group hbn
nv set vrf default router bgp neighbor swp12 type unnumbered
nv set vrf default router bgp neighbor swp13 peer-group hbn
nv set vrf default router bgp neighbor swp13 type unnumbered
nv set vrf default router bgp neighbor swp14 peer-group hbn
nv set vrf default router bgp neighbor swp14 type unnumbered
nv set vrf default router bgp path-selection multipath aspath-ignore on
nv set vrf default router bgp peer-group hbn address-family l2vpn-evpn enable on
nv set vrf default router bgp peer-group hbn remote-as external
nv set vrf default router static 0.0.0.0/0 address-family ipv4-unicast
nv set vrf default router static 0.0.0.0/0 via 172.169.50.1 type ipv4-address
nv set vrf default router static 10.0.110.0/24 address-family ipv4-unicast
nv set vrf default router static 10.0.110.0/24 via 172.169.50.1 type ipv4-address
 
nv config apply -y

The SN2201 switch (mgmt-switch) is configured as follows:

SN2201 Switch Console

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            nv set bridge domain br_default untagged 1
nv set interface swp1-4 link state up
nv set interface swp1-4 type swp
nv set interface swp1-4 bridge domain br_default
nv config apply -y

Host Configuration

Warning

Make sure that the BIOS settings on the worker node servers have SR-IOV enabled and that the servers are tuned for maximum performance.

Warning

All worker nodes must have the same PCIe placement for the BlueField-3 DPUs and must show the same interface name.

Hypervisor Installation and Configuration

The hypervisor used in this guide is based on Ubuntu 24.04 with KVM.

While this document does not detail the KVM installation process, it is important to note that the setup requires the following ISOs to deploy the Firewall, Jump, and MAAS virtual machines (VMs):

Ubuntu 24.04
pfSense-CE-2.7.2

To implement the solution, three Linux bridges must be created on the hypervisor:

Note

Ensure a DHCP record is configured for the lab-br bridge interface in your trusted LAN to assign it an IP address.

lab-br – connects the Firewall VM to the trusted LAN.
mgmt-br – Connects the various VMs to the host management network.
hs-br – Connects the Firewall VM to the high-speed network.

Additionally, an MTU of 9000 must be configured on the management and high-speed bridges (mgmt-br and hs-br) as well as their uplink interfaces to ensure optimal performance.

Hypervisor netplan configuration

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            network:
    ethernets:
        eno1:
            dhcp4: false
        eno2:
            dhcp4: false
            mtu: 9000
        ens2f0np0:
            dhcp4: false
            mtu: 9000
    bridges:
      lab-br:
         interfaces: [eno1]
         dhcp4: true
      mgmt-br:
         interfaces: [eno2]
         dhcp4: false
         mtu: 9000
      hs-br:
         interfaces: [ens2f0np0]
         dhcp4: false
         mtu: 9000
    version: 2

Apply the configuration:

Hypervisor Console

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            $ sudo netplan apply

Prepare Infrastructure Servers

Firewall VM - pfSense Installation and Interface Configuration

Download the pfSense CE (Community Edition) ISO to your hypervisor and proceed with the software installation.

Suggested spec:

vCPU: 2
RAM: 2GB
Storage: 10GB
Network interfaces
- Bridge device connected to lab-br
- Bridge device connected to mgmt-br
- Bridge device connected to hs-br

The Firewall VM must be connected to all three Linux bridges on the hypervisor. Before beginning the installation, ensure that three virtual network interfaces of type "Bridge device" are configured. Each interface should be connected to a different bridge (lab-br, mgmt-br, and hs-br) as illustrated in the diagram below.

FW_VM_NIC-version-1-modificationdate-1745218873613-api-v2.png

After completing the installation, the setup wizard displays a menu with several options, such as "Assign Interfaces" and "Reboot System." During this phase, you must configure the network interfaces for the Firewall VM.

Select Option 2: "Set interface(s) IP address" and configure the interfaces as follows:
- WAN (lab-br) – Trusted LAN IP (Static/DHCP)
- LAN (mgmt-br) – Static IP 10.0.110.254/24
- OPT1 (hs-br) – Static IP 172.169.50.1/30
Once the interface configuration is complete, use a web browser within the host management network to access the Firewall web interface and finalize the configuration.

Next, proceed with the installation of the Jump VM. This VM will serve as a platform for running a browser to access the Firewall’s web interface for post-installation configuration.

Jump VM

Suggested specifications:

vCPU: 4
RAM: 8GB
Storage: 50GB
Network interface: Bridge device, connected to mgmt-br

Procedure:

Proceed with a standard Ubuntu 24.04 installation. Use the following login credentials across all hosts in this setup:

Username
Password
depuser
user

Username	Password
depuser	user

Enable internet connectivity and DNS resolution by creating the following Netplan configuration:

Note

Use 10.0.110.254 as a temporary DNS nameserver until the MAAS VM is installed and configured. After completing the MAAS installation, update the Netplan file to replace this address with the MAAS IP: 10.0.110.252.

Jump Node netplan

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            network:
    ethernets:
        enp1s0:
            dhcp4: false
            addresses: [10.0.110.253/24]
            nameservers:
              search: [dpf.rdg.local.domain]
              addresses: [10.0.110.254]
            routes:
              - to: default
                via: 10.0.110.254
    version: 2

Apply the configuration:

Jump Node Console

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            depuser@jump:~$ sudo netplan apply

Update and upgrade the system:

Jump Node Console

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            depuser@jump:~$ sudo apt update -y
depuser@jump:~$ sudo apt upgrade -y

Install and configure the Xfce desktop environment and XRDP (complementary packages for RDP):

Jump Node Console

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            depuser@jump:~$ sudo apt install -y xfce4 xfce4-goodies
depuser@jump:~$ sudo apt install -y xrdp
depuser@jump:~$ echo "xfce4-session" | tee .xsession
depuser@jump:~$ sudo systemctl restart xrdp

Install Firefox for accessing the Firewall web interface:
Jump Node Console

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```
            
            $ sudo apt install -y firefox
        
```

Install and configure an NFS server with the /mnt/dpf_share directory:

Jump Node Console

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            $ sudo apt install -y nfs-server
$ sudo mkdir -m 777 /mnt/dpf_share
$ sudo vi /etc/exports

Add the following line to /etc/exports:

Jump Node Console

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            /mnt/dpf_share 10.0.110.0/24(rw,sync,no_subtree_check)

Restart the NFS server:

Jump Node Console

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            $ sudo systemctl restart nfs-server

Create the directory bfb under /mnt/dpf_share with the same permissions as the parent directory:
Jump Node Console

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```
            
            $ sudo mkdir -m 777 /mnt/dpf_share/bfb
        
```
Generate an SSH key pair for depuser in the jump node (later on will be imported for the MAAS admin user to provide passwordless login to provisioned servers):
Jump Node Console

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```
            
            depuser@jump:~$ ssh-keygen -t rsa
        
```

Firewall VM – Web Configuration

From your Jump node, open Firefox web browser and go to the pfSense web UI (http://10.0.110.254, default credentials are admin/pfsense). You should see a page similar to the following:

Note

The IP addresses from the trusted LAN network under "DNS servers" and "Interfaces - WAN" are blurred.

firewall_main_page_blur-version-1-modificationdate-1745218863007-api-v2.png

Proceed with the following configurations:

Note

The following screenshots display only part of the configuration view. Make sure not to miss any of the steps mentioned below!

Interfaces
- WAN – mark “Enable interface”, unmark “Block private networks and loopback addresses”
- LAN – mark “Enable interface”, “IPv4 configuration type”: Static IPv4 ("IPv4 Address": 10.0.110.254/24, "IPv4 Upstream Gateway": None), “MTU”: 9000
- OPT1 – mark “Enable interface”, “IPv4 configuration type”: Static IPv4 ("IPv4 Address": 172.169.50.1/30, "IPv4 Upstream Gateway": None), “MTU”: 9000
Firewall:
- NAT -> Port Forward -> Add rule -> “Interface”: WAN, “Address Family”: IPv4, “Protocol”: TCP, “Destination”: WAN address, “Destination port range”: (“From port”: SSH, “To port”: SSH), “Redirect target IP”: (“Type”: Address or Alias, “Address”: 10.0.110.253), “Redirect target port”: SSH, “Description”: NAT SSH
- NAT -> Port Forward -> Add rule -> “Interface”: WAN, “Address Family”: IPv4, “Protocol”: TCP, “Destination”: WAN address, “Destination port range”: (“From port”: MS RDP, “To port”: MS RDP), “Redirect target IP”: (“Type”: Address or Alias, “Address”: 10.0.110.253), “Redirect target port”: MS RDP, “Description”: NAT RDP

- Rules -> OPT1 -> Add rule -> “Action”: Pass, “Interface”: OPT1, “Address Family”: IPv4+IPv6, “Protocol”: Any, “Source”: Any, “Destination”: Any

System:
- Routing → Gateways → Add → “Interface”: OPT1, “Address Family”: IPv4, “Name”: switch, “Gateway”: 172.169.50.2 → Click "Save"→ Under "Default Gateway" - "Default gateway IPv4" choose WAN_DHCP → Click "Save"
  
  Note
  
  Note that the IP addresses from the Trusted LAN network under "Gateway" and "Monitor IP" are blurred.

- Routing → Static Routes → Add → “Destination network”: 10.0.120.0/22, “Gateway”: switch – 172.169.50.2, “Description”: To HS network → Click "Save"

MAAS VM

Suggested specifications:

vCPU: 4
RAM: 4GB
Storage: 50GB
Network interface: Bridge device, connected to mgmt-br

Procedure:

Perform a regular Ubuntu installation on the MAAS VM.

Create the following Netplan configuration to enable internet connectivity and DNS resolution:

Note

Use 10.0.110.254 as a temporary DNS nameserver. After the MAAS installation, replace this with the MAAS IP address (10.0.110.252) in both the Jump and MAAS VM Netplan files.

MaaS netplan

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            network:
    ethernets:
        enp1s0:
            dhcp4: false
            addresses: [10.0.110.252/24]
            nameservers:
              search: [dpf.rdg.local.domain]
              addresses: [10.0.110.254]
            routes:
              - to: default
                via: 10.0.110.254
    version: 2

Apply the netplan configuration:

MaaS Console

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            depuser@maas:~$ sudo netplan apply

Update and upgrade the system:

MaaS Console

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            depuser@maas:~$ sudo apt update -y
depuser@maas:~$ sudo apt upgrade -y

Install PostgreSQL and configure the database for MAAS:

MaaS Console

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            $ sudo -i
# apt install -y postgresql
# systemctl enable --now postgresql
# systemctl disable --now systemd-timesyncd
# export MAAS_DBUSER=maasuser
# export MAAS_DBPASS=maaspass
# export MAAS_DBNAME=maas
# sudo -i -u postgres psql -c "CREATE USER \"$MAAS_DBUSER\" WITH ENCRYPTED PASSWORD '$MAAS_DBPASS'"
# sudo -i -u postgres createdb -O "$MAAS_DBUSER" "$MAAS_DBNAME"

Install MAAS:

MaaS Console

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            # snap install maas

Initialize MAAS:

MaaS Console

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            # maas init region+rack --maas-url http://10.0.110.252:5240/MAAS --database-uri "postgres://$MAAS_DBUSER:$MAAS_DBPASS@localhost/$MAAS_DBNAME"

Create an admin account:

MaaS Console

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            # maas createadmin --username admin --password admin --email admin@example.com

Save the admin API key:

MaaS Console

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            # maas apikey --username admin > admin-apikey

MaaS Console

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            # maas login admin http://localhost:5240/MAAS "$(cat admin-apikey)"

Configure MAAS (Substitute <Trusted_LAN_NTP_IP> and <Trusted_LAN_DNS_IP> with the IP addresses in your environment):

MaaS Console

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            # maas admin domain update maas name="dpf.rdg.local.domain"
# maas admin maas set-config name=ntp_servers value="<Trusted_LAN_NTP_IP>"
# maas admin maas set-config name=network_discovery value="disabled"
# maas admin maas set-config name=upstream_dns value="<Trusted_LAN_DNS_IP>"
# maas admin maas set-config name=dnssec_validation value="no"
# maas admin maas set-config name=default_osystem value="ubuntu"

Define and configure IP ranges and subnets:

MaaS Console

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            # maas admin ipranges create type=dynamic start_ip="10.0.110.51" end_ip="10.0.110.120"
# maas admin ipranges create type=dynamic start_ip="10.0.110.21" end_ip="10.0.110.30"
# maas admin ipranges create type=reserved start_ip="10.0.110.10" end_ip="10.0.110.10" comment="c-plane VIP"
# maas admin ipranges create type=reserved start_ip="10.0.110.200" end_ip="10.0.110.200" comment="kamaji VIP"
# maas admin ipranges create type=reserved start_ip="10.0.110.251" end_ip="10.0.110.254" comment="dpfmgmt"
# maas admin vlan update 0 untagged dhcp_on=True primary_rack=maas
# maas admin dnsresources create fqdn=kube-vip.dpf.rdg.local.domain ip_addresses=10.0.110.10
# maas admin dnsresources create fqdn=jump.dpf.rdg.local.domain ip_addresses=10.0.110.253
# maas admin dnsresources create fqdn=fw.dpf.rdg.local.domain ip_addresses=10.0.110.254
# maas admin fabrics create
Success.
Machine-readable output follows:
{
"class_type": null,
"name": "fabric-1",
"id": 1,
...
# maas admin subnets create name="fake-dpf" cidr="20.20.20.0/24" fabric=1

Complete MAAS setup:
1. Connect to the Jump node GUI and access the MAAS UI at http://10.0.110.252:5240/MAAS.
2. On the first page, verify the "Region Name" and "DNS Forwarder," then continue.
3. On the image selection page, select Ubuntu 24.04 LTS (amd64) and sync the image.
4. Import the previously generated SSH key (id_rsa.pub) for the depuser into the MAAS admin user profile and finalize the setup.

Configure DHCP snippets:

Navigate to Settings → DHCP Snippets → Add Snippet.
Fill in the following fields:
1. Name: dpf-mgmt
2. Toggle on "Enabled"
3. Type: IP Range
4. Applies to: 10.0.110.21-10.0.110.30

Fill in the content of the DHCP snippet field with the following (replace MAC address as appropriate with your workers MGMT interface MAC):

DHCP snippet

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            # worker1
host worker1 {
   # 
   # Node DHCP snippets
   # 
 
   hardware ethernet 04:32:01:60:0d:da;
   fixed-address 10.0.110.21;
}
# worker2
host worker2 {
   # 
   # Node DHCP snippets
   # 
 
   hardware ethernet 04:32:01:5f:cb:e0;
   fixed-address 10.0.110.22;
}
# target
host target {
   #
   # Node DHCP snippets
   #
 
   hardware ethernet 0c:c4:7a:a4:b9:1c;
   fixed-address 10.0.110.25;
}

Go to Settings → Deploy, set "Default OS release" to Ubuntu 24.04 LTS Noble Numbat, and save.
Update the DNS nameserver IP address in both the Jump and MAAS VM Netplan files from 10.0.110.254 to 10.0.110.252 and reapply the configuration.

K8s Master VMs

Suggested specifications:

vCPU: 8
RAM: 16GB
Storage: 100GB
Network interface: Bridge device, connected to mgmt-br

Before provisioning the Kubernetes (K8s) Master VMs with MAAS, create the required virtual disks with empty storage. Use the following one-liner to create three 100 GB QCOW2 virtual disks:
Hypervisor Console

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```
            
            $ for i in $(seq 1 3); do qemu-img create -f qcow2 /var/lib/libvirt/images/master$i.qcow2 100G; done
        
```
This command generates the following disks in the /var/lib/libvirt/images/ directory:
- master1.qcow2
- master2.qcow2
- master3.qcow2
Configure VMs in virt-manager:
1. Open virt-manager and create three virtual machines:
  - Assign the corresponding virtual disk (master1.qcow2, master2.qcow2, or master3.qcow2) to each VM.
  - Configure each VM with the suggested specifications (vCPU, RAM, storage, and network interface).
2. During the VM setup, ensure the NIC is selected under the Boot Options tab. This ensures the VMs can PXE boot for MAAS provisioning.
3. Once the configuration is complete, shut down all the VMs.
After the VMs are created and configured, proceed to provision them via the MAAS interface. MAAS will handle the OS installation and further setup as part of the deployment process.

Provision Master VMs, Workers and Storage Target Nodes Using MAAS

Master VMs

Install virsh and Set Up SSH Access

SSH to the MAAS VM from the Jump node:

MaaS Console

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            depuser@jump:~$ ssh maas
depuser@maas:~$ sudo -i

Install the virsh client to communicate with the hypervisor:

MaaS Console

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            # apt install -y libvirt-clients

Generate an SSH key for the root user and copy it to the hypervisor user in the libvirtd group:

MaaS Console

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            # ssh-keygen -t rsa
# ssh-copy-id ubuntu@<hypervisor_MGMT_IP>

Verify SSH access and virsh communication with the hypervisor:

MaaS Console

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            # virsh -c qemu+ssh://ubuntu@<hypervisor_MGMT_IP>/system list --all

Expected output:

MaaS Console

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             Id   Name          State
------------------------------
 1    fw     running
 2    jump   running
 3    maas   running
 -    master1       shut off
 -    master2       shut off
 -    master3       shut off

Copy the SSH key to the required MAAS directory (for snap-based installations):

MaaS Console

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            # mkdir -p /var/snap/maas/current/root/.ssh
# cp .ssh/id_rsa* /var/snap/maas/current/root/.ssh/

Get MAC Addresses of the Master VMs

Retrieve the MAC addresses of the Master VMs:

MaaS Console

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            # for i in $(seq 1 3); do virsh -c qemu+ssh://ubuntu@<hypervisor_MGMT_IP>/system dumpxml master$i | grep 'mac address'; done

Example output:

MaaS Console

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            <mac address='52:54:00:a9:9c:ef'/>
<mac address='52:54:00:19:6b:4d'/>
<mac address='52:54:00:68:39:7f'/>

Add Master VMs to MAAS

Add the Master VMs to MAAS:

Info

Once added, MAAS will automatically start commissioning the newly added VMs (discovery and introspection).

MaaS Console

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            # maas admin machines create hostname=master1 architecture=amd64/generic mac_addresses='52:54:00:a9:9c:ef' power_type=virsh power_parameters_power_address=qemu+ssh://ubuntu@<hypervisor_MGMT_IP>/system power_parameters_power_id=master1 skip_bmc_config=1 testing_scripts=none
Success.
Machine-readable output follows:
{
    "description": "",
    "status_name": "Commissioning",
...
    "status": 1, 
...
    "system_id": "c3seyq",
...
    "fqdn": "master1.dpf.rdg.local.domain",
    "power_type": "virsh",
...
    "status_message": "Commissioning",
    "resource_uri": "/MAAS/api/2.0/machines/c3seyq/"
}
 
# maas admin machines create hostname=master2 architecture=amd64/generic mac_addresses='52:54:00:19:6b:4d' power_type=virsh power_parameters_power_address=qemu+ssh://ubuntu@<hypervisor_MGMT_IP>/system power_parameters_power_id=master2 skip_bmc_config=1 testing_scripts=none
 
# maas admin machines create hostname=master3 architecture=amd64/generic mac_addresses='52:54:00:68:39:7f' power_type=virsh power_parameters_power_address=qemu+ssh://ubuntu@<hypervisor_MGMT_IP>/system power_parameters_power_id=master3 skip_bmc_config=1 testing_scripts=none

Repeat the command for master2 and master3 with their respective MAC addresses.

Verify commissioning by waiting for the status to change to "Ready" in MAAS.

After commissioning, the next phase is the deployment (OS provisioning).

Configure OVS Bridges on Master VMs

To have persistency across reboots, create an OVS-bridge from each management interface of the master nodes and assign it a static IP address.

For each Master VM:

Create an OVS bridge in the MAAS Network tab:
1. Navigate to Network → Management Interface → Create Bridge.
2. Configure as follows:
  1. Name: brenp1s0 (prefix br added to the interface name)
  2. Bridge Type: Open vSwitch (ovs)
  3. Subnet: 10.0.110.0/24
  4. IP Mode: Static Assign
  5. Address: Assign 10.0.110.1 for master1, 10.0.110.2 for master2, and 10.0.110.3 for master3.
Save the interface settings for each VM.

Deploy Master VMs Using Cloud-Init

Use the following cloud-init script to configure the necessary software and ensure OVS bridge persistency:

Note

Replace enp1s0 and brenp1s0 in the following cloud-init with your interface names as displayed in MAAS network tab.

Master nodes cloud-init

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            #cloud-config
system_info:
  default_user:
    name: depuser
    passwd: "$6$jOKPZPHD9XbG72lJ$evCabLvy1GEZ5OR1Rrece3NhWpZ2CnS0E3fu5P1VcZgcRO37e4es9gmriyh14b8Jx8gmGwHAJxs3ZEjB0s0kn/"
    lock_passwd: false
    groups: [adm, audio, cdrom, dialout, dip, floppy, lxd, netdev, plugdev, sudo, video]
    sudo: ["ALL=(ALL) NOPASSWD:ALL"]
    shell: /bin/bash
ssh_pwauth: True
package_upgrade: true
package_reboot_if_required: true
package_update: true
package_upgrade: true  
packages:
  - openvswitch-switch 
  - nfs-common
runcmd:
    - |
      UPLINK_MAC=$(cat /sys/class/net/enp1s0/address)
      ovs-vsctl set Bridge brenp1s0 other-config:hwaddr=$UPLINK_MAC
      ovs-vsctl br-set-external-id brenp1s0 bridge-id brenp1s0 -- br-set-external-id brenp1s0 bridge-uplink enp1s0

Deploy the Master VMs:
1. Select all three Master VMs → Actions → Deploy.
2. Toggle Cloud-init user-data and paste the cloud-init script.
3. Start the deployment and wait for the status to change to "Ubuntu 24.04 LTS".

Verify Deployment

SSH into the Master VMs from the Jump node:

Jump Node Console

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            depuser@jump:~$ ssh master1
depuser@master1:~$

Run sudo without password:

Master1 Console

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            depuser@master1:~$ sudo -i
root@master1:~#

Verify installed packages:

Master1 Console

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            root@master1:~# apt list --installed | egrep 'openvswitch-switch|nfs-common'
nfs-common/noble,now 1:2.6.4-3ubuntu5.1 amd64 [installed]
openvswitch-switch/noble-updates,now 3.3.0-1ubuntu3.1 amd64 [installed]

Check OVS bridge attributes:

Master1 Console

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            root@master1:~# ovs-vsctl list bridge brenp1s0

Output example:

Master1 Console

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            ...
external_ids        : {bridge-id=brenp1s0, bridge-uplink=enp1s0, netplan="true", "netplan/global/set-fail-mode"=standalone, "netplan/mcast_snooping_enable"="false", "netplan/rstp_enable"="false"}
...
other_config        : {hwaddr="52:54:00:a9:9c:ef"}
...

Finalize Setup

Reboot the Master VMs to complete the provisioning:

Master1 Console

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            root@master1:~# reboot

Worker and Storage Target Nodes

Create Workers and Target Machines in MAAS

Add the worker nodes to MAAS using ipmi as the power type. Replace placeholders with your specific IPMI credentials and IP addresses:

Kernel options for worker nodes

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            # maas admin machines create hostname=worker1 architecture=amd64 power_type=ipmi power_parameters_power_driver=LAN_2_0 power_parameters_power_user=<IPMI_username_worker1> power_parameters_power_pass=<IPMI_password_worker1> power_parameters_power_address=<IPMI_address_worker1>

Output example:

MaaS Console

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            ...
Success.
Machine-readable output follows:
{
    "description": "",
    "status_name": "Commissioning",
...
    "status": 1,
...
    "system_id": "pbskd3",
...
    "fqdn": "worker1.dpf.rdg.local.domain",
...
    "power_type": "ipmi",
...
    "resource_uri": "/MAAS/api/2.0/machines/pbskd3/"
}

Repeat the command for worker2 and targetwith its respective credentials:

Kernel options for worker nodes

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            # maas admin machines create hostname=worker2 architecture=amd64 power_type=ipmi power_parameters_power_driver=LAN_2_0 power_parameters_power_user=<IPMI_username_worker2> power_parameters_power_pass=<IPMI_password_worker2> power_parameters_power_address=<IPMI_address_worker2>
# maas admin machines create hostname=target architecture=amd64 power_type=ipmi power_parameters_power_driver=LAN_2_0 power_parameters_power_user=<IPMI_username_target> power_parameters_power_pass=<IPMI_password_target> power_parameters_power_address=<IPMI_address_target>

Once added, MAAS will automatically start commissioning the Worker and Storage Target nodes (discovery and introspection).

Adjust Network Settings

For each worker node, configure the network interfaces:

Management Adapter:
- Go to Network → Select the host management adapter (e.g., ens15f0) → Create Bridge
- Name: br-dpu
- Bridge Type: Standard
- Subnet: 10.0.110.0/24
- IP Mode: DHCP
- Save the interface
BlueField Adapter:
- Select P0 on the BlueField adapter (e.g., ens5f0np0) → Actions → Edit Physical
- Fabric: Fabric-1
- Subnet: 20.20.20.0/24 (fake-dpf)
- IP Mode: DHCP
- Save the interface

Repeat these steps for the second worker node.

maas_edit_physical_interface-version-1-modificationdate-1745218863480-api-v2.png

For Storage Target Node, configure the network interfaces:

Management Adapter:
- Go to Network → Select the host management adapter (e.g., ens1s0f0) → Edit Physical
- Subnet: 10.0.110.0/24
- IP Mode: DHCP
- Save the interface
ConnectX-7 Adapter:
- Leave unchanged

Deploy Worker Nodes Using Cloud-Init

Use the following cloud-init script for deployment:

Worker node cloud-init

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            #cloud-config
system_info:
  default_user:
    name: depuser
    passwd: "$6$jOKPZPHD9XbG72lJ$evCabLvy1GEZ5OR1Rrece3NhWpZ2CnS0E3fu5P1VcZgcRO37e4es9gmriyh14b8Jx8gmGwHAJxs3ZEjB0s0kn/"
    lock_passwd: false
    groups: [adm, audio, cdrom, dialout, dip, floppy, lxd, netdev, plugdev, sudo, video]
    sudo: ["ALL=(ALL) NOPASSWD:ALL"]
    shell: /bin/bash
ssh_pwauth: true
package_reboot_if_required: true
package_update: true
package_upgrade: true
packages:
  - nfs-common
write_files:
  - path: /etc/sysctl.d/99-custom-netfilter.conf
    owner: root:root
    permissions: '0644'
    content: |
      net.bridge.bridge-nf-call-iptables=0
 
runcmd:
  - sysctl --system

Deploy the worker nodes by selecting the worker nodes in MAAS → Actions → Deploy → Customize options → Enable Cloud-init user-data → Paste the cloud-init script → Deploy.

Deploy Storage Target Node Using Cloud-Init

Use the following cloud-init script for deployment:

Target node cloud-init

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            #cloud-config
users:
  - default
  - name: depuser
    passwd: "$6$jOKPZPHD9XbG72lJ$evCabLvy1GEZ5OR1Rrece3NhWpZ2CnS0E3fu5P1VcZgcRO37e4es9gmriyh14b8Jx8gmGwHAJxs3ZEjB0s0kn/"
    lock_passwd: false
    groups: [adm, audio, cdrom, dialout, dip, floppy, lxd, netdev, plugdev, sudo, video]
    sudo: ["ALL=(ALL) NOPASSWD:ALL"]
    shell: /bin/bash
ssh_pwauth: true
package_reboot_if_required: true
package_update: true
package_upgrade: true  
packages:
  - nvme-cli

Deploy the Storage Target Node by selecting the Storage Target Node in MAAS → Actions → Deploy → Customize options → Enable Cloud-init User-Data → Paste the cloud-init script → Deploy.

Manually assign an IP address to the DATA interface after node has been deployed in MAAS via netplan according to your SPDK IPAM CIDR (in our case 10.0.124.1/24)

Target node /etc/netplan/50-cloud-init.yaml

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            network:
  version: 2
  ethernets:
    # DATA interface
    enp144s0f0np0:
      match:
        macaddress: "04:3f:72:ed:97:d6"
      optional: true
      set-name: "enp144s0f0np0"
      mtu: 1500
      addresses:
      - "10.0.124.1/24"
      nameservers:
        addresses:
        - 10.0.110.252
        search:
        - dpf.rdg.local.domain        
    enp144s0f1np1:
      match:
        macaddress: "04:3f:72:ed:97:d7"
      optional: true
      set-name: "enp144s0f1np1"
      mtu: 1500
    # Management interface
    enp1s0f0:
      match:
        macaddress: "0c:c4:7a:a4:b9:1c"
      dhcp4: true
      set-name: "enp1s0f0"
      mtu: 1500
    enp1s0f1:
      match:
        macaddress: "0c:c4:7a:a4:b9:1d"
      optional: true
      set-name: "enp1s0f1"
      mtu: 1500

Verify the Deployment

After the deployment is complete, verify that the worker nodes have been deployed successfully with the following commands:

SSH without password from the jump node:

Jump Node Console

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            depuser@jump:~$ ssh worker1
depuser@worker1:~$

Run sudo without password:

Worker1 Console

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            depuser@worker1:~$ sudo -i
root@worker1:~#

Validate that the nfs-common package is installed:

Worker1 Console

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            root@worker1:~# apt list --installed | grep 'nfs-common'
nfs-common/noble,now 1:2.6.4-3ubuntu5.1 amd64 [installed]

br_netfilter module is not loaded:

Worker1 Console

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            root@worker1:~# lsmod | grep br_netfilter
root@worker1:~#

P0 interface has dhcp4 set to true and does not have mtu line in the netplan configuration file.

Worker1 Console

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            root@worker1:~# cat /etc/netplan/50-cloud-init.yaml
network:
...
		ens5f0np0:
            dhcp4: true
            match:
                macaddress: a0:88:c2:46:78:c4
            set-name: ens5f0np0
...

Finalize Deployment

Reboot ALL nodes:

Jump Node Console

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            root@worker1:~# reboot

The infrastructure is now ready for the K8s deployment.

Provision SPDK Target Apps on Storage Target Node

Jump Node Console

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            $ ssh target
$ sudo -i

Build SPDK from source (root privileges is required!):

Jump Node Console

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            git clone https://github.com/spdk/spdk
cd spdk
 
# v24.01 is the last version that is compatible with the spdk-csi
git checkout v24.01
git submodule update --init
apt update && apt install meson python3-pyelftools -y
./scripts/pkgdep.sh --rdma
./configure --with-rdma
make

Run SPDK target:

Jump Node Console

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            # Get all nvme devices
 
lshw -c storage -businfo
 
Bus info          Device         Class          Description
===========================================================
pci@0000:08:00.0                 storage        PCIe Data Center SSD
pci@0000:00:11.4                 storage        C610/X99 series chipset sSATA Controller [AHCI mode]
pci@0000:00:1f.2                 storage        C610/X99 series chipset 6-Port SATA Controller [AHCI mode]
pci@0000:81:00.0  scsi4          storage        MegaRAID SAS-3 3108 [Invader]
 
# Start target
scripts/setup.sh
build/bin/nvmf_tgt &
 
# Add bdevs with nvme backend
scripts/rpc.py bdev_nvme_attach_controller -b Nvme0 -t PCIe -a 0000:08:00.0
 
# Add logical volume store on base bdev
scripts/rpc.py bdev_lvol_create_lvstore Nvme0n1 lvs0
 
# Display current logical volume list
scripts/rpc.py bdev_lvol_get_lvstores
 
scripts/rpc_http_proxy.py 10.0.110.25 8000 exampleuser examplepassword &

SPDK target is ready.

K8s Cluster Deployment and Configuration

Kubespray Deployment and Configuration

In this solution, the Kubernetes (K8s) cluster is deployed using a modified version of Kubespray (based on tag v2.26.0) with a non-root depuser account from the Jump Node. The modifications in Kubespray are designed to meet the DPF prerequisites, as described in the User Manual and to facilitate cluster deployment and scaling.

Download the modified Kubespray archive: modified_kubespray_v2.26.0.tar.gz.

Extract the contents and navigate to the extracted directory:

Jump Node Console

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            $ tar -xzf /home/depuser/modified_kubespray_v2.26.0.tar.gz
$ cd kubespray/
depuser@jump:~/kubespray$

Set the K8s API VIP address and DNS record. Replace it with your own IP address and DNS record if different:

Jump Node Console

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            depuser@jump:~/kubespray$ sed -i '/  #kube_vip_address:/s/.*/kube_vip_address: 10.0.110.10/' inventory/mycluster/group_vars/k8s_cluster/addons.yml
depuser@jump:~/kubespray$ sed -i '/apiserver_loadbalancer_domain_name:/s/.*/apiserver_loadbalancer_domain_name: "kube-vip.dpf.rdg.local.domain"/' roles/kubespray-defaults/defaults/main/main.yml

Install the necessary dependencies and set up the Python virtual environment:

Jump Node Console

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            depuser@jump:~/kubespray$ sudo apt -y install python3-pip jq python3.12-venv
depuser@jump:~/kubespray$ python3 -m venv .venv
depuser@jump:~/kubespray$ source .venv/bin/activate
(.venv) depuser@jump:~/kubespray$ python3 -m pip install --upgrade pip
(.venv) depuser@jump:~/kubespray$ pip install -U -r requirements.txt
(.venv) depuser@jump:~/kubespray$ pip install ruamel-yaml

Review and edit the inventory/mycluster/hosts.yaml file to define the cluster nodes. The following is the configuration for this deployment:

Note

All of the nodes are already labeled and annotated as per the DPF User Manual prerequisites.
The kube_node group is marked with # to deploy only the cluster with control plane nodes at the beginning. (Worker nodes will be added after the various components necessary for the DPF system are installed).

inventory/mycluster/hosts.yaml

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            all:
  hosts:
    master1:
      ansible_host: 10.0.110.1
      ip: 10.0.110.1
      access_ip: 10.0.110.1
      node_labels:
        "k8s.ovn.org/zone-name": "master1"
    master2:
      ansible_host: 10.0.110.2
      ip: 10.0.110.2
      access_ip: 10.0.110.2
      node_labels:
        "k8s.ovn.org/zone-name": "master2"
    master3:
      ansible_host: 10.0.110.3
      ip: 10.0.110.3
      access_ip: 10.0.110.3
      node_labels:
        "k8s.ovn.org/zone-name": "master3"
    worker1:
      ansible_host: 10.0.110.21
      ip: 10.0.110.21
      access_ip: 10.0.110.21
      node_labels:
        "node-role.kubernetes.io/worker": ""
        "k8s.ovn.org/dpu-host": ""
        "k8s.ovn.org/zone-name": "worker1"
      node_annotations:
        "k8s.ovn.org/remote-zone-migrated": "worker1"
    worker2:
      ansible_host: 10.0.110.22
      ip: 10.0.110.22
      access_ip: 10.0.110.22
      node_labels:
        "node-role.kubernetes.io/worker": ""
        "k8s.ovn.org/dpu-host": ""
        "k8s.ovn.org/zone-name": "worker2"
      node_annotations:
        "k8s.ovn.org/remote-zone-migrated": "worker2"
  children:
    kube_control_plane:
      hosts:
        master1:
        master2:
        master3:
    kube_node:
      hosts:
        worker1:
        worker2:
    etcd:
      hosts:
        master1:
        master2:
        master3:
    k8s_cluster:
      children:
        kube_control_plane:
#       kube_node:

Deploying Cluster Using Kubespray Ansible Playbook

Run the following command from the Jump Node to initiate deployment:

Note

Ensure you are in the Python virtual environment (.venv) when running the command.
Jump Node Console

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```
            
            (.venv) depuser@jump:~/kubespray$ ansible-playbook -i inventory/mycluster/hosts.yaml --become --become-user=root cluster.yml
        
```
It takes a while for this deployment to complete. Make sure there are no errors. A successful result example:

Tip

It is recommended to keep the shell from which Kubespray was running open; later on it will be useful when performing a cluster scale-out to add the worker nodes.

K8s Deployment Verification

To simplify managing the K8s cluster from the Jump Host, set up kubectl with bash auto-completion.

Copy kubectl and the kubeconfig file from master1 to the Jump Host:

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            ## Connect to master1
depuser@jump:~$ ssh master1
depuser@master1:~$ cp /usr/local/bin/kubectl /tmp/
depuser@master1:~$ sudo cp /root/.kube/config /tmp/kube-config
depuser@master1:~$ sudo chmod 644 /tmp/kube-config

In another terminal tab, copy the files to the Jump Host:

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            depuser@jump:~$ scp master1:/tmp/kubectl /tmp/
depuser@jump:~$ sudo chown root:root /tmp/kubectl
depuser@jump:~$ sudo mv /tmp/kubectl /usr/local/bin/
depuser@jump:~$ mkdir -p ~/.kube
depuser@jump:~$ scp master1:/tmp/kube-config ~/.kube/config
depuser@jump:~$ chmod 600 ~/.kube/config

Enable bash auto-completion for kubectl:

Verify if bash-completion is installed:

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            depuser@jump:~$ type _init_completion

If installed, the output includes:

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            _init_completion is a function

If bash-completion has not been installed, install it:

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            depuser@jump:~$ sudo apt install -y bash-completion

Set up the kubectl completion script:

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            depuser@jump:~$ kubectl completion bash | sudo tee /etc/bash_completion.d/kubectl > /dev/null
depuser@jump:~$ bash

Check the status of the nodes in the cluster:

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            depuser@jump:~$ kubectl get nodes

Expected output:

Note

Nodes will be in the NotReady state because the deployment did not include CNI components.

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            NAME      STATUS     ROLES           AGE   VERSION
master1   NotReady   control-plane   42m   v1.30.4
master2   NotReady   control-plane   41m   v1.30.4
master3   NotReady   control-plane   41m   v1.30.4

Check the pods in all namespaces:

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            depuser@jump:~$ kubectl get pods -A

Expected output:

Note

coredns and dns-autoscaler pods will be in the Pending state due to the absence of CNI components.

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            NAMESPACE     NAME                              READY   STATUS    RESTARTS   AGE
kube-system   coredns-776bb9db5d-ndr7j          0/1     Pending   0          41m
kube-system   dns-autoscaler-6ffb84bd6-xj9bv    0/1     Pending   0          41m
kube-system   kube-apiserver-master1            1/1     Running   0          43m
kube-system   kube-apiserver-master2            1/1     Running   0          42m
kube-system   kube-apiserver-master3            1/1     Running   0          42m
kube-system   kube-controller-manager-master1   1/1     Running   1          43m
kube-system   kube-controller-manager-master2   1/1     Running   1          42m
kube-system   kube-controller-manager-master3   1/1     Running   1          42m
kube-system   kube-scheduler-master1            1/1     Running   1          43m
kube-system   kube-scheduler-master2            1/1     Running   1          42m
kube-system   kube-scheduler-master3            1/1     Running   1          42m
kube-system   kube-vip-master1                  1/1     Running   0          43m
kube-system   kube-vip-master2                  1/1     Running   0          42m
kube-system   kube-vip-master3                  1/1     Running   0          42m

DPF Installation

Software Prerequisites and Required Variables

Start by installing the remaining software prerequisites.

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            ## Connect to master1 to copy helm client utility that was installed during kubespray deployment
$ depuser@jump:~$ ssh master1
depuser@master1:~$ cp /usr/local/bin/helm /tmp/
 
## In another tab 
depuser@jump:~$ scp master1:/tmp/helm /tmp/
depuser@jump:~$ sudo chown root:root /tmp/helm
depuser@jump:~$ sudo mv /tmp/helm /usr/local/bin/
 
## Verify that envsubst utility is installed 
depuser@jump:~$ which envsubst
/usr/bin/envsubst

Proceed to clone the doca-platform Git repository (make sure to use tag v25.4.0):

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            $ git clone https://github.com/NVIDIA/doca-platform.git
$ cd doca-platform
$ git checkout v25.4.0

Change the directory to the location of the HBN-OVN usecase, from where all the commands are run :
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```
            
            $ cd docs/public/user-guides/hbn_ovn
        
```

Remove unused components of the HBN-OVN deployment usecase :

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            $ rm -rf manifests/05* manifests/06*

Download the hbn-ovn-snap.zip file with the required YAML deployment files for this guide, then unarchive it:

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            $ unzip hbn-ovn-snap.zip
 
$ ls -Ad manifests/*
manifests/00-high-speed-switch-configuration
manifests/01-cni-installation
manifests/02-dpf-operator-installation
manifests/03-dpf-system-installation
manifests/04-enable-accelerated-cni
manifests/05-dpudeployment-installation
manifests/06-test-traffic

Use the export_vars.env file to define the required variables for the installation:

Warning

Replace the values for the variables in the following file with the values that fit your setup. Specifically, pay attention to DPU_P0 , DPU_P0_VF1 and DPUCLUSTER_INTERFACE.

export_vars.env

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            ## IP Address for the Kubernetes API server of the target cluster on which DPF is installed.
## This should never include a scheme or a port.
## e.g. 10.10.10.10
export TARGETCLUSTER_API_SERVER_HOST=10.0.110.10
 
## Port for the Kubernetes API server of the target cluster on which DPF is installed.
export TARGETCLUSTER_API_SERVER_PORT=6443
 
## IP address range for hosts in the target cluster on which DPF is installed.
## This is a CIDR in the form e.g. 10.10.10.0/24
export TARGETCLUSTER_NODE_CIDR=10.0.110.0/24
 
## Virtual IP used by the load balancer for the DPU Cluster. Must be a reserved IP from the management subnet and not allocated by DHCP.
export DPUCLUSTER_VIP=10.0.110.200
 
## DPU_P0 is the name of the first port of the DPU. This name must be the same on all worker nodes.
export DPU_P0=ens5f0np0
 
## DPU_P0_VF1 is the name of the second Virtual Function (VF) of the first port of the DPU. This name must be the same on all worker nodes.
export DPU_P0_VF1=ens5f0v1
 
## Interface on which the DPUCluster load balancer will listen. Should be the management interface of the control plane node.
export DPUCLUSTER_INTERFACE=brenp1s0
 
## IP address to the NFS server used as storage for the BFB.
export NFS_SERVER_IP=10.0.110.253
 
## The repository URL for the NVIDIA Helm chart registry.
## Usually this is the NVIDIA Helm NGC registry. For development purposes, this can be set to a different repository.
export NGC_HELM_REGISTRY_REPO_URL=https://helm.ngc.nvidia.com/nvidia/doca
 
## The repository URL for the HBN container image.
## Usually this is the NVIDIA NGC registry. For development purposes, this can be set to a different repository.
export HBN_NGC_IMAGE_URL=nvcr.io/nvidia/doca/doca_hbn
 
## The repository URL for the OVN Kubernetes Helm chart.
## Usually this is the NVIDIA GHCR repository. For development purposes, this can be set to a different repository.
export OVN_KUBERNETES_REPO_URL=oci://ghcr.io/nvidia
 
## POD_CIDR is the CIDR used for pods in the target Kubernetes cluster.
export POD_CIDR=10.233.64.0/18
 
## SERVICE_CIDR is the CIDR used for services in the target Kubernetes cluster.
## This is a CIDR in the form e.g. 10.10.10.0/24
export SERVICE_CIDR=10.233.0.0/18
 
## The DPF REGISTRY is the Helm repository URL for the DPF Operator.
## Usually this is the GHCR registry. For development purposes, this can be set to a different repository.
export REGISTRY=https://helm.ngc.nvidia.com/nvidia/doca
 
## The DPF TAG is the version of the DPF components which will be deployed in this guide.
export TAG=v25.4.0
 
## URL to the BFB used in the `bfb.yaml` and linked by the DPUSet.
export BLUEFIELD_BITSTREAM="https://content.mellanox.com/BlueField/BFBs/Ubuntu22.04/bf-bundle-3.0.0-135_25.04_ubuntu-22.04_prod.bfb"

Export environment variables for the installation:
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```
            
            $ source export_vars.env
        
```

CNI Installation

OVN Kubernetes is used as the primary CNI for the cluster. On worker nodes, the primary CNI will be accelerated by offloading work to the DPU. On control plane nodes, OVN Kubernetes will run without offloading.

Create the NS for the CNI:

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            $ kubectl create ns ovn-kubernetes

Install the OVN Kubernetes CNI components from the helm chart, while substituting the environment variables with the ones we defined before.

manifests/01-cni-installation/helm-values/ovn-kubernetes.yml

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            commonManifests:
  enabled: true
nodeWithoutDPUManifests:
  enabled: true
controlPlaneManifests:
  enabled: true
nodeWithDPUManifests:
  enabled: true
  nodeMgmtPortNetdev: $DPU_P0_VF1
  dpuServiceAccountNamespace: dpf-operator-system
gatewayOpts: --gateway-interface=$DPU_P0
## Note this CIDR is followed by a trailing /24 which informs OVN Kubernetes on how to split the CIDR per node.
podNetwork: $POD_CIDR/24
serviceNetwork: $SERVICE_CIDR
k8sAPIServer: https://$TARGETCLUSTER_API_SERVER_HOST:$TARGETCLUSTER_API_SERVER_PORT

Run the following command:

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            $ envsubst < manifests/01-cni-installation/helm-values/ovn-kubernetes.yml | helm upgrade --install -n ovn-kubernetes ovn-kubernetes ${OVN_KUBERNETES_REPO_URL}/ovn-kubernetes-chart --version $TAG --values -
 
Release "ovn-kubernetes" does not exist. Installing it now.
Pulled: ghcr.io/nvidia/ovn-kubernetes-chart:v25.4.0
Digest: sha256:bce61b35ab485f06924681c5c906bfc0ab0065ac94830c6c036418e1edf995b3
NAME: ovn-kubernetes
LAST DEPLOYED: Tue May 20 08:51:29 2025
NAMESPACE: ovn-kubernetes
STATUS: deployed
REVISION: 1
TEST SUITE: None

Verify the CNI installation:

Note

The following verification commands may need to be run multiple times to ensure the condition is met.

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            $ kubectl wait --for=condition=ready --namespace ovn-kubernetes pods --all --timeout=300s
pod/ovnkube-control-plane-7b9869d9bd-jd94x condition met
pod/ovnkube-node-2bpmd condition met
pod/ovnkube-node-d4mb8 condition met
pod/ovnkube-node-stxlv condition met
 
$ kubectl wait --for=condition=ready nodes --all
node/master1 condition met
node/master2 condition met
node/master3 condition met
 
$ kubectl wait --for=condition=ready --namespace kube-system pods --all
pod/coredns-776bb9db5d-ndr7j condition met
pod/coredns-776bb9db5d-w499z condition met
pod/dns-autoscaler-6ffb84bd6-xj9bv condition met
pod/kube-apiserver-master1 condition met
pod/kube-apiserver-master2 condition met
pod/kube-apiserver-master3 condition met
pod/kube-controller-manager-master1 condition met
pod/kube-controller-manager-master2 condition met
pod/kube-controller-manager-master3 condition met
pod/kube-scheduler-master1 condition met
pod/kube-scheduler-master2 condition met
pod/kube-scheduler-master3 condition met
pod/kube-vip-master1 condition met
pod/kube-vip-master2 condition met
pod/kube-vip-master3 condition met

DPF Operator Installation

Cert-manager Installation

Cert-manager is a powerful and extensible X.509 certificate controller for Kubernetes workloads. It obtains certificates from a variety of Issuers, both popular public Issuers as well as private ones. It ensures the certificates are valid and up-to-date and attempts to renew certificates at a configured time before expiry.

In this deployment, it's a prerequisite used to provide certificates for webhooks utilized by DPF and its dependencies.

Create the NS for the operator:

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            $ kubectl create ns dpf-operator-system

Install Cert-manager using helm.

The following values are used for helm chart installation:

manifests/02-dpf-operator-installation/helm-values/cert-manager.yml

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            startupapicheck:
  enabled: false
crds:
  enabled: true
affinity:
  nodeAffinity:
    requiredDuringSchedulingIgnoredDuringExecution:
      nodeSelectorTerms:
        - matchExpressions:
            - key: node-role.kubernetes.io/master
              operator: Exists
        - matchExpressions:
            - key: node-role.kubernetes.io/control-plane
              operator: Exists
tolerations:
  - operator: Exists
    effect: NoSchedule
    key: node-role.kubernetes.io/control-plane
  - operator: Exists
    effect: NoSchedule
    key: node-role.kubernetes.io/master
cainjector:
  affinity:
    nodeAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
        nodeSelectorTerms:
          - matchExpressions:
              - key: node-role.kubernetes.io/master
                operator: Exists
          - matchExpressions:
              - key: node-role.kubernetes.io/control-plane
                operator: Exists
  tolerations:
    - operator: Exists
      effect: NoSchedule
      key: node-role.kubernetes.io/control-plane
    - operator: Exists
      effect: NoSchedule
      key: node-role.kubernetes.io/master
webhook:
  affinity:
    nodeAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
        nodeSelectorTerms:
          - matchExpressions:
              - key: node-role.kubernetes.io/master
                operator: Exists
          - matchExpressions:
              - key: node-role.kubernetes.io/control-plane
                operator: Exists
  tolerations:
    - operator: Exists
      effect: NoSchedule
      key: node-role.kubernetes.io/control-plane
    - operator: Exists
      effect: NoSchedule
      key: node-role.kubernetes.io/master

Run the following commands:

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            $ helm repo add jetstack https://charts.jetstack.io --force-update
$ helm upgrade --install --create-namespace --namespace cert-manager cert-manager jetstack/cert-manager --version v1.16.1 -f ./manifests/02-dpf-operator-installation/helm-values/cert-manager.yml
 
Release "cert-manager" does not exist. Installing it now.
NAME: cert-manager
LAST DEPLOYED: Tue May 20 12:59:30 2025
NAMESPACE: cert-manager
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
cert-manager v1.16.1 has been deployed successfully!

Verify that all pods in the cert-manager namespace are in a ready state:

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            $ kubectl wait --for=condition=ready --namespace cert-manager pods --all
pod/cert-manager-6ffdf6c5f8-tgv69 condition met
pod/cert-manager-cainjector-66b8577665-fbr5h condition met
pod/cert-manager-webhook-5cb94cb7b6-hb29q condition met

Install a CSI to back the DPUCluster etcd

Download a local-path-provisioner helm chart to your current working directory and create a NS for it:

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            $ curl https://codeload.github.com/rancher/local-path-provisioner/tar.gz/v0.0.30 | tar -xz --strip=3 local-path-provisioner-0.0.30/deploy/chart/local-path-provisioner/
$ kubectl create ns local-path-provisioner

Use the following values are used for the installation:

manifests/02-dpf-operator-installation/helm-values/local-path-provisioner.yml

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            tolerations:
  - operator: Exists
    effect: NoSchedule
    key: node-role.kubernetes.io/control-plane
  - operator: Exists
    effect: NoSchedule
    key: node-role.kubernetes.io/master

Run the following command:

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            $ helm install -n local-path-provisioner local-path-provisioner ./local-path-provisioner --version 0.0.30 -f ./manifests/02-dpf-operator-installation/helm-values/local-path-provisioner.yml
 
NAME: local-path-provisioner
LAST DEPLOYED: Tue May 20 13:01:40 2025
NAMESPACE: local-path-provisioner
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
...

Ensure that the pod in local-path-provisioner namespace is in ready state:

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            $ kubectl wait --for=condition=ready --namespace local-path-provisioner pods --all
pod/local-path-provisioner-75f649c47c-qb5w7 condition met

Create Storage Required by the DPF Operator

The following YAML files define storage (for the BFB image) that are required by the DPF operator.

manifests/02-dpf-operator-installation/nfs-storage-for-bfb-dpf-ga.yaml

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            ---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: bfb-pv
spec:
  capacity:
    storage: 10Gi
  volumeMode: Filesystem
  accessModes:
    - ReadWriteMany
  nfs:
    path: /mnt/dpf_share/bfb
    server: $NFS_SERVER_IP
  persistentVolumeReclaimPolicy: Delete
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: bfb-pvc
  namespace: dpf-operator-system
spec:
  accessModes:
  - ReadWriteMany
  resources:
    requests:
      storage: 10Gi
  volumeMode: Filesystem

Run the following command to substitute the environment variables using envsubst and apply the YAML files:

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            $ cat manifests/02-dpf-operator-installation/*.yaml | envsubst | kubectl apply -f -

DPF Operator Deployment

The DPF Operator helm values are detailed in the following YAML file:

manifests/02-dpf-operator-installation/helm-values/dpf-operator.yml

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            kamaji-etcd:
  persistentVolumeClaim:
    storageClassName: local-path
node-feature-discovery:
  worker:
    extraEnvs:
      - name: "KUBERNETES_SERVICE_HOST"
        value: "$TARGETCLUSTER_API_SERVER_HOST"
      - name: "KUBERNETES_SERVICE_PORT"
        value: "$TARGETCLUSTER_API_SERVER_PORT"

Run the following command to substitute the environment variables and install the DPF Operator:

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            $ helm repo add --force-update dpf-repository ${REGISTRY}
$ helm repo update
$ envsubst < ./manifests/02-dpf-operator-installation/helm-values/dpf-operator.yml | helm upgrade --install -n dpf-operator-system dpf-operator dpf-repository/dpf-operator --version=$TAG --values -
 
Release "dpf-operator" does not exist. Installing it now.
NAME: dpf-operator
LAST DEPLOYED: Tue May 20 13:18:58 2025
NAMESPACE: dpf-operator-system
STATUS: deployed
REVISION: 1
TEST SUITE: None

Verify the DPF Operator installation by ensuring the deployment is available, and that all pods are in a ready:

Note

The following verification commands may need to be run multiple times to ensure the conditions are met.

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            $ kubectl rollout status deployment --namespace dpf-operator-system dpf-operator-controller-manager
deployment "dpf-operator-controller-manager" successfully rolled out
 
$ kubectl wait --for=condition=ready --namespace dpf-operator-system pods --all
pod/dpf-operator-argocd-application-controller-0 condition met
pod/dpf-operator-argocd-applicationset-controller-84d86b665f-fqd6x condition met
pod/dpf-operator-argocd-redis-584fbbf667-zbhcb condition met
pod/dpf-operator-argocd-repo-server-6bff769f95-2cjgd condition met
pod/dpf-operator-argocd-server-54fcf54589-6cvqf condition met
pod/dpf-operator-controller-manager-54f76799c5-j4dcz condition met
pod/dpf-operator-kamaji-6dcf4ccdfd-lsgvd condition met
pod/dpf-operator-kamaji-etcd-0 condition met
pod/dpf-operator-kamaji-etcd-1 condition met
pod/dpf-operator-kamaji-etcd-2 condition met
pod/dpf-operator-maintenance-operator-7776bb95d-vnh5k condition met
pod/dpf-operator-node-feature-discovery-gc-545bdbf8df-q68wp condition met
pod/dpf-operator-node-feature-discovery-master-7df7dc844c-p64zz condition met

DPF System Installation

This section involves creating the DPF system components and some basic infrastructure required for a functioning DPF-enabled cluster.

The following YAML files define the DPFOperatorConfig to install the DPF System components. They also define the DPUCluster to serve as the Kubernetes control plane for the DPU nodes.

manifests/03-dpf-system-installation/operatorconfig.yaml

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            ---
apiVersion: operator.dpu.nvidia.com/v1alpha1
kind: DPFOperatorConfig
metadata:
  name: dpfoperatorconfig
  namespace: dpf-operator-system
spec:
  overrides:
    kubernetesAPIServerVIP: $TARGETCLUSTER_API_SERVER_HOST
    kubernetesAPIServerPort: $TARGETCLUSTER_API_SERVER_PORT
  provisioningController:
    bfbPVCName: "bfb-pvc"
    dmsTimeout: 900
  kamajiClusterManager:
    disable: false

manifests/03-dpf-system-installation/dpucluster.yaml

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            ---
apiVersion: provisioning.dpu.nvidia.com/v1alpha1
kind: DPUCluster
metadata:
  name: dpu-cplane-tenant1
  namespace: dpu-cplane-tenant1
spec:
  type: kamaji
  maxNodes: 10
  version: v1.30.2
  clusterEndpoint:
    # deploy keepalived instances on the nodes that match the given nodeSelector.
    keepalived:
      # interface on which keepalived will listen. Should be the oob interface of the control plane node.
      interface: $DPUCLUSTER_INTERFACE
      # Virtual IP reserved for the DPU Cluster load balancer. Must not be allocatable by DHCP.
      vip: $DPUCLUSTER_VIP
      # virtualRouterID must be in range [1,255], make sure the given virtualRouterID does not duplicate with any existing keepalived process running on the host
      virtualRouterID: 126
      nodeSelector:
        node-role.kubernetes.io/control-plane: ""

Create namespace (NS) for the Kubernetes control plane of the DPU nodes:
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```
            
            $ kubectl create ns dpu-cplane-tenant1
        
```

Apply the previous YAML files:

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            $ cat manifests/03-dpf-system-installation/*.yaml | envsubst | kubectl apply -f -

Verify the DPF system by ensuring that the provisioning and DPUService controller manager deployments are available. Also confirm that all other deployments in the DPF Operator system are available and that the DPUCluster is ready for nodes to join.

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            $ kubectl rollout status deployment --namespace dpf-operator-system dpf-provisioning-controller-manager dpuservice-controller-manager
deployment "dpf-provisioning-controller-manager" successfully rolled out
deployment "dpuservice-controller-manager" successfully rolled out
 
$ kubectl rollout status deployment --namespace dpf-operator-system
deployment "dpf-operator-argocd-applicationset-controller" successfully rolled out
deployment "dpf-operator-argocd-redis" successfully rolled out
deployment "dpf-operator-argocd-repo-server" successfully rolled out
deployment "dpf-operator-argocd-server" successfully rolled out
deployment "dpf-operator-controller-manager" successfully rolled out
deployment "dpf-operator-kamaji" successfully rolled out
deployment "dpf-operator-maintenance-operator" successfully rolled out
deployment "dpf-operator-node-feature-discovery-gc" successfully rolled out
deployment "dpf-operator-node-feature-discovery-master" successfully rolled out
deployment "dpf-provisioning-controller-manager" successfully rolled out
deployment "dpuservice-controller-manager" successfully rolled out
deployment "kamaji-cm-controller-manager" successfully rolled out
 
$ kubectl wait --for=condition=ready --namespace dpu-cplane-tenant1 dpucluster --all
dpucluster.provisioning.dpu.nvidia.com/dpu-cplane-tenant1 condition met

Install Components to Enable Accelerated CNI Nodes

OVN Kubernetes accelerates traffic by attaching a VF to each pod using the primary CNI. This VF offloads flows to the DPU, and this section details the components needed to connect pods to the offloaded OVN Kubernetes CNI.

Install Multus and SRIOV Network Operator using NVIDIA Network Operator

Add the NVIDIA Network Operator Helm repository:

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            $ helm repo add nvidia https://helm.ngc.nvidia.com/nvidia --force-update

The following network-operator.yaml values file will be applied:

manifests/04-enable-accelerated-cni/helm-values/network-operator.yml

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            nfd:
  enabled: false
  deployNodeFeatureRules: false
sriovNetworkOperator:
  enabled: true
sriov-network-operator:
  operator:
    affinity:
      nodeAffinity:
        requiredDuringSchedulingIgnoredDuringExecution:
          nodeSelectorTerms:
            - matchExpressions:
                - key: node-role.kubernetes.io/master
                  operator: Exists
            - matchExpressions:
                - key: node-role.kubernetes.io/control-plane
                  operator: Exists
  crds:
    enabled: true
  sriovOperatorConfig:
    deploy: true
    configDaemonNodeSelector: null
operator:
  affinity:
    nodeAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
        nodeSelectorTerms:
          - matchExpressions:
              - key: node-role.kubernetes.io/master
                operator: Exists
          - matchExpressions:
              - key: node-role.kubernetes.io/control-plane
                operator: Exists

Deploy the operator:

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            $ helm upgrade --no-hooks --install --create-namespace --namespace nvidia-network-operator network-operator nvidia/network-operator --version 24.7.0 -f ./manifests/04-enable-accelerated-cni/helm-values/network-operator.yml
 
Release "network-operator" does not exist. Installing it now.
NAME: network-operator
LAST DEPLOYED: Tue May 20 13:36:57 2025
NAMESPACE: nvidia-network-operator
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
...

Ensure all the pods in nvidia-network-operator namespace are ready:

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            $ kubectl wait --for=condition=ready --namespace nvidia-network-operator pods --all
pod/network-operator-7bc7b45d67-xk2fl condition met
pod/network-operator-sriov-network-operator-86c9cd4899-6hlzd condition met

Install OVN Kubernetes resource injection webhook

The OVN Kubernetes resource injection webhook is added to each pod scheduled to a worker node that requests a VF and a Network Attachment Definition. This webhook is part of the same helm chart as the other components of the OVN Kubernetes CNI. It is installed by modifying the existing helm deployment to include the webhook component.

The following ovn-kubernetes.yaml values file will be applied:

manifests/04-enable-accelerated-cni/helm-values/ovn-kubernetes.yml

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            ovn-kubernetes-resource-injector:
  ## Enable the ovn-kubernetes-resource-injector
  enabled: true

Run the following command:

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            $ envsubst < manifests/04-enable-accelerated-cni/helm-values/ovn-kubernetes.yml | helm upgrade --install -n ovn-kubernetes ovn-kubernetes-resource-injector ${OVN_KUBERNETES_REPO_URL}/ovn-kubernetes-chart --version $TAG --values -
 
Release "ovn-kubernetes-resource-injector" does not exist. Installing it now.
Pulled: ghcr.io/nvidia/ovn-kubernetes-chart:v25.4.0
Digest: sha256:bce61b35ab485f06924681c5c906bfc0ab0065ac94830c6c036418e1edf995b3
NAME: ovn-kubernetes-resource-injector
LAST DEPLOYED: Tue May 20 13:41:38 2025
NAMESPACE: ovn-kubernetes
STATUS: deployed
REVISION: 1
TEST SUITE: None

Verify that the resource injector deployment has been successfully rolled out.

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            $ kubectl rollout status deployment --namespace ovn-kubernetes ovn-kubernetes-ovn-kubernetes-resource-injector
deployment "ovn-kubernetes-ovn-kubernetes-resource-injector" successfully rolled out

Apply NicClusterPolicy and SriovNetworkNodePolicy

Apply the following NicClusterPolicy and SriovNetworkNodePolicy configuration files should be applied.

manifests/04-enable-accelerated-cni/nic_cluster_policy.yaml

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            ---
apiVersion: mellanox.com/v1alpha1
kind: NicClusterPolicy
metadata:
  name: nic-cluster-policy
spec:
  secondaryNetwork:
    multus:
      image: multus-cni
      imagePullSecrets: []
      repository: ghcr.io/k8snetworkplumbingwg
      version: v3.9.3

manifests/04-enable-accelerated-cni/sriov_network_operator_policy.yaml

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            ---
apiVersion: sriovnetwork.openshift.io/v1
kind: SriovNetworkNodePolicy
metadata:
  name: bf3-p0-vfs
  namespace: nvidia-network-operator
spec:
  mtu: 1500
  nicSelector:
    deviceID: "a2dc"
    vendor: "15b3"
    pfNames:
    - $DPU_P0#2-45
  nodeSelector:
    node-role.kubernetes.io/worker: ""
  numVfs: 46
  resourceName: bf3-p0-vfs
  isRdma: true
  externallyManaged: true
  deviceType: netdevice
  linkType: eth

Apply those configuration files:

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            $ cat manifests/04-enable-accelerated-cni/*.yaml | envsubst | kubectl apply -f -

Verify the DPF system by ensuring that the following DaemonSets were successfully rolled out:

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            $ kubectl rollout status daemonset --namespace nvidia-network-operator kube-multus-ds sriov-network-config-daemon sriov-device-plugin
daemon set "kube-multus-ds" successfully rolled out
daemon set "sriov-network-config-daemon" successfully rolled out
daemon set "sriov-device-plugin" successfully rolled out

DPU Provisioning and Service Installation

Provisioning limitations

Note

The SPDK CSI image and helm chart are not provided as part of the DPF release. You need to build them following the instructions in dpuservices/storage/examples/spdk-csi/README.md. After building the image and chart, replace the placeholder values (such as example.com/spdk-csi, oci://example.com, etc.) in the following SPDK CSI configuration examples with your actual repository locations and version information.

Before deploying the objects under the manifests/05-dpudeployment-installationdirectory, a few adjustments need to be made.

Review dpudeployment.yaml to reference the DPUFlavor suited for SNAP:

manifests/05-dpudeployment-installation/dpudeployment.yaml

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            ---
apiVersion: svc.dpu.nvidia.com/v1alpha1
kind: DPUDeployment
metadata:
  name: ovn-hbn-snap
  namespace: dpf-operator-system
spec:
  dpus:
    bfb: bf-bundle
    flavor: dpf-provisioning-hbn-ovn-storage
    dpuSets:
    - nameSuffix: "dpuset1"
      nodeSelector:
        matchLabels:
          feature.node.kubernetes.io/dpu-enabled: "true"
  services:
    ovn:
      serviceTemplate: ovn
      serviceConfiguration: ovn
    hbn:
      serviceTemplate: hbn
      serviceConfiguration: hbn
    doca-snap:
      serviceTemplate: doca-snap
      serviceConfiguration: doca-snap
    snap-configuration:
      serviceTemplate: snap-configuration
      serviceConfiguration: snap-configuration
    snap-controller:
      serviceTemplate: snap-controller
      serviceConfiguration: snap-controller
    snap-csi-plugin:
      serviceTemplate: snap-csi-plugin
      serviceConfiguration: snap-csi-plugin
    snap-node-driver:
      serviceTemplate: snap-node-driver
      serviceConfiguration: snap-node-driver
    storage-vendor-dpu-plugin:
      serviceTemplate: storage-vendor-dpu-plugin
      serviceConfiguration: storage-vendor-dpu-plugin
    spdk-csi-controller:
      serviceTemplate: spdk-csi-controller
      serviceConfiguration: spdk-csi-controller
    spdk-csi-dpu-controller:
      serviceTemplate: spdk-csi-dpu-controller
      serviceConfiguration: spdk-csi-dpu-controller
  serviceChains:
    switches:
      - ports:
        - serviceInterface:
            matchLabels:
              uplink: p0
        - service:
            name: hbn
            interface: p0_if
      - ports:
        - serviceInterface:
            matchLabels:
              uplink: p1
        - service:
            name: hbn
            interface: p1_if
      - ports:
        - serviceInterface:
            matchLabels:
              port: ovn
        - service:
            name: hbn
            interface: pf2dpu2_if
# SNAP interface            
      - ports:
        - service:
            name: doca-snap
            interface: app_sf 
            ipam:
              matchLabels:
                svc.dpu.nvidia.com/pool: spdk-pool                
        - service:
            name: hbn
            interface: snap_if

Set the username and password for the spdk-target (as provided in SPDK apps installation):

manifests/05-dpudeployment-installation/snap-spdk-secret.yaml

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            ---
apiVersion: v1
kind: Secret
metadata:
  name: spdkcsi-secret
  namespace: dpf-operator-system
  labels:
    # this label enables replication of the secret from the host to the dpu cluster
    dpu.nvidia.com/image-pull-secret: ""
stringData:
  # name field in the "rpcTokens" list should match name of the
  # spdk target from DPUService.helmChart.values.host.config.targets.nodes
  secret.json: |-
    {
      "rpcTokens": [
        {
          "name": "spdk-target",
          "username": "exampleuser",
          "password": "examplepassword"
        }
      ]
    }

Set the ipv4Subnet settings for the spdk-pool (please note: GW IP should be assigned to DATA interface in Storage Target Node installation):

manifests/05-dpudeployment-installation/snap-hbn-ovn-ipams.yaml

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            ---
apiVersion: svc.dpu.nvidia.com/v1alpha1
kind: DPUServiceIPAM
metadata:
  name: pool1
  namespace: dpf-operator-system
spec:
  ipv4Network:
    network: "10.0.120.0/22"
    gatewayIndex: 3
    prefixSize: 29
---
apiVersion: svc.dpu.nvidia.com/v1alpha1
kind: DPUServiceIPAM
metadata:
  name: spdk-pool
  namespace: dpf-operator-system
spec:
  metadata:
    labels:
      svc.dpu.nvidia.com/pool: spdk-pool
  ipv4Subnet:
    subnet: "10.0.124.0/24"
    gateway: "10.0.124.1"
    perNodeIPCount: 4

Set the rpcURL , targetTypeand targetAddr settings according to your environment:

manifests/05-dpudeployment-installation/dpuserviceconfig_spdk-csi-controller.yaml

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            ---
apiVersion: svc.dpu.nvidia.com/v1alpha1
kind: DPUServiceConfiguration
metadata:
  name: spdk-csi-controller
  namespace: dpf-operator-system
spec:
  deploymentServiceName: "spdk-csi-controller"
  upgradePolicy:
    applyNodeEffect: false
  serviceConfiguration:
    deployInCluster: true
    helmChart:
      values:
        host:
          enabled: true
          plugin:
            image:
              # Shuold be replaced!!!
              repository: example.com/spdk-csi
              tag: v0.1.0
          config:
            targets:
              nodes:
                # name of the target
                - name: spdk-target
                  # management address
                  rpcURL: http://10.0.110.25:8000
                  # type of the target, e.g. nvme-tcp, nvme-rdma
                  targetType: nvme-rdma
                  # target service IP
                  targetAddr: 10.0.124.1
            # required parameter, name of the secret that contains connection
            # details to access the DPU cluster.
            # this secret should be created by the DPUServiceCredentialRequest API.
            dpuClusterSecret: spdk-csi-controller-dpu-cluster-credentials

The rest of the configuration files in the folder manifest/05-dpudeployment-installation/ remain the same, including:
- BFB provisioning YAML:
  bfb.yaml
- DOCA-SNAP DPUService deployment and configuration YAMLs:
  dpuserviceconfig_doca-snap.yaml
  dpuservicetemplate_doca-snap.yaml
- HBN DPUService deployment and configuration YAMLs:
  dpuserviceconfig_hbn.yaml
  dpuservicetemplate_hbn.yaml
- OVN DPUService deployment and configuration YAMLs:
  dpuserviceconfig_ovn.yaml
  dpuservicetemplate_ovn.yaml
- SNAP configuration DPUService deployment and configuration YAMLs:
  dpuserviceconfig_snap-configuration.yaml
  dpuservicetemplate_snap-configuration.yaml
- SNAP controller DPUService deployment and configuration YAMLs:
  dpuserviceconfig_snap-controller.yaml
  dpuservicetemplate_snap-controller.yaml
- SNAP CSI plugin DPUService deployment and configuration YAMLs:
  dpuserviceconfig_snap-csi-plugin.yaml
  dpuservicetemplate_snap-csi-plugin.yaml
- SNAP node driver DPUService deployment and configuration YAMLs:
  dpuserviceconfig_snap-node-driver.yaml
  dpuservicetemplate_snap-node-driver.yaml
- SPDK CSI controller DPUService deployment and configuration YAMLs:
  dpuserviceconfig_spdk-csi-controller.yaml
  dpuservicetemplate_spdk-csi-controller.yaml
- SPDK CSI DPU controller DPUService deployment and configuration YAMLs:
  dpuserviceconfig_spdk-csi-dpu-controller.yaml
  dpuservicetemplate_spdk-csi-dpu-controller.yaml
- Storage vendor DPU pludin DPUService deployment and configuration YAMLs:
  dpuserviceconfig_storage-vendor-dpu-plugin.yaml
  dpuservicetemplate_storage-vendor-dpu-plugin.yaml
- DPUServiceIPAM for the loopback interface in HBN:
  hbn-loopback-ipam.yaml
- OVN DPUServiceCredentialRequest to allow cross cluster communication:
  ovn-credentials.yaml
- OVN DPUServiceInterface to define the ports attached to OVN workloads on the DPU:
  ovn-iface.yaml
- DPUServiceInterfaces for physical ports on the DPU:
  physical-ifaces.yaml
- SNAP DPUServiceCredentialRequest to allow cross cluster communication:
  snap-credentials.yaml

Apply all of the YAML files mentioned above using the following command:

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            $ cat manifests/05-dpudeployment-installation/*.yaml | envsubst | kubectl apply -f -

Verify the DPUService installation by ensuring the DPUServices are created and have been reconciled. Also verify that the DPUServiceIPAMs, DPUServiceInterfaces and DPUServiceChains have all been reconciled:

Note

These verification commands may need to be run multiple times to ensure the conditions are met.
When using DPUDeployment, the DPUService name will have the DPUDeployment name added as prefix. For example, ovn-hbn-hbn.

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            $ kubectl wait --for=condition=ApplicationsReconciled --namespace dpf-operator-system dpuservices --all
dpuservice.svc.dpu.nvidia.com/doca-snap-sk6hj condition met
dpuservice.svc.dpu.nvidia.com/flannel condition met
dpuservice.svc.dpu.nvidia.com/hbn-gjdzr condition met
dpuservice.svc.dpu.nvidia.com/multus condition met
dpuservice.svc.dpu.nvidia.com/nvidia-k8s-ipam condition met
dpuservice.svc.dpu.nvidia.com/ovn-tfc8q condition met
dpuservice.svc.dpu.nvidia.com/ovs-cni condition met
dpuservice.svc.dpu.nvidia.com/ovs-helper condition met
dpuservice.svc.dpu.nvidia.com/servicechainset-controller condition met
dpuservice.svc.dpu.nvidia.com/servicechainset-rbac-and-crds condition met
dpuservice.svc.dpu.nvidia.com/sfc-controller condition met
dpuservice.svc.dpu.nvidia.com/snap-configuration-48rqj condition met
dpuservice.svc.dpu.nvidia.com/snap-controller-vgvfl condition met
dpuservice.svc.dpu.nvidia.com/snap-csi-plugin-b76c4 condition met
dpuservice.svc.dpu.nvidia.com/snap-node-driver-ktx2c condition met
dpuservice.svc.dpu.nvidia.com/spdk-csi-controller-gmqcd condition met
dpuservice.svc.dpu.nvidia.com/spdk-csi-dpu-controller-v5sl5 condition met
dpuservice.svc.dpu.nvidia.com/sriov-device-plugin condition met
dpuservice.svc.dpu.nvidia.com/storage-vendor-dpu-plugin-8cksj condition met
 
 
$ kubectl wait --for=condition=DPUIPAMObjectReconciled --namespace dpf-operator-system dpuserviceipam --all
dpuserviceipam.svc.dpu.nvidia.com/loopback condition met
dpuserviceipam.svc.dpu.nvidia.com/pool1 condition met
dpuserviceipam.svc.dpu.nvidia.com/spdk-pool condition met
 
$ kubectl wait --for=condition=ServiceInterfaceSetReconciled --namespace dpf-operator-system dpuserviceinterface --all
dpuserviceinterface.svc.dpu.nvidia.com/doca-snap-app-sf-v8cfj condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-p0-if-dg47c condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-p1-if-t27cz condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-pf2dpu2-if-w7w7l condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-snap-if-6trz9 condition met
dpuserviceinterface.svc.dpu.nvidia.com/ovn condition met
dpuserviceinterface.svc.dpu.nvidia.com/p0 condition met
dpuserviceinterface.svc.dpu.nvidia.com/p1 condition met
 
 
$ kubectl wait --for=condition=ServiceChainSetReconciled --namespace dpf-operator-system dpuservicechain --all
dpuservicechain.svc.dpu.nvidia.com/ovn-hbn-snap-gj8f5 condition met

K8s Cluster Scale-out

Add Worker Nodes to the Cluster

At this point, workers should be added to the cluster. As they are added, DPUs will be provisioned and DPUServices will begin to be spun up.

Return to the shell where Kubespray was previously run to deploy the cluster. Unmark the kube_node group in the hosts.yaml file, and add the worker nodes to the cluster:

Note

Ensure you are in the Python virtual environment ( .venv ) when running the command.

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            (.venv) depuser@jump:~/kubespray$ cat inventory/mycluster/hosts.yaml
...
   k8s_cluster:
      children:
        kube_control_plane:
        kube_node:
...
 
(.venv) depuser@jump:~/kubespray$ ansible-playbook -i inventory/mycluster/hosts.yaml --become --become-user=root scale.yml

The scale-out shouldn't take a long time, and a successful run should look similar to the following output:

Verification

To follow the progress of the DPU provisioning, run the following command to check in which phase it currently is:

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            $ watch -n10 "kubectl describe dpu -n dpf-operator-system | grep 'Node Name\|Type\|Last\|Phase'"
Every 10.0s: kubectl describe dpu -n dpf-operator-system | grep 'Node Name\|Type\|Last\|Phase'                                                                                                                                   jump: Tue May 20 14:54:41 2025
 
  Dpu Node Name:                                      worker1
    Last Transition Time:  2025-05-20T14:51:54Z
    Type:                  Initialized
    Last Transition Time:  2025-05-20T14:51:54Z
    Type:                  BFBReady
    Last Transition Time:  2025-05-20T14:52:09Z
    Type:                  NodeEffectReady
    Last Transition Time:  2025-05-20T14:52:10Z
    Type:                  InterfaceInitialized
    Last Transition Time:  2025-05-20T14:52:11Z
    Type:                  FWConfigured
  Phase:  OS Installing
  Dpu Node Name:                                      worker2
    Last Transition Time:  2025-05-20T14:50:34Z
    Type:                  Initialized
    Last Transition Time:  2025-05-20T14:50:34Z
    Type:                  BFBReady
    Last Transition Time:  2025-05-20T14:50:49Z
    Type:                  NodeEffectReady
    Last Transition Time:  2025-05-20T14:50:50Z
    Type:                  InterfaceInitialized
    Last Transition Time:  2025-05-20T14:50:51Z
    Type:                  FWConfigured
  Phase:  OS Installing

Validate that the DPUs have been provisioned successfully by ensuring they're in a ready state:

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            $ kubectl wait --for=condition=ready --namespace dpf-operator-system dpu --all
dpu.provisioning.dpu.nvidia.com/worker1-0000-89-00 condition met
dpu.provisioning.dpu.nvidia.com/worker2-0000-89-00 condition met

Ensure that the following DaemonSets each have two ready replicas:

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            $ kubectl wait ds --for=jsonpath='{.status.numberReady}'=2 --namespace nvidia-network-operator kube-multus-ds sriov-network-config-daemon sriov-device-plugin
daemonset.apps/kube-multus-ds condition met
daemonset.apps/sriov-network-config-daemon condition met
daemonset.apps/sriov-device-plugin condition met
 
$ kubectl wait ds --for=jsonpath='{.status.numberReady}'=2 --namespace ovn-kubernetes ovnkube-node-dpu-host
daemonset.apps/ovnkube-node-dpu-host condition met

Validate that all the different DPUServices, DPUServiceIPAMs, DPUServiceInterfaces and DPUServiceChains objects are now in a ready state

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            $ kubectl wait --for=condition=ApplicationsReady --namespace dpf-operator-system dpuservices -l svc.dpu.nvidia.com/owned-by-dpudeployment=dpf-operator-system_ovn-hbn-snap
dpuservice.svc.dpu.nvidia.com/doca-snap-sk6hj condition met
dpuservice.svc.dpu.nvidia.com/hbn-gjdzr condition met
dpuservice.svc.dpu.nvidia.com/ovn-tfc8q condition met
dpuservice.svc.dpu.nvidia.com/snap-configuration-48rqj condition met
dpuservice.svc.dpu.nvidia.com/snap-controller-vgvfl condition met
dpuservice.svc.dpu.nvidia.com/snap-csi-plugin-b76c4 condition met
dpuservice.svc.dpu.nvidia.com/snap-node-driver-ktx2c condition met
dpuservice.svc.dpu.nvidia.com/spdk-csi-controller-gmqcd condition met
dpuservice.svc.dpu.nvidia.com/spdk-csi-dpu-controller-v5sl5 condition met
dpuservice.svc.dpu.nvidia.com/storage-vendor-dpu-plugin-8cksj condition met
 
 
$ kubectl wait --for=condition=DPUIPAMObjectReady --namespace dpf-operator-system dpuserviceipam --all
dpuserviceipam.svc.dpu.nvidia.com/loopback condition met
dpuserviceipam.svc.dpu.nvidia.com/pool1 condition met
dpuserviceipam.svc.dpu.nvidia.com/spdk-pool condition met
 
$ kubectl wait --for=condition=ServiceInterfaceSetReady --namespace dpf-operator-system dpuserviceinterface --all
dpuserviceinterface.svc.dpu.nvidia.com/doca-snap-app-sf-v8cfj condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-p0-if-dg47c condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-p1-if-t27cz condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-pf2dpu2-if-w7w7l condition met
dpuserviceinterface.svc.dpu.nvidia.com/hbn-snap-if-6trz9 condition met
dpuserviceinterface.svc.dpu.nvidia.com/ovn condition met
dpuserviceinterface.svc.dpu.nvidia.com/p0 condition met
dpuserviceinterface.svc.dpu.nvidia.com/p1 condition met
 
 
$ kubectl wait --for=condition=ServiceChainSetReady --namespace dpf-operator-system dpuservicechain --all
dpuservicechain.svc.dpu.nvidia.com/ovn-hbn-snap-gj8f5 condition met

Congratulations, the DPF system has been successfully installed!

Deployment Validation

Note

The current implementation of DOCA SNAP for DPF supports only RAW Block device volumes.

To verify the DPF deployment with DOCA SNAP storage services by using following simple workload:

Deploy a simple workload pod with PVC storage provisioning:

manifests/06-test-traffic/snap-workloads.yaml

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            ---
apiVersion: v1
kind: Pod
metadata:
  name: snap-storage-pod
spec:
  containers:
    - name: myfrontend
      image: ubuntu:24.04
      command:
        - sh
        - -c
        - sleep inf  
      volumeDevices:
        - name: data
          devicePath: /dev/xvda
  volumes:
    - name: data
      persistentVolumeClaim:
        claimName: myclaim
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: myclaim
spec:
  storageClassName: snap
  accessModes:
    - ReadWriteOnce
  volumeMode: Block
  resources:
    requests:
      storage: 8Gi
---
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: snap
  annotations:
    storageclass.kubernetes.io/is-default-class: "true"
provisioner: csi.snap.nvidia.com
parameters:
  policy: "policy1"

Validate deployment with simple performance tests:

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            $ kubectl exec -it snap-storage-pod -- bash
root@snap-storage-pod:/# ls -la /dev/xvda 
brw-rw---- 1 root disk 259, 8 May 27 09:31 /dev/xvda
 
root@snap-storage-pod:/# dd if=/dev/zero of=/dev/xvda bs=4k count=2000k   
2048000+0 records in
2048000+0 records out
8388608000 bytes (8.4 GB, 7.8 GiB) copied, 2.42949 s, 3.5 GB/s

Create two job configuration files for FIO tests (FIO Ubuntu package should be installed: apt-get install -y fio):

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            root@snap-storage-pod:~# cat job-1M.fio 
[global]
ioengine=libaio
iodepth=32
direct=1
rw=read
bs=1M
numjobs=8
runtime=60
time_based
group_reporting
 
[job1]
filename=/dev/xvda
 
root@snap-storage-pod:~# cat job-4k.fio 
[global]
ioengine=libaio
direct=1
iodepth=32
rw=read
bs=64k
numjobs=8
runtime=60
time_based
group_reporting
 
[job1]
filename=/dev/xvda

Run performance tests:

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            root@snap-storage-pod:~# fio job-1M.fio 
job1: (g=0): rw=read, bs=(R) 1024KiB-1024KiB, (W) 1024KiB-1024KiB, (T) 1024KiB-1024KiB, ioengine=libaio, iodepth=32
...
fio-3.36
Starting 8 processes
Jobs: 8 (f=8): [R(8)][100.0%][r=3311MiB/s][r=3311 IOPS][eta 00m:00s]
job1: (groupid=0, jobs=8): err= 0: pid=3798: Tue May 27 09:33:41 2025
  read: IOPS=3236, BW=3237MiB/s (3394MB/s)(190GiB/60007msec)
    slat (usec): min=34, max=58507, avg=2469.73, stdev=7557.90
    clat (msec): min=5, max=161, avg=76.55, stdev=20.68
     lat (msec): min=5, max=163, avg=79.01, stdev=19.97
    clat percentiles (msec):
     |  1.00th=[   36],  5.00th=[   39], 10.00th=[   40], 20.00th=[   43],
     | 30.00th=[   84], 40.00th=[   86], 50.00th=[   87], 60.00th=[   88],
     | 70.00th=[   89], 80.00th=[   90], 90.00th=[   92], 95.00th=[   93],
     | 99.00th=[   96], 99.50th=[   99], 99.90th=[  107], 99.95th=[  114],
     | 99.99th=[  159]
   bw (  MiB/s): min= 2528, max= 3580, per=99.91%, avg=3233.68, stdev=16.98, samples=952
   iops        : min= 2524, max= 3580, avg=3233.56, stdev=17.00, samples=952
  lat (msec)   : 10=0.02%, 20=0.03%, 50=23.48%, 100=76.18%, 250=0.29%
  cpu          : usr=0.08%, sys=3.95%, ctx=1483542, majf=0, minf=203142
  IO depths    : 1=0.1%, 2=0.1%, 4=0.1%, 8=0.1%, 16=0.1%, 32=99.9%, >=64=0.0%
     submit    : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0%
     complete  : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.1%, 64=0.0%, >=64=0.0%
     issued rwts: total=194218,0,0,0 short=0,0,0,0 dropped=0,0,0,0
     latency   : target=0, window=0, percentile=100.00%, depth=32
 
Run status group 0 (all jobs):
   READ: bw=3237MiB/s (3394MB/s), 3237MiB/s-3237MiB/s (3394MB/s-3394MB/s), io=190GiB (204GB), run=60007-60007msec
 
Disk stats (read/write):
  nvme1n3: ios=1548902/0, sectors=396518912/0, merge=0/0, ticks=15298488/0, in_queue=15298488, util=99.90%
 
===================================================================================================================
root@snap-storage-pod:~# fio job-4k.fio  
job1: (g=0): rw=read, bs=(R) 64.0KiB-64.0KiB, (W) 64.0KiB-64.0KiB, (T) 64.0KiB-64.0KiB, ioengine=libaio, iodepth=32
...
fio-3.36
Starting 8 processes
Jobs: 8 (f=8): [R(8)][100.0%][r=3193MiB/s][r=51.1k IOPS][eta 00m:00s]
job1: (groupid=0, jobs=8): err= 0: pid=3856: Tue May 27 09:35:22 2025
  read: IOPS=50.8k, BW=3175MiB/s (3329MB/s)(186GiB/60020msec)
    slat (usec): min=3, max=564, avg=10.33, stdev= 6.31
    clat (usec): min=1226, max=61859, avg=5028.10, stdev=10597.80
     lat (usec): min=1243, max=61869, avg=5038.44, stdev=10597.61
    clat percentiles (usec):
     |  1.00th=[ 1680],  5.00th=[ 1811], 10.00th=[ 1926], 20.00th=[ 2114],
     | 30.00th=[ 2278], 40.00th=[ 2409], 50.00th=[ 2540], 60.00th=[ 2671],
     | 70.00th=[ 2868], 80.00th=[ 3097], 90.00th=[ 3654], 95.00th=[45876],
     | 99.00th=[51643], 99.50th=[54264], 99.90th=[56361], 99.95th=[57934],
     | 99.99th=[58983]
   bw (  MiB/s): min= 2895, max= 3316, per=100.00%, avg=3177.29, stdev= 8.07, samples=952
   iops        : min=46332, max=53068, avg=50836.59, stdev=129.11, samples=952
  lat (msec)   : 2=14.08%, 4=78.17%, 10=2.71%, 20=0.01%, 50=1.51%
  lat (msec)   : 100=3.53%
  cpu          : usr=1.06%, sys=8.50%, ctx=2446739, majf=0, minf=4446
  IO depths    : 1=0.1%, 2=0.1%, 4=0.1%, 8=0.1%, 16=0.1%, 32=100.0%, >=64=0.0%
     submit    : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.0%, >=64=0.0%
     complete  : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.1%, 64=0.0%, >=64=0.0%
     issued rwts: total=3049161,0,0,0 short=0,0,0,0 dropped=0,0,0,0
     latency   : target=0, window=0, percentile=100.00%, depth=32
 
Run status group 0 (all jobs):
   READ: bw=3175MiB/s (3329MB/s), 3175MiB/s-3175MiB/s (3329MB/s-3329MB/s), io=186GiB (200GB), run=60020-60020msec
 
Disk stats (read/write):
  nvme1n3: ios=3043368/0, sectors=389554432/0, merge=26/0, ticks=15279103/0, in_queue=15279103, util=99.86%

At the end of the test, you'll see the achieved performance.

Note

The performance results listed in this guide are indicative and should not be considered as formal performance targets for NVIDIA products.

Authors

Vitaliy Razinkov
Vitaliy Razinkov is a Solutions Architect on the NVIDIA Networking team, specializing in complex Kubernetes, OpenShift, and Microsoft solutions. With over 25 years of experience in senior technical roles, he brings deep expertise in designing and implementing advanced infrastructures. Vitaliy has authored several reference design guides on Microsoft technologies, RoCE/RDMA-accelerated machine learning in Kubernetes/OpenShift, and containerized solutions—all available on the NVIDIA Networking Documentation site.

Notice

This document is provided for information purposes only and shall not be regarded as a warranty of a certain functionality, condition, or quality of a product. NVIDIA Corporation (“NVIDIA”) makes no representations or warranties, expressed or implied, as to the accuracy or completeness of the information contained in this document and assumes no responsibility for any errors contained herein. NVIDIA shall have no liability for the consequences or use of such information or for any infringement of patents or other rights of third parties that may result from its use. This document is not a commitment to develop, release, or deliver any Material (defined below), code, or functionality. NVIDIA reserves the right to make corrections, modifications, enhancements, improvements, and any other changes to this document, at any time without notice. Customer should obtain the latest relevant information before placing orders and should verify that such information is current and complete. NVIDIA products are sold subject to the NVIDIA standard terms and conditions of sale supplied at the time of order acknowledgement, unless otherwise agreed in an individual sales agreement signed by authorized representatives of NVIDIA and customer (“Terms of Sale”). NVIDIA hereby expressly objects to applying any customer general terms and conditions with regards to the purchase of the NVIDIA product referenced in this document. No contractual obligations are formed either directly or indirectly by this document.

Last updated on Jun 17, 2025.

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SN3700 Switch Console

SN2201 Switch Console

Hypervisor netplan configuration

Hypervisor Console

Jump Node netplan

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

MaaS netplan

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

DHCP snippet

Hypervisor Console

Install virsh and Set Up SSH Access

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

MaaS Console

Get MAC Addresses of the Master VMs

MaaS Console

MaaS Console

Add Master VMs to MAAS

MaaS Console

Configure OVS Bridges on Master VMs

Deploy Master VMs Using Cloud-Init

Master nodes cloud-init

Verify Deployment

Jump Node Console

Master1 Console

Master1 Console

Master1 Console

Master1 Console

Finalize Setup

Master1 Console

Create Workers and Target Machines in MAAS

Kernel options for worker nodes

MaaS Console

Kernel options for worker nodes

Adjust Network Settings

For Storage Target Node, configure the network interfaces:

Deploy Worker Nodes Using Cloud-Init

Worker node cloud-init

Deploy Storage Target Node Using Cloud-Init

Target node cloud-init

Target node /etc/netplan/50-cloud-init.yaml

Verify the Deployment

Jump Node Console

Worker1 Console

Worker1 Console

Worker1 Console

Worker1 Console

Finalize Deployment

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

Jump Node Console

inventory/mycluster/hosts.yaml

Jump Node Console

Jump Node Console

Jump Node Console