Red Hat Summit 红帽全球峰会支持控制台（Console）开发人员开始试用联系人

5.9. 创建工作负载 pod

使用本节中的步骤为共享和主机设备创建工作负载 pod。

5.9.1. 在 RoCE 上创建共享设备 RDMA
复制链接

为 NVIDIA Network Operator 在 RDMA 上为共享设备 RDMA 创建工作负载 pod，并测试 pod 配置。

NVIDIA GPUDirect RDMA 设备在公开设备的 OpenShift Container Platform worker 节点上的 pod 共享。

先决条件

  • 确保 Operator 正在运行。
  • 删除 NicClusterPolicy 自定义资源 (CR) （如果存在）。

流程

  1. 生成自定义 pod 资源： 

    $ cat <<EOF > rdma-eth-32-workload.yaml
apiVersion: v1
kind: Pod
metadata:
  name: rdma-eth-32-workload
  namespace: default
  annotations:
    k8s.v1.cni.cncf.io/networks: rdmashared-net
spec:
  nodeSelector:
    kubernetes.io/hostname: nvd-srv-32.nvidia.eng.rdu2.dc.redhat.com
  containers:
  - image: quay.io/edge-infrastructure/nvidia-tools:0.1.5
    name: rdma-eth-32-workload
    resources:
      limits:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_eth: 1
      requests:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_eth: 1

EOF

$ cat <<EOF > rdma-eth-33-workload.yaml
apiVersion: v1
kind: Pod
metadata:
  name: rdma-eth-33-workload
  namespace: default
  annotations:
    k8s.v1.cni.cncf.io/networks: rdmashared-net
spec:
  nodeSelector:
    kubernetes.io/hostname: nvd-srv-33.nvidia.eng.rdu2.dc.redhat.com
  containers:
  - image: quay.io/edge-infrastructure/nvidia-tools:0.1.5
    name: rdma-eth-33-workload
    securityContext:
      capabilities:
        add: [ "IPC_LOCK" ]
    resources:
      limits:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_eth: 1
      requests:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_eth: 1
EOF

  2. 使用以下命令在集群中创建 pod： 

    $ oc create -f rdma-eth-32-workload.yaml

    输出示例

    pod/rdma-eth-32-workload created
     

    $ oc create -f rdma-eth-33-workload.yaml

    输出示例

    pod/rdma-eth-33-workload created

  3. 使用以下命令验证 pod 是否正在运行： 

    $ oc get pods -n default

    输出示例

    NAME                   READY   STATUS    RESTARTS   AGE
rdma-eth-32-workload   1/1     Running   0          25s
rdma-eth-33-workload   1/1     Running   0          22s

5.9.2. 在 RoCE 上创建主机设备 RDMA
复制链接

为 NVIDIA Network Operator 为主机设备 Remote Direct Memory Access (RDMA) 创建工作负载 pod，并测试 pod 配置。

先决条件

  • 确保 Operator 正在运行。
  • 删除 NicClusterPolicy 自定义资源 (CR) （如果存在）。

流程

  1. 生成一个新的主机设备 NicClusterPolicy (CR)，如下所示： 

    $ cat <<EOF > network-hostdev-nic-cluster-policy.yaml
apiVersion: mellanox.com/v1alpha1
kind: NicClusterPolicy
metadata:
  name: nic-cluster-policy
spec:
  ofedDriver:
    image: doca-driver
    repository: nvcr.io/nvidia/mellanox
    version: 24.10-0.7.0.0-0
    startupProbe:
      initialDelaySeconds: 10
      periodSeconds: 20
    livenessProbe:
      initialDelaySeconds: 30
      periodSeconds: 30
    readinessProbe:
      initialDelaySeconds: 10
      periodSeconds: 30
    env:
    - name: UNLOAD_STORAGE_MODULES
      value: "true"
    - name: RESTORE_DRIVER_ON_POD_TERMINATION
      value: "true"
    - name: CREATE_IFNAMES_UDEV
      value: "true"
  sriovDevicePlugin:
      image: sriov-network-device-plugin
      repository: ghcr.io/k8snetworkplumbingwg
      version: v3.7.0
      config: |
        {
          "resourceList": [
              {
                  "resourcePrefix": "nvidia.com",
                  "resourceName": "hostdev",
                  "selectors": {
                      "vendors": ["15b3"],
                      "isRdma": true
                  }
              }
          ]
        }
EOF

  2. 使用以下命令在集群中创建 NicClusterPolicy CR： 

    $ oc create -f network-hostdev-nic-cluster-policy.yaml

    输出示例

    nicclusterpolicy.mellanox.com/nic-cluster-policy created

  3. 在 DOCA/MOFED 容器中使用以下命令验证主机设备 NicClusterPolicy CR: 

    $ oc get pods -n nvidia-network-operator

    输出示例

    NAME                                                          READY   STATUS    RESTARTS   AGE
mofed-rhcos4.16-696886fcb4-ds-9sgvd                           2/2     Running   0          2m37s
mofed-rhcos4.16-696886fcb4-ds-lkjd4                           2/2     Running   0          2m37s
nvidia-network-operator-controller-manager-68d547dbbd-qsdkf   1/1     Running   0          141m
sriov-device-plugin-6v2nz                                     1/1     Running   0          2m14s
sriov-device-plugin-hc4t8                                     1/1     Running   0          2m14s

  4. 使用以下命令确认资源出现在集群 oc describe node 部分中： 

    $ oc describe node -l node-role.kubernetes.io/worker=| grep -E 'Capacity:|Allocatable:' -A7

    输出示例

    Capacity:
  cpu:                 128
  ephemeral-storage:   1561525616Ki
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              263596708Ki
  nvidia.com/hostdev:  2
  pods:                250
Allocatable:
  cpu:                 127500m
  ephemeral-storage:   1438028263499
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              262445732Ki
  nvidia.com/hostdev:  2
  pods:                250
--
Capacity:
  cpu:                 128
  ephemeral-storage:   1561525616Ki
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              263596704Ki
  nvidia.com/hostdev:  2
  pods:                250
Allocatable:
  cpu:                 127500m
  ephemeral-storage:   1438028263499
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              262445728Ki
  nvidia.com/hostdev:  2
  pods:                250

  5. 创建 HostDeviceNetwork CR 文件： 

    $ cat <<EOF >  hostdev-network.yaml
apiVersion: mellanox.com/v1alpha1
kind: HostDeviceNetwork
metadata:
  name: hostdev-net
spec:
  networkNamespace: "default"
  resourceName: "hostdev"
  ipam: |
    {
      "type": "whereabouts",
      "range": "192.168.3.225/28",
      "exclude": [
       "192.168.3.229/30",
       "192.168.3.236/32"
      ]
    }
EOF

  6. 使用以下命令在集群中创建 HostDeviceNetwork 资源： 

    $ oc create -f hostdev-network.yaml

    输出示例

    hostdevicenetwork.mellanox.com/hostdev-net created

  7. 使用以下命令确认资源出现在集群 oc describe node 部分中： 

    $ oc describe node -l node-role.kubernetes.io/worker=| grep -E 'Capacity:|Allocatable:' -A8

    输出示例

    Capacity:
  cpu:                 128
  ephemeral-storage:   1561525616Ki
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              263596708Ki
  nvidia.com/gpu:      2
  nvidia.com/hostdev:  2
  pods:                250
Allocatable:
  cpu:                 127500m
  ephemeral-storage:   1438028263499
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              262445732Ki
  nvidia.com/gpu:      2
  nvidia.com/hostdev:  2
  pods:                250
--
Capacity:
  cpu:                 128
  ephemeral-storage:   1561525616Ki
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              263596680Ki
  nvidia.com/gpu:      2
  nvidia.com/hostdev:  2
  pods:                250
Allocatable:
  cpu:                 127500m
  ephemeral-storage:   1438028263499
  hugepages-1Gi:       0
  hugepages-2Mi:       0
  memory:              262445704Ki
  nvidia.com/gpu:      2
  nvidia.com/hostdev:  2
  pods:                250

5.9.3. 在 RoCE 上创建 SR-IOV 旧模式 RDMA
复制链接

在 RoCE 上配置单根 I/O 虚拟化 (SR-IOV) 旧模式主机设备 RDMA。

流程

  1. 生成一个新的主机设备 NicClusterPolicy 自定义资源 (CR)： 

    $ cat <<EOF > network-sriovleg-nic-cluster-policy.yaml
apiVersion: mellanox.com/v1alpha1
kind: NicClusterPolicy
metadata:
  name: nic-cluster-policy
spec:
  ofedDriver:
    image: doca-driver
    repository: nvcr.io/nvidia/mellanox
    version: 24.10-0.7.0.0-0
    startupProbe:
      initialDelaySeconds: 10
      periodSeconds: 20
    livenessProbe:
      initialDelaySeconds: 30
      periodSeconds: 30
    readinessProbe:
      initialDelaySeconds: 10
      periodSeconds: 30
    env:
    - name: UNLOAD_STORAGE_MODULES
      value: "true"
    - name: RESTORE_DRIVER_ON_POD_TERMINATION
      value: "true"
    - name: CREATE_IFNAMES_UDEV
      value: "true"
EOF

  2. 使用以下命令在集群中创建策略： 

    $ oc create -f network-sriovleg-nic-cluster-policy.yaml

    输出示例

    nicclusterpolicy.mellanox.com/nic-cluster-policy created

  3. 在 DOCA/MOFED 容器中使用以下命令验证 pod： 

    $ oc get pods -n nvidia-network-operator

    输出示例

    NAME                                                          READY   STATUS    RESTARTS      AGE
mofed-rhcos4.16-696886fcb4-ds-4mb42                           2/2     Running   0             40s
mofed-rhcos4.16-696886fcb4-ds-8knwq                           2/2     Running   0             40s
nvidia-network-operator-controller-manager-68d547dbbd-qsdkf   1/1     Running   13 (4d ago)   4d21h

  4. 为您要在 SR-IOV 传统模式下运行的设备生成虚拟功能 (VF) 的 SriovNetworkNodePolicy CR。请参见以下示例： 

    $ cat <<EOF > sriov-network-node-policy.yaml
apiVersion: sriovnetwork.openshift.io/v1
kind: SriovNetworkNodePolicy
metadata:
  name: sriov-legacy-policy
  namespace:  openshift-sriov-network-operator
spec:
  deviceType: netdevice
  mtu: 1500
  nicSelector:
    vendor: "15b3"
    pfNames: ["ens8f0np0#0-7"]
  nodeSelector:
    feature.node.kubernetes.io/pci-15b3.present: "true"
  numVfs: 8
  priority: 90
  isRdma: true
  resourceName: sriovlegacy
EOF

  5. 使用以下命令在集群中创建 CR：

    注意

    确保启用了 SR-IOV 全局启用。如需更多信息，请参阅无法启用 SR-IOV，并在 Red Hat Enterprise Linux 中接收消息 "not enough MMIO resources for SR-IOV "。 

    $ oc create -f sriov-network-node-policy.yaml

    输出示例

    sriovnetworknodepolicy.sriovnetwork.openshift.io/sriov-legacy-policy created

  6. 每个节点都被禁用调度。节点重新引导以应用配置。您可以使用以下命令查看节点： 

    $ oc get nodes

    输出示例

    NAME                                       STATUS                        ROLES                         AGE     VERSION
edge-19.edge.lab.eng.rdu2.redhat.com       Ready                         control-plane,master,worker   5d      v1.29.8+632b078
nvd-srv-32.nvidia.eng.rdu2.dc.redhat.com   Ready                         worker                        4d22h   v1.29.8+632b078
nvd-srv-33.nvidia.eng.rdu2.dc.redhat.com   NotReady,SchedulingDisabled   worker                        4d22h   v1.29.8+632b078

  7. 节点重启后，通过在每个节点中打开 debug pod 来验证 VF 接口是否存在。运行以下命令: 

    a$ oc debug node/nvd-srv-33.nvidia.eng.rdu2.dc.redhat.com

    输出示例

    Starting pod/nvd-srv-33nvidiaengrdu2dcredhatcom-debug-cqfjz ...
To use host binaries, run `chroot /host`
Pod IP: 10.6.135.12
If you don't see a command prompt, try pressing enter.
sh-5.1# chroot /host
sh-5.1# ip link show | grep ens8
26: ens8f0np0: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc mq state UP mode DEFAULT group default qlen 1000
42: ens8f0v0: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
43: ens8f0v1: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
44: ens8f0v2: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
45: ens8f0v3: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
46: ens8f0v4: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
47: ens8f0v5: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
48: ens8f0v6: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000
49: ens8f0v7: <BROADCAST,MULTICAST> mtu 1500 qdisc noop state DOWN mode DEFAULT group default qlen 1000

  8. 如有必要，在第二个节点上重复前面的步骤。

  9. 可选：使用以下命令确认资源出现在集群 oc describe node 部分中： 

    $ oc describe node -l node-role.kubernetes.io/worker=| grep -E 'Capacity:|Allocatable:' -A8

    输出示例

    Capacity:
  cpu:                       128
  ephemeral-storage:         1561525616Ki
  hugepages-1Gi:             0
  hugepages-2Mi:             0
  memory:                    263596692Ki
  nvidia.com/gpu:            2
  nvidia.com/hostdev:        0
  openshift.io/sriovlegacy:  8
--
Allocatable:
  cpu:                       127500m
  ephemeral-storage:         1438028263499
  hugepages-1Gi:             0
  hugepages-2Mi:             0
  memory:                    262445716Ki
  nvidia.com/gpu:            2
  nvidia.com/hostdev:        0
  openshift.io/sriovlegacy:  8
--
Capacity:
  cpu:                       128
  ephemeral-storage:         1561525616Ki
  hugepages-1Gi:             0
  hugepages-2Mi:             0
  memory:                    263596688Ki
  nvidia.com/gpu:            2
  nvidia.com/hostdev:        0
  openshift.io/sriovlegacy:  8
--
Allocatable:
  cpu:                       127500m
  ephemeral-storage:         1438028263499
  hugepages-1Gi:             0
  hugepages-2Mi:             0
  memory:                    262445712Ki
  nvidia.com/gpu:            2
  nvidia.com/hostdev:        0
  openshift.io/sriovlegacy:  8

  10. SR-IOV 传统模式的 VF 就绪后，生成 SriovNetwork CR 文件。请参见以下示例： 

    $ cat <<EOF > sriov-network.yaml
apiVersion: sriovnetwork.openshift.io/v1
kind: SriovNetwork
metadata:
  name: sriov-network
  namespace:  openshift-sriov-network-operator
spec:
  vlan: 0
  networkNamespace: "default"
  resourceName: "sriovlegacy"
  ipam: |
    {
      "type": "whereabouts",
      "range": "192.168.3.225/28",
      "exclude": [
       "192.168.3.229/30",
       "192.168.3.236/32"
      ]
    }
EOF

  11. 使用以下命令在集群中创建自定义资源： 

    $ oc create -f sriov-network.yaml

    输出示例

    sriovnetwork.sriovnetwork.openshift.io/sriov-network created

5.9.4. 在 Infiniband 上创建共享设备 RDMA
复制链接

为 Infiniband 安装为共享设备远程内存访问 (RDMA) 创建工作负载 pod。

流程

  1. 生成自定义 pod 资源： 

    $ cat <<EOF > rdma-ib-32-workload.yaml
apiVersion: v1
kind: Pod
metadata:
  name: rdma-ib-32-workload
  namespace: default
  annotations:
    k8s.v1.cni.cncf.io/networks: example-ipoibnetwork
spec:
  nodeSelector:
    kubernetes.io/hostname: nvd-srv-32.nvidia.eng.rdu2.dc.redhat.com
  containers:
  - image: quay.io/edge-infrastructure/nvidia-tools:0.1.5
    name: rdma-ib-32-workload
    resources:
      limits:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_ib: 1
      requests:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_ib: 1
EOF

$ cat <<EOF > rdma-ib-32-workload.yaml
apiVersion: v1
kind: Pod
metadata:
  name: rdma-ib-33-workload
  namespace: default
  annotations:
    k8s.v1.cni.cncf.io/networks: example-ipoibnetwork
spec:
  nodeSelector:
    kubernetes.io/hostname: nvd-srv-33.nvidia.eng.rdu2.dc.redhat.com
  containers:
  - image: quay.io/edge-infrastructure/nvidia-tools:0.1.5
    name: rdma-ib-33-workload
    securityContext:
      capabilities:
        add: [ "IPC_LOCK" ]
    resources:
      limits:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_ib: 1
      requests:
        nvidia.com/gpu: 1
        rdma/rdma_shared_device_ib: 1
EOF

  2. 使用以下命令在集群中创建 pod： 

    $ oc create -f rdma-ib-32-workload.yaml

    输出示例

    pod/rdma-ib-32-workload created
     

    $ oc create -f rdma-ib-33-workload.yaml

    输出示例

    pod/rdma-ib-33-workload created

  3. 使用以下命令验证 pod 是否正在运行： 

    $ oc get pods

    输出示例

    NAME                  READY   STATUS    RESTARTS   AGE
rdma-ib-32-workload   1/1     Running   0          10s
rdma-ib-33-workload   1/1     Running   0          3s

Red Hat logoGithubredditYoutubeTwitter

学习

尝试、购买和销售

社区

关于红帽文档

通过我们的产品和服务，以及可以信赖的内容，帮助红帽用户创新并实现他们的目标。 了解我们当前的更新.

让开源更具包容性

红帽致力于替换我们的代码、文档和 Web 属性中存在问题的语言。欲了解更多详情，请参阅红帽博客.

關於紅帽

我们提供强化的解决方案，使企业能够更轻松地跨平台和环境（从核心数据中心到网络边缘）工作。

Theme

© 2026 Red Hat返回顶部