Revert "在k8s中，配置GPU节点"

.gitignore

@@ -6,4 +6,3 @@ hosts
 *.crt
 *.pem
 roles/prepare/files/ca*
-.idea

21.gpunode.yml

@@ -1,3 +0,0 @@
-- hosts: gpu-node
-  roles:
-  - gpu

docs/08-配置GPU-node节点.md

@@ -1,46 +0,0 @@
-## 08-配置GPU-node节点.md
-
-推荐阅读[官方GPU节点配置文档](https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus/)
-
-### 1. 允许k8s系统使用Device Plugins
-
-实现方式：通过修改kube-apiserver, kubelet, kube-proxy配置文件模板
-
-因为GPU node是kube node的子集，正常执行`90.setup.yml`搭建k8s即可实现此目标
-
-### 2. 配置GPU节点
-在[官方驱动网页](http://www.nvidia.com/Download/index.aspx?lang=en-uk)下载对应操作系统与显卡的驱动，
-改名为nvidia-diag-driver-local-repo.deb，
-并放入到invertory file中{{ base_dir }}路线下的 bin 文件夹中
-
-执行命令：`ansible-playbook 21.gpunode.yml`
-
-相当于完成以下任务
-
-#### 1). GPU 节点安装 nvidia driver 
-建议在node上只安装驱动，而不安装CUDA包，所有CUDA包都放到镜像中去，否则容易出现版本不匹配的问题。
-
-
-
-#### 2). GPU 节点安装 nvidia docker 2.0
-这一部分可能失败，原因可能是系统所用docker版本与nvidia docker 2.0依赖的docker版本不一致，
-具体参考[文档](https://github.com/NVIDIA/nvidia-docker/wiki/Frequently-Asked-Questions)
-
-    
-可以通过命令`apt-cache madison nvidia-docker2 nvidia-container-runtime`查询可以安装的nvidia docker 2.0 
-的 docker 版本
-    
-可以通过命令`dpkg -l | grep docker`来查看实际安装docker 版本
-    
-nvidia docker 安装失败，可以[手动更新docker](https://docs.docker.com/engine/installation/linux/docker-ce/ubuntu/#upgrade-docker-ce),
-再重新运行安装playbook
-
-
-#### 3). GPU 节点配置 nvidia-container-runtime 为 docker default runtime
-
-通过修改`/etc/docker/daemon.json`实现
-
-### 3. 配置Nvidia device plugin
-执行命令 `kubectl create -f manifests/gpu-device-plugin/v1.9/nvidia-device-plugin.yml`
-
-可以通过执行`kubectl describe nodes | grep nvidia.com/gpu` 来查看GPU节点配置是否成功

example/hosts.allinone.example

@@ -14,11 +14,6 @@
 [kube-node]
 192.168.1.1 NODE_ID=node1 NODE_IP="192.168.1.1"
 
-#gpu-node 是 kube-node的子集
-[gpu-node]
-192.168.1.1 NODE_IP="192.168.1.1"
-
-
 [kube-cluster:children]
 kube-node
 kube-master

example/hosts.m-masters.example

@@ -30,12 +30,6 @@ MASTER_PORT="8443"		# api-server 服务端口
 192.168.1.3 NODE_ID=node2 NODE_IP="192.168.1.3"
 192.168.1.4 NODE_ID=node3 NODE_IP="192.168.1.4"
 
-#gpu-node 是 kube-node的子集
-[gpu-node]
-192.168.1.2 NODE_IP="192.168.1.2"
-192.168.1.3 NODE_IP="192.168.1.3"
-
-
 [kube-cluster:children]
 kube-node
 kube-master

example/hosts.s-master.example

@@ -18,12 +18,6 @@
 192.168.1.2 NODE_ID=node2 NODE_IP="192.168.1.2"
 192.168.1.3 NODE_ID=node3 NODE_IP="192.168.1.3"
 
-#gpu-node 是 kube-node的子集
-[gpu-node]
-192.168.1.2 NODE_IP="192.168.1.2"
-192.168.1.3 NODE_IP="192.168.1.3"
-
-
 [kube-cluster:children]
 kube-node
 kube-master

manifests/gpu-device-plugin/v1.8/nvidia-device-plugin.yml

@@ -1,24 +0,0 @@
-apiVersion: extensions/v1beta1
-kind: DaemonSet
-metadata:
-  name: nvidia-device-plugin-daemonset
-spec:
-  template:
-    metadata:
-      labels:
-        name: nvidia-device-plugin-ds
-    spec:
-      containers:
-      - image: nvidia/k8s-device-plugin:1.8
-        name: nvidia-device-plugin-ctr
-        securityContext:
-          allowPrivilegeEscalation: false
-          capabilities:
-            drop: ["ALL"]
-        volumeMounts:
-          - name: device-plugin
-            mountPath: /var/lib/kubelet/device-plugins
-      volumes:
-        - name: device-plugin
-          hostPath:
-            path: /var/lib/kubelet/device-plugins

manifests/gpu-device-plugin/v1.9/nvidia-device-plugin.yml

@@ -1,25 +0,0 @@
-apiVersion: extensions/v1beta1
-kind: DaemonSet
-metadata:
-  name: nvidia-device-plugin-daemonset
-  namespace: kube-system
-spec:
-  template:
-    metadata:
-      labels:
-        name: nvidia-device-plugin-ds
-    spec:
-      containers:
-      - image: nvidia/k8s-device-plugin:1.9
-        name: nvidia-device-plugin-ctr
-        securityContext:
-          allowPrivilegeEscalation: false
-          capabilities:
-            drop: ["ALL"]
-        volumeMounts:
-          - name: device-plugin
-            mountPath: /var/lib/kubelet/device-plugins
-      volumes:
-        - name: device-plugin
-          hostPath:
-            path: /var/lib/kubelet/device-plugins

roles/gpu/files/daemon.json

@@ -1,12 +0,0 @@
-{
-  "registry-mirrors": ["https://registry.docker-cn.com"], 
-  "max-concurrent-downloads": 6,
-  "default-runtime": "nvidia",
-  "runtimes": {
-      "nvidia": {
-          "path": "/usr/bin/nvidia-container-runtime",
-          "runtimeArgs": []
-      }
-  }
-}
-

roles/gpu/tasks/main.yml

@@ -1,30 +0,0 @@
-- name: 下载nvidia driver安装包
-  copy: src={{ base_dir }}/bin/nvidia-diag-driver-local-repo.deb dest=/tmp/nvidia-diag-driver-local-repo.deb
-  when: ansible_distribution == "Ubuntu"
-
-- name: 安装nvidia dirver驱动
-  apt:
-    deb: /tmp/nvidia-diag-driver-local-repo.deb
-  when: ansible_distribution == "Ubuntu"
-
-- name: Add the package repositories 1
-  shell: curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
-  when: ansible_distribution == "Ubuntu"
-
-- name: Add the package repositories 2
-  shell: curl -s -L https://nvidia.github.io/nvidia-docker/ubuntu16.04/amd64/nvidia-docker.list | tee /etc/apt/sources.list.d/nvidia-docker.list
-  when: ansible_distribution == "Ubuntu"
-
-- name: Update apt-get and Install nvidia docker 2
-  apt:
-    name: nvidia-docker2
-    update_cache: yes
-  when: ansible_distribution == "Ubuntu"
-
-- name: 配置nvidia docker runtime
-  copy: src=daemon.json dest=/etc/docker/daemon.json
-
-- name: restart docker
-  service:
-    name: docker
-    state: restarted

roles/kube-master/templates/kube-apiserver.service.j2

@@ -31,7 +31,6 @@ ExecStart={{ bin_dir }}/kube-apiserver \
   --audit-log-maxsize=100 \
   --audit-log-path=/var/lib/audit.log \
   --event-ttl=1h \
-  --feature-gates="DevicePlugins=true" \
   --v=2
 Restart=on-failure
 RestartSec=5

roles/kube-node/templates/kube-proxy.service.j2

@@ -12,7 +12,6 @@ ExecStart={{ bin_dir }}/kube-proxy \
   --hostname-override={{ NODE_IP }} \
   --kubeconfig=/etc/kubernetes/kube-proxy.kubeconfig \
   --logtostderr=true \
-  --feature-gates="DevicePlugins=true" \
   --v=2
 Restart=on-failure
 RestartSec=5

roles/kube-node/templates/kubelet.service.j2

@@ -23,7 +23,6 @@ ExecStart={{ bin_dir }}/kubelet \
   --allow-privileged=true \
   --fail-swap-on=false \
   --logtostderr=true \
-  --feature-gates="DevicePlugins=true" \
   --v=2
 #kubelet cAdvisor 默认在所有接口监听 4194 端口的请求, 以下iptables限制内网访问
 ExecStartPost=/sbin/iptables -A INPUT -s 10.0.0.0/8 -p tcp --dport 4194 -j ACCEPT