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实验kubernetes的CPU绑定策略

news 2025/8/22 15:34:25

CPU 管理配置

CPU 管理策略通过 kubelet 参数 --cpu-manager-policy 或 KubeletConfiguration 中的 cpuManagerPolicy 字段来指定。支持两种策略：

none：默认策略。
static：允许为节点上具有某些资源特征的 Pod 赋予增强的 CPU 亲和性和独占性。

更改 CPU 管理器策略

以minikube为例，修改kubelet配置：

1、添加配置：

kubectl edit configmaps kubelet-config -n kube-system

cpuManagerPolicy: static
kubeReserved: {cpu: 100m, memory: 100Mi}

2、在节点机器删除 rm /var/lib/kubelet/cpu_manager_state

3、重启kubelet。

4、观察是否启动成功：

systemctl status kubelet

journalctl -f

5、查看 /var/lib/kubelet/cpu_manager_state 是否变化，如：

cat /var/lib/kubelet/cpu_manager_state
{"policyName":"static","defaultCpuSet":"0-3","checksum":611748604}

设置pod绑定cpu核数

1、绑定cpu的pod配置（Guaranteed Pod）：

apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx
spec:
replicas: 2
strategy:
    type: RollingUpdate
    rollingUpdate:
      maxUnavailable: 100%
selector:
    matchLabels:
      app: nginx
template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
        - name: nginx
          image: docker.io/nginx:1.27.0
          imagePullPolicy: Never
          resources:
            requests:
              cpu: 1
              memory: "50Mi"
            limits:
              cpu: 1
              memory: "50Mi"
          ports:
            - name: http
              containerPort: 80
      terminationGracePeriodSeconds: 6

2、没有绑定cpu的pod配置（非Guaranteed Pod）：

apiVersion: apps/v1
kind: Deployment
metadata:
name: hello
spec:
replicas: 2
strategy:
    type: RollingUpdate
    rollingUpdate:
      maxUnavailable: 100%
selector:
    matchLabels:
      app: hello
template:
    metadata:
      labels:
        app: hello
    spec:
      containers:
        - name: myhello
          image: docker.io/library/myhello:v1.4
          imagePullPolicy: Never
          ports:
            - name: http
              containerPort: 8000
      terminationGracePeriodSeconds: 6

3、先后部署hello和nginx：

kubectl apply -f hello-deployment-rs2.yaml

kubectl apply -f nginx-deployment-rs2.yaml

观察cpu绑定效果

1、只部署hello后的绑定情况：

docker ps | grep hello

docker inspect fa0c12f34ae5 | grep -i pid

taskset -pc 94245

pid 94245's current affinity list: 0-3

2、然后继续部署nginx容器的绑定情况：

docker ps | grep nginx
docker inspect 0d42e09a0f56 | grep -i pid
taskset -pc 59820
pid 59820's current affinity list: 1

2、查看hello容器的cpu绑定情况：

taskset -pc 94245
pid 94245's current affinity list: 0,2,3

3、查看kubelet的cpu_manager_state：

cat /var/lib/kubelet/cpu_manager_state

{"policyName":"static","defaultCpuSet":"0,2-3","entries":{"9268f4b8-bf6c-4910-9f3a-a9ac879ffc60":{"nginx":"1"}},"checksum":1987962493}

4、删除nginx容器：

kubectl delete -f nginx-deployment-rs2.yaml

5、再次查看kubelet的cpu_manager_state：

cat /var/lib/kubelet/cpu_manager_state

{"policyName":"static","defaultCpuSet":"0,2-3","entries":{"9268f4b8-bf6c-4910-9f3a-a9ac879ffc60":{"nginx":"1"}},"checksum":1987962493}

6、再次查看hello的cpu绑定状态：