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kubernetes操作记录(六)

kubernetes系统学习

发布于：2019年5月30日

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kubernetes 操作记录六

调度器、预选策略及优选函数

整个调度大致可以分为三个过程: Predicate(预先) –> Priority(优选) –> Select(选定)

调度器:
预选策略:
CheckNodeCondition: 检查节点本身是否正常;
GeneralPredicates:
HostName: 检查Pod对象是否定义了 pod.spec.hostname,
PodFitsHostPorts:pods.spec.containers.ports.hostPort
MatchNodeSelector: pods.sepc.nodeSelector
PodFitsResources: 检查Pod的资源需求是否能被节点的需求所满足
NoDiskConflicts:检查Pod依赖的存储卷是否能满足需求;
PodToleratesNodeTaints: 检查Pod上的spec.tolerations可容忍的污点是否完全包含节点上的污点;
PodToleratesNodeNoExecuteTaints: 不能执行的污点,这个预选策略默认是不检查的;
CheckNodeLabelPresence: 检查节点指定标签的存在性;
CheckServiceAffinity: 把这个Pod调度到它所属的Service,已经调度完成其它Pod所在的节点上去;
MaxEBSVolumeCount:
MaxGCEPDVolumeCount:
MaxAzureDiskVolumeCount:
CheckVolumeBinding:
NoVolumeZoneConflict:
CheckNodeMemoryPressure:检查节点内存资源是否处于压力过大的状态;
CheckNodePidPressure:检查PId状态是否紧缺;
CheckNodeDiskPressure:
MatchInterPodAffity:

优选函数
LeastRequested:
(cpu(capacity-sum(requested))*10/capacity)+memory((capacity-sum(requested))*10/capacity))/2
BalancedResourceAllocation:
CPU和内存资源被占用率相近的胜出;
NodePreferAvoidPods:
节点注解信息”scheduler .alpha.kubernetes.io/preferAvoidPods”
TaintToleration: 将Pod对象的spec.tolerations列表项与节点的taints列表项进行匹配度检查，匹配条目越多，得分越低;
SelectorSpreading: 标签选择器的分散度，与当前Pod对象同属的标签选择器，选择适配的其它Pod的对象所在的节点，越多的，得分越底，否则得分越高;
InterPodAffinity: 遍历Pod的亲和性条目，并将那些能够匹配到给定节点的条目相加，结果值越大，得分越低;
NodeAffinity: 根据NodeSelecter进行匹配度检查，能成功匹配的越多，得分就越高;
MostRequested: 空闲量越小的，得分越大。他会尽量把一个节点的资源先用完;
NodeLabel: 标签越多，得分越高;
ImageLocality: 此节点是否有此Pod 所需要的镜像，拥有镜像越多的，得分越高，而它是根据镜像体积大小之和来计算的;

kubernetes 高级调度方式

节点选择器: nodeSelector, nodeName
节点亲和性调度: nodeAffinity

注: 当调度选择器选择了不存的标签时，Pod 会成为Pending状态
nodeSelector:
disktype: harddisk

节点亲和性调度;

硬亲和 

# vim pod-nodeaffinity-demo.yaml
apiVersion: v1
kind: Pod
metadata:
  name: pod-node-affinity-demo
  labels:
    app: myapp
    tier: frontend
spec:
  containers:
  - name: myapp
    image: ikubernetes/myapp:v1
  affinity:
    nodeAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
        nodeSelectorTerms:
        - matchExpressions:
          - key: zone
            operator: In
            values:
            - foo
            - bar

软亲和

# vIm  pod-nodeaffinity-demo-2.yaml
apiVersion: v1
kind: Pod
metadata:
  name: pod-node-affinity-demo-2
  labels:
    app: myapp
    tier: frontend
spec:
  containers:
  - name: myapp
    image: ikubernetes/myapp:v1
  affinity:
    nodeAffinity:
      preferredDuringSchedulingIgnoredDuringExecution:
      - preference:
          matchExpressions:
          - key: zone
            operator: In
            values:
            - foo
            - bar
        weight: 60

# vim pod-required-affinity-demo.yaml
apiVersion: v1
kind: Pod
metadata:
  name: pod-first
  labels:
    app: myapp
    tier: frontend
spec:
  containers:
  - name: myapp
    image: ikubernetes/myapp:v1
---
apiVersion: v1
kind: Pod
metadata:
  name: pod-second
  labels:
    app: backend
    tier: db
spec:
  containers:
  - name: busybox
    image: busybox:latest
    imagePullPolicy: IfNotPresent
    command: ["sh","-c","sleep 3600"]
  affinity:
    podAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
      - labelSelector:
          matchExpressions:
          - {key: app, operator: In, values: ["myapp"]}
        topologyKey: kubernetes.io/hostname

注: podAntiAffinity 一定不会调度到同一节点上

taint 的effect定义对Pod排斥效果:
NoSchedule: 仅影响调度过程，对现存的Pod对象不产生影响;
NoExecute: 既影响调度过程，也影响现存的Pod对象; 不容忍的Pod对象将被驱逐;
PreferNoSchedule: 

# kubectl taint node node01 node-type=production:NoSchedule
# kubectl  taint node  node02 node-type=dev:NoExecute

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp-deploy
  namespace: default
spec:
  replicas: 5
  selector:
    matchLabels:
      app: myapp
      release: canary
  template:
    metadata:
      labels:
        app: myapp
        release: canary
    spec:
      containers:
      - name: myapp
        image: ikubernetes/myapp:v2
        ports:
        - name: http
          containerPort: 80
      tolerations:
      - key: "node-type"
        operator: "Equal"
        value: "production" 
        effect: "NoSchedule"

      tolerations:
      - key: "node-type"
        operator: "Equal"
        value: "production" 
        effect: "NoExecute"
        tolerationSeconds: 3600

      tolerations:
      - key: "node-type"
        operator: "Exists"
        value: ""
        effect: "NoExecute"

容器资源需求、限制、及HeapSter

requests: 需求，最低保障;
limits: 限制，硬限制;
limits 一般大于等于 requests

CPU: 1颗逻辑CPU
1逻辑核心=1000,millicores
500m = 0.5CPU
内存:
E、P、T、G、M、K
Ei、Pi

取消节点污点

# kubectl taint node node01  node-type-

apiVersion: v1
kind: Pod
metadata:
  name: pod-demo
  namespace: renjin
  labels:
    app: myapp
    tier: frontend
spec:
  containers:
  - name: myapp
    image: ikubernetes/stress-ng
    command: ["/usr/bin/stress-ng", "-c 1", "--metrics-brief"]
    resources:
      requests:
        cpu: "500m"
        memory: "128Mi"
      limits:
        cpu: "500m"
        memory: "512Mi"

QoS:
Guranteed: 每个容器同时设置CPU和内在的requests和limits,
cpu.limits=cpu.requests memory.limits=memory.request
Burstable:至少有一个容器设置CPU或内存资源的requests
BestEffort: 没有任何一个容器设置了requests或limits属性;最低优先级别; 是自动配置的;

配置influxdb

    # wget https://raw.githubusercontent.com/kubernetes-retired/heapster/master/deploy/kube-config/influxdb/influxdb.yaml
   # 更改以下内容
   apiVersion: apps/v1

   spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: influxdb   

    spec:
      containers:
      - name: influxdb
        image: registry.cn-hangzhou.aliyuncs.com/google_containers/heapster-influxdb-amd64:v1.5.2
#  kubectl apply -f influxdb.yaml

配置heapster-rbac

# wget https://raw.githubusercontent.com/kubernetes-retired/heapster/master/deploy/kube-config/rbac/heapster-rbac.yaml
# kubectl  apply -f heapster-rbac.yaml

配置heapster

# wget https://raw.githubusercontent.com/kubernetes-retired/heapster/master/deploy/kube-config/influxdb/heapster.yaml
# 修改以下内容
apiVersion: apps/v1
spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: heapster
image: registry.cn-hangzhou.aliyuncs.com/google_containers/heapster-amd64:v1.5.4
spec:
  ports:
  - port: 80
    targetPort: 8082
  type: NodePort
# kubectl  apply -f heapster.yaml

# kubectl get svc -n kube-system
NAME                   TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)                  AGE
heapster               NodePort    10.101.89.141   <none>        80:31261/TCP             63s
kube-dns               ClusterIP   10.96.0.10      <none>        53/UDP,53/TCP,9153/TCP   48d
kubernetes-dashboard   NodePort    10.103.25.80    <none>        443:30660/TCP            21d
monitoring-influxdb    ClusterIP   10.103.131.36   <none>        8086/TCP                 153m

看下图说明，heapster此时可以调通

grafana配置

# wget https://raw.githubusercontent.com/kubernetes-retired/heapster/master/deploy/kube-config/influxdb/grafana.yaml
# vim grafana.yaml # 修改以下内容
apiVersion: apps/v1
spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: grafana
      image: registry.cn-hangzhou.aliyuncs.com/google_containers/heapster-grafana-amd64:v5.0.4
        ports:
  - port: 80
    targetPort: 3000
  type: NodePort
# kubectl apply -f grafana.yaml

更新于：2023年12月4日

linux

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sre

kubernetes

nodeSelector

HeapSter

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