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kube-scheduler作为kubemaster核心组件运行在master节点上面，主要是watch kube-apiserver中未被调度的Pod，如果有，通过调度算法找到最适合的节点Node，然后通过kube-apiserver以对象（pod名称、Node节点名称等）的形式写入到etcd中来完成调度，kube-scheduler的高可用与kube-controller-manager一样，需要使用选举的方式产生。

下载https://dl.k8s.io/v1.17.0/kubernetes-server-linux-amd64.tar.gz二进制文件并分发到所有master节点服务器。

创建kubeconfig文件并分发

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

kubectl config set-cluster kubernetes \

  --certificate-authority=/data/k8s/work/ca.pem \

  --embed-certs=true \

  --server=${KUBE_APISERVER} \

  --kubeconfig=kube-scheduler.kubeconfig

kubectl config set-credentials system:kube-scheduler \

  --client-certificate=kube-scheduler.pem \

  --client-key=kube-scheduler-key.pem \

  --embed-certs=true \

  --kubeconfig=kube-scheduler.kubeconfig

kubectl config set-context system:kube-scheduler \

  --cluster=kubernetes \

  --user=system:kube-scheduler \

  --kubeconfig=kube-scheduler.kubeconfig

kubectl config use-context system:kube-scheduler --kubeconfig=kube-scheduler.kubeconfig

for node_ip in ${MASTER_IPS[@]}

do

    echo ">>> ${node_ip}"

    scp kube-scheduler.kubeconfig root@${node_ip}:/etc/kubernetes/

done

创建kube-scheduler配置文件模板

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

cat >kube-scheduler.yaml.template <<EOF

apiVersion: kubescheduler.config.k8s.io/v1alpha1

kind: KubeSchedulerConfiguration

bindTimeoutSeconds: 600

clientConnection:

  burst: 200

  kubeconfig: "/etc/kubernetes/kube-scheduler.kubeconfig"

  qps: 100

enableContentionProfiling: false

enableProfiling: true

hardPodAffinitySymmetricWeight: 1

healthzBindAddress: 127.0.0.1:10251

leaderElection:

  leaderElect: true

metricsBindAddress: ##NODE_IP##:10251

EOF

替换并分发配置文件

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

# 替换

for (( i=0; i < 3; i++ ))

do

    sed -e "s/##NODE_NAME##/${NODE_NAMES[i]}/" -e "s/##NODE_IP##/${NODE_IPS[i]}/" kube-scheduler.yaml.template > kube-scheduler-${NODE_IPS[i]}.yaml

done

# 分发

for node_ip in ${MASTER_IPS[@]}

do

    echo ">>> ${node_ip}"

    scp kube-scheduler-${node_ip}.yaml root@${node_ip}:/etc/kubernetes/kube-scheduler.yaml

done

创建kube-scheduler启动文件模板

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

cat > kube-scheduler.service.template <<EOF

[Unit]

Description=Kubernetes Scheduler

Documentation=https://github.com/GoogleCloudPlatform/kubernetes

[Service]

WorkingDirectory=${K8S_DIR}/kube-scheduler

ExecStart=/data/k8s/bin/kube-scheduler \\

  --config=/etc/kubernetes/kube-scheduler.yaml \\

  --bind-address=##NODE_IP## \\

  --secure-port=10259 \\

  --port=10251 \\

  --tls-cert-file=/etc/kubernetes/cert/kube-scheduler.pem \\

  --tls-private-key-file=/etc/kubernetes/cert/kube-scheduler-key.pem \\

  --authentication-kubeconfig=/etc/kubernetes/kube-scheduler.kubeconfig \\

  --client-ca-file=/etc/kubernetes/cert/ca.pem \\

  --requestheader-allowed-names="aggregator" \\

  --requestheader-client-ca-file=/etc/kubernetes/cert/ca.pem \\

  --requestheader-extra-headers-prefix="X-Remote-Extra-" \\

  --requestheader-group-headers=X-Remote-Group \\

  --requestheader-username-headers=X-Remote-User \\

  --authorization-kubeconfig=/etc/kubernetes/kube-scheduler.kubeconfig \\

  --logtostderr=true \\

  --v=2

Restart=always

RestartSec=5

StartLimitInterval=0

[Install]

WantedBy=multi-user.target

EOF

启动参数详解

启动模块替换并分发

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

# 替换模板文件

for (( i=0; i < 3; i++ ))

do

    sed -e "s/##NODE_NAME##/${NODE_NAMES[i]}/" -e "s/##NODE_IP##/${NODE_IPS[i]}/" kube-scheduler.service.template > kube-scheduler-${NODE_IPS[i]}.service

done

# 分发

for node_ip in ${MASTER_IPS[@]}

do

    echo ">>> ${node_ip}"

    scp kube-scheduler-${node_ip}.service root@${node_ip}:/etc/systemd/system/kube-scheduler.service

done

启动kube-scheduler

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

for node_ip in ${MASTER_IPS[@]}

do

    echo ">>> ${node_ip}"

    ssh root@${node_ip} "mkdir -p ${K8S_DIR}/kube-scheduler"

    ssh root@${node_ip} "systemctl daemon-reload && systemctl enable kube-scheduler && systemctl restart kube-scheduler"

done

进程验证

#!/bin/bash

cd /data/k8s/work

source /data/k8s/bin/env.sh

for node_ip in ${MASTER_IPS[@]}

do

    echo ">>> ${node_ip}"

    ssh root@${node_ip} "netstat -antp |grep kube-schedule|grep LISTEN|grep -v grep"

done

验证结果

>>> 192.168.16.104

tcp 0      0 192.168.16.104:10251     0.0.0.0:* LISTEN 24327/kube-schedule

tcp 0      0 127.0.0.1:10251          0.0.0.0:* LISTEN 24327/kube-schedule

tcp 0      0 192.168.16.104:10259     0.0.0.0:* LISTEN 24327/kube-schedule

>>> 192.168.16.105

tcp 0      0 192.168.16.105:10251     0.0.0.0:* LISTEN 24448/kube-schedule

tcp 0      0 127.0.0.1:10251          0.0.0.0:* LISTEN 24448/kube-schedule

tcp 0      0 192.168.16.105:10259     0.0.0.0:* LISTEN 24448/kube-schedule

>>> 192.168.16.106

tcp 0      0 192.168.16.106:10251     0.0.0.0:* LISTEN 15659/kube-schedule

tcp 0      0 127.0.0.1:10251          0.0.0.0:* LISTEN 15659/kube-schedule

tcp 0      0 192.168.16.106:10259     0.0.0.0:* LISTEN 15659/kube-schedule

查看kube-scheduler leader

[root@master01 ~]# kubectl get endpoints kube-scheduler --namespace=kube-system  -o yaml

apiVersion: v1

kind: Endpoints

metadata:

  annotations:

    control-plane.alpha.kubernetes.io/leader: '{"holderIdentity":"master03.k8s.vip_1cd7c2d0-67c5-4dec-917f-8b3d504072a5","leaseDurationSeconds":15,"acquireTime":"2020-01-28T09:06:30Z","renewTime":"2020-01-28T09:15:54Z","leaderTransitions":3}'

  creationTimestamp: "2019-12-28T13:59:00Z"

  name: kube-scheduler

  namespace: kube-system

  resourceVersion: "7272253"

  selfLink: /api/v1/namespaces/kube-system/endpoints/kube-scheduler

  uid: f5d06d23-dcb8-459d-881d-6bd1003dcf71

[root@master01 ~]#

总结

1.kube-scheduler提供非安全端口10251，安全端口10259；

2.kube-scheduler 部署3节点高可用，通过选举产生leader；

3.它监视kube-apiserver提供的watch接口，它根据预选和优选策略两个环节找一个最佳适配，然后调度到此节点；

10.第九篇 kube-scheduler 安装及验证

创建kubeconfig文件并分发

创建kube-scheduler配置文件模板

替换并分发配置文件

创建kube-scheduler启动文件模板

启动参数详解

启动模块替换并分发

启动kube-scheduler

进程验证

查看kube-scheduler leader

总结

10.第九篇 kube-scheduler 安装及验证的相关教程结束。

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