事件查看

[root@clientvm ~]# kubectl describe pod nginx2 
[root@clientvm ~]# kubectl logs nginx2

节点维护

禁止调度

[root@clientvm ~]# kubectl cordon worker1.example.com
node/worker1.example.com cordoned
[root@clientvm ~]# kubectl get node
NAME                  STATUS                     ROLES    AGE   VERSION
master.example.com    Ready                      master   19d   v1.19.4
worker1.example.com   Ready,SchedulingDisabled   <none>   18d   v1.19.4
worker2.example.com   Ready                      <none>   18d   v1.19.4

驱逐Pod

[root@clientvm ~]# kubectl drain worker1.example.com --ignore-daemonsets
node/worker1.example.com already cordoned
WARNING: ignoring DaemonSet-managed Pods: kube-system/kube-proxy-c9ghq
node/worker1.example.com drained

重新开始调度

[root@clientvm ~]# kubectl uncordon worker1.example.com
node/worker1.example.com uncordoned
[root@clientvm ~]#
[root@clientvm ~]# kubectl get node
NAME                  STATUS   ROLES    AGE   VERSION
master.example.com    Ready    master   19d   v1.19.4
worker1.example.com   Ready    <none>   18d   v1.19.4
worker2.example.com   Ready    <none>   18d   v1.19.4

cordon 停止调度
影响最小，只会将node调为SchedulingDisabled
之后再发创建pod，不会被调度到该节点
旧有的pod不会受到影响，仍正常对外提供服务
恢复调度
kubectl uncordon node_name
================================================
drain 驱逐节点
首先，驱逐node上的pod，其他节点重新创建
接着，将节点调为 SchedulingDisabled
恢复调度
kubectl uncordon node_name

安装Metrics Server

Metrics Server是Kubernetes内置自动缩放管道的可扩展，高效的容器资源指标来源。
Metrics Server从Kubelet收集资源指标，并通过Metrics API在Kubernetes apiserver中公开它们，以供Horizontal Pod Autoscaler使用。 还可以通过kubectl top访问Metrics API，从而更容易调试自动缩放。
Metrics Server提供：

• 适用于大多数群集的Deployment
• 可扩展支持多达5,000个节点集群
• 资源效率：Metrics Server使用1m核心CPU和每个节点3 MB内存

安装参考官方文档：
https://github.com/kubernetes-sigs/metrics-server
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
下载components.yaml后要修改如下内容：

      containers:
      - args:
        - --cert-dir=/tmp
        - --secure-port=4443
        - --kubelet-preferred-address-types=InternalIP
        - --kubelet-insecure-tls
        - --kubelet-use-node-status-port
        image: bitnami/metrics-server:0.4.1

[root@clientvm ~]# kubectl apply -f /resources/yaml/metrics-server-components.yaml
serviceaccount/metrics-server created
clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
clusterrole.rbac.authorization.k8s.io/system:metrics-server created
rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created
clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created
service/metrics-server created
deployment.apps/metrics-server created

查看

[root@clientvm ~]# kubectl top node
NAME                  CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%
master.example.com    119m         2%     1417Mi          51%
worker1.example.com   24m          0%     953Mi           20%
worker2.example.com   1079m        26%    1079Mi          23%
[root@clientvm ~]# kubectl top pod
NAME                     CPU(cores)   MEMORY(bytes)
nginx-taint              0m           1Mi
nginx2                   0m           1Mi
readiness-exec           2m           0Mi
test-pod-secret-volume   0m           1Mi
with-node-affinity       0m           1Mi
with-pod-affinity        0m           1Mi

HPA(Horizontal Pod Autoscaler)

Pod 水平自动扩缩（Horizontal Pod Autoscaler） 可以基于 CPU 利用率自动扩缩 Deployment、ReplicaSet 和 StatefulSet 中的 Pod 数量。 Pod 自动扩缩不适用于无法扩缩的对象，比如 DaemonSet。

Pod 水平自动扩缩器的实现是一个控制回路，由控制器管理器(/etc/kubernetes/manifests/kube-controller-manager.yaml)的 --horizontal-pod-autoscaler-sync-period 参数指定周期（默认值为 15 秒），其他可用值：
—horizontal-pod-autoscaler-downscale-stabilization：即自从上次缩容执行结束后，多久可以再次执行缩容，默认时间是 5 分钟
--horizontal-pod-autoscaler-initial-readiness-delay 参数（默认为 30s）用于设置 Pod 准备时间， 在此时间内的 Pod 统统被认为未就绪。
--horizontal-pod-autoscaler-cpu-initialization-period 参数（默认为5分钟） 用于设置 Pod 的初始化时间， 在此时间内的 Pod，CPU 资源度量值将不会被采纳。

对于按 Pod 统计的资源指标（如 CPU），控制器从资源指标 API 中获取每一个 HorizontalPodAutoscaler 指定的 Pod 的度量值，如果设置了目标使用率， 控制器获取每个 Pod 中的容器资源使用情况，并计算资源使用率。

注：自 Kubernetes 1.11 起，从 Heapster 获取指标特性已废弃。

HPA默认行为：

behavior:
  scaleDown:
    stabilizationWindowSeconds: 300
    policies:
    - type: Percent
      value: 100
      periodSeconds: 15
  scaleUp:
    stabilizationWindowSeconds: 0
    policies:
    - type: Percent
      value: 100
      periodSeconds: 15
    - type: Pods
      value: 4
      periodSeconds: 15
    selectPolicy: Max

HPA实验
1） 创建Deployment & Service

[root@clientvm ~]# cat hpa-example.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: php-apache
spec:
  selector:
    matchLabels:
      run: php-apache
  replicas: 1
  template:
    metadata:
      labels:
        run: php-apache
    spec:
      containers:
      - name: php-apache
        image: pilchard/hpa-example
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 80
        resources:
          limits:
            cpu: 500m
          requests:
            cpu: 200m
---
apiVersion: v1
kind: Service
metadata:
  name: php-apache
  labels:
    run: php-apache
spec:
  ports:
  - port: 80
  selector:
    run: php-apache

[root@clientvm ~]# kubectl apply -f hpa-example.yaml
deployment.apps/php-apache created
service/php-apache created
[root@master manifests]# curl 10.105.137.102
OK!

2） 创建HPA

[root@clientvm ~]# kubectl autoscale deployment -h
Usage:
  kubectl autoscale (-f FILENAME | TYPE NAME | TYPE/NAME) [--min=MINPODS] --max=MAXPODS [--cpu-percent=CPU] [options]
Examples:
  # Auto scale a deployment "foo", with the number of pods between 2 and 10, no target CPU utilization specified so a
default autoscaling policy will be used:
  kubectl autoscale deployment foo --min=2 --max=10
  # Auto scale a replication controller "foo", with the number of pods between 1 and 5, target CPU utilization at 80%:
  kubectl autoscale rc foo --max=5 --cpu-percent=80

[root@clientvm ~]# kubectl autoscale deployment --max=10 php-apache --cpu-percent=30
horizontalpodautoscaler.autoscaling/php-apache autoscaled
[root@clientvm ~]# kubectl get hpa
NAME         REFERENCE               TARGETS   MINPODS   MAXPODS   REPLICAS   AGE
php-apache   Deployment/php-apache   0%/30%    1         10        1          20s

3） 测试
在master上使用ab工具发送大量并发

[root@master manifests]# ab -n 1000 -c 200  http://10.105.137.102/

在clientvm节点上观察

[root@clientvm ~]# kubectl get pod -w
NAME                          READY   STATUS    RESTARTS   AGE
nginx2                        1/1     Running   0          4d23h
php-apache-69f8f79bfc-sbzhm   1/1     Running   0          8m48s
php-apache-69f8f79bfc-wdwwq   0/1     Pending   0          0s
php-apache-69f8f79bfc-wdwwq   0/1     Pending   0          0s
php-apache-69f8f79bfc-fkb7k   0/1     Pending   0          0s
php-apache-69f8f79bfc-92pv4   0/1     Pending   0          0s
php-apache-69f8f79bfc-fkb7k   0/1     Pending   0          0s
php-apache-69f8f79bfc-92pv4   0/1     Pending   0          0s
php-apache-69f8f79bfc-wdwwq   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-fkb7k   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-92pv4   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-92pv4   1/1     Running             0          2s
php-apache-69f8f79bfc-fkb7k   1/1     Running             0          2s
php-apache-69f8f79bfc-wdwwq   1/1     Running             0          2s
php-apache-69f8f79bfc-fwb5x   0/1     Pending             0          0s
php-apache-69f8f79bfc-fwb5x   0/1     Pending             0          0s
php-apache-69f8f79bfc-s5624   0/1     Pending             0          0s
php-apache-69f8f79bfc-qkf7f   0/1     Pending             0          0s
php-apache-69f8f79bfc-s5624   0/1     Pending             0          0s
php-apache-69f8f79bfc-jbgtp   0/1     Pending             0          0s
php-apache-69f8f79bfc-qkf7f   0/1     Pending             0          0s
php-apache-69f8f79bfc-fwb5x   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-jbgtp   0/1     Pending             0          0s
php-apache-69f8f79bfc-s5624   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-qkf7f   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-jbgtp   0/1     ContainerCreating   0          0s
php-apache-69f8f79bfc-qkf7f   1/1     Running             0          3s
php-apache-69f8f79bfc-jbgtp   1/1     Running             0          3s
php-apache-69f8f79bfc-fwb5x   1/1     Running             0          3s

[root@clientvm k8s]# kubectl get hpa
NAME         REFERENCE               TARGETS    MINPODS   MAXPODS   REPLICAS   AGE
php-apache   Deployment/php-apache   206%/30%   1         10        10         7m3s

HPA的算法：

期望副本数 = ceil[当前副本数 * (当前指标 / 期望指标)]

etcd

Backup Etcd

1. 在master节点上查找etcd 容器

   [root@master manifests]# docker ps | grep etcd
   44623e84772a        d4ca8726196c                                        "etcd --advertise-cl…"   6 days ago          Up 6 days                               k8s_etcd_etcd-master.example.com_kube-system_1511fba334ccb18c8972b0adfa135f94_0

2. copy etcdctl命令到本机

   [root@master manifests]# docker cp 44623e84772a:/usr/local/bin/etcdctl /usr/bin/

3. 根据 静态Pod etcd.yaml文件的内容指定ca相关证书备份etcd

[root@master manifests]# ETCDCTL_API=3 etcdctl --endpoints=https://127.0.0.1:2379 \
--cacert=/etc/kubernetes/pki/etcd/ca.crt \
--cert=/etc/kubernetes/pki/etcd/peer.crt \
--key=/etc/kubernetes/pki/etcd/peer.key snapshot save /tmp/etcd.db

1. 验证 ```bash [root@master manifests]# ETCDCTL_API=3 etcdctl —write-out=table snapshot status /tmp/etcd.db +—————+—————+——————+——————+ | HASH | REVISION | TOTAL KEYS | TOTAL SIZE | +—————+—————+——————+——————+ | 88cde7c7 | 1498047 | 1854 | 3.3 MB | +—————+—————+——————+——————+

<a name="Gl4Ri"></a>
## Restore Etcd
1. 停止 kubelet
```bash
[root@master manifests]# systemctl stop kubelet.service

1. 删除原有DB数据

   [root@master manifests]# cd /var/lib/etcd/
   [root@master etcd]# ls
   member
   [root@master etcd]# rm -rf /var/lib/etcd

2. 根据 静态Pod etcd.yaml文件的内容，Restore Backup

[root@master manifests]# ETCDCTL_API=3 etcdctl snapshot restore /tmp/etcd.db \
> --data-dir="/var/lib/etcd" \
> --name=master.example.com --skip-hash-check \
> --initial-advertise-peer-urls=https://127.0.0.1:2380 \
> --initial-cluster=master.example.com=https://127.0.0.1:2380

1. 启动 kubelet 服务

   [root@master manifests]# systemctl start kubelet.service

2. 验证

   [root@master manifests]# ETCDCTL_API=3 etcdctl --endpoints=https://127.0.0.1:2379 --cacert=/etc/kubernetes/pki/etcd/ca.crt --cert=/etc/kubernetes/pki/etcd/peer.crt --key=/etc/kubernetes/pki/etcd/peer.key endpoint health
   https://127.0.0.1:2379 is healthy: successfully committed proposal: took = 11.884856ms

   [root@clientvm ~]# kubectl get pod -n kube-system
   NAME                                         READY   STATUS    RESTARTS   AGE
   calico-kube-controllers-6dfcd885bf-dk4jj     1/1     Running   0          6d23h
   calico-node-7nlkr                            1/1     Running   0          6d23h
   calico-node-8xdqh                            1/1     Running   0          6d23h
   calico-node-dskkk                            1/1     Running   0          6d23h
   coredns-6d56c8448f-lsl8p                     1/1     Running   0          7d
   coredns-6d56c8448f-t8t55                     1/1     Running   0          23h
   etcd-master.example.com                      1/1     Running   1          7d
   kube-apiserver-master.example.com            1/1     Running   0          7d
   kube-controller-manager-master.example.com   1/1     Running   1          6d21h
   kube-proxy-2ddnd                             1/1     Running   0          7d
   kube-proxy-cjl2b                             1/1     Running   0          6d23h
   kube-proxy-n5djk                             1/1     Running   0          6d23h
   kube-scheduler-master.example.com            1/1     Running   1          6d21h
   metrics-server-85b5d6b8fb-vmprh              1/1     Running   0          3h51m

集群升级

升级Master节点

1. 选择要升级的版本

   [root@master ~]# yum list --showduplicates kubeadm
   kubeadm.x86_64                                                                 1.19.0-0                                                                  kubernetes
   kubeadm.x86_64                                                                 1.19.0-0                                                                  local
   kubeadm.x86_64                                                                 1.19.1-0                                                                  kubernetes
   kubeadm.x86_64                                                                 1.19.2-0                                                                  kubernetes
   kubeadm.x86_64                                                                 1.19.3-0                                                                  kubernetes
   kubeadm.x86_64                                                                 1.19.4-0                                                                  kubernetes
   kubeadm.x86_64                                                                 1.19.5-0                                                                  kubernetes
   kubeadm.x86_64                                                                 1.20.0-0                                                                  kubernetes

2. 升级kubeadm

   [root@master ~]# yum install kubeadm-1.19.1-0 -y

3. 验证版本

   [root@master ~]# kubeadm version
   kubeadm version: &version.Info{Major:"1", Minor:"19", GitVersion:"v1.19.1", GitCommit:"206bcadf021e76c27513500ca24182692aabd17e", GitTreeState:"clean", BuildDate:"2020-09-09T11:24:31Z", GoVersion:"go1.15", Compiler:"gc", Platform:"linux/amd64"}

4. 设置不可调度，并驱逐控制节点上的Pod

   [root@clientvm ~]# kubectl drain master.example.com --ignore-daemonsets

5. 在master上执行升级计划

   kubeadm upgrade plan

6. 在master执行升级命令

修改集群配置对应版本，然后执行升级

[root@master ~]# kubeadm upgrade apply v1.19.1 
......
[upgrade/successful] SUCCESS! Your cluster was upgraded to "v1.19.1". Enjoy!
[upgrade/kubelet] Now that your control plane is upgraded, please proceed with upgrading your kubelets if you haven't already done so.

1. 恢复节点调度

   [root@clientvm ~]# kubectl uncordon master.example.com

2. 升级kubelet和kubectl

   yum install -y kubelet-1.19.1-0 kubectl-1.19.1-0

3. 重启kubelet 服务

   systemctl daemon-reload
   systemctl restart kubelet

   [root@master ~]# kubectl get node
   NAME                  STATUS   ROLES    AGE    VERSION
   master.example.com    Ready    master   7d1h   v1.19.1
   worker1.example.com   Ready    <none>   7d1h   v1.19.0
   worker2.example.com   Ready    <none>   7d1h   v1.19.0

   逐个升级worker节点

4. 在worker节点上升级kubeadm

   [root@worker1 ~]# yum install kubeadm-1.19.1-0
   [root@worker1 ~]# kubeadm upgrade node

5. 将节点标记为不可调度并逐出工作负载，为维护做好准备

   kubectl drain worker1.example.com --ignore-daemonsets

6. 升级kubelet和kubectl

   yum install -y kubelet-1.19.1-0 kubectl-1.19.1-0

7. 重启 kubelet 服务

   systemctl daemon-reload
   systemctl restart kubelet

8. 恢复节点调度

   kubectl uncordon worker1.example.com

   [root@master ~]# kubectl get node
   NAME                  STATUS   ROLES    AGE    VERSION
   master.example.com    Ready    master   7d1h   v1.19.1
   worker1.example.com   Ready    <none>   7d1h   v1.19.1
   worker2.example.com   Ready    <none>   7d1h   v1.19.0

9. 验证集群状态，并逐一升级其他worker节点

   [root@master ~]# kubectl get node
   NAME                  STATUS   ROLES    AGE    VERSION
   master.example.com    Ready    master   7d1h   v1.19.1
   worker1.example.com   Ready    <none>   7d1h   v1.19.1
   worker2.example.com   Ready    <none>   7d1h   v1.19.1

10. 升级完成后验证集群组件

    [root@clientvm ~]# kubectl get pod -n kube-system
    NAME                                         READY   STATUS    RESTARTS   AGE
    calico-kube-controllers-6dfcd885bf-dk4jj     1/1     Running   0          7d1h
    calico-node-7nlkr                            1/1     Running   0          7d1h
    calico-node-8xdqh                            1/1     Running   0          7d1h
    calico-node-dskkk                            1/1     Running   0          7d1h
    coredns-6d56c8448f-h6wvr                     1/1     Running   0          6m41s
    coredns-6d56c8448f-lsl8p                     1/1     Running   0          7d1h
    etcd-master.example.com                      1/1     Running   0          6m57s
    kube-apiserver-master.example.com            1/1     Running   0          6m42s
    kube-controller-manager-master.example.com   1/1     Running   0          6m40s
    kube-proxy-8422l                             1/1     Running   0          6m4s
    kube-proxy-df9t9                             1/1     Running   0          5m55s
    kube-proxy-vmm7j                             1/1     Running   0          5m25s
    kube-scheduler-master.example.com            1/1     Running   0          6m38s
    metrics-server-85b5d6b8fb-vmprh              1/1     Running   0          5h23m

    [root@clientvm ~]# kubectl version
    Client Version: version.Info{Major:"1", Minor:"19", GitVersion:"v1.19.1", GitCommit:"206bcadf021e76c27513500ca24182692aabd17e", GitTreeState:"clean", BuildDate:"2020-09-09T11:26:42Z", GoVersion:"go1.15", Compiler:"gc", Platform:"linux/amd64"}
    Server Version: version.Info{Major:"1", Minor:"19", GitVersion:"v1.19.1", GitCommit:"206bcadf021e76c27513500ca24182692aabd17e", GitTreeState:"clean", BuildDate:"2020-09-09T11:18:22Z", GoVersion:"go1.15", Compiler:"gc", Platform:"linux/amd64"}