关于kubernetes:Kubernetes实用技巧

kubectl 命令太多太长记不住？
- 查看资源缩写
```
kubectl describe 回车 
```

配置 kubectl 主动补全命令

source <(kubectl completion bash)

kubectl 写 yaml 太累，找样例太麻烦？

用 run 命令生成

kubectl run --image=nginx my-deploy -o yaml --dry-run > my-deploy.yaml

用 get 命令导出

kubectl get statefulset/foo -o=yaml --export > new.yaml

Pod 亲和性上面字段的拼写遗记了

kubectl explain pod.spec.affinity.podAffinity

监控集群组件
- 集群整体状态
```
kubectl cluster-info 
```

更多集群信息

kubectl cluster-info dump

组件 metrics

curl localhost:10250/stats/summary

组件监控情况

curl localhost:10250/healthz

治理 K8s 组件日志

# 组件日志
/var/log/kube-apiserver.log
/var/log/kube-proxy.log
/var/log/kube-controller-manager.log
/var/log/kubelet.log

应用 systemd 治理

 journalctl -u kubelet

应用 K8s 插件部署

 kubectl logs -f kube-proxy

治理 K8s 利用日志

从容器规范输入截获

 kubectl logs -f {pod name} -c {container name}
 docker logs -f {docker name}

 apiVersion: v1
 kind: Pod
 metadata:
   name: test-pod
 spec:
   containers:
   - image: test-webserver
     name: test-container
     volumeMounts:
     - mountPath: /log
       name: log-volume
   volumes:
   - name: log-volume
     hostPath:
       path: /var/k8s/log

Deployment 降级与回滚

创立 Deployment

kubectl run {deployment} --image={image} --replicas={rep.}

降级 Deployment

kubectl set image deployment/nginx-deployment nginx=nignx:1.9.1
kubectl set resources deployment/nginx-deployment -c=nginx --limits=cpu=200m,memory=512Mi

降级策略

minReadySeconds: 5
strategy:
  type: RollingUpdata
    maxSurge: 1 #默认 25%
    maxUnavailable: 1 #默认 25%

暂停 Deployment

kubectl rollout pause deployment/nginx-deployment

复原 Deployment

kubectl rollout resume deployment/nginx-deployment

查问降级状态

kubectl rollout status deployment/nginx-deployment

查问降级历史

kubectl rollout history deploy/nginx-deployment
kubectl rollout history deploy/nginx-deployment --revision=2

回滚

kubectl rollout undo deployment/nginx-deployment --to-revision=2

利用弹性伸缩

kubectl scale deployment nginx-deployment --replicas=10

对接了 Heapster, 和 HPA 联动后

kubectl autoscale deployment nginx-deployment --min=10 --max=15 --cpu-percent=80