K8S从入门到放弃-第六章 pod控制器详解
文章目录6.1pod控制器介绍6.2 ReplicaSet(RS)5.3 Deployment(Deploy)6.4 Horizontal Pod Autoscaler(HPA)6.5 DaemonSet(DS)6.6 Job6.7 CronJob(cj)本章节主要介绍各种Pod控制器的详细使用。6.1pod控制器介绍在kubernetes中,按照pod的创建方式可以将其分为两类:●自主式pod:
文章目录
本章节主要介绍各种Pod控制器的详细使用。
6.1 pod控制器介绍
在kubernetes中,按照pod的创建方式可以将其分为两类:
●自主式pod: kubernetes直接创建出来的pod,这种pod删除后就没有了,也不会重建
●控制器创建的pod:通过控制器创建的pod,这种pod删除了之后还会自动重建
什么是Pod控制器
Pod控制器是管理pod的中间层,使用了pod控制器之后,我们只需要告诉pod控制器,想要多少个什么样
的pod就可以了,它就会创建出满足条件的pod并确保每一个pod处于用户期望的状态, 如果pod在运行中出
现故障,控制器会基于指定策略重启动或者重建pod。
在kubernetes中,有很多类型的pod控制器,每种都有自己的适合的场景,常见的有下面这些:
●ReplicationController: 比较原始的pod控制器,已经被废弃,由ReplicaSet替代
●ReplicaSet: 保证指定数量的pod运行,并支持pod数量变更,镜像版本变更
●Deployment: 通过控制ReplicaSet来控制pod, 并支持滚动升级、版本回退
●Horizontal Pod Autoscaler:可以根据集群负载自动调整Pod的数量,实现削峰填谷
●DaemonSet:在集群中的指定Node.上都运行一个副本,-般用于守护进程类的任务
●Job: 它创建出来的pod只要完成任务就立即退出,用于执行- -次性任务
●Cronjob: 它创建的pod会周期性的执行,用于执行周期性任务
●StatefulSet: 管理有状态应用
6.2 ReplicaSet(RS)
ReplicaSet的主要作用是保证一定数量的pod能够正常运行,它会持续监听这些pod的运行状态,一旦pod发生
故障,就会重启或重建。同时它还支持对pod数量的扩缩容和版本镜像的升级。
ReplicaSet的资源清单文件:
apiVersion: apps/v1 #版本号
kind: ReplicaSet #类型
metadata: #元数据
name: # rs名称
namespace: #所属命名空间
labels: #标签
controller: rs
spec: #详情描述
replicas: 3 #副本数量
selector: #选择器,通过它指定该控制器管理哪些pod
matchLabels: # Labels匹配规则
app: nginx-pod
matchExpressions: # Expressions匹配规则
- {key: app, operator: In, values: [nginx-pod]}
template: #模板,当副本数量不足时,会根据下面的模板创建pod副本
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
ports:
- containerPort: 80
在这里面,需要新了解的配置项就是spec下面几个选项:
●replicas: 指定副本数量,其实就是当前rs创建出来的pod的数量,默认为1
●selector: 选择器,它的作用是建立pod控制器和pod之间的关联关系,采用的Label Selector机制
在pod模板上定义label,在控制器上定义选择器,就可以表明当前控制器能管理哪些pod了
●template: 模板,就是当前控制器创建pod所使用的模板板,里面其实就是前一章学过的pod的定义
创建ReplicaSet
创建pc-replicaset.yaml文件,内容如下:
apiVersion: apps/v1
kind: ReplicaSet
metadata:
name: pc-replicaset
namespace: dev
spec:
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
#创建rs
[root@master ~]# kubectl create -f pc-replicaset.yaml
replicaset.apps/pc-replicaset created
#查看rs
# DESIRED :期望副本数量
# CURRENT :当前副本数量
# READY :已经准备好提供服务的副本数量
[root@master ~]# kubectl get rs pc-replicaset -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
pc-replicaset 3 3 3 4m45s nginx nginx:1.17.1 app=nginx-pod
#查看当前控制器创建出来的pod
#这里发现控制器创建出来的pod的名称是在控制器名称后面拼接了- xxxx随机码
[root@master ~]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
pc-replicaset-9szxk 1/1 Running 0 5m45s
pc-replicaset-bkp9c 1/1 Running 0 5m45s
pc-replicaset-fhk46 1/1 Running 0 5m45s
扩缩容
#编辑rs的副本数量,修改spec:replicas: 6即可
[root@master ~]# kubectl edit rs pc-replicaset -n dev
replicaset.apps/pc-replicaset edited
[root@master ~]# kubectl get rs pc-replicaset -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
pc-replicaset 6 6 6 9m45s nginx nginx:1.17.1 app=nginx-pod
#当然也可以直接使用命令实现
#使用scale命令实现扩缩容,后面--replicas=n直 接指定目标数量即可
[root@master ~]# kubectl scale rs pc-replicaset --replicas=2 -n dev
replicaset.apps/pc-replicaset scaled
[root@master ~]# kubectl get rs pc-replicaset -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
pc-replicaset 2 2 2 11m nginx nginx:1.17.1 app=nginx-pod
[root@master ~]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
pc-replicaset-bkp9c 1/1 Running 0 12m
pc-replicaset-fhk46 1/1 Running 0 12m
镜像升级
#编辑rs的容器镜像 - image: nginx:1.17.2
[root@master ~]# kubectl edit rs pc-replicaset -n dev
replicaset.apps/pc-replicaset edited
[root@master ~]# kubectl get rs pc-replicaset -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
pc-replicaset 2 2 2 16m nginx nginx:1.17.2 app=nginx-pod
#同样的道理,也可以使用命令完成这个工作
# kubectl set image rs rs名称容器=镜像版本-n namespace
[root@master ~]# kubectl set image rs pc-replicaset nginx=nginx:1.17.1 -n dev
replicaset.apps/pc-replicaset image updated
[root@master ~]# kubectl get rs pc-replicaset -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
pc-replicaset 2 2 2 18m nginx nginx:1.17.1 app=nginx-pod
删除ReplicaSet
#使用kubectl delete命令会删除此RS以及它管理的Pod
#在kubernetes删除RS前,会将RS的replicasclear调整为0,等待所有的Pod被删除后,在执行RS对象的删除
[root@master ~]# kubectl delete rs pc-replicaset -n dev
replicaset.apps "pc-replicaset" deleted
[root@master ~]# kubectl get rs pc-replicaset -n dev
Error from server (NotFound): replicasets.apps "pc-replicaset" not found
#如果希望仅仅删除RS对象(保留Pod),可以使用kubectl delete命 令时添加--cascade=false选项(不推荐)。
[root@master ~]# kubectl delete rs pc-replicaset -n dev --cascade=false
replicaset.apps "pc-replicaset" deleted
[ root@master ~]# kubectl get pods -n dev
#也可以使用yam1直接删除(推荐)
[root@master ~]# kubectl delete -f pc.replicaset.yaml
replicaset.apps "pc-replicaset" deleted
5.3 Deployment(Deploy)
为了更好的解决服务编排的问题,kubernetes在V1.2版本开始, 引入了Deployment控制器。 值得一提的是,
这种控制器并不直接管理pod,而是通过管理ReplicaSet来间接管理Pod, 即: Deployment管理ReplicaSet,
ReplicaSet管理Pod。所以Deployment比ReplicaSet功能更加强大。
Deployment主要功能有下面几个:
●支持ReplicaSet的所有功能
●支持发布的停止、继续
●支持版本滚动升级和版本回退
Deployment的资源清单文件:
apiVersion: apps/v1 #版本号
kind: Deployment #类型
metadata: #元数据
name: # rs名称
namespace: #所属命名空间
labels: #标签
controller: deploy
spec: #详情描述
replicas: 3 #副本数量
revisionHistoryLimit: 3 #保留历史版本,默认是10
paused: false #暂停部署,默认是false
progressDeadlineSeconds: 600 #部署超时时间(s),默认是600
strategy: #策略
type: RollingUpdate #滚动更新策略
rollingUpdate: #滚动更新
maxSurge: 30% #最大额外可以存在的副本数,可以为百分比,也可以为整数
maxUnavailable: 30% #最大不可用状态的Pod的最大值,可以为百分比,也可以为整数
selector: #选择器,通过它指定该控制器管理哪些pod
matchLabels:# Label s匹配规则
app: nginx-pod
matchExpressions: # Expressions匹配规则
- {key: app, operator: In, values: [nginx-pod]}
template: #模板,当副本数量不足时,会根据下面的模板创建pod副本
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
ports:
- containerPort: 80
创建deployment
创建pc-deployment.yaml,内容如下:
apiVersion: apps/v1
kind: Deployment
metadata:
name: pc-deployment
namespace: dev
spec:
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
#创建deployment
# --record=true
记录每次的版本变化
[root@master ~]# kubectl create -f pc-deployment.yaml --record=true
deployment.apps/pc-deployment created
#查看deployment
# UP-TO-DATE最新版本的pod的数量
# AVAILABLE当前可用的pod的数量
[root@master ~]# kubectl get deploy -n dev -o wide
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
pc-deployment 3/3 3 3 90m nginx nginx:1.17.1 app=nginx-pod
#查看rs
#发现rs的名称是在原来deployment的名字后面添加了一个10位数的随机串
[root@master ~]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
pc-deployment-5d89bdfbf9 3 3 3 2m12s
#查看pod
[root@master ~]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
pc-deployment-5d89bdfbf9-66dv8 1/1 Running 0 2m20s
pc-deployment-5d89bdfbf9-x6vn7 1/1 Running 0 2m20s
pc-deployment-5d89bdfbf9-xvrxz 1/1 Running 0 2m20s
扩缩容
#变更副本数量为5个
[root@master ~]# kubectl scale deploy pc-deployment --replicas=5 -n dev
deployment.apps/pc-deployment scaled
#查看deployment
[root@master ~]# kubectl get deploy pc-deployment -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
pc-deployment 5/5 5 5 9m51s
#查看pod
[root@master ~]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
pc-deployment-5d89bdfbf9-5dp4g 1/1 Running 0 31s
pc-deployment-5d89bdfbf9-66dv8 1/1 Running 0 6m24s
pc-deployment-5d89bdfbf9-777zl 1/1 Running 0 31s
pc-deployment-5d89bdfbf9-x6vn7 1/1 Running 0 6m24s
pc-deployment-5d89bdfbf9-xvrxz 1/1 Running 0 6m24s
#用edit编辑模式编辑deployment的副本数量,修改spec:replicas:3即可
[root@master ~]# kubectl edit deploy pc-deployment -n dev
Edit cancelled, no changes made.
#查看pod
[root@master ~]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
pc-deployment-5d89bdfbf9-66dv8 1/1 Running 0 7m46s
pc-deployment-5d89bdfbf9-777zl 0/1 Terminating 0 113s
pc-deployment-5d89bdfbf9-x6vn7 1/1 Running 0 7m46s
pc-deployment-5d89bdfbf9-xvrxz 1/1 Running 0 7m46s
镜像更新
Deployment支持两种镜像更新的策略:重建更新和滚动更新(默认),可以通过strategy选项进行配置。
strategy:指定新的Pod替换旧的Pod的策略,支持两个属性:
type:指定策略类型,支持两种策略
Recreate:在创建出新的Pod之前会先杀掉所有已存在的Pod
RollingUpdate:滚动更新,就是杀死一部分, 就启动一部分,在更新过程中,存在两个版本Pod
rollingUpdate:当type为RollingUpdate时生效,用于为RollingUpdate设置参数, 支持两个属性:
maxUnavailable:用来指定在升级过程中不可用Pod的最大数量,默认为25%。
maxSurge:用来指定在升级过程中 可以超过期望的Pod的最大数量,默认为25%。
重建更新
1)编辑pc-deployment.yaml,在spec节点下添加更新策略
spec:
strategy: #策略
type: Recreate #重建更新策略
apiVersion: apps/v1
kind: Deployment
metadata:
name: pc-deployment
namespace: dev
spec:
strategy: #策略
type: Recreate #重建更新策略
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
2)创建deploy进行验证
[root@master ~]# kubectl apply -f pc-deployment.yaml
deployment.apps/pc-deployment created
#新开一个窗口去监视pod的状态
[root@master ~]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
pc-deployment-5d89bdfbf9-7bfz8 1/1 Running 0 38s
pc-deployment-5d89bdfbf9-f4bp2 1/1 Running 0 38s
pc-deployment-5d89bdfbf9-kww9m 1/1 Running 0 38s
pc-deployment-5d89bdfbf9-7bfz8 1/1 Terminating 0 2m21s
pc-deployment-5d89bdfbf9-f4bp2 1/1 Terminating 0 2m21s
pc-deployment-5d89bdfbf9-kww9m 1/1 Terminating 0 2m21s
pc-deployment-5d89bdfbf9-kww9m 0/1 Terminating 0 2m23s
pc-deployment-5d89bdfbf9-7bfz8 0/1 Terminating 0 2m23s
pc-deployment-5d89bdfbf9-kww9m 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-kww9m 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-kww9m 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-7bfz8 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-7bfz8 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-7bfz8 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-f4bp2 0/1 Terminating 0 2m24s
pc-deployment-5d89bdfbf9-f4bp2 0/1 Terminating 0 2m30s
pc-deployment-5d89bdfbf9-f4bp2 0/1 Terminating 0 2m30s
pc-deployment-675d469f8b-x9dqc 0/1 Pending 0 0s
pc-deployment-675d469f8b-42xf9 0/1 Pending 0 0s
pc-deployment-675d469f8b-ndqcw 0/1 Pending 0 0s
pc-deployment-675d469f8b-x9dqc 0/1 Pending 0 0s
pc-deployment-675d469f8b-42xf9 0/1 Pending 0 0s
pc-deployment-675d469f8b-ndqcw 0/1 Pending 0 0s
pc-deployment-675d469f8b-x9dqc 0/1 ContainerCreating 0 0s
pc-deployment-675d469f8b-42xf9 0/1 ContainerCreating 0 0s
pc-deployment-675d469f8b-ndqcw 0/1 ContainerCreating 0 0s
pc-deployment-675d469f8b-x9dqc 1/1 Running 0 37s
pc-deployment-675d469f8b-42xf9 1/1 Running 0 58s
pc-deployment-675d469f8b-ndqcw 1/1 Running 0 73s
#在原来窗口更新镜像
[root@master ~]# kubectl set image deploy pc-deployment nginx=nginx:1.17.2 -n dev
deployment.apps/pc-deployment image updated
滚动更新
1)编辑pc-deployment.yaml,在spec节点下添加更新策略
strategy: #策略
type: RollingUpdate #滚动更新策略
rollingUpdate:
maxUnavailable: 25%
maxSurge: 25%
apiVersion: apps/v1
kind: Deployment
metadata:
name: pc-deployment
namespace: dev
spec:
strategy: #策略
type: RollingUpdate #滚动更新策略
rollingUpdate:
maxUnavailable: 25%
maxSurge: 25%
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
2)创建deploy进行验证
[root@master ~]# kubectl apply -f pc-deployment.yaml
deployment.apps/pc-deployment unchanged
#开一个新窗口
[root@master ~]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
pc-deployment-5d89bdfbf9-9vhgf 1/1 Running 0 59s
pc-deployment-5d89bdfbf9-hmtml 1/1 Running 0 61s
pc-deployment-5d89bdfbf9-hmvpz 1/1 Running 0 56s
pc-deployment-7865c58bdf-hj9tv 0/1 Pending 0 0s
pc-deployment-7865c58bdf-hj9tv 0/1 Pending 0 0s
pc-deployment-7865c58bdf-hj9tv 0/1 ContainerCreating 0 0s
pc-deployment-7865c58bdf-hj9tv 1/1 Running 0 41s
pc-deployment-5d89bdfbf9-hmvpz 1/1 Terminating 0 2m20s
pc-deployment-7865c58bdf-fs4rs 0/1 Pending 0 0s
pc-deployment-7865c58bdf-fs4rs 0/1 Pending 0 0s
pc-deployment-7865c58bdf-fs4rs 0/1 ContainerCreating 0 0s
pc-deployment-5d89bdfbf9-hmvpz 0/1 Terminating 0 2m23s
pc-deployment-5d89bdfbf9-hmvpz 0/1 Terminating 0 2m25s
pc-deployment-5d89bdfbf9-hmvpz 0/1 Terminating 0 2m25s
pc-deployment-7865c58bdf-fs4rs 1/1 Running 0 5s
pc-deployment-5d89bdfbf9-9vhgf 1/1 Terminating 0 2m28s
pc-deployment-7865c58bdf-hjbmm 0/1 Pending 0 0s
pc-deployment-7865c58bdf-hjbmm 0/1 Pending 0 0s
pc-deployment-7865c58bdf-hjbmm 0/1 ContainerCreating 0 0s
pc-deployment-7865c58bdf-hjbmm 1/1 Running 0 3s
pc-deployment-5d89bdfbf9-9vhgf 0/1 Terminating 0 2m31s
pc-deployment-5d89bdfbf9-hmtml 1/1 Terminating 0 2m33s
pc-deployment-5d89bdfbf9-9vhgf 0/1 Terminating 0 2m31s
pc-deployment-5d89bdfbf9-hmtml 0/1 Terminating 0 2m35s
pc-deployment-5d89bdfbf9-hmtml 0/1 Terminating 0 2m36s
pc-deployment-5d89bdfbf9-hmtml 0/1 Terminating 0 2m36s
pc-deployment-5d89bdfbf9-9vhgf 0/1 Terminating 0 2m39s
pc-deployment-5d89bdfbf9-9vhgf 0/1 Terminating 0 2m39s
#在原来窗口更新一下镜像
[root@master ~]# kubectl set image deploy pc-deployment nginx=nginx:1.17.3 -n dev
deployment.apps/pc-deployment image updated
滚动升级过程
镜像更新中rs的变化:
#查看rs,发现原来的rs的依旧存在,只是pod数量变为了0,而后又新产生了一一个rs, pod数量为4
#其实这就是deployment能够进行版本回退的奥妙所在,后面会详细解释
[root@master ~]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
pc-deployment-5d89bdfbf9 0 0 0 17m
pc-deployment-675d469f8b 0 0 0 14m
pc-deployment-7865c58bdf 3 3 3 7m45s
[root@master ~]# kubectl delete -f pc-deployment.yaml
deployment.apps "pc-deployment" deleted
[root@master ~]# kubectl create -f pc-deployment.yaml --record
deployment.apps/pc-deployment created
[root@master ~]# kubectl get deploy,rs,pod -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/pc-deployment 3/3 3 3 65s
NAME DESIRED CURRENT READY AGE
replicaset.apps/pc-deployment-5d89bdfbf9 3 3 3 65s
NAME READY STATUS RESTARTS AGE
pod/pc-deployment-5d89bdfbf9-6rdgg 1/1 Running 0 65s
pod/pc-deployment-5d89bdfbf9-mpdh7 1/1 Running 0 65s
pod/pc-deployment-5d89bdfbf9-vhkhj 1/1 Running 0 65s
为了查看明显效果,在开启两个master窗口
#执行回退命令
[root@master ~]# kubectl set image deploy pc-deployment nginx=nginx:1.17.2 -n dev
deployment.apps/pc-deployment image updated
[root@master ~]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
pc-deployment-5d89bdfbf9 0 0 0 7m46s
pc-deployment-675d469f8b 3 3 3 85s
#监控rs的实时变化
[root@master ~]# kubectl get rs -n dev -w
NAME DESIRED CURRENT READY AGE
pc-deployment-5d89bdfbf9 3 3 3 4m47s
pc-deployment-675d469f8b 1 0 0 0s
pc-deployment-675d469f8b 1 0 0 0s
pc-deployment-675d469f8b 1 1 0 0s
pc-deployment-675d469f8b 1 1 1 2s
pc-deployment-5d89bdfbf9 2 3 3 6m23s
pc-deployment-5d89bdfbf9 2 3 3 6m23s
pc-deployment-5d89bdfbf9 2 2 2 6m23s
pc-deployment-675d469f8b 2 1 1 2s
pc-deployment-675d469f8b 2 1 1 2s
pc-deployment-675d469f8b 2 2 1 2s
pc-deployment-675d469f8b 2 2 2 5s
pc-deployment-5d89bdfbf9 1 2 2 6m26s
pc-deployment-675d469f8b 3 2 2 5s
pc-deployment-5d89bdfbf9 1 2 2 6m26s
pc-deployment-675d469f8b 3 2 2 5s
pc-deployment-5d89bdfbf9 1 1 1 6m26s
pc-deployment-675d469f8b 3 3 2 5s
pc-deployment-675d469f8b 3 3 3 8s
pc-deployment-5d89bdfbf9 0 1 1 6m29s
pc-deployment-5d89bdfbf9 0 1 1 6m29s
pc-deployment-5d89bdfbf9 0 0 0 6m29s
#监控pod的实时变化
[root@master ~]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
pc-deployment-5d89bdfbf9-6rdgg 1/1 Running 0 4m58s
pc-deployment-5d89bdfbf9-mpdh7 1/1 Running 0 4m58s
pc-deployment-5d89bdfbf9-vhkhj 1/1 Running 0 4m58s
pc-deployment-675d469f8b-nfrqs 0/1 Pending 0 0s
pc-deployment-675d469f8b-nfrqs 0/1 Pending 0 0s
pc-deployment-675d469f8b-nfrqs 0/1 ContainerCreating 0 0s
pc-deployment-675d469f8b-nfrqs 1/1 Running 0 2s
pc-deployment-5d89bdfbf9-6rdgg 1/1 Terminating 0 6m23s
pc-deployment-675d469f8b-jrmhc 0/1 Pending 0 0s
pc-deployment-675d469f8b-jrmhc 0/1 Pending 0 0s
pc-deployment-675d469f8b-jrmhc 0/1 ContainerCreating 0 0s
pc-deployment-5d89bdfbf9-6rdgg 0/1 Terminating 0 6m26s
pc-deployment-675d469f8b-jrmhc 1/1 Running 0 3s
pc-deployment-5d89bdfbf9-vhkhj 1/1 Terminating 0 6m26s
pc-deployment-675d469f8b-xzs4c 0/1 Pending 0 0s
pc-deployment-675d469f8b-xzs4c 0/1 Pending 0 0s
pc-deployment-675d469f8b-xzs4c 0/1 ContainerCreating 0 0s
pc-deployment-5d89bdfbf9-6rdgg 0/1 Terminating 0 6m28s
pc-deployment-5d89bdfbf9-6rdgg 0/1 Terminating 0 6m28s
pc-deployment-675d469f8b-xzs4c 1/1 Running 0 3s
pc-deployment-5d89bdfbf9-vhkhj 0/1 Terminating 0 6m29s
pc-deployment-5d89bdfbf9-mpdh7 1/1 Terminating 0 6m29s
pc-deployment-5d89bdfbf9-vhkhj 0/1 Terminating 0 6m30s
pc-deployment-5d89bdfbf9-vhkhj 0/1 Terminating 0 6m30s
pc-deployment-5d89bdfbf9-mpdh7 0/1 Terminating 0 6m31s
pc-deployment-5d89bdfbf9-mpdh7 0/1 Terminating 0 6m32s
pc-deployment-5d89bdfbf9-mpdh7 0/1 Terminating 0 6m32s
版本回退
deployment支持版本升级过程中的暂停、继续功能以及版本回退等诸多功能,下面具体来看.
kubectl rollout:版本升级相关功能,支持下面的选项:
●status 显示当前升级状态
●history 显示升级历史记录
●pause 暂停版本升级过程
●resume 继续已经暂停的版本升级过程
●restart 重启版本升级过程
●undo 回滚到上一级版本(可以使用–to-revision回滚到指定版本)
#查看当前升级版本的状态
[root@master ~]# kubectl rollout status deploy pc-deployment -n dev
deployment "pc-deployment" successfully rolled out
#查看升级历史记录
[root@master ~]# kubectl rollout history deploy pc-deployment -n dev
deployment.apps/pc-deployment
REVISION CHANGE-CAUSE
1 kubectl create --filename=pc-deployment.yaml --record=true
2 kubectl create --filename=pc-deployment.yaml --record=true
#查看有两次历史记录,说明有一次升级
#查看当前版本号
[root@master ~]# kubectl get deployment -o wide -n dev
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
pc-deployment 3/3 3 3 24m nginx nginx:1.17.3 app=nginx-pod
[root@master ~]# kubectl get deployment,rs -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/pc-deployment 3/3 3 3 25m
NAME DESIRED CURRENT READY AGE
replicaset.apps/pc-deployment-5d89bdfbf9 0 0 0 25m
replicaset.apps/pc-deployment-675d469f8b 0 0 0 19m
replicaset.apps/pc-deployment-7865c58bdf 3 3 3 4m19s
#版本回滚
#这里直接使用--to-revision=1回滚到了1版本,如果省略这个选项,就是回退到上个版本,就是2版本
[root@master ~]# kubectl rollout undo deployment pc-deployment --to-revision=1 -n dev
deployment.apps/pc-deployment rolled back
[root@master ~]# kubectl get deployment -n dev -o wide
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
pc-deployment 3/3 3 3 29m nginx nginx:1.17.1 app=nginx-pod
[root@master ~]# kubectl get deployment,rs -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/pc-deployment 3/3 3 3 30m
NAME DESIRED CURRENT READY AGE
replicaset.apps/pc-deployment-5d89bdfbf9 3 3 3 30m
replicaset.apps/pc-deployment-675d469f8b 0 0 0 23m
replicaset.apps/pc-deployment-7865c58bdf 0 0 0 9m1s
#查看历史记录
[root@master ~]# kubectl rollout history deploy pc-deployment -n dev
deployment.apps/pc-deployment
REVISION CHANGE-CAUSE
2 kubectl create --filename=pc-deployment.yaml --record=true
3 kubectl create --filename=pc-deployment.yaml --record=true
4 kubectl create --filename=pc-deployment.yaml --record=true
#查看rs,发现第一个rs中有3个pod运行,后面两个版本的rs中pod为运行
#其实deployment之所以可是实现版本的回滚,就是通过记录下历史rs来实现的,
#一旦想回滚到哪个版本,只需要将当前版本pod数量降为0,然后将回滚版本的pod提升为目标数量就可以了
[root@master ~]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
pc-deployment-5d89bdfbf9 3 3 3 31m
pc-deployment-675d469f8b 0 0 0 25m
pc-deployment-7865c58bdf 0 0 0 10m
金丝雀发布
Deployment支持更新过程中的控制,如”暂停(pause)"或"继续(resume)"更新操作。
比如有一批新的Pod资源创建完成后立即暂停更新过程, 此时,仅存在一部分新版本的应用, 主体部分还是旧
的版本。然后,再筛选一小部分的用户请求路由到新版本的Pod应用,继续观察能否稳定地按期望的方式运行。确
定没问题之后再继续完成余下的Pod资源滚动更新,否则立即回滚更新操作。这就是所谓的金丝雀发布。
#更新deployment的版本,并配置暂停deployment
[root@master ~]# kubectl set image deploy pc-deployment nginx=nginx:1.17.4 -n dev && kubectl rollout pause deployment pc-deployment -n dev
deployment.apps/pc-deployment image updated
deployment.apps/pc-deployment paused
[root@master ~]# kubectl get deployment,rs -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/pc-deployment 3/3 1 3 37m
NAME DESIRED CURRENT READY AGE
replicaset.apps/pc-deployment-5d89bdfbf9 3 3 3 37m
replicaset.apps/pc-deployment-675d469f8b 0 0 0 31m
replicaset.apps/pc-deployment-6c9f56fcfb 1 1 0 14s
replicaset.apps/pc-deployment-7865c58bdf 0 0 0 16m
#观察更新状态
[root@master ~]# kubectl rollout status deployment pc-deployment -n dev
Waiting for deployment "pc-deployment" rollout to finish: 1 out of 3 new replicas have been updated...
#确保更新的pod没问题了,继续更新
[root@master ~]# kubectl rollout resume deployment pc-deployment -n dev
deployment.apps/pc-deployment resumed
[root@master ~]# kubectl get rs -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
pc-deployment-5d89bdfbf9 0 0 0 42m nginx nginx:1.17.1 app=nginx-pod,pod-template-hash=5d89bdfbf9
pc-deployment-675d469f8b 0 0 0 35m nginx nginx:1.17.2 app=nginx-pod,pod-template-hash=675d469f8b
pc-deployment-6c9f56fcfb 3 3 3 5m nginx nginx:1.17.4 app=nginx-pod,pod-template-hash=6c9f56fcfb
pc-deployment-7865c58bdf 0 0 0 21m nginx nginx:1.17.3 app=nginx-pod,pod-template-hash=7865c58bdf
[root@master ~]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
pc-deployment-6c9f56fcfb-q5h8v 1/1 Running 0 2m
pc-deployment-6c9f56fcfb-qsjxj 1/1 Running 0 5m25s
pc-deployment-6c9f56fcfb-zxfsc 1/1 Running 0 2m3s
删除Deployment
#删除deployment, 其下的rs和pod也将被删除
[root@master ~]# kubectl delete -f pc-deployment.yaml
deployment.apps "pc-deployment" deleted
6.4 Horizontal Pod Autoscaler(HPA)
在前面的课程中,我们可以通过手工执行kubectl scale
命令实现Pod扩容,但是这显然不符合Kubernetes
的定位目标–自动化、智能化。Kubernetes期望可以通过监测Pod的使用情况, 实现pod数量的自动调整,于是就
产生了HPA这种控制器。
HPA可以获取每个pod利用率,然后和HPA中定义的指标进行对比,同时计算出需要伸缩的具体值,最后实现
pod的数量的调整。其实HPA与之前的Deployment一样,也属于一种Kubernetes资源对象,它通过追踪分析目标
pod的负载变化情况,来确定是否需要针对性地调整目标pod的副本数。
1安装metrics-server
metrics-server可以用来收集集群中的资源使用情况
#安装git
[root@master ~]# yum install git -y
#获取metrics-server,注意使用的版本
[root@master ~]# git clone -b v0.3.6 https://github.com/kubernetes-incubator/metrics-server
[root@master ~]# ls metrics-server/
cmd CONTRIBUTING.md Gopkg.lock hack Makefile OWNERS_ALIASES README.md vendor
code-of-conduct.md deploy Gopkg.toml LICENSE OWNERS pkg SECURITY_CONTACTS version
#修改deployment,注意修改的是镜像和初始化参数
[root@master ~]# cd metrics-server/deploy/1.8+/
[root@master 1.8+]# vim metrics-server-deployment.yaml
hostNetwork: true
image: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-server-amd64:v0.3.6
args:
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP,Hostname,InternalDNS,ExternalDNS,ExternalIP
#安装metrics-server
[root@master 1.8+]# kubectl apply -f ./
clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created
rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created
apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created
serviceaccount/metrics-server created
deployment.apps/metrics-server created
service/metrics-server created
clusterrole.rbac.authorization.k8s.io/system:metrics-server created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created
#查看启动的pod
[root@master 1.8+]# kubectl get pods -n kube-system
NAME READY STATUS RESTARTS AGE
metrics-server-6b976979db-fjh6q 1/1 Running 0 81s
#使用kubectl top node查看资源使用情况(稍微等待一会在执行)
[root@master 1.8+]# kubectl top nodes
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
master 328m 16% 1099Mi 58%
node1 40m 2% 682Mi 36%
node2 77m 3% 350Mi 18%
[root@master 1.8+]# kubectl top pod -n kube-system
NAME CPU(cores) MEMORY(bytes)
coredns-6955765f44-jmr9b 3m 8Mi
coredns-6955765f44-wrzpn 3m 10Mi
etcd-master 23m 135Mi
kube-apiserver-master 43m 304Mi
kube-controller-manager-master 26m 43Mi
kube-flannel-ds-amd64-ltfjq 4m 8Mi
kube-flannel-ds-amd64-xqrqj 4m 11Mi
kube-proxy-fdp9p 1m 14Mi
kube-proxy-lqxxn 1m 29Mi
kube-proxy-w7xwm 2m 15Mi
kube-scheduler-master 5m 15Mi
metrics-server-6b976979db-fjh6q 1m 11Mi
#至此,netrics-server安装完成
2准备deployment和service
为了操作简单,直接使用命令
#创建deployment
[root@master 1.8+]# kubectl run nginx --image=nginx:1.17.1 --requests=cpu=100m -n dev
#创建service (--type=Nodeport是外部都可以访问)
[root@master 1.8+]# kubectl expose deployment nginx --type=NodePort --port=80 -n dev
#查看创建的资源
[root@master 1.8+]# kubectl get deploy,pod,svc -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/nginx 1/1 1 1 2m6s
NAME READY STATUS RESTARTS AGE
pod/nginx-778cb5fb7b-vhlfn 1/1 Running 0 2m6s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/nginx NodePort 10.99.6.142 <none> 80:30135/TCP 6s
#可以用master的ip+30135端口去访问
3部署HPA
创建pc-hpa.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: pc-hpa
namespace: dev
spec:
minReplicas: 1 # 最小pod数量
maxReplicas: 10 #最大pod数量
targetCPUUtilizationPercentage: 3 # CPU使用率指标
scaleTargetRef: # 指定要控制的nginx信息
apiVersion: apps/v1
kind: Deployment
name: nginx
#创建hpa
[root@master ~]# kubectl create -f pc-hpa.yaml
horizontalpodautoscaler.autoscaling/pc-hpa created
#查看hpa
[root@master ~]# kubectl get hpa -n dev
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
pc-hpa Deployment/nginx <unknown>/3% 1 10 0 8s
[root@master ~]# kubectl get hpa -n dev
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
pc-hpa Deployment/nginx 0%/3% 1 10 1 94s
为了效果明显,在开3个master窗口,监控实时变化
1个窗口监控deployment的变化
1个窗口监控pod的变化
1个窗口监控hpa的变化
我们用ab进行压测
#安装ab压测命令
[root@node2 ~]# yum install httpd-tools -y
[root@node2 ~]# ab -n 100000 -c 1000 http://10.0.0.103:30135/
[root@master ~]# kubectl get deploy -n dev -w
NAME READY UP-TO-DATE AVAILABLE AGE
nginx 1/1 1 1 55m
taint1 1/1 1 1 12d
taint2 1/1 1 1 12d
taint3 1/1 1 1 12d
nginx 1/4 1 1 79m
nginx 1/4 1 1 79m
nginx 1/4 1 1 79m
nginx 1/4 4 1 79m
nginx 2/4 4 2 80m
nginx 3/4 4 3 80m
nginx 4/4 4 4 80m
nginx 4/6 4 4 80m
nginx 4/6 4 4 80m
nginx 4/6 4 4 80m
nginx 4/6 6 4 80m
nginx 5/6 6 5 80m
nginx 6/6 6 6 80m
nginx 6/10 6 6 80m
nginx 6/10 6 6 80m
nginx 6/10 6 6 80m
nginx 6/10 10 6 80m
nginx 7/10 10 7 80m
nginx 8/10 10 8 80m
nginx 9/10 10 9 80m
nginx 10/10 10 10 80m
nginx 10/1 10 10 86m
nginx 10/1 10 10 86m
nginx 1/1 1 1 86m
[root@master ~]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
nginx-778cb5fb7b-vhlfn 1/1 Running 0 55m
pod-toleration 1/1 Running 0 12d
taint1-766c47bf55-rxzbx 1/1 Running 0 12d
taint2-84946958cf-5m6nd 1/1 Running 0 12d
taint3-57d45f9d4c-s8xbv 1/1 Running 0 12d
nginx-778cb5fb7b-47n2f 0/1 Pending 0 0s
nginx-778cb5fb7b-frbst 0/1 Pending 0 0s
nginx-778cb5fb7b-47n2f 0/1 Pending 0 0s
nginx-778cb5fb7b-km65w 0/1 Pending 0 0s
nginx-778cb5fb7b-frbst 0/1 Pending 0 0s
nginx-778cb5fb7b-km65w 0/1 Pending 0 0s
nginx-778cb5fb7b-47n2f 0/1 ContainerCreating 0 0s
nginx-778cb5fb7b-frbst 0/1 ContainerCreating 0 0s
nginx-778cb5fb7b-km65w 0/1 ContainerCreating 0 0s
nginx-778cb5fb7b-frbst 1/1 Running 0 13s
nginx-778cb5fb7b-km65w 1/1 Running 0 13s
nginx-778cb5fb7b-47n2f 1/1 Running 0 13s
nginx-778cb5fb7b-2vkqj 0/1 Pending 0 0s
nginx-778cb5fb7b-9mr68 0/1 Pending 0 0s
nginx-778cb5fb7b-2vkqj 0/1 Pending 0 0s
nginx-778cb5fb7b-9mr68 0/1 Pending 0 0s
nginx-778cb5fb7b-2vkqj 0/1 ContainerCreating 0 0s
nginx-778cb5fb7b-9mr68 0/1 ContainerCreating 0 0s
nginx-778cb5fb7b-2vkqj 1/1 Running 0 9s
nginx-778cb5fb7b-9mr68 1/1 Running 0 10s
nginx-778cb5fb7b-9hw7f 0/1 Pending 0 0s
nginx-778cb5fb7b-jr5qk 0/1 Pending 0 0s
nginx-778cb5fb7b-9hw7f 0/1 Pending 0 0s
nginx-778cb5fb7b-nvzbz 0/1 Pending 0 0s
nginx-778cb5fb7b-jr5qk 0/1 Pending 0 0s
nginx-778cb5fb7b-4r5hl 0/1 Pending 0 0s
nginx-778cb5fb7b-nvzbz 0/1 Pending 0 0s
nginx-778cb5fb7b-9hw7f 0/1 ContainerCreating 0 0s
nginx-778cb5fb7b-4r5hl 0/1 Pending 0 0s
nginx-778cb5fb7b-jr5qk 0/1 ContainerCreating 0 1s
nginx-778cb5fb7b-nvzbz 0/1 ContainerCreating 0 1s
nginx-778cb5fb7b-4r5hl 0/1 ContainerCreating 0 1s
nginx-778cb5fb7b-jr5qk 1/1 Running 0 6s
nginx-778cb5fb7b-4r5hl 1/1 Running 0 6s
nginx-778cb5fb7b-9hw7f 1/1 Running 0 6s
nginx-778cb5fb7b-nvzbz 1/1 Running 0 6s
nginx-778cb5fb7b-47n2f 1/1 Terminating 0 6m35s
nginx-778cb5fb7b-jr5qk 1/1 Terminating 0 5m50s
nginx-778cb5fb7b-9hw7f 1/1 Terminating 0 5m50s
nginx-778cb5fb7b-nvzbz 1/1 Terminating 0 5m50s
nginx-778cb5fb7b-9mr68 1/1 Terminating 0 6m20s
nginx-778cb5fb7b-km65w 1/1 Terminating 0 6m35s
nginx-778cb5fb7b-frbst 1/1 Terminating 0 6m35s
nginx-778cb5fb7b-4r5hl 1/1 Terminating 0 5m50s
nginx-778cb5fb7b-2vkqj 1/1 Terminating 0 6m20s
nginx-778cb5fb7b-jr5qk 0/1 Terminating 0 5m55s
nginx-778cb5fb7b-4r5hl 0/1 Terminating 0 5m55s
nginx-778cb5fb7b-nvzbz 0/1 Terminating 0 5m55s
nginx-778cb5fb7b-9hw7f 0/1 Terminating 0 5m55s
nginx-778cb5fb7b-frbst 0/1 Terminating 0 6m40s
nginx-778cb5fb7b-2vkqj 0/1 Terminating 0 6m25s
nginx-778cb5fb7b-47n2f 0/1 Terminating 0 6m41s
nginx-778cb5fb7b-nvzbz 0/1 Terminating 0 5m56s
nginx-778cb5fb7b-nvzbz 0/1 Terminating 0 5m56s
nginx-778cb5fb7b-jr5qk 0/1 Terminating 0 5m57s
nginx-778cb5fb7b-47n2f 0/1 Terminating 0 6m42s
nginx-778cb5fb7b-km65w 0/1 Terminating 0 6m43s
nginx-778cb5fb7b-9hw7f 0/1 Terminating 0 5m58s
nginx-778cb5fb7b-9hw7f 0/1 Terminating 0 5m59s
nginx-778cb5fb7b-9hw7f 0/1 Terminating 0 5m59s
nginx-778cb5fb7b-frbst 0/1 Terminating 0 6m44s
nginx-778cb5fb7b-frbst 0/1 Terminating 0 6m44s
nginx-778cb5fb7b-frbst 0/1 Terminating 0 6m44s
nginx-778cb5fb7b-9mr68 0/1 Terminating 0 6m30s
nginx-778cb5fb7b-9mr68 0/1 Terminating 0 6m30s
nginx-778cb5fb7b-9mr68 0/1 Terminating 0 6m30s
nginx-778cb5fb7b-4r5hl 0/1 Terminating 0 6m
nginx-778cb5fb7b-4r5hl 0/1 Terminating 0 6m
nginx-778cb5fb7b-4r5hl 0/1 Terminating 0 6m
nginx-778cb5fb7b-2vkqj 0/1 Terminating 0 6m31s
nginx-778cb5fb7b-2vkqj 0/1 Terminating 0 6m31s
nginx-778cb5fb7b-2vkqj 0/1 Terminating 0 6m31s
nginx-778cb5fb7b-km65w 0/1 Terminating 0 6m47s
nginx-778cb5fb7b-km65w 0/1 Terminating 0 6m47s
nginx-778cb5fb7b-47n2f 0/1 Terminating 0 6m50s
nginx-778cb5fb7b-47n2f 0/1 Terminating 0 6m50s
nginx-778cb5fb7b-jr5qk 0/1 Terminating 0 6m5s
nginx-778cb5fb7b-jr5qk 0/1 Terminating 0 6m5s
[root@master ~]# kubectl get hpa -n dev -w
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
pc-hpa Deployment/nginx 0%/3% 1 10 1 3m52s
pc-hpa Deployment/nginx 0%/3% 1 10 1 5m20s
pc-hpa Deployment/nginx 1%/3% 1 10 1 18m
pc-hpa Deployment/nginx 0%/3% 1 10 1 19m
pc-hpa Deployment/nginx 0%/3% 1 10 1 24m
pc-hpa Deployment/nginx 17%/3% 1 10 1 27m
pc-hpa Deployment/nginx 17%/3% 1 10 4 27m
pc-hpa Deployment/nginx 17%/3% 1 10 6 27m
pc-hpa Deployment/nginx 139%/3% 1 10 6 28m
pc-hpa Deployment/nginx 139%/3% 1 10 10 28m
pc-hpa Deployment/nginx 0%/3% 1 10 10 29m
pc-hpa Deployment/nginx 0%/3% 1 10 10 33m
pc-hpa Deployment/nginx 0%/3% 1 10 1 34m
6.5 DaemonSet(DS)
DaemonSet类型的控制器可以保证集群中的每一台(或指定)节点上都运行一个副本,一般适用于日志收集、
节点监控等场景。也就是说,如果一个pod提供的功能是节点级别的(每个节点都需要且只需要一个), 那么这类
Pod就适合使用DaemonSet类型的控制器创建。
DaemonSet控制器的特点:
●每当向集群中添加一个节点时,指定的pod副本也将添加到该节点上
●当节点从集群中移除时,pod也就被垃圾回收了
下面先来看下DaemonSet的资源清单文件
apiVersion: apps/v1 #版本号
kind: DaemonSet #类型
metadata: #元数据
name: # rs名称
namespace: #所属命名空间
labels: #标签
controller: daemonset
spec: #详情描述
revisionHistoryLimit: 3 #保留历史版本
updateStrategy: #更新策略
type: RollingUpdate #滚动更新策略
rollingUpdate: #滚动更新
maxUnavailable: 1 #最大不可用状态的Pod的最大值,可以为百分比,也可以为整数
selector: #选择器,通过它指定该控制器管理哪些pod
matchLabels: # Labels匹配规则
app: nginx-pod
matchExpressions: # Expressions匹配规则
- {key: app, operator: In, values: [nginx-pod]}
template: #模板,当副本数量不足时,会根据下面的模板创建pod副本
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
ports:
- containerPort: 80
创建pc-daemonset.yaml,内容如下:
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: pc-daemonset
namespace: dev
spec:
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
#创建daemonset
[root@master ~]# kubectl create -f pc-daemonset.yaml
#查看daemonset
[root@master ~]# kubectl get ds pc-daemonset -n dev
NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE
pc-daemonset 2 2 2 2 2 <none> 10m
[root@master ~]# kubectl get pods -n dev -o wide
#(如果有node3节点,会在node3节点立马启动一个pod)
#删除daemonset
[root@master ~]# kubectl delete -f pc-daemonset.yaml
daemonset.apps "pc-daemonset" deleted
6.6 Job
Job,主要用于负责**批量处理(一次要处理指定数量任务)短暂的一次性(每个任务仅运行一次就结束)**任务。Job特点如下:
●当ob创建的pod执行成功时, Job将记录成功结束的pod数量
●当成功结束的pod达到指定的数量时, Job将完成执行
apiVersion: batch/v1 #版本号
kind: Job #类型
metadata: #元数据
name: # rs名称
namespace: #所属命名空间
labels: #标签
controller: job
spec: #详情描述
completions: 1 #指定job需要成功运行Pods的次数。默认值: 1
parallelism: 1 #指定job在任一时刻应该并发运行Pods的数量 。默认值: 1
activeDeadlineSeconds: 30 #指定job可运行的时间期限,超过时间还未结束,系统将会尝试进行终止。
backoffLimit: 6 #指定job失败后进行重试的次数。默认是6
manualSelector: true #是否可以使用selector选择器选择pod,默认是false
selector: #选择器,通过它指定该控制器管理哪些pod
matchLabels:# Labels匹配规则
app: counter-pod
matchExpressions: # Expressions匹配规则
- {key: app,operator: In,values: [counter-pod]}
template: #模板,当副本数量不足时,会根据下面的模板创建pod副本
metadata:
labels:
app: counter-pod
spec:
restartPolicy: Never #重启策略只能设置为Never或者OnFailure
containers:
- name: counter
image: busybox:1.30
command: [ "bin/sh", "-c","fori in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 2 ;done" ]
关于重启策略设置的说明:
如果指定为OnFailure,则job会在pod出现故障时重启容器,而不是创建pod, failed次数不变
如果指定为Never,则job会在pod出现故障时创建新的pod,并且故障pod不会消失,也不会重启,failed次数加1
如果指定为Always的话,就意味着一直重启, 意味着job任务会重复去执行了,当然不对,所以不能设置为Always
创建pc-job.yaml,内容如下:
apiVersion: batch/v1
kind: Job
metadata:
name: pc-job
namespace: dev
spec:
manualSelector: true
selector:
matchLabels:
app: counter-pod
template:
metadata:
labels:
app: counter-pod
spec:
restartPolicy: Never
containers:
- name: counter
image: busybox:1.30
command: ["bin/sh","-c","for i in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 3 ;done" ]
#创建job
[root@master ~]# kubectl create -f pc-job.yaml
job.batch/pc-job created
为了效果明显,在开启两个master窗口,一个监控job,一个监控pod
[root@master ~]# kubectl get job -n dev -w
NAME COMPLETIONS DURATION AGE
pc-job 0/1 0s
pc-job 0/1 0s 0s
pc-job 1/1 30s 30s
[root@master ~]# kubectl get pod -n dev -w
NAME READY STATUS RESTARTS AGE
pc-job-rl6qq 0/1 Pending 0 0s
pc-job-rl6qq 0/1 Pending 0 0s
pc-job-rl6qq 0/1 ContainerCreating 0 0s
pc-job-rl6qq 1/1 Running 0 3s
pc-job-rl6qq 0/1 Completed 0 30s
测试第二个参数
#先删除job
[root@master ~]# kubectl delete -f pc-job.yaml
job.batch "pc-job" deleted
#修改pc-job.yaml文件的配置
apiVersion: batch/v1
kind: Job
metadata:
name: pc-job
namespace: dev
spec:
manualSelector: true
completions: 6 #指定job需要成功运行Pods的次数。默认值: 1
parallelism: 3 #指定job在任一时刻应该并发运行Pods的数量 。默认值: 1
selector:
matchLabels:
app: counter-pod
template:
metadata:
labels:
app: counter-pod
spec:
restartPolicy: Never
containers:
- name: counter
image: busybox:1.30
command: ["bin/sh","-c","for i in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 3 ;done" ]
#开启监控job的窗口(先开启)
[root@master ~]# kubectl get job -n dev -w
NAME COMPLETIONS DURATION AGE
pc-job 0/6 0s
pc-job 0/6 0s 0s
pc-job 1/6 30s 30s
pc-job 2/6 30s 30s
pc-job 3/6 31s 31s
pc-job 4/6 61s 61s
pc-job 5/6 61s 61s
pc-job 6/6 61s 61s
#接下来,调整下pod运行的总数量和并行数量即:在spec下设置下面两个选项
#completions: 6 #指定job需要成功运行Pods的次数为6
#parallelism: 3 #指定job并发运行Pods的数量为3
#然后重新运行job,观察效果,此时会发现,job会每次运行3个pod,总共执行了6个pod
#开启监控pod的窗口(先开启)
[root@master ~]# kubectl get pod -n dev -w
NAME READY STATUS RESTARTS AGE
pc-job-7wxg7 0/1 Pending 0 0s
pc-job-ktg88 0/1 Pending 0 0s
pc-job-mj987 0/1 Pending 0 0s
pc-job-7wxg7 0/1 Pending 0 0s
pc-job-ktg88 0/1 Pending 0 0s
pc-job-mj987 0/1 Pending 0 0s
pc-job-7wxg7 0/1 ContainerCreating 0 0s
pc-job-ktg88 0/1 ContainerCreating 0 0s
pc-job-mj987 0/1 ContainerCreating 0 0s
pc-job-7wxg7 1/1 Running 0 3s
pc-job-ktg88 1/1 Running 0 3s
pc-job-mj987 1/1 Running 0 3s
pc-job-7wxg7 0/1 Completed 0 30s
pc-job-7nrvk 0/1 Pending 0 0s
pc-job-7nrvk 0/1 Pending 0 0s
pc-job-ktg88 0/1 Completed 0 30s
pc-job-fk6ml 0/1 Pending 0 0s
pc-job-fk6ml 0/1 Pending 0 0s
pc-job-7nrvk 0/1 ContainerCreating 0 0s
pc-job-fk6ml 0/1 ContainerCreating 0 0s
pc-job-mj987 0/1 Completed 0 31s
pc-job-dw8hp 0/1 Pending 0 0s
pc-job-dw8hp 0/1 Pending 0 0s
pc-job-dw8hp 0/1 ContainerCreating 0 0s
pc-job-fk6ml 1/1 Running 0 3s
pc-job-7nrvk 1/1 Running 0 3s
pc-job-dw8hp 1/1 Running 0 2s
pc-job-fk6ml 0/1 Completed 0 30s
pc-job-7nrvk 0/1 Completed 0 31s
pc-job-dw8hp 0/1 Completed 0 30s
#创建新的job(后执行)
[root@master ~]# kubectl create -f pc-job.yaml
job.batch/pc-job created
#删除job
[root@master ~]# kubectl delete -f pc-job.yaml
job.batch "pc-job" deleted
6.7 CronJob(cj)
CronJob控制器以Job控制器资源为其管控对象,并借助它管理pod资源对象,Job控制器定义的作业任务在其控
制器资源创建之后便会立即执行,但CronJob可以以类似于Linux操作系统的周期性任务作业计划的方式控制其运
行时间点及重复运行的方式。也就是说,CronJob可以在特定的时间点(反复的)去运行job任务。
Cronjob的资源清单文件:
apiVersion: batch/v1beta1 #版本号
kind: CronJob #类型
metadata: #元数据
name: # rs名称
namespace: #所属命名空间
labels: #标签
controller: cronjob
spec: #详情描述
schedule: # cron格式的作业调度运行时间点,用于控制任务在什么时间执行
concurrencyPolicy: #并发执行策略,用于定义前一-次作业运行尚未完成时是否以及如何运行后一次的作业
failedJobHistoryLimit: #为失败的任务执行保留的历史记录数,默认为1
successfulJobHistoryLimit: #为成功的任务执行保留的历史记录数,默认为3
startingDeadlineSeconds: #启动作业错误的超时时长
jobTemplate: # job控制器模板,用于为cronjob控制器生成job对象;下面其实就是job的定义
metadata:
spec:
completions: 1
parallelism: 1
activeDeadlineSeconds: 30
backoffLimit: 6
manualSelector: true
selector:
matchLabels:
app: counter-pod
matchExpressions:规则
- {key: app,operator: In, values: [counter-pod]}
template:
metadata:
labels:
app: counter-pod
spec:
restartPolicy: Never
containers:
- name: counter
image: busybox:1.30
command: [ "bin/sh","-c","for i in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 2;done" ]
需要重点解释的几个选项:
schedule: cron表达式,用于指定任务的执行时间
*/1 * * * *
<分钟> <小时> <日> <月份> <星期>
分钟值从θ到59.
小时值从0到23.
日值从1到31.
月值从1到12.
星期值从θ到6,0代表星期日
多个时间可以用逗号隔开;范围可以用连字符给出; *可以作为通配符; /表示每 ...
concurrencyPolicy:
Allow: 允许Jobs并发运行(默认)
Forbid: 禁止并发运行, 如果上一次运行尚未完成,则跳过下一次运行
Replace:替换,取消当前正在运行的作业并用新作业替换它
创建pc-crjob.yaml
apiVersion: batch/v1beta1
kind: CronJob
metadata:
name: pc-cronjob
namespace: dev
labels:
controller: cronjob
spec:
schedule: "*/1 * * * *"
jobTemplate:
metadata:
spec:
template:
spec:
restartPolicy: Never
containers:
- name: counter
image: busybox:1 .30
command: ["bin/sh","-c","for i in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 3 ;done" ]
开启查看cj的窗口
[root@master ~]# kubectl get cj -n dev -w
NAME SCHEDULE SUSPEND ACTIVE LAST SCHEDULE AGE
pc-cronjob */1 * * * * False 0 <none> 0s
pc-cronjob */1 * * * * False 1 6s 32s
pc-cronjob */1 * * * * False 0 36s 62s
pc-cronjob */1 * * * * False 1 6s 92s
pc-cronjob */1 * * * * False 0 36s 2m2s
pc-cronjob */1 * * * * False 0 65s 2m31s
开启查看job的窗口
[root@master ~]# kubectl get pod -n dev -w
NAME READY STATUS RESTARTS AGE
pc-cronjob-1619249520-vxwx7 0/1 Pending 0 0s
pc-cronjob-1619249520-vxwx7 0/1 Pending 0 0s
pc-cronjob-1619249520-vxwx7 0/1 ContainerCreating 0 0s
pc-cronjob-1619249520-vxwx7 1/1 Running 0 2s
pc-cronjob-1619249520-vxwx7 0/1 Completed 0 29s
pc-cronjob-1619249580-9lmr2 0/1 Pending 0 0s
pc-cronjob-1619249580-9lmr2 0/1 Pending 0 0s
pc-cronjob-1619249580-9lmr2 0/1 ContainerCreating 0 0s
pc-cronjob-1619249580-9lmr2 1/1 Running 0 2s
pc-cronjob-1619249580-9lmr2 0/1 Completed 0 29s
pc-cronjob-1619249520-vxwx7 0/1 Terminating 0 119s
pc-cronjob-1619249580-9lmr2 0/1 Terminating 0 59s
pc-cronjob-1619249580-9lmr2 0/1 Terminating 0 59s
pc-cronjob-1619249520-vxwx7 0/1 Terminating 0 119s
开启查看pod的窗口
[root@master ~]# kubectl get job -n dev -w
NAME COMPLETIONS DURATION AGE
pc-cronjob-1619249520 0/1 0s
pc-cronjob-1619249520 0/1 0s 0s
pc-cronjob-1619249520 1/1 29s 29s
pc-cronjob-1619249580 0/1 0s
pc-cronjob-1619249580 0/1 0s 0s
pc-cronjob-1619249580 1/1 29s 29s
pc-cronjob-1619249580 1/1 29s 59s
pc-cronjob-1619249520 1/1 29s 119s
#创建cronjob
[root@master ~]# kubectl create -f pc-crjob.yaml
cronjob.batch/pc-cronjob created
#删除cronjob
[root@master ~]# kubectl delete -f pc-crjob.yaml
cronjob.batch "pc-cronjob" deleted
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