6. Pod控制器详解 6.1 Pod控制器介绍 Pod是kubernetes的最小管理单元，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：kubernetes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Pod控制器之后，只需要告诉Pod控制器，想要多少个什么样的Pod就可以了，它会创建出满足条件的Pod并确保每一个Pod资源处于用户期望的目标状态。如果Pod资源在运行中出现故障，它会基于指定策略重新编排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：保证副本数量一直维持在期望值，并支持pod数量扩缩容，镜像版本升级
Deployment：通过控制ReplicaSet来控制Pod，并支持滚动升级、回退版本
Horizontal Pod Autoscaler：可以根据集群负载自动水平调整Pod的数量，实现削峰填谷
DaemonSet：在集群中的指定Node上运行且仅运行一个副本，一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，不需要重启或重建，用于执行一次性任务
Cronjob：它创建的Pod负责周期性任务控制，不需要持续后台运行
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数量的扩缩容和镜像版本的升降级。
ReplicaSet的资源清单文件：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 apiVersion: apps/v1 kind: ReplicaSet metadata: name: namespace: labels: controller: rs spec: replicas: 3 selector: matchLabels: app: nginx-pod matchExpressions: - {key: app , operator: In , values: [nginx-pod ]} template: 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：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 # 创建rs [root@k8s-master01 ~]# 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@k8s-master01 ~]# kubectl get rs pc-replicaset -n dev -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR pc-replicaset 3 3 3 22s 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-xxxxx随机码 [root@k8s-master01 ~]# kubectl get pod -n dev NAME READY STATUS RESTARTS AGE pc-replicaset-6vmvt 1/1 Running 0 54s pc-replicaset-fmb8f 1/1 Running 0 54s pc-replicaset-snrk2 1/1 Running 0 54s
扩缩容
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 # 编辑rs的副本数量，修改spec:replicas: 6即可 [root@k8s-master01 ~]# kubectl edit rs pc-replicaset -n dev replicaset.apps/pc-replicaset edited # 查看pod [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-replicaset-6vmvt 1/1 Running 0 114m pc-replicaset-cftnp 1/1 Running 0 10s pc-replicaset-fjlm6 1/1 Running 0 10s pc-replicaset-fmb8f 1/1 Running 0 114m pc-replicaset-s2whj 1/1 Running 0 10s pc-replicaset-snrk2 1/1 Running 0 114m # 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@k8s-master01 ~]# kubectl scale rs pc-replicaset --replicas=2 -n dev replicaset.apps/pc-replicaset scaled # 命令运行完毕，立即查看，发现已经有4个开始准备退出了 [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-replicaset-6vmvt 0/1 Terminating 0 118m pc-replicaset-cftnp 0/1 Terminating 0 4m17s pc-replicaset-fjlm6 0/1 Terminating 0 4m17s pc-replicaset-fmb8f 1/1 Running 0 118m pc-replicaset-s2whj 0/1 Terminating 0 4m17s pc-replicaset-snrk2 1/1 Running 0 118m # 稍等片刻，就只剩下2个了 [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-replicaset-fmb8f 1/1 Running 0 119m pc-replicaset-snrk2 1/1 Running 0 119m
镜像升级
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # 编辑rs的容器镜像 - image: nginx:1.17.2 [root@k8s-master01 ~]# kubectl edit rs pc-replicaset -n dev replicaset.apps/pc-replicaset edited # 再次查看，发现镜像版本已经变更了 [root@k8s-master01 ~]# kubectl get rs -n dev -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES ... pc-replicaset 2 2 2 140m nginx nginx:1.17.2 ... # 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@k8s-master01 ~]# kubectl set image rs pc-replicaset nginx=nginx:1.17.1 -n dev replicaset.apps/pc-replicaset image updated # 再次查看，发现镜像版本已经变更了 [root@k8s-master01 ~]# kubectl get rs -n dev -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES ... pc-replicaset 2 2 2 145m nginx nginx:1.17.1 ...
删除ReplicaSet
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # 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@k8s-master01 ~]# kubectl delete rs pc-replicaset -n dev replicaset.apps "pc-replicaset" deleted [root@k8s-master01 ~]# kubectl get pod -n dev -o wide No resources found in dev namespace. # 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@k8s-master01 ~]# kubectl delete rs pc-replicaset -n dev --cascade=false replicaset.apps "pc-replicaset" deleted [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-replicaset-cl82j 1/1 Running 0 75s pc-replicaset-dslhb 1/1 Running 0 75s # 也可以使用yaml直接删除(推荐) [root@k8s-master01 ~]# kubectl delete -f pc-replicaset.yaml replicaset.apps "pc-replicaset" deleted
6.3 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来简介管理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
支持滚动升级和回滚版本
Deployment的资源清单文件：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 apiVersion: apps/v1 kind: Deployment metadata: name: namespace: labels: controller: deploy spec: replicas: 3 revisionHistoryLimit: 3 paused: false progressDeadlineSeconds: 600 strategy: type: RollingUpdate rollingUpdate: maxSurge: 30 % maxUnavailable: 30 % selector: matchLabels: app: nginx-pod matchExpressions: - {key: app , operator: In , values: [nginx-pod ]} template: 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：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 # 创建deployment [root@k8s-master01 ~]# 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@k8s-master01 ~]# kubectl get deploy pc-deployment -n dev NAME READY UP-TO-DATE AVAILABLE AGE pc-deployment 3/3 3 3 15s # 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@k8s-master01 ~]# kubectl get rs -n dev NAME DESIRED CURRENT READY AGE pc-deployment-6696798b78 3 3 3 23s # 查看pod [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-deployment-6696798b78-d2c8n 1/1 Running 0 107s pc-deployment-6696798b78-smpvp 1/1 Running 0 107s pc-deployment-6696798b78-wvjd8 1/1 Running 0 107s
扩缩容
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 # 变更副本数量为5个 [root@k8s-master01 ~]# kubectl scale deploy pc-deployment --replicas=5 -n dev deployment.apps/pc-deployment scaled # 查看deployment [root@k8s-master01 ~]# kubectl get deploy pc-deployment -n dev NAME READY UP-TO-DATE AVAILABLE AGE pc-deployment 5/5 5 5 2m # 查看pod [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-deployment-6696798b78-d2c8n 1/1 Running 0 4m19s pc-deployment-6696798b78-jxmdq 1/1 Running 0 94s pc-deployment-6696798b78-mktqv 1/1 Running 0 93s pc-deployment-6696798b78-smpvp 1/1 Running 0 4m19s pc-deployment-6696798b78-wvjd8 1/1 Running 0 4m19s # 编辑deployment的副本数量，修改spec:replicas: 4即可 [root@k8s-master01 ~]# kubectl edit deploy pc-deployment -n dev deployment.apps/pc-deployment edited # 查看pod [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-deployment-6696798b78-d2c8n 1/1 Running 0 5m23s pc-deployment-6696798b78-jxmdq 1/1 Running 0 2m38s pc-deployment-6696798b78-smpvp 1/1 Running 0 5m23s pc-deployment-6696798b78-wvjd8 1/1 Running 0 5m23s
镜像更新
deployment支持两种更新策略:重建更新和滚动更新,可以通过strategy指定策略类型,支持两个属性:
1 2 3 4 5 6 7 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
编辑pc-deployment.yaml,在spec节点下添加更新策略
1 2 3 spec: strategy: type: Recreate
创建deploy进行验证
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 # 变更镜像 [root@k8s-master01 ~]# kubectl set image deployment pc-deployment nginx=nginx:1.17.2 -n dev deployment.apps/pc-deployment image updated # 观察升级过程 [root@k8s-master01 ~]# kubectl get pods -n dev -w NAME READY STATUS RESTARTS AGE pc-deployment-5d89bdfbf9-65qcw 1/1 Running 0 31s pc-deployment-5d89bdfbf9-w5nzv 1/1 Running 0 31s pc-deployment-5d89bdfbf9-xpt7w 1/1 Running 0 31s pc-deployment-5d89bdfbf9-xpt7w 1/1 Terminating 0 41s pc-deployment-5d89bdfbf9-65qcw 1/1 Terminating 0 41s pc-deployment-5d89bdfbf9-w5nzv 1/1 Terminating 0 41s pc-deployment-675d469f8b-grn8z 0/1 Pending 0 0s pc-deployment-675d469f8b-hbl4v 0/1 Pending 0 0s pc-deployment-675d469f8b-67nz2 0/1 Pending 0 0s pc-deployment-675d469f8b-grn8z 0/1 ContainerCreating 0 0s pc-deployment-675d469f8b-hbl4v 0/1 ContainerCreating 0 0s pc-deployment-675d469f8b-67nz2 0/1 ContainerCreating 0 0s pc-deployment-675d469f8b-grn8z 1/1 Running 0 1s pc-deployment-675d469f8b-67nz2 1/1 Running 0 1s pc-deployment-675d469f8b-hbl4v 1/1 Running 0 2s
滚动更新
编辑pc-deployment.yaml,在spec节点下添加更新策略
1 2 3 4 5 6 spec: strategy: type: RollingUpdate rollingUpdate: maxSurge: 25 % maxUnavailable: 25 %
创建deploy进行验证
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 # 变更镜像 [root@k8s-master01 ~]# kubectl set image deployment pc-deployment nginx=nginx:1.17.3 -n dev deployment.apps/pc-deployment image updated # 观察升级过程 [root@k8s-master01 ~]# kubectl get pods -n dev -w NAME READY STATUS RESTARTS AGE pc-deployment-c848d767-8rbzt 1/1 Running 0 31m pc-deployment-c848d767-h4p68 1/1 Running 0 31m pc-deployment-c848d767-hlmz4 1/1 Running 0 31m pc-deployment-c848d767-rrqcn 1/1 Running 0 31m pc-deployment-966bf7f44-226rx 0/1 Pending 0 0s pc-deployment-966bf7f44-226rx 0/1 ContainerCreating 0 0s pc-deployment-966bf7f44-226rx 1/1 Running 0 1s pc-deployment-c848d767-h4p68 0/1 Terminating 0 34m pc-deployment-966bf7f44-cnd44 0/1 Pending 0 0s pc-deployment-966bf7f44-cnd44 0/1 ContainerCreating 0 0s pc-deployment-966bf7f44-cnd44 1/1 Running 0 2s pc-deployment-c848d767-hlmz4 0/1 Terminating 0 34m pc-deployment-966bf7f44-px48p 0/1 Pending 0 0s pc-deployment-966bf7f44-px48p 0/1 ContainerCreating 0 0s pc-deployment-966bf7f44-px48p 1/1 Running 0 0s pc-deployment-c848d767-8rbzt 0/1 Terminating 0 34m pc-deployment-966bf7f44-dkmqp 0/1 Pending 0 0s pc-deployment-966bf7f44-dkmqp 0/1 ContainerCreating 0 0s pc-deployment-966bf7f44-dkmqp 1/1 Running 0 2s pc-deployment-c848d767-rrqcn 0/1 Terminating 0 34m # 至此，新版本的pod创建完毕，就版本的pod销毁完毕 # 中间过程是滚动进行的，也就是边销毁边创建
滚动更新的过程：
镜像更新中rs的变化
1 2 3 4 5 6 7 # 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@k8s-master01 ~]# kubectl get rs -n dev NAME DESIRED CURRENT READY AGE pc-deployment-6696798b78 0 0 0 7m37s pc-deployment-6696798b11 0 0 0 5m37s pc-deployment-c848d76789 4 4 4 72s
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）
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 # 查看当前升级版本的状态 [root@k8s-master01 ~]# kubectl rollout status deploy pc-deployment -n dev deployment "pc-deployment" successfully rolled out # 查看升级历史记录 [root@k8s-master01 ~]# 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 3 kubectl create --filename=pc-deployment.yaml --record=true # 可以发现有三次版本记录，说明完成过两次升级 # 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@k8s-master01 ~]# kubectl rollout undo deployment pc-deployment --to-revision=1 -n dev deployment.apps/pc-deployment rolled back # 查看发现，通过nginx镜像版本可以发现到了第一版 [root@k8s-master01 ~]# kubectl get deploy -n dev -o wide NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES pc-deployment 4/4 4 4 74m nginx nginx:1.17.1 # 查看rs，发现第一个rs中有4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@k8s-master01 ~]# kubectl get rs -n dev NAME DESIRED CURRENT READY AGE pc-deployment-6696798b78 4 4 4 78m pc-deployment-966bf7f44 0 0 0 37m pc-deployment-c848d767 0 0 0 71m
金丝雀发布
Deployment控制器支持控制更新过程中的控制，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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 # 更新deployment的版本，并配置暂停deployment [root@k8s-master01 ~]# 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 # 观察更新状态 [root@k8s-master01 ~]# kubectl rollout status deploy pc-deployment -n dev Waiting for deployment "pc-deployment" rollout to finish: 2 out of 4 new replicas have been updated... # 监控更新的过程，可以看到已经新增了一个资源，但是并未按照预期的状态去删除一个旧的资源，就是因为使用了pause暂停命令 [root@k8s-master01 ~]# kubectl get rs -n dev -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES pc-deployment-5d89bdfbf9 3 3 3 19m nginx nginx:1.17.1 pc-deployment-675d469f8b 0 0 0 14m nginx nginx:1.17.2 pc-deployment-6c9f56fcfb 2 2 2 3m16s nginx nginx:1.17.4 [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-deployment-5d89bdfbf9-rj8sq 1/1 Running 0 7m33s pc-deployment-5d89bdfbf9-ttwgg 1/1 Running 0 7m35s pc-deployment-5d89bdfbf9-v4wvc 1/1 Running 0 7m34s pc-deployment-6c9f56fcfb-996rt 1/1 Running 0 3m31s pc-deployment-6c9f56fcfb-j2gtj 1/1 Running 0 3m31s # 确保更新的pod没问题了，继续更新 [root@k8s-master01 ~]# kubectl rollout resume deploy pc-deployment -n dev deployment.apps/pc-deployment resumed # 查看最后的更新情况 [root@k8s-master01 ~]# kubectl get rs -n dev -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES pc-deployment-5d89bdfbf9 0 0 0 21m nginx nginx:1.17.1 pc-deployment-675d469f8b 0 0 0 16m nginx nginx:1.17.2 pc-deployment-6c9f56fcfb 4 4 4 5m11s nginx nginx:1.17.4 [root@k8s-master01 ~]# kubectl get pods -n dev NAME READY STATUS RESTARTS AGE pc-deployment-6c9f56fcfb-7bfwh 1/1 Running 0 37s pc-deployment-6c9f56fcfb-996rt 1/1 Running 0 5m27s pc-deployment-6c9f56fcfb-j2gtj 1/1 Running 0 5m27s pc-deployment-6c9f56fcfb-rf84v 1/1 Running 0 37s
删除Deployment
1 2 3 # 删除deployment，其下的rs和pod也将被删除 [root@k8s-master01 ~]# kubectl delete -f pc-deployment.yaml deployment.apps "pc-deployment" deleted
6.4 Horizontal Pod Autoscaler(HPA) 在前面的课程中，我们已经可以实现通过手工执行kubectl scale命令实现Pod扩容或缩容，但是这显然不符合Kubernetes的定位目标–自动化、智能化。 Kubernetes期望可以实现通过监测Pod的使用情况，实现pod数量的自动调整，于是就产生了Horizontal Pod Autoscaler（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RC控制的所有目标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，这是HPA的实现原理。
接下来，我们来做一个实验
1 安装metrics-server
metrics-server可以用来收集集群中的资源使用情况
1 2 3 4 5 6 7 8 9 10 11 12 13 # 安装git [root@k8s-master01 ~]# yum install git -y # 获取metrics-server, 注意使用的版本 [root@k8s-master01 ~]# git clone -b v0.3.6 https://github.com/kubernetes-incubator/metrics-server # 修改deployment, 注意修改的是镜像和初始化参数 [root@k8s-master01 ~]# cd /root/metrics-server/deploy/1.8+/ [root@k8s-master01 1.8+]# vim metrics-server-deployment.yaml 按图中添加下面选项 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 # 安装metrics-server [root@k8s-master01 1.8+]# kubectl apply -f ./ # 查看pod运行情况 [root@k8s-master01 1.8+]# kubectl get pod -n kube-system metrics-server-6b976979db-2xwbj 1/1 Running 0 90s # 使用kubectl top node 查看资源使用情况 [root@k8s-master01 1.8+]# kubectl top node NAME CPU(cores) CPU% MEMORY(bytes) MEMORY% k8s-master01 289m 14% 1582Mi 54% k8s-node01 81m 4% 1195Mi 40% k8s-node02 72m 3% 1211Mi 41% [root@k8s-master01 1.8+]# kubectl top pod -n kube-system NAME CPU(cores) MEMORY(bytes) coredns-6955765f44-7ptsb 3m 9Mi coredns-6955765f44-vcwr5 3m 8Mi etcd-master 14m 145Mi ... # 至此,metrics-server安装完成
2 准备deployment和servie
创建pc-hpa-pod.yaml文件，内容如下：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 apiVersion: apps/v1 kind: Deployment metadata: name: nginx namespace: dev spec: strategy: type: RollingUpdate replicas: 1 selector: matchLabels: app: nginx-pod template: metadata: labels: app: nginx-pod spec: containers: - name: nginx image: nginx:1.17.1 resources: limits: cpu: "1" requests: cpu: "100m"
1 2 # 创建service [root@k8s-master01 1.8+]# kubectl expose deployment nginx --type=NodePort --port=80 -n dev
1 2 3 4 5 6 7 8 9 10 # 查看 [root@k8s-master01 1.8+]# kubectl get deployment,pod,svc -n dev NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/nginx 1/1 1 1 47s NAME READY STATUS RESTARTS AGE pod/nginx-7df9756ccc-bh8dr 1/1 Running 0 47s NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/nginx NodePort 10.101.18.29 <none> 80:31830/TCP 35s
3 部署HPA
创建pc-hpa.yaml文件，内容如下：
1 2 3 4 5 6 7 8 9 10 11 12 13 apiVersion: autoscaling/v1 kind: HorizontalPodAutoscaler metadata: name: pc-hpa namespace: dev spec: minReplicas: 1 maxReplicas: 10 targetCPUUtilizationPercentage: 3 scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: nginx
1 2 3 4 5 6 7 8 # 创建hpa [root@k8s-master01 1.8+]# kubectl create -f pc-hpa.yaml horizontalpodautoscaler.autoscaling/pc-hpa created # 查看hpa [root@k8s-master01 1.8+]# kubectl get hpa -n dev NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE pc-hpa Deployment/nginx 0%/3% 1 10 1 62s
4 测试
使用压测工具对service地址192.168.5.4:31830进行压测，然后通过控制台查看hpa和pod的变化
hpa变化
1 2 3 4 5 6 7 8 9 10 11 [root@k8s-master01 ~]# kubectl get hpa -n dev -w NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE pc-hpa Deployment/nginx 0%/3% 1 10 1 4m11s pc-hpa Deployment/nginx 0%/3% 1 10 1 5m19s pc-hpa Deployment/nginx 22%/3% 1 10 1 6m50s pc-hpa Deployment/nginx 22%/3% 1 10 4 7m5s pc-hpa Deployment/nginx 22%/3% 1 10 8 7m21s pc-hpa Deployment/nginx 6%/3% 1 10 8 7m51s pc-hpa Deployment/nginx 0%/3% 1 10 8 9m6s pc-hpa Deployment/nginx 0%/3% 1 10 8 13m pc-hpa Deployment/nginx 0%/3% 1 10 1 14m
deployment变化
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 [root@k8s-master01 ~]# kubectl get deployment -n dev -w NAME READY UP-TO-DATE AVAILABLE AGE nginx 1/1 1 1 11m nginx 1/4 1 1 13m nginx 1/4 1 1 13m nginx 1/4 1 1 13m nginx 1/4 4 1 13m nginx 1/8 4 1 14m nginx 1/8 4 1 14m nginx 1/8 4 1 14m nginx 1/8 8 1 14m nginx 2/8 8 2 14m nginx 3/8 8 3 14m nginx 4/8 8 4 14m nginx 5/8 8 5 14m nginx 6/8 8 6 14m nginx 7/8 8 7 14m nginx 8/8 8 8 15m nginx 8/1 8 8 20m nginx 8/1 8 8 20m nginx 1/1 1 1 20m
pod变化
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 [root@k8s-master01 ~]# kubectl get pods -n dev -w NAME READY STATUS RESTARTS AGE nginx-7df9756ccc-bh8dr 1/1 Running 0 11m nginx-7df9756ccc-cpgrv 0/1 Pending 0 0s nginx-7df9756ccc-8zhwk 0/1 Pending 0 0s nginx-7df9756ccc-rr9bn 0/1 Pending 0 0s nginx-7df9756ccc-cpgrv 0/1 ContainerCreating 0 0s nginx-7df9756ccc-8zhwk 0/1 ContainerCreating 0 0s nginx-7df9756ccc-rr9bn 0/1 ContainerCreating 0 0s nginx-7df9756ccc-m9gsj 0/1 Pending 0 0s nginx-7df9756ccc-g56qb 0/1 Pending 0 0s nginx-7df9756ccc-sl9c6 0/1 Pending 0 0s nginx-7df9756ccc-fgst7 0/1 Pending 0 0s nginx-7df9756ccc-g56qb 0/1 ContainerCreating 0 0s nginx-7df9756ccc-m9gsj 0/1 ContainerCreating 0 0s nginx-7df9756ccc-sl9c6 0/1 ContainerCreating 0 0s nginx-7df9756ccc-fgst7 0/1 ContainerCreating 0 0s nginx-7df9756ccc-8zhwk 1/1 Running 0 19s nginx-7df9756ccc-rr9bn 1/1 Running 0 30s nginx-7df9756ccc-m9gsj 1/1 Running 0 21s nginx-7df9756ccc-cpgrv 1/1 Running 0 47s nginx-7df9756ccc-sl9c6 1/1 Running 0 33s nginx-7df9756ccc-g56qb 1/1 Running 0 48s nginx-7df9756ccc-fgst7 1/1 Running 0 66s nginx-7df9756ccc-fgst7 1/1 Terminating 0 6m50s nginx-7df9756ccc-8zhwk 1/1 Terminating 0 7m5s nginx-7df9756ccc-cpgrv 1/1 Terminating 0 7m5s nginx-7df9756ccc-g56qb 1/1 Terminating 0 6m50s nginx-7df9756ccc-rr9bn 1/1 Terminating 0 7m5s nginx-7df9756ccc-m9gsj 1/1 Terminating 0 6m50s nginx-7df9756ccc-sl9c6 1/1 Terminating 0 6m50s
6.5 DaemonSet(DS) DaemonSet类型的控制器可以保证在集群中的每一台（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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 apiVersion: apps/v1 kind: DaemonSet metadata: name: namespace: labels: controller: daemonset spec: revisionHistoryLimit: 3 updateStrategy: type: RollingUpdate rollingUpdate: maxUnavailable: 1 selector: matchLabels: app: nginx-pod matchExpressions: - {key: app , operator: In , values: [nginx-pod ]} template: 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：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # 创建daemonset [root@k8s-master01 ~]# kubectl create -f pc-daemonset.yaml daemonset.apps/pc-daemonset created # 查看daemonset [root@k8s-master01 ~]# kubectl get ds -n dev -o wide NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES pc-daemonset 2 2 2 2 2 24s nginx nginx:1.17.1 # 查看pod,发现在每个Node上都运行一个pod [root@k8s-master01 ~]# kubectl get pods -n dev -o wide NAME READY STATUS RESTARTS AGE IP NODE pc-daemonset-9bck8 1/1 Running 0 37s 10.244.1.43 node1 pc-daemonset-k224w 1/1 Running 0 37s 10.244.2.74 node2 # 删除daemonset [root@k8s-master01 ~]# 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Job创建的pod执行成功结束时，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
Job的资源清单文件：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 apiVersion: batch/v1 kind: Job metadata: name: namespace: labels: controller: job spec: completions: 1 parallelism: 1 activeDeadlineSeconds: 30 backoffLimit: 6 manualSelector: true selector: matchLabels: app: counter-pod matchExpressions: - {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" ]
1 2 3 4 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：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 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" ]
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 # 创建job [root@k8s-master01 ~]# kubectl create -f pc-job.yaml job.batch/pc-job created # 查看job [root@k8s-master01 ~]# kubectl get job -n dev -o wide -w NAME COMPLETIONS DURATION AGE CONTAINERS IMAGES SELECTOR pc-job 0/1 21s 21s counter busybox:1.30 app=counter-pod pc-job 1/1 31s 79s counter busybox:1.30 app=counter-pod # 通过观察pod状态可以看到，pod在运行完毕任务后，就会变成Completed状态 [root@k8s-master01 ~]# kubectl get pods -n dev -w NAME READY STATUS RESTARTS AGE pc-job-rxg96 1/1 Running 0 29s pc-job-rxg96 0/1 Completed 0 33s # 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 # parallelism: 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 [root@k8s-master01 ~]# kubectl get pods -n dev -w NAME READY STATUS RESTARTS AGE pc-job-684ft 1/1 Running 0 5s pc-job-jhj49 1/1 Running 0 5s pc-job-pfcvh 1/1 Running 0 5s pc-job-684ft 0/1 Completed 0 11s pc-job-v7rhr 0/1 Pending 0 0s pc-job-v7rhr 0/1 Pending 0 0s pc-job-v7rhr 0/1 ContainerCreating 0 0s pc-job-jhj49 0/1 Completed 0 11s pc-job-fhwf7 0/1 Pending 0 0s pc-job-fhwf7 0/1 Pending 0 0s pc-job-pfcvh 0/1 Completed 0 11s pc-job-5vg2j 0/1 Pending 0 0s pc-job-fhwf7 0/1 ContainerCreating 0 0s pc-job-5vg2j 0/1 Pending 0 0s pc-job-5vg2j 0/1 ContainerCreating 0 0s pc-job-fhwf7 1/1 Running 0 2s pc-job-v7rhr 1/1 Running 0 2s pc-job-5vg2j 1/1 Running 0 3s pc-job-fhwf7 0/1 Completed 0 12s pc-job-v7rhr 0/1 Completed 0 12s pc-job-5vg2j 0/1 Completed 0 12s # 删除job [root@k8s-master01 ~]# 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：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 apiVersion: batch/v1beta1 kind: CronJob metadata: name: namespace: labels: controller: cronjob spec: schedule: concurrencyPolicy: failedJobHistoryLimit: successfulJobHistoryLimit: startingDeadlineSeconds: jobTemplate: 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 20;done" ]
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 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 0 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 0 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-cronjob.yaml，内容如下：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 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" ]
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 # 创建cronjob [root@k8s-master01 ~]# kubectl create -f pc-cronjob.yaml cronjob.batch/pc-cronjob created # 查看cronjob [root@k8s-master01 ~]# kubectl get cronjobs -n dev NAME SCHEDULE SUSPEND ACTIVE LAST SCHEDULE AGE pc-cronjob */1 * * * * False 0 <none> 6s # 查看job [root@k8s-master01 ~]# kubectl get jobs -n dev NAME COMPLETIONS DURATION AGE pc-cronjob-1592587800 1/1 28s 3m26s pc-cronjob-1592587860 1/1 28s 2m26s pc-cronjob-1592587920 1/1 28s 86s # 查看pod [root@k8s-master01 ~]# kubectl get pods -n dev pc-cronjob-1592587800-x4tsm 0/1 Completed 0 2m24s pc-cronjob-1592587860-r5gv4 0/1 Completed 0 84s pc-cronjob-1592587920-9dxxq 1/1 Running 0 24s # 删除cronjob [root@k8s-master01 ~]# kubectl delete -f pc-cronjob.yaml cronjob.batch "pc-cronjob" deleted
