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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
ReplicaSet(RS)
RS概述
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：
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
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，里面其实就是专栏pod详解学的定义
创建与删除RS
创建rs-controller.yaml文件，内容如下：
apiVersion: apps/v1
kind: ReplicaSet
metadata:
name: rs-controller
namespace: dev
spec:
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx
创建RS
# 创建rs
[root@master k8sYamlForCSDN]# kubectl apply -f rs-controller.yaml
replicaset.apps/rs-controller 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 k8sYamlForCSDN]# kubectl get rs rs-controller -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
rs-controller 3 3 3 75s nginx nginx 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@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
rs-controller-rr598 1/1 Running 0 47s
rs-controller-tmfd7 1/1 Running 0 47s
rs-controller-xgrst 1/1 Running 0 47s
删除RS
# 只推荐第一种，第二三种做了解即可
# 1. 使用yaml直接删除(推荐)
[root@master k8sYamlForCSDN]# kubectl delete -f rs-controller.yaml
replicaset.apps "rs-controller" deleted
# 2. 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 k8sYamlForCSDN]# kubectl delete rs rs-controller -n dev
replicaset.apps "rs-controller" deleted
[root@master k8sYamlForCSDN]# kubectl get pod -n dev
No resources found in dev namespace.
# 3. 如果希望只删除RS对象，而留下正在运行的pod，需要在kubectl delete命令的时候增加--cascade=orphan选项
[root@master k8sYamlForCSDN]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
rs-controller 6 6 3 15s
[root@master k8sYamlForCSDN]# kubectl delete rs rs-controller -n dev --cascade=orphan
replicaset.apps "rs-controller" deleted
[root@master k8sYamlForCSDN]# kubectl get rs -n dev
No resources found in dev namespace.
[root@master k8sYamlForCSDN]# kubectl get pod -n dev
NAME READY STATUS RESTARTS AGE
rs-controller-9h5zd 1/1 Running 0 38s
rs-controller-jk4h6 1/1 Running 0 38s
rs-controller-lmlwn 1/1 Running 0 38s
扩缩容
# 第一种方式
# 修改yaml文件，把replicas=3改成1，重新apply，此时rs会更新
[root@master k8sYamlForCSDN]# kubectl apply -f rs-controller.yaml
replicaset.apps/rs-controller created
[root@master k8sYamlForCSDN]# vi rs-controller.yaml
[root@master k8sYamlForCSDN]# kubectl apply -f rs-controller.yaml
replicaset.apps/rs-controller configured
# 命令运行完毕，立即查看，发现已经有2个开始准备退出了
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
rs-controller-h654s 0/1 Terminating 0 18s
rs-controller-l67tb 0/1 Terminating 0 18s
rs-controller-s4g7b 1/1 Running 0 18s
# 稍等片刻，就只剩下1个了
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
rs-controller-s4g7b 1/1 Running 0 81s
# 第二种方式
# 编辑rs的副本数量，修改spec:replicas: 2即可，注意用这种方法，yaml文件中的数量是不改变的
[root@master k8sYamlForCSDN]# kubectl edit rs rs-controller -n dev
replicaset.apps/rs-controller edited
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
rs-controller-9mf77 1/1 Running 0 26s
rs-controller-s4g7b 1/1 Running 0 3m23s
# 第三种方式
# 使用scale命令实现，后面--replicas=n直接指定目标数量即可，注意用这种方法，yaml文件中的数量是不改变的
[root@master k8sYamlForCSDN]# kubectl scale rs rs-controller -n dev --replicas=3
replicaset.apps/rs-controller scaled
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
rs-controller-7d9wf 0/1 ContainerCreating 0 6s
rs-controller-9mf77 1/1 Running 0 119s
rs-controller-s4g7b 1/1 Running 0 4m56s
镜像升级
# 第一种方式(推荐)
# 修改yaml文件，把image=nginx改成nginx:1.17.1，重新apply，此时rs会更新
[root@master k8sYamlForCSDN]# vi rs-controller.yaml
[root@master k8sYamlForCSDN]# kubectl apply -f rs-controller.yaml
replicaset.apps/rs-controller configured
[root@master k8sYamlForCSDN]# kubectl get rs -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES
rs-controller 1 1 1 6m42s nginx nginx:1.17.1
# 第二种方式
# 编辑rs的image，修改imagenginx:1.17.2即可，注意用这种方法，yaml文件中的配置是不改变的
[root@master k8sYamlForCSDN]# kubectl edit rs rs-controller -n dev
replicaset.apps/rs-controller edited
[root@master k8sYamlForCSDN]# kubectl get rs -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES
rs-controller 1 1 1 8m41s nginx nginx:1.17.2
# 第三种方式，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 k8sYamlForCSDN]# kubectl set image rs rs-controller -n dev nginx=nginx:1.17.3
replicaset.apps/rs-controller image updated
[root@master k8sYamlForCSDN]# kubectl get rs -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES
rs-controller 1 1 1 9m50s nginx nginx:1.17.3
Deployment(Deploy)
Deploy概述
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。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
- 支持滚动升级和回滚版本
Deployment的资源清单文件：
apiVersion: apps/v1 # 版本号
kind: Deployment # 类型
metadata: # 元数据
name: # Deploy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（rs，用于版本回退）
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: # 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
ports:
- containerPort: 80
创建deployment
创建deploy-controller.yaml，内容如下：
apiVersion: apps/v1
kind: Deployment
metadata:
name: deploy-controller
namespace: dev
spec:
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx
# 创建deployment
[root@master k8sYamlForCSDN]# kubectl apply -f deploy-controller.yaml
deployment.apps/deploy-controller 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 k8sYamlForCSDN]# kubectl get deploy deploy-controller -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deploy-controller 3/3 3 3 40s
[root@master k8sYamlForCSDN]# kubectl get deployments.apps -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deploy-controller 3/3 3 3 47s
# 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 k8sYamlForCSDN]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
deploy-controller-7f87645cd8 3 3 3 65s
# 查看pod
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
deploy-controller-7f87645cd8-28vcs 1/1 Running 0 73s
deploy-controller-7f87645cd8-dgnsb 1/1 Running 0 73s
deploy-controller-7f87645cd8-qfczb 1/1 Running 0 73s
扩缩容
# 第一种方式
# 修改yaml文件，把replicas=3改成2，重新apply，此时rs会更新
[root@master k8sYamlForCSDN]# vi deploy-controller.yaml
[root@master k8sYamlForCSDN]# kubectl apply -f deploy-controller.yaml
deployment.apps/deploy-controller configured
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
deploy-controller-7f87645cd8-dgnsb 1/1 Running 0 5m53s
deploy-controller-7f87645cd8-qfczb 1/1 Running 0 5m53s
# 第二种方式
# 编辑rs的副本数量，修改spec:replicas: 1即可，注意用这种方法，yaml文件中的数量是不改变的
[root@master k8sYamlForCSDN]# kubectl edit deploy deploy-controller -n dev
deployment.apps/deploy-controller edited
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
deploy-controller-7f87645cd8-qfczb 1/1 Running 0 7m56s
# 第三种方式
# 使用scale命令实现，后面--replicas=n直接指定目标数量即可，注意用这种方法，yaml文件中的数量是不改变的
[root@master k8sYamlForCSDN]# kubectl scale deploy deploy-controller -n dev --replicas=3
deployment.apps/deploy-controller scaled
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
deploy-controller-7f87645cd8-2dwpp 0/1 ContainerCreating 0 1s
deploy-controller-7f87645cd8-bb9xt 0/1 ContainerCreating 0 1s
deploy-controller-7f87645cd8-qfczb 1/1 Running 0 8m45s
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:
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:在创建出新的Pod之前会先杀掉所有已存在的Pod
- 编辑deploy-controller.yaml,在spec节点下添加更新策略
apiVersion: apps/v1
kind: Deployment
metadata:
name: deploy-controller
namespace: dev
spec:
strategy: # 策略
type: Recreate # 重建更新
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx
- 创建deploy进行验证
# 变更镜像
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
deploy-controller-7f87645cd8-925wr 1/1 Running 0 35s 10.244.2.65 node2 <none> <none>
deploy-controller-7f87645cd8-l4f82 1/1 Running 0 35s 10.244.2.64 node2 <none> <none>
deploy-controller-7f87645cd8-ljwfx 1/1 Running 0 35s 10.244.1.44 node1 <none> <none>
[root@master k8sYamlForCSDN]# kubectl set image deploy deploy-controller -n dev nginx=nginx:1.17.1
deployment.apps/deploy-controller image updated
# 观察升级过程
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -o wide -w
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
deploy-controller-7f87645cd8-925wr 1/1 Running 0 39s 10.244.2.65 node2 <none> <none>
deploy-controller-7f87645cd8-l4f82 1/1 Running 0 39s 10.244.2.64 node2 <none> <none>
deploy-controller-7f87645cd8-ljwfx 1/1 Running 0 39s 10.244.1.44 node1 <none> <none>
deploy-controller-7f87645cd8-925wr 1/1 Terminating 0 49s 10.244.2.65 node2 <none> <none>
deploy-controller-7f87645cd8-l4f82 1/1 Terminating 0 49s 10.244.2.64 node2 <none> <none>
deploy-controller-7f87645cd8-ljwfx 1/1 Terminating 0 49s 10.244.1.44 node1 <none> <none>
deploy-controller-6f44b7b85d-whjxq 0/1 Pending 0 0s <none> <none> <none> <none>
deploy-controller-6f44b7b85d-4nvzz 0/1 Pending 0 0s <none> <none> <none> <none>
deploy-controller-6f44b7b85d-hjk7x 0/1 Pending 0 0s <none> <none> <none> <none>
deploy-controller-6f44b7b85d-whjxq 0/1 ContainerCreating 0 0s <none> node1 <none> <none>
deploy-controller-6f44b7b85d-hjk7x 0/1 ContainerCreating 0 0s <none> node1 <none> <none>
deploy-controller-6f44b7b85d-4nvzz 0/1 ContainerCreating 0 0s <none> node2 <none> <none>
deploy-controller-6f44b7b85d-4nvzz 1/1 Running 0 2s 10.244.2.66 node2 <none> <none>
deploy-controller-6f44b7b85d-hjk7x 1/1 Running 0 16s 10.244.1.46 node1 <none> <none>
deploy-controller-6f44b7b85d-whjxq 1/1 Running 0 31s 10.244.1.45 node1 <none> <none>
滚动更新: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
- 编辑deploy-controller.yaml,在spec节点下添加更新策略
apiVersion: apps/v1
kind: Deployment
metadata:
name: deploy-controller
namespace: dev
spec:
strategy: # 策略
type: RollingUpdate # 滚动更新
rollingUpdate:
maxSurge: 25%
maxUnavailable: 25%
replicas: 3
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx
- 创建deploy进行验证
# 创建deploy
[root@master k8sYamlForCSDN]# kubectl apply -f deploy-controller.yaml
deployment.apps/deploy-controller configured
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
deploy-controller-7f87645cd8-4b2rf 1/1 Running 0 74s
deploy-controller-7f87645cd8-7tqnr 1/1 Running 0 57s
deploy-controller-7f87645cd8-cgmft 1/1 Running 0 55s
# 更新镜像
[root@master k8sYamlForCSDN]# kubectl set image deploy deploy-controller -n dev nginx=nginx:1.17.1
deployment.apps/deploy-controller image updated
# 滚动更新，不是先全杀掉在启动，而是一个杀掉，启动一个，滚动的形式
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -o wide -w
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
deploy-controller-7f87645cd8-4b2rf 1/1 Running 0 86s 10.244.2.67 node2 <none> <none>
deploy-controller-7f87645cd8-7tqnr 1/1 Running 0 69s 10.244.1.47 node1 <none> <none>
deploy-controller-7f87645cd8-cgmft 1/1 Running 0 67s 10.244.1.48 node1 <none> <none>
deploy-controller-6f44b7b85d-xckc9 0/1 Pending 0 0s <none> <none> <none> <none>
deploy-controller-6f44b7b85d-xckc9 0/1 ContainerCreating 0 0s <none> node2 <none> <none>
deploy-controller-6f44b7b85d-xckc9 1/1 Running 0 16s 10.244.2.68 node2 <none> <none>
deploy-controller-7f87645cd8-7tqnr 1/1 Terminating 0 92s 10.244.1.47 node1 <none> <none>
deploy-controller-6f44b7b85d-mxm5q 0/1 Pending 0 0s <none> node1 <none> <none>
deploy-controller-6f44b7b85d-mxm5q 0/1 ContainerCreating 0 0s <none> node1 <none> <none>
deploy-controller-6f44b7b85d-mxm5q 1/1 Running 0 17s 10.244.1.49 node1 <none> <none>
deploy-controller-7f87645cd8-7tqnr 0/1 Terminating 0 93s 10.244.1.47 node1 <none> <none>
deploy-controller-7f87645cd8-cgmft 1/1 Terminating 0 107s 10.244.1.48 node1 <none> <none>
deploy-controller-6f44b7b85d-ftztf 0/1 Pending 0 0s <none> <none> <none> <none>
deploy-controller-6f44b7b85d-ftztf 0/1 ContainerCreating 0 0s <none> node2 <none> <none>
deploy-controller-7f87645cd8-cgmft 0/1 Terminating 0 108s 10.244.1.48 node1 <none> <none>
deploy-controller-6f44b7b85d-ftztf 1/1 Running 0 17s 10.244.2.69 node2 <none> <none>
deploy-controller-7f87645cd8-4b2rf 1/1 Terminating 0 2m23s 10.244.2.67 node2 <none> <none>
# 至此，新版本的pod创建完毕，旧版本的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：
版本回退
镜像更新中rs的变化:
# 创建deploy，并添加一个参数记录版本
[root@master k8sYamlForCSDN]# kubectl apply -f deploy-controller.yaml --record
Flag --record has been deprecated, --record will be removed in the future
deployment.apps/deploy-controller created
# 更新镜像
[root@master k8sYamlForCSDN]# kubectl set image deploy deploy-controller -n dev nginx=nginx:1.17.1
deployment.apps/deploy-controller image updated
# 查看RS
# 发现原来的RS中的pod被删除了，又重新创建了新的RS
[root@master k8sYamlForCSDN]# kubectl get rs -n dev -w
NAME DESIRED CURRENT READY AGE
deploy-controller-7f87645cd8 3 3 1 11s
...
deploy-controller-6f44b7b85d 3 3 3 35s
...
deploy-controller-7f87645cd8 0 0 0 90s
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 k8sYamlForCSDN]# kubectl rollout status deployment deploy-controller -n dev
deployment "deploy-controller" successfully rolled out
# 查看升级历史记录
[root@master k8sYamlForCSDN]# kubectl rollout history deployment deploy-controller -n dev
deployment.apps/deploy-controller
REVISION CHANGE-CAUSE
1 kubectl apply --filename=deploy-controller.yaml --record=true
2 kubectl apply --filename=deploy-controller.yaml --record=true
# 升级镜像
[root@master k8sYamlForCSDN]# kubectl set image deploy deploy-controller -n dev nginx=nginx:1.17.2
deployment.apps/deploy-controller image updated
# 查看当前升级版本的状态
[root@master k8sYamlForCSDN]# kubectl rollout status deployment deploy-controller -n dev
Waiting for deployment "deploy-controller" rollout to finish: 1 out of 3 new replicas have been updated...
Waiting for deployment "deploy-controller" rollout to finish: 2 out of 3 new replicas have been updated...
Waiting for deployment "deploy-controller" rollout to finish: 1 old replicas are pending termination...
deployment "deploy-controller" successfully rolled out
# 查看升级历史记录
# 可以发现有三次版本记录，说明完成过两次升级
[root@master k8sYamlForCSDN]# kubectl rollout history deployment deploy-controller -n dev
deployment.apps/deploy-controller
REVISION CHANGE-CAUSE
1 kubectl apply --filename=deploy-controller.yaml --record=true
2 kubectl apply --filename=deploy-controller.yaml --record=true
3 kubectl apply --filename=deploy-controller.yaml --record=true
# 版本回滚
# 这里直接使用--to-revision=1回滚到了1版本(nginx)， 如果省略这个选项，就是回退到上个版本，就是2版本(nginx1.17.1),目前是3版本（1.17.2）
[root@master k8sYamlForCSDN]# kubectl rollout undo deployment deploy-controller -n dev --to-revision=1
deployment.apps/deploy-controller rolled back
# 查看发现，通过nginx镜像版本可以发现到了第一版
[root@master k8sYamlForCSDN]# kubectl get deploy -n dev -o wide
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
deploy-controller 3/3 2 3 10m nginx nginx app=nginx-pod
# 查看rs，发现第三个rs中有3个pod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 k8sYamlForCSDN]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
deploy-controller-67db8df7f5 0 0 0 7m36s
deploy-controller-6f44b7b85d 0 0 0 12m
deploy-controller-7f87645cd8 3 3 3 13m
金丝雀发布
eployment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。
# 更新deployment的版本，并配置暂停deployment
[root@master k8sYamlForCSDN]# kubectl set image deploy deploy-controller -n dev nginx=nginx:1.17.1 && kubectl rollout pause deploy deploy-controller -n dev
deployment.apps/deploy-controller image updated
deployment.apps/deploy-controller paused
#观察更新状态
# 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@master k8sYamlForCSDN]# kubectl get rs -n dev
NAME DESIRED CURRENT READY AGE
deploy-controller-67db8df7f5 0 0 0 19m
deploy-controller-6f44b7b85d 1 1 1 24m
deploy-controller-7f87645cd8 3 3 3 25m
[root@master k8sYamlForCSDN]# kubectl rollout status deploy deploy-controller -n dev
Waiting for deployment "deploy-controller" 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 k8sYamlForCSDN]# kubectl rollout resume deploy deploy-controller -n dev
deployment.apps/deploy-controller resumed
# 查看最后的更新情况
[root@master k8sYamlForCSDN]# kubectl get rs -n dev -o wide
NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR
deploy-controller-67db8df7f5 0 0 0 23m nginx nginx:1.17.2
deploy-controller-6f44b7b85d 3 3 3 28m nginx nginx:1.17.1
deploy-controller-7f87645cd8 0 0 0 29m nginx nginx
[root@master k8sYamlForCSDN]# kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
deploy-controller-6f44b7b85d-7gfp7 1/1 Running 0 2m13s
deploy-controller-6f44b7b85d-b6n2b 1/1 Running 0 5m30s
deploy-controller-6f44b7b85d-cg4vq 1/1 Running 0 116s
删除Deployment
# 删除deployment，其下的rs和pod也将被删除
[root@master k8sYamlForCSDN]# kubectl delete -f deploy-controller.yaml
deployment.apps "deploy-controller" deleted
Horizontal Pod Autoscaler(HPA)
HPA概述
我们已经可以实现通过手工执行kubectl scale命令或者edit和改yaml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。
1.安装metrics-server
metrics-server可以用来收集集群中的资源使用情况
# 从一个能访问外网的地方下载一个yaml文件
https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/high-availability.yaml
# 修改yaml的参数
# 找到这个 -> image: k8s.gcr.io/metrics-server/metrics-server:v0.6.1
# 替换为 -> image: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-server:v0.6.1
# 再增加几个参数
hostNetwork: true
args:
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP,Hostname,InternalDNS,ExternalDNS,ExternalIP
# 如图
# 将编辑好的yaml文件复制到linux中
[root@master k8sYamlForCSDN]# vi components.yaml
# 运行
[root@master k8sYamlForCSDN]# kubectl apply -f 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
apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created
# 查看pod运行情况
[root@master k8sYamlForCSDN]# kubectl get pods -n kube-system
NAME READY STATUS RESTARTS AGE
......
metrics-server-77ccdd66cf-h7279 1/1 Running 0 7m53s
# 使用kubectl top nodes 查看资源使用情况
[root@master k8sYamlForCSDN]# kubectl top nodes
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
master 84m 4% 1116Mi 64%
node1 21m 1% 646Mi 37%
node2 16m 0% 466Mi 27%
[root@master k8sYamlForCSDN]# kubectl top pods -n kube-system
NAME CPU(cores) MEMORY(bytes)
coredns-64897985d-7bx2c 2m 20Mi
coredns-64897985d-w5c4q 1m 17Mi
etcd-master 11m 126Mi
kube-apiserver-master 31m 306Mi
kube-controller-manager-master 13m 84Mi
kube-flannel-ds-78vrj 1m 20Mi
kube-flannel-ds-lv5jf 2m 19Mi
kube-flannel-ds-tk9c6 2m 20Mi
kube-proxy-vxflz 1m 30Mi
kube-proxy-w886d 1m 20Mi
kube-proxy-xb7kp 1m 19Mi
kube-scheduler-master 2m 36Mi
metrics-server-77ccdd66cf-h7279 4m 18Mi
# 至此,metrics-server安装完成
我这里提供一份编写博文时用的并且已经修改好的yaml文件，2022年3月2日22点38分
apiVersion: v1
kind: ServiceAccount
metadata:
labels:
k8s-app: metrics-server
name: metrics-server
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
labels:
k8s-app: metrics-server
rbac.authorization.k8s.io/aggregate-to-admin: "true"
rbac.authorization.k8s.io/aggregate-to-edit: "true"
rbac.authorization.k8s.io/aggregate-to-view: "true"
name: system:aggregated-metrics-reader
rules:
- apiGroups:
- metrics.k8s.io
resources:
- pods
- nodes
verbs:
- get
- list
- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
labels:
k8s-app: metrics-server
name: system:metrics-server
rules:
- apiGroups:
- ""
resources:
- nodes/metrics
verbs:
- get
- apiGroups:
- ""
resources:
- pods
- nodes
verbs:
- get
- list
- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
labels:
k8s-app: metrics-server
name: metrics-server-auth-reader
namespace: kube-system
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
labels:
k8s-app: metrics-server
name: metrics-server:system:auth-delegator
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:auth-delegator
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
labels:
k8s-app: metrics-server
name: system:metrics-server
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:metrics-server
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
---
apiVersion: v1
kind: Service
metadata:
labels:
k8s-app: metrics-server
name: metrics-server
namespace: kube-system
spec:
ports:
- name: https
port: 443
protocol: TCP
targetPort: https
selector:
k8s-app: metrics-server
---
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
k8s-app: metrics-server
name: metrics-server
namespace: kube-system
spec:
selector:
matchLabels:
k8s-app: metrics-server
strategy:
rollingUpdate:
maxUnavailable: 0
template:
metadata:
labels:
k8s-app: metrics-server
spec:
hostNetwork: true
containers:
- args:
- --cert-dir=/tmp
- --secure-port=4443
- --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname
- --kubelet-use-node-status-port
- --metric-resolution=15s
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP,Hostname,InternalDNS,ExternalDNS,ExternalIP
# image: k8s.gcr.io/metrics-server/metrics-server:v0.6.1
image: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-server:v0.6.1
imagePullPolicy: IfNotPresent
livenessProbe:
failureThreshold: 3
httpGet:
path: /livez
port: https
scheme: HTTPS
periodSeconds: 10
name: metrics-server
ports:
- containerPort: 4443
name: https
protocol: TCP
readinessProbe:
failureThreshold: 3
httpGet:
path: /readyz
port: https
scheme: HTTPS
initialDelaySeconds: 20
periodSeconds: 10
resources:
requests:
cpu: 100m
memory: 200Mi
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
runAsNonRoot: true
runAsUser: 1000
volumeMounts:
- mountPath: /tmp
name: tmp-dir
nodeSelector:
kubernetes.io/os: linux
priorityClassName: system-cluster-critical
serviceAccountName: metrics-server
volumes:
- emptyDir: {}
name: tmp-dir
---
apiVersion: apiregistration.k8s.io/v1
kind: APIService
metadata:
labels:
k8s-app: metrics-server
name: v1beta1.metrics.k8s.io
spec:
group: metrics.k8s.io
groupPriorityMinimum: 100
insecureSkipTLSVerify: true
service:
name: metrics-server
namespace: kube-system
version: v1beta1
versionPriority: 100
2.准备deployment和servie
准备deployment和servie的yaml文件
apiVersion: apps/v1
kind: Deployment
metadata:
name: deploy-nginx
namespace: dev
spec:
selector:
matchLabels:
run: "nginx"
template:
metadata:
labels:
run: "nginx"
spec:
containers:
- name: nginx
image: nginx
ports:
- containerPort: 80
protocol: TCP
---
apiVersion: v1
kind: Service
metadata:
name: svc-deploy-nginx
namespace: dev
spec:
type: NodePort
clusterIP: 10.109.68.72
selector:
run: "nginx"
ports:
- port: 6872
targetPort: 80
protocol: TCP
[root@master k8sYamlForCSDN]# vi svc-deploy.yaml
# 创建
[root@master k8sYamlForCSDN]# kubectl apply -f svc-deploy.yaml
deployment.apps/deploy-nginx created
# 查看
[root@master k8sYamlForCSDN]# kubectl get deploy,pods,svc -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/deploy-nginx 0/1 1 0 3s
NAME READY STATUS RESTARTS AGE
pod/deploy-nginx-69ccc6c65-mbhds 0/1 ContainerCreating 0 3s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/svc-deploy-nginx NodePort 10.109.68.72 <none> 6872:30709/TCP 3s
[root@master k8sYamlForCSDN]# kubectl get deploy,pods,svc -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/deploy-nginx 1/1 1 1 62s
NAME READY STATUS RESTARTS AGE
pod/deploy-nginx-69ccc6c65-mbhds 1/1 Running 0 62s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/svc-deploy-nginx NodePort 10.109.68.72 <none> 6872:30709/TCP 62s
3.部署HPA
创建hpa.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: 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3%
scaleTargetRef: # 指定要控制的nginx信息
apiVersion: apps/v1
kind: Deployment
name: deploy-nginx
[root@master k8sYamlForCSDN]# vi hpa.yaml
# 创建hpa
[root@master k8sYamlForCSDN]# kubectl apply -f hpa.yaml
horizontalpodautoscaler.autoscaling/hpa created
# 查看hpa，发现是unknow，为什么呢？
[root@master k8sYamlForCSDN]# kubectl get hpa -n dev
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa Deployment/deploy-nginx <unknown>/3% 1 10 1 21s
好，现在启动，压测，发现没有自动伸缩，怎么回事呢？我们查看hpa看看
[root@master k8sYamlForCSDN]# kubectl describe hpa -n dev
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning FailedComputeMetricsReplicas 7m5s (x12 over 9m50s) horizontal-pod-autoscaler invalid metrics (1 invalid out of 1), first error is: failed to get cpu utilization: missing request for cpu
Warning FailedGetResourceMetric 4m50s (x21 over 9m50s) horizontal-pod-autoscaler failed to get cpu utilization: missing request for cpu
==这是因为我们上面创建的 Pod 对象没有添加 request 资源声明，这样导致 HPA 读取不到 CPU 指标信息，所以如果要想让 HPA 生效，对应的 Pod 资源必须添加 requests 资源声明==，好，现在我们需要更新之前的deploy的yaml文件
# 其实这里与之前的就加了个resources.cpu资源配额的限制
apiVersion: apps/v1
kind: Deployment
metadata:
name: deploy-nginx
namespace: dev
spec:
selector:
matchLabels:
run: "nginx"
template:
metadata:
labels:
run: "nginx"
spec:
containers:
- name: nginx
image: nginx
ports:
- containerPort: 80
protocol: TCP
resources:
requests:
cpu: 100m
---
apiVersion: v1
kind: Service
metadata:
name: svc-deploy-nginx
namespace: dev
spec:
type: NodePort
clusterIP: 10.109.68.72
selector:
run: "nginx"
ports:
- port: 6872
targetPort: 80
protocol: TCP
# 修改完后重新启动
[root@master k8sYamlForCSDN]# kubectl apply -f svc-deploy.yaml
deployment.apps/deploy-nginx created
service/svc-deploy-nginx created
[root@master k8sYamlForCSDN]# kubectl apply -f hpa.yaml
horizontalpodautoscaler.autoscaling/hpa created
[root@master k8sYamlForCSDN]# kubectl get svc -n dev -o wide
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
service/svc-deploy-nginx NodePort 10.109.68.72 <none> 6872:30627/TCP 3m16s run=nginx
[root@master k8sYamlForCSDN]# kubectl get hpa -n dev -w
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa Deployment/deploy-nginx 0%/3% 1 10 1 75s
4.测试
使用压测工具对service地址192.168.109.100:30627进行压测，然后通过控制台查看hpa和pod的变化
# deployment变化
[root@master k8sYamlForCSDN]# kubectl get deploy -n dev -w
NAME READY UP-TO-DATE AVAILABLE AGE
deploy-nginx 8/8 8 8 5m9s
deploy-nginx 8/10 8 8 7m4s
deploy-nginx 8/10 8 8 7m4s
deploy-nginx 8/10 8 8 7m4s
deploy-nginx 8/10 10 8 7m4s
deploy-nginx 9/10 10 9 7m7s
deploy-nginx 10/10 10 10 7m21s
......
# hpa变化
[root@master k8sYamlForCSDN]# kubectl get hpa -n dev -w
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa Deployment/deploy-nginx 25%/3% 1 10 2 3m45s
hpa Deployment/deploy-nginx 23%/3% 1 10 4 4m
hpa Deployment/deploy-nginx 7%/3% 1 10 8 4m15s
hpa Deployment/deploy-nginx 12%/3% 1 10 8 4m31s
......
# pod变化
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
deploy-nginx-dbcdd8c84-gc5tk 1/1 Running 0 3m39s
deploy-nginx-dbcdd8c84-zm7gf 1/1 Running 0 6s
deploy-nginx-dbcdd8c84-2whpd 0/1 Pending 0 0s
deploy-nginx-dbcdd8c84-qf62m 0/1 Pending 0 0s
deploy-nginx-dbcdd8c84-2whpd 0/1 Pending 0 0s
deploy-nginx-dbcdd8c84-qf62m 0/1 Pending 0 0s
......
DaemonSet(DS)
DS概述
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node节点时，指定的 Pod 副本也将添加到该节点上
- 当node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: # ds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
ports:
- containerPort: 80
DS使用
创建ds-controller.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
# 创建daemonset
[root@master k8sYamlForCSDN]# kubectl apply -f ds-controller.yaml
daemonset.apps/pc-daemonset created
# 查看daemonset
[root@master k8sYamlForCSDN]# kubectl get ds -n dev -o wide
NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE CONTAINERS IMAGES SELECTOR
pc-daemonset 2 2 2 2 2 <none> 21s nginx nginx app=nginx-pod
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
# 查看pod,发现在每个Node上都运行一个pod
pc-daemonset-kwr9b 1/1 Running 0 96s 10.244.1.68 node1 <none> <none>
pc-daemonset-x4hn9 1/1 Running 0 96s 10.244.2.88 node2 <none> <none>
# 删除daemonset
[root@master k8sYamlForCSDN]# kubectl delete -f ds-controller.yaml
daemonset.apps "pc-daemonset" deleted
Job
Job概述
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：
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","for i 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
Job使用
创建job-controller.yaml，内容如下：
apiVersion: batch/v1
kind: Job
metadata:
name: job-controller
namespace: dev
spec:
manualSelector: true
selector:
matchLabels:
app: counter-pod
template:
metadata:
labels:
app: counter-pod
spec:
restartPolicy: Never
containers:
- name: counter
image: busybox
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 k8sYamlForCSDN]# kubectl apply -f job-controller.yaml
job.batch/job-controller created
# 查看job
[root@master k8sYamlForCSDN]# kubectl get job -n dev -w
NAME COMPLETIONS DURATION AGE
job-controller 0/1 29s 29s
job-controller 1/1 43s 43s
# 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@master k8sYamlForCSDN]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
job-controller-pdv2b 1/1 Running 0 41s
job-controller-pdv2b 0/1 Completed 0 69s
# 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
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
job-controller-cxfph 0/1 Pending 0 0s
job-controller-dblrr 0/1 Pending 0 0s
job-controller-vs66r 0/1 Pending 0 0s
job-controller-cxfph 0/1 ContainerCreating 0 0s
job-controller-dblrr 0/1 ContainerCreating 0 0s
job-controller-vs66r 0/1 ContainerCreating 0 0s
job-controller-cxfph 1/1 Running 0 2s
job-controller-vs66r 1/1 Running 0 3s
job-controller-dblrr 1/1 Running 0 17s
...
CronJob(CJ)
CJ概述
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
failedJobsHistoryLimit: # 为失败的任务执行保留的历史记录数，默认为1
successfulJobsHistoryLimit: # 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 20;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 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，则跳过本次运行
Replace: 替换，取消上一轮正在运行的作业并用新作业替换它
CJ使用
创建cj-controller.yaml，内容如下： 这里设置每分钟执行一次job，一个job执行30秒
apiVersion: batch/v1beta1
kind: CronJob
metadata:
name: cj-controller
namespace: dev
labels:
controller: cronjob
spec:
schedule: "*/1 * * * *"
jobTemplate:
spec:
template:
spec:
restartPolicy: Never
containers:
- name: counter
image: busybox
command: ["bin/sh","-c","for i in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 3;done"]
# 创建cronjob
[root@master k8sYamlForCSDN]# kubectl apply -f cj-controller.yaml
cronjob.batch/cj-controller created
# 查看cronjob
[root@master k8sYamlForCSDN]# kubectl get cj -n dev -w
NAME SCHEDULE SUSPEND ACTIVE LAST SCHEDULE AGE
cj-controller */1 * * * * False 0 <none> 0s
cj-controller */1 * * * * False 1 0s 40s
cj-controller */1 * * * * False 0 43s 83s
cj-controller */1 * * * * False 1 0s 100s
cj-controller */1 * * * * False 0 43s 2m23s
# 查看job
[root@master k8sYamlForCSDN]# kubectl get job -n dev -o wide -w
NAME COMPLETIONS DURATION AGE CONTAINERS IMAGES SELECTOR
cj-controller-27437247 0/1 0s counter busybox controller-uid=12de3ba4-9222-4adf-af7d-958ab57024b8
cj-controller-27437247 0/1 0s 0s counter busybox controller-uid=12de3ba4-9222-4adf-af7d-958ab57024b8
cj-controller-27437247 0/1 43s 43s counter busybox controller-uid=12de3ba4-9222-4adf-af7d-958ab57024b8
cj-controller-27437247 1/1 43s 43s counter busybox controller-uid=12de3ba4-9222-4adf-af7d-958ab57024b8
cj-controller-27437248 0/1 0s counter busybox controller-uid=5fad1afc-d639-47a2-98ce-3980f92e9cdb
cj-controller-27437248 0/1 0s 0s counter busybox controller-uid=5fad1afc-d639-47a2-98ce-3980f92e9cdb
cj-controller-27437248 0/1 43s 43s counter busybox controller-uid=5fad1afc-d639-47a2-98ce-3980f92e9cdb
cj-controller-27437248 1/1 43s 43s counter busybox controller-uid=5fad1afc-d639-47a2-98ce-3980f92e9cdb
# 查看pod
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -w
NAME READY STATUS RESTARTS AGE
cj-controller-27437247-ftbqv 0/1 Pending 0 0s
cj-controller-27437247-ftbqv 0/1 Pending 0 0s
cj-controller-27437247-ftbqv 0/1 ContainerCreating 0 0s
cj-controller-27437247-ftbqv 1/1 Running 0 16s
cj-controller-27437247-ftbqv 0/1 Completed 0 43s
cj-controller-27437247-ftbqv 0/1 Completed 0 43s
cj-controller-27437248-kf5nn 0/1 Pending 0 0s
cj-controller-27437248-kf5nn 0/1 Pending 0 0s
cj-controller-27437248-kf5nn 0/1 ContainerCreating 0 0s
cj-controller-27437248-kf5nn 1/1 Running 0 16s
cj-controller-27437248-kf5nn 0/1 Completed 0 43s
cj-controller-27437248-kf5nn 0/1 Completed 0 43s
# 删除cronjob
[root@master ~]# kubectl delete -f pc-cronjob.yaml
cronjob.batch "pc-cronjob" deleted
StatefulSet
StatefulSet概述
无状态应用：
- 认为Pod都是一样的。
- 没有顺序要求。
- 不用考虑在哪个Node节点上运行。
- 随意进行伸缩和扩展。
有状态应用：
- 有顺序的要求。
- 认为每个Pod都是不一样的。
- 需要考虑在哪个Node节点上运行。
- 需要按照顺序进行伸缩和扩展。
- 让每个Pod都是独立的，保持Pod启动顺序和唯一性。
- StatefulSet是Kubernetes提供的管理有状态应用的负载管理控制器。
- StatefulSet部署需要HeadLinessService（无头服务）。
为什么需要HeadLinessService（无头服务）？
- 在用Deployment时，每一个Pod名称是没有顺序的，是随机字符串，因此是Pod名称是无序的，但是在StatefulSet中要求必须是有序 ，每一个Pod不能被随意取代，Pod重建后pod名称还是一样的。
- 而Pod的IP是变化的，所以是以Pod名称来识别。Pod名称是Pod唯一性的标识符，必须持久稳定有效。这时候要用到无头服务，它可以给每个Pod一个唯一的名称 。
StatefulSet常用来部署RabbitMQ集群、Zookeeper集群、MySQL集群、Eureka集群等。
StatefulSet使用
创建pc-stateful.yaml文件，内容如下：
apiVersion: v1
kind: Service
metadata:
name: service-headliness
namespace: dev
spec:
selector:
app: nginx-pod
clusterIP: None # 将clusterIP设置为None，即可创建headliness Service
type: ClusterIP
ports:
- port: 80 # Service的端口
targetPort: 80 # Pod的端口
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: pc-statefulset
namespace: dev
spec:
replicas: 3
serviceName: service-headliness
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx
ports:
- containerPort: 80
# 创建
[root@master k8sYamlForCSDN]# kubectl apply -f pc-stateful.yaml
service/service-headliness created
statefulset.apps/pc-statefulset created
# 查看
[root@master k8sYamlForCSDN]# kubectl get pods -n dev -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pc-statefulset-0 1/1 Running 0 90s 10.244.2.2 node2 <none> <none>
pc-statefulset-1 1/1 Running 0 69s 10.244.1.77 node1 <none> <none>
pc-statefulset-2 1/1 Running 0 53s 10.244.2.3 node2 <none> <none>
[root@master k8sYamlForCSDN]# kubectl get statefulset -n dev -o wide
NAME READY AGE CONTAINERS IMAGES
pc-statefulset 3/3 100s nginx nginx
# 删除
[root@master k8sYamlForCSDN]# kubectl delete -f pc-stateful.yaml
service "service-headliness" deleted
statefulset.apps "pc-statefulset" deleted
# 查看域名的解析情况
# 首先查找域名服务器的ip地址
[root@master k8sYamlForCSDN]# kubectl exec -it pc-deployment-6d99999569-dxpzt -n dev /bin/sh
# cat /etc/resolv.conf
nameserver 10.96.0.10
search dev.svc.cluster.local svc.cluster.local cluster.local
options ndots:5
# 解析
[root@master k8sYamlForCSDN]# dig @10.96.0.10 service-headliness.dev.svc.cluster.local
...
;; ANSWER SECTION:
service-headliness.dev.svc.cluster.local. 30 IN A 10.244.2.4
service-headliness.dev.svc.cluster.local. 30 IN A 10.244.2.5
service-headliness.dev.svc.cluster.local. 30 IN A 10.244.1.78
Deployment和StatefulSet的区别
- Deployment和StatefulSet的区别：Deployment没有唯一标识而StatefulSet有唯一标识。
- StatefulSet的唯一标识是根据主机名+一定规则生成的。
- StatefulSet的唯一标识是主机名.无头Service名称.命名空间.svc.cluster.local。
StatefulSet的金丝雀发布
StatefulSet支持两种更新策略：OnDelete和RollingUpdate（默认），其中OnDelete表示删除之后才更新，RollingUpdate表示滚动更新。
updateStrategy:
rollingUpdate: # 如果更新的策略是OnDelete，那么rollingUpdate就失效
partition: 2 # 表示从第2个分区开始更新，默认是0
type: RollingUpdate /OnDelete # 滚动更新
示例：pc-statefulset.yaml
apiVersion: v1
kind: Service
metadata:
name: service-headliness
namespace: dev
spec:
selector:
app: nginx-pod
clusterIP: None # 将clusterIP设置为None，即可创建headliness Service
type: ClusterIP
ports:
- port: 80 # Service的端口
targetPort: 80 # Pod的端口
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: pc-statefulset
namespace: dev
spec:
replicas: 3
serviceName: service-headliness
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx
ports:
- containerPort: 80
updateStrategy:
rollingUpdate:
partition: 0
type: RollingUpdate
