BoyChai's Blog - 容器编排引擎 https://blog.boychai.xyz/index.php/tag/%E5%AE%B9%E5%99%A8%E7%BC%96%E6%8E%92%E5%BC%95%E6%93%8E/ Kubernetes-容器编排引擎(资源配额-ResourceQuota) https://blog.boychai.xyz/index.php/archives/45/ 2022-12-17T06:36:00+00:00 ResourceQuota概述当多个团队去共享使用一个Kubernetes集群时,会出现不均匀的资源使用,默认情况下资源先到先得,这个时候可以通过ResourceQuota来对命名空间资源使用总量做限制,从而解决这个问题。使用前提ResourceQuota功能是一个准入控制插件,默认已经启用。检查是否开启ResourceQuota功能的方法如下:[root@master ~]# kubectl -n kube-system get pod|grep apiserver kube-apiserver-master.host.com 1/1 Running 27 (17h ago) 61d [root@master ~]# kubectl -n kube-system exec kube-apiserver-master.host.com -- kube-apiserver -h|grep enable-admission-plugins --admission-control strings Admission is divided into two phases. In the first phase, only mutating admission plugins run. In the second phase, only validating admission plugins run. The names in the below list may represent a validating plugin, a mutating plugin, or both. The order of plugins in which they are passed to this flag does not matter. Comma-delimited list of: AlwaysAdmit, AlwaysDeny, AlwaysPullImages, CertificateApproval, CertificateSigning, CertificateSubjectRestriction, DefaultIngressClass, DefaultStorageClass, DefaultTolerationSeconds, DenyServiceExternalIPs, EventRateLimit, ExtendedResourceToleration, ImagePolicyWebhook, LimitPodHardAntiAffinityTopology, LimitRanger, MutatingAdmissionWebhook, NamespaceAutoProvision, NamespaceExists, NamespaceLifecycle, NodeRestriction, OwnerReferencesPermissionEnforcement, PersistentVolumeClaimResize, PersistentVolumeLabel, PodNodeSelector, PodSecurity, PodTolerationRestriction, Priority, ResourceQuota, RuntimeClass, SecurityContextDeny, ServiceAccount, StorageObjectInUseProtection, TaintNodesByCondition, ValidatingAdmissionWebhook. (DEPRECATED: Use --enable-admission-plugins or --disable-admission-plugins instead. Will be removed in a future version.) --enable-admission-plugins strings admission plugins that should be enabled in addition to default enabled ones (NamespaceLifecycle, LimitRanger, ServiceAccount, TaintNodesByCondition, PodSecurity, Priority, DefaultTolerationSeconds, DefaultStorageClass, StorageObjectInUseProtection, PersistentVolumeClaimResize, RuntimeClass, CertificateApproval, CertificateSigning, CertificateSubjectRestriction, DefaultIngressClass, MutatingAdmissionWebhook, ValidatingAdmissionWebhook, ResourceQuota). Comma-delimited list of admission plugins: AlwaysAdmit, AlwaysDeny, AlwaysPullImages, CertificateApproval, CertificateSigning, CertificateSubjectRestriction, DefaultIngressClass, DefaultStorageClass, DefaultTolerationSeconds, DenyServiceExternalIPs, EventRateLimit, ExtendedResourceToleration, ImagePolicyWebhook, LimitPodHardAntiAffinityTopology, LimitRanger, MutatingAdmissionWebhook, NamespaceAutoProvision, NamespaceExists, NamespaceLifecycle, NodeRestriction, OwnerReferencesPermissionEnforcement, PersistentVolumeClaimResize, PersistentVolumeLabel, PodNodeSelector, PodSecurity, PodTolerationRestriction, Priority, ResourceQuota, RuntimeClass, SecurityContextDeny, ServiceAccount, StorageObjectInUseProtection, TaintNodesByCondition, ValidatingAdmissionWebhook. The order of plugins in this flag does not matter. 在"--enable-admission-plugins"中寻找"ResourceQuota"发现已经开启。支持的资源支持的资源描述limits.cpu/memory所有Pod上限资源配置总量不超过该值 (所有非终止状态的Pod)requests.cpu/memory所有Pod请求资源配置总量不超过该值 (所有非终止状态的Pod)cpu/memory等同于requests.cpu/requests.memoryrequests.storage所有PVC请求容量总和不超过该值persistentvolumeclaims所有PVC数量总和不超过该值\<storage-class-name\>.storageclass.storage.k8s.io/requests.storage所有与\<storage-class-name\>相关的PVC请求容量总和不超过该值\<storage-class-name\>.storageclass.storage.k8s.io/persistentvolumeclaims所有与\<storage-class-name\>相关的PVC数量总和不超过该值pods、 count/deployments.apps、count/statfulsets.apps、count/services(services.loadbalancers、 services.nodeports)count/secrets、 count/configmaps、count/job.batch、count/cronjobs.batch创建资源数量不超过该值资源清单计算资源配额apiVersion: v1 kind: ResourceQuota metadata: name: compute-resources namespace: test spec: hard: requests.cpu: "1" requests.memory: 10Gi limits.cpu: "4" limits.memory: 20Gi存储资源配额apiVersion: v1 kind: ResourceQuota metadata: name: storage-resources namespace: test spec: hard: requests.storage: 10Gi managed-nfs-storage.storageclass.storage.k8s.io/requests.storage: 10Gi"managed-nfs-storage"是动态存储类的名称。对象数量配额apiVersion: v1 kind: ResourceQuota metadata: name: object-counts namespace: test spec: hard: pods: "10" count/deployments.apps: "3" count/services: "3"限制的是个数,命名空间的总数量不能超过该值。配额状态[root@master ~]# kubectl get quota -n test NAME AGE REQUEST LIMIT compute-resources 41m requests.cpu: 0/4, requests.memory: 0/10Gi limits.cpu: 0/6, limits.memory: 0/12Gi object-counts 4m6s count/deployments.apps: 0/3, count/services: 0/3, pods: 0/10 storage-resources 6m16s managed-nfs-storage.storageclass.storage.k8s.io/requests.storage: 0/10Gi, requests.storage: 0/10Gi通过上面的命令可以查看额配资源使用的情况。 Kubernetes-容器编排引擎(Dashboard_v2.6.1-安装) https://blog.boychai.xyz/index.php/archives/33/ 2022-09-07T05:18:12+00:00 DashBoard概述为了提供更丰富的用户体验,kubernetes还开发了一个基于web的用户界面(Dashboard)。用户可以使用Dashboard部署容器化的应用,还可以监控应用的状态,执行故障排查以及管理kubernetes中各种资源。DashBoard部署# 下载DashBoard的部署资源清单 curl -o Dashboard-Deploy.yaml https://raw.githubusercontent.com/kubernetes/dashboard/v2.6.1/aio/deploy/recommended.yaml # 修改Dashboard-Deploy.yaml # 为方便访问,修改如下 # 修改名字为kubernetes-dashboard的Service为NodePod网络模式 kind: Service apiVersion: v1 metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard namespace: kubernetes-dashboard spec: type: NodePort # 新增 ports: - port: 443 targetPort: 8443 nodePort: 30010 # 新增 selector: k8s-app: kubernetes-dashboard # 部署 [root@master yaml]# kubectl create -f Dashboard-Deploy.yaml namespace/kubernetes-dashboard created serviceaccount/kubernetes-dashboard created service/kubernetes-dashboard created secret/kubernetes-dashboard-certs created secret/kubernetes-dashboard-csrf created secret/kubernetes-dashboard-key-holder created configmap/kubernetes-dashboard-settings created role.rbac.authorization.k8s.io/kubernetes-dashboard created clusterrole.rbac.authorization.k8s.io/kubernetes-dashboard created rolebinding.rbac.authorization.k8s.io/kubernetes-dashboard created clusterrolebinding.rbac.authorization.k8s.io/kubernetes-dashboard created deployment.apps/kubernetes-dashboard created service/dashboard-metrics-scraper created deployment.apps/dashboard-metrics-scraper created # 查看kubernetes-dashboard命名空间的资源状态 [root@master yaml]# kubectl get pod,svc -n kubernetes-dashboard NAME READY STATUS RESTARTS AGE pod/dashboard-metrics-scraper-8c47d4b5d-dn44t 1/1 Running 0 16s pod/kubernetes-dashboard-6c75475678-nc75l 1/1 Running 0 16s NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/dashboard-metrics-scraper ClusterIP 10.101.132.8 <none> 8000/TCP 16s service/kubernetes-dashboard NodePort 10.107.180.253 <none> 443:30010/TCP 16sDashBoard使用# 创建账号 [root@master yaml]# kubectl create serviceaccount dashboard-admin -n kubernetes-dashboard serviceaccount/dashboard-admin created # 授权 [root@master yaml]# kubectl create clusterrolebinding dashboard-admin-rb --clusterrole=cluster-admin --serviceaccount=kubernetes-dashboard:dashboard-admin clusterrolebinding.rbac.authorization.k8s.io/dashboard-admin-rb created # 创建账号token # 最好保存一下 [root@master yaml]# kubectl -n kubernetes-dashboard create token dashboard-admin eyJhbGciOiJSUzI1NiIsImtpZCI6Imp0alA1dHU2MXNTa21ab19OTWNLRDBkc0VKWll3QVhYWmMyeGF6MG55ajgifQ.eyJhdWQiOlsiaHR0cHM6Ly9rdWJlcm5ldGVzLmRlZmF1bHQuc3ZjLmNsdXN0ZXIubG9jYWwiXSwiZXhwIjoxNjYyNTMwNzQ4LCJpYXQiOjE2NjI1MjcxNDgsImlzcyI6Imh0dHBzOi8va3ViZXJuZXRlcy5kZWZhdWx0LnN2Yy5jbHVzdGVyLmxvY2FsIiwia3ViZXJuZXRlcy5pbyI6eyJuYW1lc3BhY2UiOiJrdWJlcm5ldGVzLWRhc2hib2FyZCIsInNlcnZpY2VhY2NvdW50Ijp7Im5hbWUiOiJkYXNoYm9hcmQtYWRtaW4iLCJ1aWQiOiI2MGJiMmEwYy1kMTAxLTRjZjItYjhmMC1lMWJiMmYzNzA0MTgifX0sIm5iZiI6MTY2MjUyNzE0OCwic3ViIjoic3lzdGVtOnNlcnZpY2VhY2NvdW50Omt1YmVybmV0ZXMtZGFzaGJvYXJkOmRhc2hib2FyZC1hZG1pbiJ9.mrwKwkGbehwE8EXUbq1hlg5mpQJP7GAY_m0BFj6nJORYbZ2R4ZtC1RxY72RqKZIDVfA1xQIeAQh-p82iYDgwCGUIx6wvPBe9jsTi1kse-2xLkTjW0OPdORaXRjL3_yQUSVJSFVk9cplZYjac8lkKGdHpD6SCuIZYxfPCUvnHLyQRjpGsRExhZeVGl8gqGDXaTkG50CUzSEEXHfYV5oXSxZa9m3UtFuYR9aoYuamr-5KulfmlGd9UO9t_aer_Kd0db1grcq-m2QqpVPSA-5kYrrOoLBOtIawU-u5-IV82UOoer4twq4B-6numtkcakwAOEs1K0qgcJixx_Ak8nQ1tvw访问并登录DashBoard访问地址为https://集群主机:30010登陆时把上面生成的token粘贴进去即可 Kubernetes-容器编排引擎(安全认证简述) https://blog.boychai.xyz/index.php/archives/31/ 2022-09-07T05:16:00+00:00 访问控制概述Kubernetes作为一个分布式集群的管理工具,保证集群的安全性是其一个重要的任务。所谓的安全性其实就是保证对Kubernetes的各种客户端进行认证和鉴权操作。客户端在Kubernetes集群中,客户端通常有两类:User Account:一般是独立于kubernetes之外的其他服务管理的用户账号。Service Account:kubernetes管理的账号,用于为Pod中的服务进程在访问Kubernetes时提供身份标识。认证、授权与准入控制ApiServer是访问及管理资源对象的唯一入口。任何一个请求访问ApiServer,都要经过下面三个流程:Authentication(认证):身份鉴别,只有正确的账号才能够通过认证Authorization(授权): 判断用户是否有权限对访问的资源执行特定的动作Admission Control(准入控制):用于补充授权机制以实现更加精细的访问控制功能。认证方式Kubernetes集群安全的最关键点在于如何识别并认证客户端身份,它提供了3种客户端身份认证方式:HTTP Base认证:通过用户名+密码的方式认证这种认证方式是把“用户名:密码”用BASE64算法进行编码后的字符串放在HTTP请求中的Header Authorization域里发送给服务端。服务端收到后进行解码,获取用户名及密码,然后进行用户身份认证的过程。HTTP Token认证:通过一个Token来识别合法用户这种认证方式是用一个很长的难以被模仿的字符串--Token来表明客户身份的一种方式。每个Token对应一个用户名,当客户端发起API调用请求时,需要在HTTP Header里放入Token,API Server接到Token后会跟服务器中保存的token进行比对,然后进行用户身份认证的过程。HTTPS证书认证:基于CA根证书签名的双向数字证书认证方式这种认证方式是安全性最高的一种方式,但是同时也是操作起来最麻烦的一种方式。证书申请和下发 HTTPS通信双方的服务器向CA机构申请证书,CA机构下发根证书、服务端证书及私钥给申请者客户端和服务端的双向认证 1> 客户端向服务器端发起请求,服务端下发自己的证书给客户端, 客户端接收到证书后,通过私钥解密证书,在证书中获得服务端的公钥, 客户端利用服务器端的公钥认证证书中的信息,如果一致,则认可这个服务器 2> 客户端发送自己的证书给服务器端,服务端接收到证书后,通过私钥解密证书, 在证书中获得客户端的公钥,并用该公钥认证证书信息,确认客户端是否合法服务器端和客户端进行通信 服务器端和客户端协商好加密方案后,客户端会产生一个随机的秘钥并加密,然后发送到服务器端。 服务器端接收这个秘钥后,双方接下来通信的所有内容都通过该随机秘钥加密注意: Kubernetes允许同时配置多种认证方式,只要其中任意一个方式认证通过即可 Kubernetes-容器编排引擎(数据存储) https://blog.boychai.xyz/index.php/archives/30/ 2022-09-06T16:15:30+00:00 数据存储概述容器的生命周期可能很短,会被频繁地创建和销毁。那么容器在销毁时,保存在容器中的数据也会被清除。这种结果对用户来说,在某些情况下是不乐意看到的。为了持久化保存容器的数据,kubernetes引入了Volume的概念。Volume是Pod中能够被多个容器访问的共享目录,它被定义在Pod上,然后被一个Pod里的多个容器挂载到具体的文件目录下,kubernetes通过Volume实现同一个Pod中不同容器之间的数据共享以及数据的持久化存储。Volume的生命容器不与Pod中单个容器的生命周期相关,当容器终止或者重启时,Volume中的数据也不会丢失。数据存储类型简单存储:EmptyDir、HostPath、NFS高级存储:PV、PVC配置存储:ConfigMap、Secret简单存储EmptyDirEmptyDir是最基础的Volume类型,一个EmptyDir就是Host上的一个空目录。​ EmptyDir是在Pod被分配到Node时创建的,它的初始内容为空,并且无须指定宿主机上对应的目录文件,因为kubernetes会自动分配一个目录,当Pod销毁时, EmptyDir中的数据也会被永久删除。 EmptyDir用途如下:临时空间,例如用于某些应用程序运行时所需的临时目录,且无须永久保留一个容器需要从另一个容器中获取数据的目录(多容器共享目录)在一个Pod中准备两个容器nginx和busybox,然后声明一个Volume分别挂在到两个容器的目录中,然后nginx容器负责向Volume中写日志,busybox中通过命令将日志内容读到控制台。创建Volume-Emptydir.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: volume-emptydir namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - containerPort: 80 volumeMounts: # 将logs-volume挂在到nginx容器中,对应的目录为 /var/log/nginx - name: logs-volume mountPath: /var/log/nginx - name: busybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","tail -f /logs/access.log"] # 初始命令,动态读取指定文件中内容 volumeMounts: # 将logs-volume 挂在到busybox容器中,对应的目录为 /logs - name: logs-volume mountPath: /logs volumes: # 声明volume, name为logs-volume,类型为emptyDir - name: logs-volume emptyDir: {}# 创建Pod [root@master yaml]# kubectl create -f Volume-Emptydir.yaml pod/volume-emptydir created # 查看Pod [root@master yaml]# kubectl get pod -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES volume-emptydir 2/2 Running 0 76s 10.244.67.121 work1.host.com <none> <none> # 访问nginx [root@master yaml]# curl 10.244.67.121 ...... <h1>Welcome to nginx!</h1> ...... # 查看busybox日志 [root@master yaml]# kubectl logs -f volume-emptydir -n default -c busybox 10.244.34.192 - - [06/Sep/2022:12:50:33 +0000] "GET / HTTP/1.1" 200 615 "-" "curl/7.61.1" "-"HostPathEmptyDir中数据不会被持久化,它会随着Pod的结束而销毁,如果想简单的将数据持久化到主机中,可以选择HostPath。HostPath就是将Node主机中一个实际目录挂在到Pod中,以供容器使用,这样的设计就可以保证Pod销毁了,但是数据依据可以存在于Node主机上。创建Volume-Hostpath.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: volume-hostpath namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - containerPort: 80 volumeMounts: - name: logs-volume mountPath: /var/log/nginx - name: busybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","tail -f /logs/access.log"] volumeMounts: - name: logs-volume mountPath: /logs volumes: - name: logs-volume hostPath: path: /root/logs type: DirectoryOrCreate # 目录存在就使用,不存在就先创建后使用关于type的值的一点说明: DirectoryOrCreate 目录存在就使用,不存在就先创建后使用 Directory 目录必须存在 FileOrCreate 文件存在就使用,不存在就先创建后使用 File 文件必须存在 Socket unix套接字必须存在 CharDevice 字符设备必须存在 BlockDevice 块设备必须存在# 创建Pod [root@master yaml]# kubectl create -f Volume-Hostpath.yaml pod/volume-hostpath created # 查看Pod # 发现部署在work1下面 [root@master yaml]# kubectl get pods volume-hostpath -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES volume-hostpath 2/2 Running 0 17s 10.244.67.94 work1.host.com <none> <none> # 访问nginx [root@master yaml]# curl 10.244.67.94 ...... <h1>Welcome to nginx!</h1> ...... # 查看文件 # 在work1主机里查看/root/logs/目录 [root@work1 ~]# ls /root/logs/ access.log error.log [root@work1 ~]# cat /root/logs/access.log 10.244.34.192 - - [06/Sep/2022:12:57:39 +0000] "GET / HTTP/1.1" 200 615 "-" "curl/7.61.1" "-"NFSHostPath可以解决数据持久化的问题,但是一旦Node节点故障了,Pod如果转移到了别的节点,又会出现问题了,此时需要准备单独的网络存储系统,比较常用的用NFS、CIFS。NFS是一个网络文件存储系统,可以搭建一台NFS服务器,然后将Pod中的存储直接连接到NFS系统上,这样的话,无论Pod在节点上怎么转移,只要Node跟NFS的对接没问题,数据就可以成功访问。# 在master主机安装nfs服务 [root@master ~]# yum -y install rpcbind nfs-utils # 创建共享目录 [root@master ~]# mkdir /root/data/nfs -pv mkdir: created directory '/root/data' mkdir: created directory '/root/data/nfs' # 编写配置文件 [root@master ~]# vim /etc/exports [root@master ~]# more /etc/exports /root/data/nfs 192.16.1.0/24(rw,no_root_squash) # 启动nfs服务 [root@master ~]# systemctl enable --now rpcbind&&systemctl enable --now nfs-server Created symlink /etc/systemd/system/multi-user.target.wants/rpcbind.service → /usr/lib/systemd/system/rpcbind.service. Created symlink /etc/systemd/system/multi-user.target.wants/nfs-server.service → /usr/lib/systemd/system/nfs-server.service. # 更新配置 [root@master ~]# exportfs -r # 在work节点安装nfs-utils [root@work1 ~]# yum -y install nfs-utils [root@work2 ~]# yum -y install nfs-utils # 在work节点验证nfs [root@work1 ~]# showmount -e master.host.com Export list for master.host.com: /root/data/nfs 192.16.1.0/24 [root@work2 ~]# showmount -e master.host.com Export list for master.host.com: /root/data/nfs 192.16.1.0/24创建Volume-Nfs.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: volume-nfs namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - containerPort: 80 volumeMounts: - name: logs-volume mountPath: /var/log/nginx - name: busybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","tail -f /logs/access.log"] volumeMounts: - name: logs-volume mountPath: /logs volumes: - name: logs-volume nfs: server: 192.16.1.10 #nfs服务器地址 path: /root/data/nfs #共享文件路径# 创建Pod [root@master yaml]# kubectl create -f Volume-Nfs.yaml pod/volume-nfs created # 查看Pod [root@master yaml]# kubectl get pods volume-nfs -n default NAME READY STATUS RESTARTS AGE volume-nfs 2/2 Running 0 9s # 查看master节点nfs的目录 # 发现已经有数据了 [root@master yaml]# ls /root/data/nfs/ access.log error.log高级存储前面已经介绍了NFS提供存储,此时就要求用户会搭建NFS系统,并且会在yaml配置nfs。由于kubernetes支持的存储系统有很多,要求客户全都掌握,显然不现实。为了能够屏蔽底层存储实现的细节,方便用户使用, kubernetes引入PV和PVC两种资源对象。PV(Persistent Volume)是持久化卷的意思,是对底层的共享存储的一种抽象。一般情况下PV由kubernetes管理员进行创建和配置,它与底层具体的共享存储技术有关,并通过插件完成与共享存储的对接。PVC(Persistent Volume Claim)是持久卷声明的意思,是用户对于存储需求的一种声明。换句话说,PVC其实就是用户向kubernetes系统发出的一种资源需求申请。使用了PV和PVC之后,工作可以得到进一步的细分:存储:存储工程师维护PV:kubernetes管理员维护PVC:kubernetes用户维护PVPV(Persistent Volume)是持久化卷的意思,是对底层的共享存储的一种抽象。一般情况下PV由kubernetes管理员进行创建和配置,它与底层具体的共享存储技术有关,并通过插件完成与共享存储的对接。PV是存储资源的抽象,下面是是资源清单格式apiVersion: v1 kind: PersistentVolume metadata: name: pv2 spec: nfs: # 存储类型,与底层真正存储对应 capacity: # 存储能力,目前只支持存储空间的设置 storage: 2Gi accessModes: # 访问模式 storageClassName: # 存储类别 persistentVolumeReclaimPolicy: # 回收策略存储类型底层实际存储的类型,kubernetes支持多种存储类型,每种存储类型的配置都有所差异存储能力(capacity)​ 目前只支持存储空间的设置( storage=1Gi ),不过未来可能会加入IOPS、吞吐量等指标的配置访问模式(accessModes)用于描述用户应用对存储资源的访问权限,访问权限包括下面几种方式:ReadWriteOnce(RWO):读写权限,但是只能被单个节点挂载ReadOnlyMany(ROX): 只读权限,可以被多个节点挂载ReadWriteMany(RWX):读写权限,可以被多个节点挂载需要注意的是,底层不同的存储类型可能支持的访问模式不同回收策略(persistentVolumeReclaimPolicy)当PV不再被使用了之后,对其的处理方式。目前支持三种策略:Retain (保留) 保留数据,需要管理员手工清理数据Recycle(回收) 清除 PV 中的数据,效果相当于执行 rm -rf /thevolume/*Delete (删除) 与 PV 相连的后端存储完成 volume 的删除操作,当然这常见于云服务商的存储服务需要注意的是,底层不同的存储类型可能支持的回收策略不同存储类别PV可以通过storageClassName参数指定一个存储类别具有特定类别的PV只能与请求了该类别的PVC进行绑定未设定类别的PV则只能与不请求任何类别的PVC进行绑定状态(status)一个 PV 的生命周期中,可能会处于4中不同的阶段:Available(可用): 表示可用状态,还未被任何 PVC 绑定Bound(已绑定): 表示 PV 已经被 PVC 绑定Released(已释放): 表示 PVC 被删除,但是资源还未被集群重新声明Failed(失败): 表示该 PV 的自动回收失败使用NFS作为存储,来创建PV,NFS配置如下# master节点创建nfs存储 [root@master ~]# cat /etc/exports /root/data/pv1 192.16.1.0/24(rw,no_root_squash) /root/data/pv2 192.16.1.0/24(rw,no_root_squash) /root/data/pv3 192.16.1.0/24(rw,no_root_squash) [root@master ~]# exportfs -r # work节点查看 [root@work1 ~]# showmount -e 192.16.1.10 Export list for 192.16.1.10: /root/data/pv3 192.16.1.0/24 /root/data/pv2 192.16.1.0/24 /root/data/pv1 192.16.1.0/24创建Pv-Env.yaml,内容如下apiVersion: v1 kind: PersistentVolume metadata: name: pv1 spec: capacity: storage: 1Gi accessModes: - ReadWriteMany persistentVolumeReclaimPolicy: Retain nfs: path: /root/data/pv1 server: 192.16.1.10 --- apiVersion: v1 kind: PersistentVolume metadata: name: pv2 spec: capacity: storage: 2Gi accessModes: - ReadWriteMany persistentVolumeReclaimPolicy: Retain nfs: path: /root/data/pv2 server: 192.16.1.10 --- apiVersion: v1 kind: PersistentVolume metadata: name: pv3 spec: capacity: storage: 3Gi accessModes: - ReadWriteMany persistentVolumeReclaimPolicy: Retain nfs: path: /root/data/pv3 server: 192.16.1.10# 创建Pv [root@master yaml]# kubectl create -f Pv-Env.yaml persistentvolume/pv1 created persistentvolume/pv2 created persistentvolume/pv3 created # 查看Pv [root@master yaml]# kubectl get pv NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE pv1 1Gi RWX Retain Available 23s pv2 2Gi RWX Retain Available 23s pv3 3Gi RWX Retain Available 23sPVCPVC(Persistent Volume Claim)是持久卷声明的意思,是用户对于存储需求的一种声明。换句话说,PVC其实就是用户向kubernetes系统发出的一种资源需求申请。PVC是资源的申请,用来声明对存储空间、访问模式、存储类别需求信息。下面是是资源清单格式apiVersion: v1 kind: PersistentVolumeClaim metadata: name: pvc namespace: dev spec: accessModes: # 访问模式 selector: # 采用标签对PV选择 storageClassName: # 存储类别 resources: # 请求空间 requests: storage: 5Gi访问模式(accessModes)​ 用于描述用户应用对存储资源的访问权限选择条件(selector)通过Label Selector的设置,可使PVC对于系统中己存在的PV进行筛选存储类别(storageClassName)PVC在定义时可以设定需要的后端存储的类别,只有设置了该class的pv才能被系统选出资源请求(Resources )描述对存储资源的请求创建Pvc-Basic.yaml,内容如下apiVersion: v1 kind: PersistentVolumeClaim metadata: name: pvc1 namespace: default spec: accessModes: - ReadWriteMany resources: requests: storage: 1Gi --- apiVersion: v1 kind: PersistentVolumeClaim metadata: name: pvc2 namespace: default spec: accessModes: - ReadWriteMany resources: requests: storage: 1Gi --- apiVersion: v1 kind: PersistentVolumeClaim metadata: name: pvc3 namespace: default spec: accessModes: - ReadWriteMany resources: requests: storage: 1Gi# 创建Pvc [root@master yaml]# kubectl create -f Pvc-Basic.yaml persistentvolumeclaim/pvc1 created persistentvolumeclaim/pvc2 created persistentvolumeclaim/pvc3 created # 查看Pvc [root@master yaml]# kubectl get pvc -n default -o wide NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE VOLUMEMODE pvc1 Bound pv1 1Gi RWX 34s Filesystem pvc2 Bound pv2 2Gi RWX 34s Filesystem pvc3 Bound pv3 3Gi RWX 34s Filesystem # 查看Pv状态 [root@master yaml]# kubectl get pv -o wide NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE VOLUMEMODE pv1 1Gi RWX Retain Bound default/pvc1 15m Filesystem pv2 2Gi RWX Retain Bound default/pvc2 15m Filesystem pv3 3Gi RWX Retain Bound default/pvc3 15m FilesystemPod使用Pvc作为存储,创建Pvc-Pod.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pvc-pod1 namespace: default spec: containers: - name: busybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","while true;do echo pod1 >> /root/out.txt; sleep 10; done;"] volumeMounts: - name: volume mountPath: /root/ volumes: - name: volume persistentVolumeClaim: claimName: pvc1 readOnly: false --- apiVersion: v1 kind: Pod metadata: name: pvc-pod2 namespace: default spec: containers: - name: busybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","while true;do echo pod2 >> /root/out.txt; sleep 10; done;"] volumeMounts: - name: volume mountPath: /root/ volumes: - name: volume persistentVolumeClaim: claimName: pvc2 readOnly: false # 创建Pod [root@master yaml]# kubectl create -f Pvc-Pod.yaml pod/pvc-pod1 created pod/pvc-pod2 created # 查看Pod [root@master yaml]# kubectl get pods -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pvc-pod1 1/1 Running 0 27s 10.244.67.75 work1.host.com <none> <none> pvc-pod2 1/1 Running 0 27s 10.244.67.90 work1.host.com <none> <none> # 查看Pvc [root@master yaml]# kubectl get pv -n dev -o wide NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE VOLUMEMODE pv1 1Gi RWX Retain Bound default/pvc1 21m Filesystem pv2 2Gi RWX Retain Bound default/pvc2 21m Filesystem pv3 3Gi RWX Retain Bound default/pvc3 21m Filesystem # 查看nfs中的存储文件 [root@master yaml]# cat /root/data/pv1/out.txt pod1 pod1 pod1 [root@master yaml]# cat /root/data/pv2/out.txt pod2 pod2 pod2生命周期PVC和PV是一一对应的,PV和PVC之间的相互作用遵循以下生命周期:资源供应:管理员手动创建底层存储和PV资源绑定:用户创建PVC,kubernetes负责根据PVC的声明去寻找PV,并绑定在用户定义好PVC之后,系统将根据PVC对存储资源的请求在已存在的PV中选择一个满足条件的一旦找到,就将该PV与用户定义的PVC进行绑定,用户的应用就可以使用这个PVC了如果找不到,PVC则会无限期处于Pending状态,直到等到系统管理员创建了一个符合其要求的PVPV一旦绑定到某个PVC上,就会被这个PVC独占,不能再与其他PVC进行绑定了资源使用:用户可在pod中像volume一样使用pvcPod使用Volume的定义,将PVC挂载到容器内的某个路径进行使用。资源释放:用户删除pvc来释放pv当存储资源使用完毕后,用户可以删除PVC,与该PVC绑定的PV将会被标记为“已释放”,但还不能立刻与其他PVC进行绑定。通过之前PVC写入的数据可能还被留在存储设备上,只有在清除之后该PV才能再次使用。资源回收:kubernetes根据pv设置的回收策略进行资源的回收对于PV,管理员可以设定回收策略,用于设置与之绑定的PVC释放资源之后如何处理遗留数据的问题。只有PV的存储空间完成回收,才能供新的PVC绑定和使用配置存储ConfigMapConfigMap是一种比较特殊的存储卷,它的主要作用是用来存储配置信息的。创建Cm-Basic.yaml,内容如下:apiVersion: v1 kind: ConfigMap metadata: name: configmap namespace: default data: info: | username:admin password:123456# 创建Cm [root@master yaml]# kubectl create -f Cm-Basic.yaml configmap/configmap created # 查看Cm [root@master yaml]# kubectl describe cm configmap -n default Name: configmap Namespace: default Labels: <none> Annotations: <none> Data ==== info: ---- username:admin password:123456 BinaryData ==== Events: <none>创建Cm-Pod.yaml来使用Cm,内容如下apiVersion: v1 kind: Pod metadata: name: cm-pod namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 volumeMounts: # 将configmap挂载到目录 - name: config mountPath: /configmap/config volumes: # 引用configmap - name: config configMap: name: configmap# 创建Pod [root@master yaml]# kubectl create -f Cm-Pod.yaml pod/cm-pod created # 查看Pod [root@master yaml]# kubectl get pod cm-pod -n default NAME READY STATUS RESTARTS AGE cm-pod 1/1 Running 0 13s # 进入容器查看数据 [root@master yaml]# kubectl exec -it cm-pod -n default /bin/sh kubectl exec [POD] [COMMAND] is DEPRECATED and will be removed in a future version. Use kubectl exec [POD] -- [COMMAND] instead. # ls /configmap/config/ info # cat /configmap/config/info username:admin password:123456 # 可以看到映射已经成功,每个configmap都映射成了一个目录 # key--->文件 value---->文件中的内容 # 此时如果更新configmap的内容, 容器中的值也会动态更新Secret在kubernetes中,还存在一种和ConfigMap非常类似的对象,称为Secret对象。它主要用于存储敏感信息,例如密码、秘钥、证书等等。# 首先使用base64对数据进行编码 [root@master yaml]# echo -n 'admin' | base64 YWRtaW4= [root@master yaml]# echo -n '123456' | base64 MTIzNDU2创建Secret-Basic.yaml,内容如下apiVersion: v1 kind: Secret metadata: name: secret namespace: default type: Opaque data: username: YWRtaW4= password: MTIzNDU2# 创建Secret [root@master yaml]# kubectl create -f Secret-Basic.yaml secret/secret created # 查看Secret详情 # 发现配置只显示大小 [root@master yaml]# kubectl describe secret -n default Name: secret Namespace: default Labels: <none> Annotations: <none> Type: Opaque Data ==== password: 6 bytes username: 5 bytes创建Secret-Pod.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: secret-pod namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 volumeMounts: # 将secret挂载到目录 - name: config mountPath: /secret/config volumes: - name: config secret: secretName: secret# 创建Pod [root@master yaml]# kubectl create -f Secret-Pod.yaml pod/secret-pod created # 查看Pod [root@master yaml]# kubectl get pod secret-pod -n default NAME READY STATUS RESTARTS AGE secret-pod 1/1 Running 0 68s # 进入容器查看secret信息 # 发现会自动解码 [root@master yaml]# kubectl exec -it secret-pod /bin/sh -n default kubectl exec [POD] [COMMAND] is DEPRECATED and will be removed in a future version. Use kubectl exec [POD] -- [COMMAND] instead. # ls /secret/config password username # cat /secret/config/username admin # cat /secret/config/password 123456 Kubernetes-容器编排引擎(Ingress-nginx) https://blog.boychai.xyz/index.php/archives/29/ 2022-09-06T09:19:00+00:00 Ingress概述Service对集群之外暴露服务的主要方式有两种:NotePort和LoadBalancer,但是这两种方式,都有一定的缺点:NodePort方式的缺点是会占用很多集群机器的端口,那么当集群服务变多的时候,这个缺点就愈发明显LB方式的缺点是每个service需要一个LB,浪费、麻烦,并且需要kubernetes之外设备的支持基于这种现状,kubernetes提供了Ingress资源对象,Ingress只需要一个NodePort或者一个LB就可以满足暴露多个Service的需求。工作机制大致如下图表示:实际上,Ingress相当于一个7层的负载均衡器,是kubernetes对反向代理的一个抽象,它的工作原理类似于Nginx,可以理解成在Ingress里建立诸多映射规则,Ingress Controller通过监听这些配置规则并转化成Nginx的反向代理配置 , 然后对外部提供服务。在这里有两个核心概念:ingress:kubernetes中的一个对象,作用是定义请求如何转发到service的规则ingress controller:具体实现反向代理及负载均衡的程序,对ingress定义的规则进行解析,根据配置的规则来实现请求转发,实现方式有很多,比如Nginx, Contour, Haproxy等等Ingress(以Nginx为例)的工作原理如下:用户编写Ingress规则,说明哪个域名对应kubernetes集群中的哪个ServiceIngress控制器动态感知Ingress服务规则的变化,然后生成一段对应的Nginx反向代理配置Ingress控制器会将生成的Nginx配置写入到一个运行着的Nginx服务中,并动态更新到此为止,其实真正在工作的就是一个Nginx了,内部配置了用户定义的请求转发规则Ingress使用环境配置环境为3个deploy,分别部署3个pod,镜像依次为nginx,apache,tomcat,并对应部署了三个service创建文件Ingress-Env.yaml,内容如下--- apiVersion: apps/v1 kind: Deployment metadata: name: ingress-env-nginx namespace: default spec: replicas: 3 selector: matchLabels: ingress-env: nginx-pod template: metadata: labels: ingress-env: nginx-pod spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 --- apiVersion: apps/v1 kind: Deployment metadata: name: ingress-env-httpd namespace: default spec: replicas: 3 selector: matchLabels: ingress-env: httpd-pod template: metadata: labels: ingress-env: httpd-pod spec: containers: - name: httpd image: docker.io/library/httpd:2.4.54 --- apiVersion: apps/v1 kind: Deployment metadata: name: ingress-env-tomcat namespace: default spec: replicas: 3 selector: matchLabels: ingress-env: tomcat-pod template: metadata: labels: ingress-env: tomcat-pod spec: containers: - name: tomcat image: docker.io/library/tomcat:8.5-jre10-slim --- apiVersion: v1 kind: Service metadata: name: ingress-env-nginx-svc namespace: default spec: selector: ingress-env: nginx-pod clusterIP: 10.97.2.1 # service的ip地址,如果不写,默认会生成一个 type: ClusterIP ports: - port: 80 # Service端口 targetPort: 80 # pod端口 --- apiVersion: v1 kind: Service metadata: name: ingress-env-httpd-svc namespace: default spec: selector: ingress-env: httpd-pod clusterIP: 10.97.2.2 # service的ip地址,如果不写,默认会生成一个 type: ClusterIP ports: - port: 80 # Service端口 targetPort: 80 # pod端口 --- apiVersion: v1 kind: Service metadata: name: ingress-env-tomcat-svc namespace: default spec: selector: ingress-env: tomcat-pod clusterIP: 10.97.2.3 # service的ip地址,如果不写,默认会生成一个 type: ClusterIP ports: - port: 80 # Service端口 targetPort: 8080 # pod端口 # 创建环境 [root@master yaml]# kubectl create -f Ingress-Env.yaml deployment.apps/ingress-env-nginx created deployment.apps/ingress-env-httpd created deployment.apps/ingress-env-tomcat created service/ingress-env-nginx-svc created service/ingress-env-httpd-svc created service/ingress-env-tomcat-svc created # 查看Pod [root@master yaml]# kubectl get pod -n default NAME READY STATUS RESTARTS AGE ingress-env-httpd-59b9f557c4-gjvhn 1/1 Running 0 15s ingress-env-httpd-59b9f557c4-j6q9b 1/1 Running 0 15s ingress-env-httpd-59b9f557c4-zp9fv 1/1 Running 0 15s ingress-env-nginx-7d899c7648-4r7gx 1/1 Running 0 15s ingress-env-nginx-7d899c7648-6fzq9 1/1 Running 0 15s ingress-env-nginx-7d899c7648-stv77 1/1 Running 0 15s ingress-env-tomcat-679896868f-27zhq 1/1 Running 0 15s ingress-env-tomcat-679896868f-w9gd6 1/1 Running 0 15s ingress-env-tomcat-679896868f-wwwnn 1/1 Running 0 15s # 查看deploy [root@master yaml]# kubectl get deploy -n default NAME READY UP-TO-DATE AVAILABLE AGE ingress-env-httpd 3/3 3 3 31s ingress-env-nginx 3/3 3 3 31s ingress-env-tomcat 3/3 3 3 31s # 查看svc [root@master yaml]# kubectl get svc -n default NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE ingress-env-httpd-svc ClusterIP 10.97.2.2 <none> 80/TCP 44s ingress-env-nginx-svc ClusterIP 10.97.2.1 <none> 80/TCP 44s ingress-env-tomcat-svc ClusterIP 10.97.2.3 <none> 80/TCP 44s # 测试svc # 都有页面返回即可 [root@master yaml]# curl 10.97.2.1 ...... <h1>Welcome to nginx!</h1> ...... [root@master yaml]# curl 10.97.2.2 <html><body><h1>It works!</h1></body></html> [root@master yaml]# curl 10.97.2.3 ...... <h2>If you're seeing this, you've successfully installed Tomcat. Congratulations!</h2> ......Ingress-nginx安装# 下载Ingress的部署资源清单 # 我这里的版本是v1.3.0 [root@master yaml]# curl -o Ingress-Deploy.yaml https://raw.githubusercontent.com/kubernetes/ingress-nginx/controller-v1.3.0/deploy/static/provider/cloud/deploy.yaml % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 15490 100 15490 0 0 15694 0 --:--:-- --:--:-- --:--:-- 15678 # 替换镜像 # Ingress-Deploy里面会用到两个镜像 # 一个是ingress-nginx/controller:1.3.0还有一个是ingress-nginx-kube-webhook-certgen:v1.1.1 # 默认都是从k8s镜像仓库下载的,都被墙了,需要把这两个修改为其他的,这里我自己科学上网pull下来放到仓库了修改内容如下 # 注意一共有三个镜像配置,有两个kube-webhook-certgen,三个都要改 image: registry.k8s.io/ingress-nginx/controller:v1.3.0... > image: docker.io/boychai/ingress-nginx-controlle:v1.3.0 image image: registry.k8s.io/ingress-nginx/kube-webhook-certgen:v1.1.1... > image: docker.io/boychai/ingress-nginx-kube-webhook-certgen:v1.1.1 # 添加hostNetwork配置 # 在Ingress-Deploy的里面会有段Deployment的配置大概在388行 # 在Deployment.spec.template.spec添加hostNetwork:true ...... 412 spec: 413 hostNetwork: true 414 containers: 415 - args: 416 - /nginx-ingress-controller 417 - --publish-service=$(POD_NAMESPACE)/ingress-nginx-controller ...... # 创建Ingress-Nginx [root@master yaml]# kubectl create -f Ingress-Deploy.yaml namespace/ingress-nginx created serviceaccount/ingress-nginx created serviceaccount/ingress-nginx-admission created role.rbac.authorization.k8s.io/ingress-nginx created role.rbac.authorization.k8s.io/ingress-nginx-admission created clusterrole.rbac.authorization.k8s.io/ingress-nginx created clusterrole.rbac.authorization.k8s.io/ingress-nginx-admission created rolebinding.rbac.authorization.k8s.io/ingress-nginx created rolebinding.rbac.authorization.k8s.io/ingress-nginx-admission created clusterrolebinding.rbac.authorization.k8s.io/ingress-nginx created clusterrolebinding.rbac.authorization.k8s.io/ingress-nginx-admission created configmap/ingress-nginx-controller created service/ingress-nginx-controller created service/ingress-nginx-controller-admission created deployment.apps/ingress-nginx-controller created job.batch/ingress-nginx-admission-create created job.batch/ingress-nginx-admission-patch created ingressclass.networking.k8s.io/nginx created validatingwebhookconfiguration.admissionregistration.k8s.io/ingress-nginx-admission created # 查看pod [root@master yaml]# kubectl get pod -n ingress-nginx NAME READY STATUS RESTARTS AGE ingress-nginx-admission-create-69hcz 0/1 Completed 0 50s ingress-nginx-admission-patch-pwm7c 0/1 Completed 0 49s ingress-nginx-controller-7fc79df64f-tcx85 1/1 Running 0 50s # 查看service [root@master yaml]# kubectl get svc -n ingress-nginx NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE ingress-nginx-controller LoadBalancer 10.104.11.86 <pending> 80:32637/TCP,443:31430/TCP 80s ingress-nginx-controller-admission ClusterIP 10.99.43.141 <none> 443/TCP 80s Ingress-nginx使用ingress可以代理http和https,如果要使用https需要导入证书相关文件到secret,操作如下# 创建tls目录并生成私钥和证书 [root@master yaml]# mkdir tls [root@master tls]# openssl req -x509 -sha256 -nodes -days 365 -newkey rsa:2048 -keyout tls.key -out tls.crt -subj "/C=CN/ST=QD/L=QD/O=nginx/CN=host.com" Generating a RSA private key .....+++++ ................................+++++ writing new private key to 'tls.key' ----- [root@master tls]# ls tls.crt tls.key # 导入到secret [root@master tls]# kubectl create secret tls tls-secret --key tls.key --cert tls.crt secret/tls-secret created # 查看secret [root@master tls]# kubectl get secret NAME TYPE DATA AGE tls-secret kubernetes.io/tls 2 75s创建Ingress-Basic.yaml,内容如下apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: ingress-basic spec: tls: - hosts: - nginx.host.com - apache.host.com - tomcat.host.com secretName: tls.secret # 指定证书配 ingressClassName: nginx rules: - host: "nginx.host.com" http: paths: - pathType: Prefix path: / backend: service: name: ingress-env-nginx-svc port: number: 80 - host: "apache.host.com" http: paths: - pathType: Prefix path: / backend: service: name: ingress-env-httpd-svc port: number: 80 - host: "tomcat.host.com" http: paths: - pathType: Prefix path: / backend: service: name: ingress-env-tomcat-svc port: number: 80# 创建Ingres [root@master yaml]# kubectl create -f Ingress-Basic.yaml ingress.networking.k8s.io/ingress-basic created # 查看Ingress [root@master yaml]# kubectl get Ingress -n default NAME CLASS HOSTS ADDRESS PORTS AGE ingress-basic nginx nginx.host.com,apache.host.com,tomcat.host.com 80, 443 12s # 查看Ingress详情 [root@master yaml]# kubectl describe Ingress ingress-basic -n default ...... TLS: tls.secret terminates apache.host.com,tomcat.host.com Rules: Host Path Backends ---- ---- -------- nginx.host.com / ingress-env-nginx-svc:80 (10.244.52.248:80,10.244.67.124:80,10.244.67.80:80) apache.host.com / ingress-env-httpd-svc:80 (10.244.52.238:80,10.244.67.114:80,10.244.67.75:80) tomcat.host.com / ingress-env-tomcat-svc:80 (10.244.52.229:8080,10.244.67.103:8080,10.244.67.70:8080) ...... # 访问测试 # 当域名[nginx,apache,tomcat].host.com解析到work节点之后去访问即可 # master我没有消除污点也没有配置ingres的容忍所以只能访问work节点 [root@master yaml]# curl -k --tlsv1 https://nginx.host.com ...... <h1>Welcome to nginx!</h1> ...... [root@master yaml]# curl -k --tlsv1 https://apache.host.com <html><body><h1>It works!</h1></body></html> [root@master yaml]# curl -k --tlsv1 https://tomcat.host.com ...... <h2>If you're seeing this, you've successfully installed Tomcat. Congratulations!</h2> ......http代理上面的配置是https的代理,如果要用http的话把tls段全部删掉就可以了 Kubernetes-容器编排引擎(Service详解) https://blog.boychai.xyz/index.php/archives/28/ 2022-09-05T05:32:00+00:00 Service概述在kubernetes中,pod是应用程序的载体,可以通过pod的ip来访问应用程序,但是pod的ip地址不是固定的,这也就意味着不方便直接采用pod的ip对服务进行访问。为了解决这个问题,kubernetes提供了Service资源,Service会对提供同一个服务的多个pod进行聚合,并且提供一个统一的入口地址。通过访问Service的入口地址就能访问到后面的pod服务。Service在很多情况下只是一个概念,真正起作用的其实是kube-proxy服务进程,每个Node节点上都运行着一个kube-proxy服务进程。当创建Service的时候会通过api-server向etcd写入创建的service的信息,而kube-proxy会基于监听的机制发现这种Service的变动,然后它会将最新的Service信息转换成对应的访问规则。工作模式userspace 模式userspace模式下,kube-proxy会为每一个Service创建一个监听端口,发向Cluster IP的请求被Iptables规则重定向到kube-proxy监听的端口上,kube-proxy根据LB算法选择一个提供服务的Pod并和其建立链接,以将请求转发到Pod上。该模式下,kube-proxy充当了一个四层负责均衡器的角色。由于kube-proxy运行在userspace中,在进行转发处理时会增加内核和用户空间之间的数据拷贝,虽然比较稳定,但是效率比较低。iptables模式iptables模式下,kube-proxy为service后端的每个Pod创建对应的iptables规则,直接将发向Cluster IP的请求重定向到一个Pod IP。该模式下kube-proxy不承担四层负责均衡器的角色,只负责创建iptables规则。该模式的优点是较userspace模式效率更高,但不能提供灵活的LB策略,当后端Pod不可用时也无法进行重试。ipvs模式ipvs模式和iptables类似,kube-proxy监控Pod的变化并创建相应的ipvs规则。ipvs相对iptables转发效率更高。除此以外,ipvs支持更多的LB算法。设置工作模式# 以ipvs为例,使用之前请安装ipvs模块(安装集群时已经安装) # 编辑kube-proxy cm修改mode为"ipvs" [root@master yaml]# kubectl edit cm kube-proxy -n kube-system configmap/kube-proxy edited ...... mode: "ipvs" ...... # 删除kube-proxy使其自动重启更新配置 [root@master yaml]# kubectl delete pod -l k8s-app=kube-proxy -n kube-system pod "kube-proxy-5r4xw" deleted pod "kube-proxy-qww6b" deleted pod "kube-proxy-th7hm" deleted # 查看ipvs规则 # 发现配置已生效 [root@master yaml]# ipvsadm -Ln IP Virtual Server version 1.2.1 (size=4096) Prot LocalAddress:Port Scheduler Flags -> RemoteAddress:Port Forward Weight ActiveConn InActConn TCP 10.96.0.1:443 rr -> 192.16.1.10:6443 Masq 1 0 0 TCP 10.96.0.10:53 rr -> 10.244.52.213:53 Masq 1 0 0 -> 10.244.52.218:53 Masq 1 0 0 TCP 10.96.0.10:9153 rr -> 10.244.52.213:9153 Masq 1 0 0 -> 10.244.52.218:9153 Masq 1 0 0 UDP 10.96.0.10:53 rr -> 10.244.52.213:53 Masq 1 0 0 -> 10.244.52.218:53 Masq 1 0 0Service资源清单kind: Service # 资源类型 apiVersion: v1 # 资源版本 metadata: # 元数据 name: service # 资源名称 namespace: <命名空间> spec: # 描述 selector: # 标签选择器,用于确定当前service代理哪些pod type: <Service类型> clusterIP: <虚拟服务的ip地址> sessionAffinity: # session亲和性,支持ClientIP、None两个选项 ports: # 端口信息 - protocol: <协议> port: <service端口> targetPort: <pod端口> nodePort: <主机端口>Service类型如下:ClusterIP:默认值,它是Kubernetes系统自动分配的虚拟IP,只能在集群内部访问NodePort:将Service通过指定的Node上的端口暴露给外部,通过此方法,就可以在集群外部访问服务LoadBalancer:使用外接负载均衡器完成到服务的负载分发,注意此模式需要外部云环境支持ExternalName: 把集群外部的服务引入集群内部,直接使用Service使用实验环境在使用service之前,首先利用Deployment创建出3个pod,注意要为pod设置app=nginx-pod的标签。创建Service-Env.yaml,内容如下apiVersion: apps/v1 kind: Deployment metadata: name: service-env namespace: default spec: replicas: 3 selector: matchLabels: app: service-env template: metadata: labels: app: service-env spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - containerPort: 80# 创建deploy [root@master yaml]# kubectl create -f Service-Env.yaml deployment.apps/service-env created # 查看pod详情 [root@master yaml]# kubectl get pods -n default -o wide --show-labels NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES LABELS service-env-77bd9f74d4-7qntr 1/1 Running 0 108s 10.244.52.222 work2.host.com <none> <none> service-env-77bd9f74d4-9hs5k 1/1 Running 0 108s 10.244.67.84 work1.host.com <none> <none> service-env-77bd9f74d4-s5hh5 1/1 Running 0 108s 10.244.67.79 work1.host.com <none> <none> # 为了方便测试修改nginx的访问页面为podip # 给容器依次修改 [root@master yaml]# kubectl exec -it service-env-77bd9f74d4-7qntr -n default /bin/sh kubectl exec [POD] [COMMAND] is DEPRECATED and will be removed in a future version. Use kubectl exec [POD] -- [COMMAND] instead. # echo 10.244.52.222 > /usr/share/nginx/html/index.html # exit [root@master yaml]# kubectl exec -it service-env-77bd9f74d4-9hs5k -n default /bin/sh kubectl exec [POD] [COMMAND] is DEPRECATED and will be removed in a future version. Use kubectl exec [POD] -- [COMMAND] instead. # echo 10.244.67.84 > /usr/share/nginx/html/index.html # exit [root@master yaml]# kubectl exec -it service-env-77bd9f74d4-s5hh5 -n default /bin/sh kubectl exec [POD] [COMMAND] is DEPRECATED and will be removed in a future version. Use kubectl exec [POD] -- [COMMAND] instead. # echo 10.244.67.79 > /usr/share/nginx/html/index.html # exit # 访问测试 [root@master yaml]# curl 10.244.52.222 10.244.52.222 [root@master yaml]# curl 10.244.67.84 10.244.67.84 [root@master yaml]# curl 10.244.67.79 10.244.67.79ClusterIP创建Service-Clusterip.yaml,内容如下apiVersion: v1 kind: Service metadata: name: service-clusterip namespace: default spec: selector: app: service-env clusterIP: 10.97.1.1 # service的ip地址,如果不写,默认会生成一个 type: ClusterIP ports: - port: 80 # Service端口 targetPort: 80 # pod端口# 创建service [root@master yaml]# kubectl create -f Service-Clusterip.yaml service/service-clusterip created # 查看service [root@master yaml]# kubectl get svc -n default -o wide NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 2d18h <none> service-clusterip ClusterIP 10.97.1.1 <none> 80/TCP 4m42s app=service-env # 查看service详情 # 里面有一个Endpoints,里面就是pod入口 [root@master yaml]# kubectl describe svc service-clusterip -n default Name: service-clusterip Namespace: default Labels: <none> Annotations: <none> Selector: app=service-env Type: ClusterIP IP Family Policy: SingleStack IP Families: IPv4 IP: 10.97.1.1 IPs: 10.97.1.1 Port: <unset> 80/TCP TargetPort: 80/TCP Endpoints: 10.244.52.222:80,10.244.67.79:80,10.244.67.84:80 Session Affinity: None Events: <none> # 查看ipvs的映射规则 [root@master yaml]# ipvsadm -Ln ...... TCP 10.97.1.1:80 rr -> 10.244.52.222:80 Masq 1 0 0 -> 10.244.67.79:80 Masq 1 0 0 -> 10.244.67.84:80 Masq 1 0 0 ...... # 访问测试 # http://10.97.1.1:80 [root@master yaml]# curl http://10.97.1.1:80 10.244.67.84 [root@master yaml]# curl http://10.97.1.1:80 10.244.67.79 [root@master yaml]# curl http://10.97.1.1:80 10.244.52.222HeadLinessEndpoint是kubernetes中的一个资源对象,存储在etcd中,用来记录一个service对应的所有pod的访问地址,它是根据service配置文件中selector描述产生的。一个Service由一组Pod组成,这些Pod通过Endpoints暴露出来,Endpoints是实现实际服务的端点集合。换句话说,service和pod之间的联系是通过endpoints实现的。创建Service-Headliness.yaml,内容如下apiVersion: v1 kind: Service metadata: name: service-headliness namespace: default spec: selector: app: service-env clusterIP: None # 将clusterIP设置为None,即可创建headliness Service type: ClusterIP ports: - port: 80 targetPort: 80# 创建service [root@master yaml]# kubectl create -f Service-Headliness.yaml service/service-headliness created # 查看service # 发现CLUSTER-IP未分配IP [root@master yaml]# kubectl get svc service-headliness -n default -o wide NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR service-headliness ClusterIP None <none> 80/TCP 43s app=service-env # 查看service详情 [root@master yaml]# kubectl describe svc service-headliness -n default Name: service-headliness Namespace: default Labels: <none> Annotations: <none> Selector: app=service-env Type: ClusterIP IP Family Policy: SingleStack IP Families: IPv4 IP: None IPs: None Port: <unset> 80/TCP TargetPort: 80/TCP Endpoints: 10.244.52.222:80,10.244.67.79:80,10.244.67.84:80 Session Affinity: None Events: <none> # 查看域名的解析情况 [root@master yaml]# kubectl exec -it pc-deployment-6895856946-9b24j -n default /bin/sh kubectl exec [POD] [COMMAND] is DEPRECATED and will be removed in a future version. Use kubectl exec [POD] -- [COMMAND] instead. # cat /etc/resolv.conf search default.svc.cluster.local svc.cluster.local cluster.local host.com nameserver 10.96.0.10 options ndots:5 # exit # 查看域名解析记录 [root@master yaml]# dig @10.96.0.10 service-headliness.default.svc.cluster.local +short 10.244.67.84 10.244.52.222 10.244.67.79NodePort如果希望将Service暴露给集群外部使用,那么就要使用到另外一种类型的Service,称为NodePort类型。NodePort的工作原理其实就是将service的端口映射到Node的一个端口上,然后就可以通过NodeIp:NodePort来访问service了。创建Service-Nodeport.yaml,内容如下apiVersion: v1 kind: Service metadata: name: service-nodeport namespace: default spec: selector: app: service-env type: NodePort # service类型 ports: - port: 80 nodePort: 30002 # 指定绑定的node的端口(默认的取值范围是:30000-32767), 如果不指定,会默认分配 targetPort: 80# 创建service [root@master yaml]# kubectl create -f Service-Nodeport.yaml service/service-nodeport created # 查看service [root@master yaml]# kubectl get svc -n default -o wide NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR service-nodeport NodePort 10.101.89.79 <none> 80:30002/TCP 20s app=service-env # 访问测试 # 访问每个节点的30002端口 [root@master yaml]# curl http://master.host.com:30002 10.244.67.84 [root@master yaml]# curl http://work1.host.com:30002 10.244.67.79 [root@master yaml]# curl http://work2.host.com:30002 10.244.67.84LoadBalancerLoadBalancer和NodePort很相似,目的都是向外部暴露一个端口,区别在于LoadBalancer会在集群的外部再来做一个负载均衡设备,而这个设备需要外部环境支持的,外部服务发送到这个设备上的请求,会被设备负载之后转发到集群中。实现LoadBalancer需要外部设备,这里不做演示。ExternalNameExternalName类型的Service用于引入集群外部的服务,它通过externalName属性指定外部一个服务的地址,然后在集群内部访问此service就可以访问到外部的服务了。创建Service-Externalname.yaml,内容如下apiVersion: v1 kind: Service metadata: name: service-externalname namespace: default spec: type: ExternalName # service类型 externalName: www.baidu.com #改成ip地址也可以# 创建service [root@master yaml]# kubectl create -f Service-Externalname.yaml service/service-externalname created # 查看域名解析记录 [root@master yaml]# dig @10.96.0.10 service-externalname.default.svc.cluster.local +short www.baidu.com. 39.156.66.14 39.156.66.18注意service域名解析记录的域名组成如下[资源名称].[命名空间].svc.cluster.local Kubernetes-容器编排引擎(Pod控制器详解) https://blog.boychai.xyz/index.php/archives/27/ 2022-09-04T06:07:00+00:00 Pod控制器概述引入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。类别在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)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。资源清单apiVersion: apps/v1 # 版本号 kind: ReplicaSet # 类型 metadata: name: namespace: labels: spec: replicas: <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 matchExpressions: # Expressions匹配规则 - {key: <lableskey>, operator: <匹配方式>, values: <lablesvalue>} 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: spec: containers: - name: image: ports: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1selector: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RS创建Pc-Replicaset.yaml文件,内容如下:apiVersion: apps/v1 kind: ReplicaSet metadata: name: pc-replicaset namespace: default spec: replicas: 3 selector: matchLabels: app: nginx-pod template: metadata: labels: app: nginx-pod spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1# 创建rs [root@master yaml]# 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 yaml]# kubectl get rs pc-replicaset -n default -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR pc-replicaset 3 3 3 2m41s nginx docker.io/library/nginx:1.23.1 app=nginx-pod # 查看当前控制器创建出来的pod # 控制器创建的pod的名称是在控制器名称后面拼接了-xxxxx随机码 [root@master yaml]# kubectl get pod -n default NAME READY STATUS RESTARTS AGE pc-replicaset-fvjg2 1/1 Running 0 3m53s pc-replicaset-lzfc2 1/1 Running 0 3m53s pc-replicaset-q7hrm 1/1 Running 0 3m53s扩缩容# 在线编辑配置 # 修改spce.replicas为6即可 [root@master yaml]# kubectl edit rs pc-replicaset -n default replicaset.apps/pc-replicaset edited # 查看Pod数量 [root@master yaml]# kubectl get pod -n default NAME READY STATUS RESTARTS AGE pc-replicaset-49zl6 1/1 Running 0 67s pc-replicaset-5ngpl 1/1 Running 0 67s pc-replicaset-fvjg2 1/1 Running 0 6m45s pc-replicaset-lzfc2 1/1 Running 0 6m45s pc-replicaset-pnstd 1/1 Running 0 67s pc-replicaset-q7hrm 1/1 Running 0 6m45s # 使用命令 # 使用scale实现扩缩容replicas为扩缩容的数量 [root@master yaml]# kubectl scale rs pc-replicaset --replicas=2 -n default replicaset.apps/pc-replicaset scaled # 查看Pod数量 [root@master yaml]# kubectl get pod -n default|grep pc NAME READY STATUS RESTARTS AGE pc-replicaset-fvjg2 1/1 Running 0 8m39s pc-replicaset-q7hrm 1/1 Running 0 8m39s镜像升级# 在线编辑配置 # 修改spce.template.spec.containers.image为docker.io/library/nginx:latest即可 [root@master yaml]# kubectl edit rs pc-replicaset -n default replicaset.apps/pc-replicaset edited # 查看rs状态 # 镜像版本已经变更了 [root@master yaml]# kubectl get rs -n default -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR pc-replicaset 2 2 2 14m nginx docker.io/library/nginx:latest app=nginx-pod # 使用命令 # kubectl set image rs rs名称 容器=镜像版本 -n namespace [root@master yaml]# kubectl set image rs pc-replicaset nginx=docker.io/library/nginx:1.23.1 -n default replicaset.apps/pc-replicaset image updated # 再次查看 # 镜像版本已经变更了 [root@master yaml]# kubectl get rs -n default -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES SELECTOR pc-replicaset 2 2 2 17m nginx docker.io/library/nginx:1.23.1 app=nginx-pod删除RS# 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 yaml]# kubectl delete rs pc-replicaset -n default replicaset.apps "pc-replicaset" deleted [root@master yaml]# kubectl get pod -n default -o wide No resources found in default 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@master yaml]# kubectl delete rs pc-replicaset -n default --cascade=false replicaset.apps "pc-replicaset" deleted [root@master yaml]# kubectl get pods -n default 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@master yaml]# kubectl delete -f Pc-Replicaset.yaml replicaset.apps "pc-replicaset" deletedDeployment(Deploy)概述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资源清单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 spec: # 详情描述 replicas: <副本数量> revisionHistoryLimit: <保留历史版本数量> 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: <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 matchExpressions: # Expressions匹配规则 - {key: <lableskey>, operator: <匹配方式>, values: <lablesvalue>} 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: spec: containers: - name: image: ports:创建deploy创建Pc-Deployment.yaml,内容如下apiVersion: apps/v1 kind: Deployment metadata: name: pc-deployment namespace: default spec: replicas: 3 selector: matchLabels: app: nginx-pod template: metadata: labels: app: nginx-pod spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1# 创建deploy [root@master yaml]# kubectl create -f Pc-Deployment.yaml --record=true Flag --record has been deprecated, --record will be removed in the future deployment.apps/pc-deployment created # 查看deploy # UP-TO-DATE 最新版本的pod的数量 # AVAILABLE 当前可用的pod的数量 [root@master yaml]# kubectl get deploy pc-deployment -n default NAME READY UP-TO-DATE AVAILABLE AGE pc-deployment 3/3 3 3 85s # 查看rs # 发现rs的名称是在原来查看deploy的名字后面添加了一个10位数的随机串 [root@master yaml]# kubectl get rs -n default NAME DESIRED CURRENT READY AGE pc-deployment-6895856946 3 3 3 2m14s # 查看pod [root@master yaml]# kubectl get pods -n default NAME READY STATUS RESTARTS AGE pc-deployment-6895856946-7nbs4 1/1 Running 0 3m30s pc-deployment-6895856946-g5n6g 1/1 Running 0 3m30s pc-deployment-6895856946-jkqnm 1/1 Running 0 3m30s扩缩容# 命令方式 [root@master yaml]# kubectl scale deploy pc-deployment --replicas=5 -n default deployment.apps/pc-deployment scaled # 查看deploy [root@master yaml]# kubectl get deploy pc-deployment -n default NAME READY UP-TO-DATE AVAILABLE AGE pc-deployment 5/5 5 5 3m24s # 查看pod数量 [root@master yaml]# kubectl get pods -n default NAME READY STATUS RESTARTS AGE pc-deployment-6895856946-2tpfc 1/1 Running 0 4m2s pc-deployment-6895856946-5pn96 1/1 Running 0 4m2s pc-deployment-6895856946-792dj 1/1 Running 0 4m2s pc-deployment-6895856946-89vrz 1/1 Running 0 117s pc-deployment-6895856946-hl7pz 1/1 Running 0 117s # 在线编辑方式 # 修改spec.replicase为3 [root@master yaml]# kubectl edit deploy pc-deployment -n default deployment.apps/pc-deployment edited # 查看deploy [root@master yaml]# kubectl get deploy pc-deployment -n default NAME READY UP-TO-DATE AVAILABLE AGE pc-deployment 3/3 3 3 6m18s # 查看pod数量 [root@master yaml]# kubectl get pods -n default NAME READY STATUS RESTARTS AGE pc-deployment-6895856946-792dj 1/1 Running 0 6m44s pc-deployment-6895856946-89vrz 1/1 Running 0 6m44s pc-deployment-6895856946-792dj 1/1 Running 0 6m44s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# 修改配置清单,并更新配置 # 修改spec.strategy.type为Recreate [root@master yaml]# vim Pc-Deployment.yaml [root@master yaml]# kubectl apply -f Pc-Deployment.yaml deployment.apps/pc-deployment configured # 命令方式更变镜像 [root@master yaml]# kubectl set image deployment pc-deployment nginx=docker.io/library/nginx:latest -n default deployment.apps/pc-deployment image updated # 查看升级过程 [root@master yaml]# kubectl get pods -n default -w NAME READY STATUS RESTARTS AGE pc-deployment-6895856946-9zvpn 1/1 Terminating 0 5s pc-deployment-6895856946-bnz2v 1/1 Terminating 0 5s pc-deployment-6895856946-6dswz 0/1 Terminating 0 5s pc-deployment-74556686fb-f76kc 0/1 Pending 0 0s pc-deployment-74556686fb-g48rh 0/1 Pending 0 0s pc-deployment-74556686fb-m2rvf 0/1 Pending 0 0s pc-deployment-74556686fb-f76kc 0/1 ContainerCreating 0 0s pc-deployment-74556686fb-g48rh 0/1 ContainerCreating 0 0s pc-deployment-74556686fb-m2rvf 0/1 ContainerCreating 0 0s pc-deployment-74556686fb-g48rh 1/1 Running 0 1s pc-deployment-74556686fb-f76kc 1/1 Running 0 2s pc-deployment-74556686fb-m2rvf 1/1 Running 0 2s滚动更新# 修改配置清单,并更新配置 # 修改spec.strategy.type为RollingUpdate,并添加rollingUpdate配置 [root@master yaml]# vim Pc-Deployment.yaml spec: strategy: type: RollingUpdate rollingUpdate: maxSurge: 33% maxUnavailable: 33% [root@master yaml]# kubectl apply -f Pc-Deployment.yaml deployment.apps/pc-deployment configured # 更变镜像 [root@master yaml]# kubectl set image deployment pc-deployment nginx=docker.io/library/nginx:latest -n default deployment.apps/pc-deployment image updated # 查看升级过程 [root@master yaml]# kubectl get pod -n default -w pc-deployment-6895856946-47gjm 1/1 Running 0 2m33s pc-deployment-6895856946-4rhkr 1/1 Running 0 2m32s pc-deployment-6895856946-6xg5w 1/1 Running 0 2m30s pc-deployment-74556686fb-7bz2k 0/1 Pending 0 0s pc-deployment-74556686fb-7bz2k 0/1 ContainerCreating 0 0s pc-deployment-74556686fb-7bz2k 1/1 Running 0 1s pc-deployment-6895856946-47gjm 1/1 Terminating 0 2m43s pc-deployment-74556686fb-xnvx5 0/1 Pending 0 0s pc-deployment-74556686fb-xnvx5 0/1 ContainerCreating 0 0s pc-deployment-74556686fb-xnvx5 1/1 Running 0 2s pc-deployment-6895856946-4rhkr 1/1 Terminating 0 2m44s pc-deployment-74556686fb-zgrss 0/1 Pending 0 0s pc-deployment-74556686fb-zgrss 0/1 ContainerCreating 0 0s pc-deployment-74556686fb-zgrss 1/1 Running 0 1s pc-deployment-6895856946-6xg5w 1/1 Terminating 0 2m43s # 至此,新版本的pod创建完毕,旧版本的pod销毁完毕滚动更新的过程如下:版本回退在镜像更新之后,查看rs的变化,变化如下# 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3,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 yaml]# kubectl get rs -n default NAME DESIRED CURRENT READY AGE pc-deployment-6696798b78 0 0 0 7m37s pc-deployment-6696798b11 0 0 0 5m37s pc-deployment-c848d76789 3 3 3 72sdeployment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,命令如下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 yaml]# kubectl rollout status deploy pc-deployment -n default deployment "pc-deployment" successfully rolled out # 查看升级历史记录 [root@master yaml]# kubectl rollout history deploy pc-deployment -n default 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 # 版本回滚 # --to-revision=1 # 1是最初创建的版本,2是上一个,3是现在的 [root@master yaml]# kubectl rollout undo deployment pc-deployment --to-revision=1 -n default deployment.apps/pc-deployment rolled back # 查看发现,通过nginx镜像版本可以发现到了最初版本 [root@master yaml]# kubectl get deploy -n default -o wide NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR pc-deployment 3/3 1 3 47m nginx docker.io/library/nginx:1.32.1 app=nginx-pod # 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 [root@master yaml]# kubectl get rs -n default NAME DESIRED CURRENT READY AGE pc-deployment-6696798b78 3 3 3 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。# 更新deployment的版本,并配置暂停deployment [root@master yaml]# kubectl set image deploy pc-deployment nginx=docker.io/library/nginx:latest -n default && kubectl rollout pause deployment pc-deployment -n default deployment.apps/pc-deployment image updated deployment.apps/pc-deployment paused # 查看更新状态 [root@master yaml]# kubectl rollout status deploy pc-deployment -n default  Waiting for deployment "pc-deployment" rollout to finish: 1 out of 3 new replicas have been updated... # 查看rs [root@master yaml]# kubectl get rs -n default -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES pc-deployment-5d89bdfbf9 2 2 2 19m nginx docker.io/library/nginx:1.32.1 pc-deployment-675d469f8b 0 0 0 14m nginx docker.io/library/nginx:latest pc-deployment-6c9f56fcfb 1 1 1 3m16s nginx docker.io/library/nginx:1.32.1 # 查看Pod [root@master yaml]# kubectl get rs -n default -o wide 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-6c9f56fcfb-j2gtj 1/1 Running 0 3m31s # 继续更新 [root@master yaml]# kubectl rollout resume deploy pc-deployment -n default deployment.apps/pc-deployment resumed # 查看rs [root@master yaml]# kubectl get rs -n default -o wide NAME DESIRED CURRENT READY AGE CONTAINERS IMAGES pc-deployment-5d89bdfbf9 0 0 0 21m nginx docker.io/library/nginx:1.32.1 pc-deployment-675d469f8b 0 0 0 16m nginx docker.io/library/nginx:latest pc-deployment-6c9f56fcfb 3 3 3 5m11s nginx docker.io/library/nginx:1.32.1 # 查看Pod [root@master yaml]# kubectl get pods -n default NAME READY STATUS RESTARTS AGE pc-deployment-6c9f56fcfb-996rt 1/1 Running 0 5m27s pc-deployment-6c9f56fcfb-7bfwh 1/1 Running 0 37s pc-deployment-6c9f56fcfb-rf84v 1/1 Running 0 37s删除deploy# 删除deployment,deploy管理的rs和pod将也会被删除 [root@master yaml]# kubectl delete -f Pc-Deployment.yaml deployment.apps "pc-deployment" deletedDaemonSet(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。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 也就被垃圾回收了资源清单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 spec: # 详情描述 revisionHistoryLimit: <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 - {key: value} 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: spec: containers: - name: image: ports:创建DS创建文件Pc-Daemonset.yaml,内容如下apiVersion: apps/v1 kind: DaemonSet metadata: name: pc-daemonset namespace: default spec: selector: matchLabels: app: nginx-pod template: metadata: labels: app: nginx-pod spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1# 创建DS [root@master yaml]# kubectl create -f Pc-Daemonset.yaml daemonset.apps/pc-daemonset created # 查看DS [root@master yaml]# kubectl get ds -n default -o wide NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE CONTAINERS IMAGES SELECTOR pc-daemonset 2 2 2 2 2 <none> 104s nginx docker.io/library/nginx:1.23.1 app=nginx-pod # 查看pod,发现在每个work节点上都运行一个pod [root@master yaml]# kubectl get pods -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pc-daemonset-h6q4b 1/1 Running 0 2m23s 10.244.67.78 work1.host.com <none> <none> pc-daemonset-lghrj 1/1 Running 0 2m23s 10.244.52.209 work2.host.com <none> <none>删除DS# 删除DS [root@master yaml]# kubectl delete -f Pc-dDaemonset.yaml daemonset.apps "pc-daemonset" deletedJob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将完成执行资源清单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: <可运行时间期限> # 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: false # 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 - {key: value} 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: spec: restartPolicy: <重启策略> # 重启策略只能设置为Never或者OnFailure containers: - name: image: command: 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Job创建Pc-Job.yaml,内容如下apiVersion: batch/v1 kind: Job metadata: name: pc-job namespace: default spec: manualSelector: true selector: matchLabels: app: counter-pod template: metadata: labels: app: counter-pod spec: restartPolicy: Never containers: - name: counter image: docker.io/library/busybox:1.35.0 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 yaml]# kubectl create -f Pc-Job.yaml job.batch/pc-job created # 持续观察Job状态 [root@master yaml]# kubectl get job -n default -o wide -w NAME COMPLETIONS DURATION AGE CONTAINERS IMAGES SELECTOR pc-job 0/1 1s 1s counter docker.io/library/busybox:1.35.0 app=counter-pod pc-job 0/1 3s 3s counter docker.io/library/busybox:1.35.0 app=counter-pod # 查看Pod状态 # 可以发现pod运行完命令之后就会边车Completed [root@master yaml]# kubectl get pod -n default -o wide -w NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pc-job-6qwpd 1/1 Running 0 29s 10.244.67.81 work1.host.com <none> <none> pc-job-6qwpd 0/1 Completed 0 119s 10.244.67.81 work1.host.com <none> <none>删除Job# 删除job [root@master yaml]# kubectl delete -f Pc-Job.yaml job.batch "pc-job" deletedCronJob(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。资源清单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: matchExpressions: 规则 - {key: app, operator: In, values: [counter-pod]} template: metadata: labels: spec: restartPolicy: containers: - name: image: command: 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CJ创建Pc-Cronjob.yaml,内容如下:apiVersion: batch/v1beta1 kind: CronJob metadata: name: pc-cronjob namespace: default labels: controller: cronjob spec: schedule: "*/1 * * * *" jobTemplate: metadata: spec: template: spec: restartPolicy: Never containers: - name: counter image: docker.io/library/busybox:1.35.0 command: ["bin/sh","-c","for i in 9 8 7 6 5 4 3 2 1; do echo $i;sleep 3;done"]# 创建CJ [root@master yaml]# kubectl create -f Pc-Cronjob.yaml Warning: batch/v1beta1 CronJob is deprecated in v1.21+, unavailable in v1.25+; use batch/v1 CronJob cronjob.batch/pc-cronjob created # 查看CJ [root@master yaml]# kubectl get cronjobs -n default NAME SCHEDULE SUSPEND ACTIVE LAST SCHEDULE AGE pc-cronjob */1 * * * * False 1 9s 58s # 查看job [root@master yaml]# kubectl get job -n default NAME COMPLETIONS DURATION AGE pc-cronjob-27705149 0/1 2m8s 2m8s pc-cronjob-27705150 0/1 68s 68s pc-cronjob-27705151 0/1 8s 8s # 查看pod [root@master yaml]# kubectl get pods -n default NAME READY STATUS RESTARTS AGE pc-cronjob-27705149-kms26 0/1 Completed 0 2m37s pc-cronjob-27705150-2mvkv 0/1 Completed 0 97s pc-cronjob-27705151-dvr8c 1/1 Running 0 37s删除CJ[root@master yaml]# kubectl delete -f Pc-Cronjob.yaml Warning: batch/v1beta1 CronJob is deprecated in v1.21+, unavailable in v1.25+; use batch/v1 CronJob cronjob.batch "pc-cronjob" deleted Kubernetes-容器编排引擎(Pod详解) https://blog.boychai.xyz/index.php/archives/26/ 2022-08-29T14:25:00+00:00 概述Pod什么是Pod?Pod 是在 Kubernetes 中创建和管理的、最小的可部署的计算单元。Pod(就像在鲸鱼荚或者豌豆荚中)是一组(一个或多个) 容器; 这些容器共享存储、网络、以及怎样运行这些容器的声明。 Pod 中的内容总是并置(colocated)的并且一同调度,在共享的上下文中运行。 Pod 所建模的是特定于应用的 “逻辑主机”,其中包含一个或多个应用容器, 这些容器相对紧密地耦合在一起。 在非云环境中,在相同的物理机或虚拟机上运行的应用类似于在同一逻辑主机上运行的云应用。Pod的结构每一个Pod都可以包含一个或者多个容器,这些容器分为两种:程序容器,业务容器,数量可多可少Pause容器,这是每个Pod都会有的一个根容器,他的作用有两个:可以以它为依据,评估整个Pod的健康状态可以在跟容器上设置ip地址,其他容器都用此ip(Pod IP),以实现Pod内部的网络通信资源清单apiVersion: v1 #必选,版本号,例如v1 kind: Pod   #必选,资源类型,例如 Pod metadata:   #必选,元数据 name: string #必选,Pod名称 namespace: string #Pod所属的命名空间,默认为"default" labels:    #自定义标签列表 - name: string   spec: #必选,Pod中容器的详细定义 containers: #必选,Pod中容器列表 - name: string #必选,容器名称 image: string #必选,容器的镜像名称 imagePullPolicy: [ Always|Never|IfNotPresent ] #获取镜像的策略 command: [string] #容器的启动命令列表,如不指定,使用打包时使用的启动命令 args: [string] #容器的启动命令参数列表 workingDir: string #容器的工作目录 volumeMounts: #挂载到容器内部的存储卷配置 - name: string #引用pod定义的共享存储卷的名称,需用volumes[]部分定义的的卷名 mountPath: string #存储卷在容器内mount的绝对路径,应少于512字符 readOnly: boolean #是否为只读模式 ports: #需要暴露的端口库号列表 - name: string #端口的名称 containerPort: int #容器需要监听的端口号 hostPort: int #容器所在主机需要监听的端口号,默认与Container相同 protocol: string #端口协议,支持TCP和UDP,默认TCP env: #容器运行前需设置的环境变量列表 - name: string #环境变量名称 value: string #环境变量的值 resources: #资源限制和请求的设置 limits: #资源限制的设置 cpu: string #Cpu的限制,单位为core数,将用于docker run --cpu-shares参数 memory: string #内存限制,单位可以为Mib/Gib,将用于docker run --memory参数 requests: #资源请求的设置 cpu: string #Cpu请求,容器启动的初始可用数量 memory: string #内存请求,容器启动的初始可用数量 lifecycle: #生命周期钩子 postStart: #容器启动后立即执行此钩子,如果执行失败,会根据重启策略进行重启 preStop: #容器终止前执行此钩子,无论结果如何,容器都会终止 livenessProbe: #对Pod内各容器健康检查的设置,当探测无响应几次后将自动重启该容器 exec:   #对Pod容器内检查方式设置为exec方式 command: [string] #exec方式需要制定的命令或脚本 httpGet: #对Pod内个容器健康检查方法设置为HttpGet,需要制定Path、port path: string port: number host: string scheme: string HttpHeaders: - name: string value: string tcpSocket: #对Pod内个容器健康检查方式设置为tcpSocket方式 port: number initialDelaySeconds: 0 #容器启动完成后首次探测的时间,单位为秒 timeoutSeconds: 0    #对容器健康检查探测等待响应的超时时间,单位秒,默认1秒 periodSeconds: 0    #对容器监控检查的定期探测时间设置,单位秒,默认10秒一次 successThreshold: 0 failureThreshold: 0 securityContext: privileged: false restartPolicy: [Always | Never | OnFailure] #Pod的重启策略 nodeName: <string> #设置NodeName表示将该Pod调度到指定到名称的node节点上 nodeSelector: obeject #设置NodeSelector表示将该Pod调度到包含这个label的node上 imagePullSecrets: #Pull镜像时使用的secret名称,以key:secretkey格式指定 - name: string hostNetwork: false #是否使用主机网络模式,默认为false,如果设置为true,表示使用宿主机网络 volumes: #在该pod上定义共享存储卷列表 - name: string #共享存储卷名称 (volumes类型有很多种) emptyDir: {} #类型为emtyDir的存储卷,与Pod同生命周期的一个临时目录。为空值 hostPath: string #类型为hostPath的存储卷,表示挂载Pod所在宿主机的目录 path: string    #Pod所在宿主机的目录,将被用于同期中mount的目录 secret:    #类型为secret的存储卷,挂载集群与定义的secret对象到容器内部 scretname: string items: - key: string path: string configMap: #类型为configMap的存储卷,挂载预定义的configMap对象到容器内部 name: string items: - key: string path: stringPod配置基本配置创建一个名字为Pod-Basic.yaml文件,内容如下:apiVersion: v1 kind: Pod metadata: name: pod-basic namespace: default labels: app: pod spec: containers: - name: mynginx image: docker.io/library/nginx:1.23.1 - name: mybusybox image: docker.io/library/busybox:1.35.0上面定义了一个比较简单Pod的配置,名字叫做"pod-basic",命名空间在"default"下, 并给他打了一个标签叫做"app:pod",并定义了两个容器:mynginx: 使用docker镜像仓库的nginx镜像版本为1.23.1busybox: 使用docker镜像仓库的busybox镜像版本为2.4.54定义好资源清单之后可以使用下面的命令进行管理:# 创建pod [root@master yaml]# kubectl create -f Pod-Basic.yaml pod/pod-basic created # 查看pod状态 # "-n default"是指定命名空间,这里不加也可以查询到,因为不加默认查询的就是default命名空间下的资源 # READY 1/2 表示当前Pod中有2个容器,其中1个准备就绪,1个未就绪 # RESTARTS 重启次数,因为有1个容器故障了,Pod一直在重启试图恢复它 [root@master yaml]# kubectl get pod -n default NAME READY STATUS RESTARTS AGE pod-basic 1/2 NotReady 2 (29s ago) 43s # 查看pod的详细信息 [root@master yaml]# kubectl describe pod pod-basic -n default镜像拉取创建Pod-ImagePull.yaml文件,内容如下:apiVersion: v1 kind: Pod metadata: name: pod-imagepull namespace: default spec: containers: - name: mynginx image: docker.io/library/nginx:1.23.1 imagePullPolicy: Always # 设置镜像拉取策略 - name: mybusybox image: docker.io/library/busybox:2.4.54imagePullPolicy,用于设置镜像拉取策略,kubernetes支持配置三种拉取策略:Always:总是从远程仓库拉取镜像(一直远程下载)IfNotPresent:本地有则使用本地镜像,本地没有则从远程仓库拉取镜像(本地有就本地 本地没远程下载)Never:只使用本地镜像,从不去远程仓库拉取,本地没有就报错 (一直使用本地)默认值说明:​ 如果镜像tag为具体版本号, 默认策略是:IfNotPresent​ 如果镜像tag为:latest(最终版本) ,默认策略是always# 创建pod [root@master yaml]# kubectl create -f Pod-ImagePull.yaml pod/pod-imagepull created # 查看Pod详情 # 此时明显可以看到nginx镜像有一步Pulling image "nginx:1.17.1"的过程 [root@master yaml]# kubectl describe pod pod-imagepull -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 5s default-scheduler Successfully assigned default/pod-imagepull to work1.host.com Normal Pulling 4s kubelet Pulling image "docker.io/library/nginx:1.23.1" Normal Pulled 1s kubelet Successfully pulled image "docker.io/library/nginx:1.23.1" in 2.762104819s Normal Created 1s kubelet Created container mynginx Normal Started 1s kubelet Started container mynginx Normal Pulled 1s (x2 over 1s) kubelet Container image "docker.io/library/busybox:1.35.0" already present on machine Normal Created 1s (x2 over 1s) kubelet Created container mybusybox Normal Started 1s kubelet Started container mybusybox启动命令在上面的配置中mybusybox容器一直没有成功运行,原因就是mybusybox容器不是一个程序,而是一个类似于一个工具类的合集,kubernetes集群启动后,会因为没有程序支撑运行而关闭容器。解决方法就是让他一直运行一个命令或者程。创建Pod-Command.yaml文件,内容如下:apiVersion: v1 kind: Pod metadata: name: pod-command namespace: default labels: app: pod spec: containers: - name: mynginx image: docker.io/library/nginx:1.23.1 - name: mybusybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","touch /tmp/hello.txt;while true;do /bin/echo $(date +%T) >> /tmp/hello.txt; sleep 3; done;"]command:在pod中的容器初始化完成之后运行的命令。命令解释:​ "/bin/sh","-c" 使用sh来执行命令​ touch /tmp/hello.txt; 在/tmp下创建一个hello.txt文件​ while true;do /bin/echo $(date +%T) >> /tmp/hello.txt; sleep 3; done;每过三秒就往/tmp/hello.txt文件里面追加当前的时间# 创建pod [root@master yaml]# kubectl create -f Pod-Command.yaml pod/pod-command created # 查看Pod状态 # 这个时候俩容器就都正常运行了 [root@master yaml]# kubectl get pod [root@master yaml]# kubectl get pod NAME READY STATUS RESTARTS AGE pod-command 2/2 Running 0 1m38s # 进入容器查看文件内容 [root@master yaml]# kubectl exec pod-command -n default -it -c mybusybox /bin/sh / # tail -f /tmp/hello.txt 12:55:27 12:55:30 12:55:33 12:55:36 12:55:39 12:55:42特别说明: 通过上面发现command已经可以完成启动命令和传递参数的功能,为什么这里还要提供一个args选项,用于传递参数呢?这其实跟docker有点关系,kubernetes中的command、args两项其实是实现覆盖Dockerfile中ENTRYPOINT的功能。 1 如果command和args均没有写,那么用Dockerfile的配置。 2 如果command写了,但args没有写,那么Dockerfile默认的配置会被忽略,执行输入的command 3 如果command没写,但args写了,那么Dockerfile中配置的ENTRYPOINT的命令会被执行,使用当前args的参数 4 如果command和args都写了,那么Dockerfile的配置被忽略,执行command并追加上args参数环境变量创建Pod-Env.yaml文件,内容如下:apiVersion: v1 kind: Pod metadata: name: pod-env namespace: default spec: containers: - name: mybusybox image: docker.io/library/busybox:1.35.0 command: ["/bin/sh","-c","while true;do /bin/echo $(date +%T);sleep 60; done;"] env: # 设置环境变量列表 - name: "username" value: "admin" - name: "password" value: "123456"env: 环境变量,用于在pod中的容器设置环境变量。# 创建pod [root@master yaml]# kubectl create -f Pod-Env.yaml pod/pod-env created # 进入容器,输出环境变量 [root@master yaml]# kubectl exec pod-env -n default -c mybusybox -it /bin/sh / # echo $username admin / # echo $password 123456这种方式不是很推荐,推荐将这些配置单独存储在配置文件中,这种方式将在后面介绍。端口设置要对容器的端口设置需要对containers的ports选项进行修改,先看一下ports支持的子选项[root@master yaml]# kubectl explain pod.spec.containers.ports KIND: Pod VERSION: v1 RESOURCE: ports <[]Object> DESCRIPTION: List of ports to expose from the container. Exposing a port here gives the system additional information about the network connections a container uses, but is primarily informational. Not specifying a port here DOES NOT prevent that port from being exposed. Any port which is listening on the default "0.0.0.0" address inside a container will be accessible from the network. Cannot be updated. ContainerPort represents a network port in a single container. FIELDS: containerPort <integer> -required- # 容器要监听的端口(0<x<65536) Number of port to expose on the pod's IP address. This must be a valid port number, 0 < x < 65536. hostIP <string> # 要将外部端口绑定到的主机IP(一般省略) What host IP to bind the external port to. hostPort <integer> # 容器要在主机上公开的端口,如果设置,主机上只能运行容器的一个副本(一般省略) Number of port to expose on the host. If specified, this must be a valid port number, 0 < x < 65536. If HostNetwork is specified, this must match ContainerPort. Most containers do not need this. name <string> # 端口名称,如果指定,必须保证name在pod中是唯一的 If specified, this must be an IANA_SVC_NAME and unique within the pod. Each named port in a pod must have a unique name. Name for the port that can be referred to by services. protocol <string> # 端口协议。必须是UDP、TCP或SCTP。默认为“TCP”。 Protocol for port. Must be UDP, TCP, or SCTP. Defaults to "TCP". Possible enum values: - `"SCTP"` is the SCTP protocol. - `"TCP"` is the TCP protocol. - `"UDP"` is the UDP protocol.创建Pod-Ports.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-ports namespace: default spec: containers: - name: mynginx image: docker.io/library/nginx:1.23.1 ports: # 设置容器暴露的端口列表 - name: nginx-port containerPort: 80 protocol: TCP# 创建Pod [root@master yaml]# kubectl create -f Pod-Ports.yaml pod/pod-ports created # 查看pod # 在下面可以明显看到配置信息 [root@master ~]# [root@master yaml]# kubectl get pod pod-ports -n default -o yaml ...... spec: containers: - image: docker.io/library/nginx:1.23.1 imagePullPolicy: IfNotPresent name: mynginx ports: - containerPort: 80 name: nginx-port protocol: TCP ...... podIP: 10.244.52.207 ...... # 访问服务 # 访问容器中的程序需要使用的是`podIp:containerPort` [root@master yaml]# curl http://10.244.52.207:80 <!DOCTYPE html> <html> <head> <title>Welcome to nginx!</title> <style> html { color-scheme: light dark; } body { width: 35em; margin: 0 auto; font-family: Tahoma, Verdana, Arial, sans-serif; } </style> </head> <body> <h1>Welcome to nginx!</h1> <p>If you see this page, the nginx web server is successfully installed and working. Further configuration is required.</p> <p>For online documentation and support please refer to <a href="http://nginx.org/">nginx.org</a>.<br/> Commercial support is available at <a href="http://nginx.com/">nginx.com</a>.</p> <p><em>Thank you for using nginx.</em></p> </body> </html>资源配额容器中的程序要运行,肯定是要占用一定资源的,比如cpu和内存等,如果不对某个容器的资源做限制,那么它就可能吃掉大量资源,导致其它容器无法运行。针对这种情况,kubernetes提供了对内存和cpu的资源进行配额的机制,这种机制主要通过resources选项实现,他有两个子选项:limits:用于限制运行时容器的最大占用资源,当容器占用资源超过limits时会被终止,并进行重启requests :用于设置容器需要的最小资源,如果环境资源不够,容器将无法启动可以通过上面两个选项设置资源的上下限。创建Pod-Resources.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-resources namespace: default spec: containers: - name: mynginx image: docker.io/library/nginx:1.23.1 resources: # 资源配额 limits: # 限制资源(上限) cpu: "2" # CPU限制,单位是core数 memory: "10Gi" # 内存限制 requests: # 请求资源(下限) cpu: "1" # CPU限制,单位是core数 memory: "10Mi" # 内存限制CPU和Memory的单位说明:CPU: core数,可以为整数或小数Memory: 内存大小,可以使用Gi、Mi、G、M等形式# 创建Pod [root@master yaml]# kubectl create -f Pod-Resources.yaml pod/pod-resources created # 查看发现pod运行状态 [root@master yaml]# kubectl get pod pod-resources -n default NAME READY STATUS RESTARTS AGE pod-resources 1/1 Running 0 88s # 删除Pod [root@master yaml]# kubectl delete -f Pod-Resources.yaml pod "pod-resources" deleted # 编辑Pod-Resources.yaml,修改requests的限制 ...... requests: cpu: "1" memory: "10Gi" ...... # 创建Pod [root@master yaml]# kubectl create -f Pod-Resources.yaml pod/pod-resources created # 查看Pod状态,Pod启动失败 [root@master yaml]# kubectl get pod pod-resources -n default NAME READY STATUS RESTARTS AGE pod-resources 0/1 Pending 0 29s # 查看Pod详细信息会看到报错 [root@master yaml]# kubectl describe pod pod-resources -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 97s default-scheduler 0/3 nodes are available: 1 node(s) had untolerated taint {node-role.kubernetes.io/master: }, 3 Insufficient memory. preemption: 0/3 nodes are available: 1 Preemption is not helpful for scheduling, 2 No preemption victims found for incoming pod. # 上面的报错指三个节点内存不足Pod生命周期生命周期过程Pod生命周期一般是Pod对象从创建至终的这段时间范围称为pod的生命周期,它主要包含下面的过程:pod创建过程运行初始化容器(init container)过程运行主容器(main container)容器启动后钩子(post start)、容器终止前钩子(pre stop)容器的存活性探测(liveness probe)、就绪性探测(readiness probe)pod终止过程在整个生命周期中,Pod会出现5种状态(相位),分别如下:挂起(Pending):apiserver已经创建了pod资源对象,但它尚未被调度完成或者仍处于下载镜像的过程中运行中(Running):pod已经被调度至某节点,并且所有容器都已经被kubelet创建完成成功(Succeeded):pod中的所有容器都已经成功终止并且不会被重启失败(Failed):所有容器都已经终止,但至少有一个容器终止失败,即容器返回了非0值的退出状态未知(Unknown):apiserver无法正常获取到pod对象的状态信息,通常由网络通信失败所导致创建和终止pod的创建过程用户通过kubectl或其他api客户端提交需要创建的pod信息给apiServerapiServer开始生成pod对象的信息,并将信息存入etcd,然后返回确认信息至客户端apiServer开始反映etcd中的pod对象的变化,其它组件使用watch机制来跟踪检查apiServer上的变动scheduler发现有新的pod对象要创建,开始为Pod分配主机并将结果信息更新至apiServernode节点上的kubelet发现有pod调度过来,尝试调用启动容器,并将结果回送至apiServerapiServer将接收到的pod状态信息存入etcd中pod的终止过程用户向apiServer发送删除pod对象的命令apiServcer中的pod对象信息会随着时间的推移而更新,在宽限期内(默认30s),pod被视为dead将pod标记为terminating状态kubelet在监控到pod对象转为terminating状态的同时启动pod关闭过程端点控制器监控到pod对象的关闭行为时将其从所有匹配到此端点的service资源的端点列表中移除如果当前pod对象定义了preStop钩子处理器,则在其标记为terminating后即会以同步的方式启动执行pod对象中的容器进程收到停止信号宽限期结束后,若pod中还存在仍在运行的进程,那么pod对象会收到立即终止的信号kubelet请求apiServer将此pod资源的宽限期设置为0从而完成删除操作,此时pod对于用户已不可见初始化容器初始化容器是在pod的主容器启动之前要运行的容器,主要是做一些主容器的前置工作,它具有两大特征:初始化容器必须运行完成直至结束,若某初始化容器运行失败,那么kubernetes需要重启它直到成功完成初始化容器必须按照定义的顺序执行,当且仅当前一个成功之后,后面的一个才能运行初始化容器有很多的应用场景,下面列出的是最常见的几个:提供主容器镜像中不具备的工具程序或自定义代码初始化容器要先于应用容器串行启动并运行完成,因此可用于延后应用容器的启动直至其依赖的条件得到满足假设要以主容器运行一个web程序,但是要求在运行之前需要能够连接上mysql和redis所在的服务器,为了方便测试,事先规划好数据库服务器地址。创建文件Pod-InitContainer.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-initcontainer namespace: default spec: containers: - name: main-container image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 initContainers: - name: test-mysql image: docker.io/library/busybox:1.35.0 command: ['sh', '-c', 'until ping 192.16.1.100 -c 1 ; do echo waiting for mysql...; sleep 2; done;'] - name: test-redis image: docker.io/library/busybox:1.35.0 command: ['sh', '-c', 'until ping 192.16.1.200 -c 1 ; do echo waiting for reids...; sleep 2; done;']# 创建Pod [root@master yaml]# kubectl create -f Pod-InitContainer.yaml pod/pod-initcontainer created # 查看状态 # 发现pod一直卡在第一个初始化容器过程中,后面的容器不会运行 [root@master yaml]# kubectl describe pod pod-initcontainer -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 66s default-scheduler Successfully assigned default/pod-initcontainer to work1.host.com Normal Pulled 66s kubelet Container image "docker.io/library/busybox:1.35.0" already present on machine Normal Created 66s kubelet Created container test-mysql Normal Started 66s kubelet Started container test-mysql # 动态查看pod状态 [root@master yaml]# kubectl get pods pod-initcontainer -n default -w NAME READY STATUS RESTARTS AGE pod-initcontainer 0/1 Init:0/2 0 5m1s pod-initcontainer 0/1 Init:1/2 0 5m4s pod-initcontainer 0/1 Init:1/2 0 5m5s pod-initcontainer 0/1 PodInitializing 0 5m17s pod-initcontainer 1/1 Running 0 5m18s # 开一个新的终端链接并执行以下命令查看pod状态 [root@master ~]# ifconfig ens33:1 192.16.1.100 netmask 255.255.255.0 up [root@master ~]# ifconfig ens33:1 192.16.1.200 netmask 255.255.255.0 up钩子函数钩子函数能够感知自身生命周期中的事件,并在相应的时刻到来时运行用户指定的程序代码。kubernetes在主容器的启动之后和停止之前提供了两个钩子函数:post start:容器创建之后执行,如果失败了会重启容器pre stop :容器终止之前执行,执行完成之后容器将成功终止,在其完成之前会阻塞删除容器的操作钩子处理器支持使用下面三种方式定义动作:Exec命令:在容器内执行一次命令…… lifecycle: postStart: exec: command: - cat - /tmp/healthy ……TCPSocket:在当前容器尝试访问指定的socket…… lifecycle: postStart: tcpSocket: port: 8080 ……HTTPGet:在当前容器中向某url发起http请求…… lifecycle: postStart: httpGet: path: / #URI地址 port: 80 #端口号 host: 192.168.109.100 #主机地址 scheme: HTTP #支持的协议,http或者https ……以exec方式为例,创建Pod-Hook-Exec.yaml文件,内容如下apiVersion: v1 kind: Pod metadata: name: pod-hook-exec namespace: default spec: containers: - name: main-container image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 lifecycle: postStart: exec: # 在容器启动的时候执行一个命令,修改掉nginx的默认首页内容 command: ["/bin/sh", "-c", "echo postStart... > /usr/share/nginx/html/index.html"] preStop: exec: # 在容器停止之前停止nginx服务 command: ["/usr/sbin/nginx","-s","quit"]# 创建Pod [root@master yaml]# kubectl create -f Pod-Hook-Exec.yaml pod/pod-hook-exec created # 查看Pod [root@master yaml]# kubectl get pods pod-hook-exec -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-hook-exec 1/1 Running 0 52s 10.244.52.213 work2.host.com <none> <none> # 访问Pod [root@master yaml]# curl 10.244.52.213 postStart...容器探测容器探测用于检测容器中的应用实例是否正常工作,是保障业务可用性的一种传统机制。如果经过探测,实例的状态不符合预期,那么kubernetes就会把该问题实例" 摘除 ",不承担业务流量。kubernetes提供了两种探针来实现容器探测,分别是:liveness probes:存活性探针,用于检测应用实例当前是否处于正常运行状态,如果不是,k8s会重启容器readiness probes:就绪性探针,用于检测应用实例当前是否可以接收请求,如果不能,k8s不会转发流量livenessProbe 决定是否重启容器,readinessProbe 决定是否将请求转发给容器。上面两种探针目前均支持三种探测方式:Exec命令:在容器内执行一次命令,如果命令执行的退出码为0,则认为程序正常,否则不正常…… livenessProbe: exec: command: - cat - /tmp/healthy ……TCPSocket:将会尝试访问一个用户容器的端口,如果能够建立这条连接,则认为程序正常,否则不正常…… livenessProbe: tcpSocket: port: 8080 ……HTTPGet:调用容器内Web应用的URL,如果返回的状态码在200和399之间,则认为程序正常,否则不正常…… livenessProbe: httpGet: path: / #URI地址 port: 80 #端口号 host: 127.0.0.1 #主机地址 scheme: HTTP #支持的协议,http或者https ……以liveness probes为例,做几个演示:方式一:Exec创建Pod-Liveness-Exec.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-liveness-exec namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 livenessProbe: exec: command: ["/bin/cat","/tmp/hello.txt"] # 执行一个查看文件的命令# 创建Pod [root@master yaml]# kubectl create -f Pod-Liveness-Exec.yaml pod/pod-liveness-exec created # 查看Pod详情 # 发现nginx容器启动之后就进行了健康检查 # 检查失败之后容器就呗kill掉了,之后容器 [root@master yaml]# kubectl describe pods pod-liveness-exec -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 25s default-scheduler Successfully assigned default/pod-liveness-exec to work1.host.com Normal Pulled 24s kubelet Container image "docker.io/library/nginx:1.23.1" already present on machine Normal Created 24s kubelet Created container nginx Normal Started 24s kubelet Started container nginx Warning Unhealthy 5s (x2 over 15s) kubelet Liveness probe failed: /bin/cat: /tmp/hello.txt: No such file or directory # 查看Pod状态 # 发现RESTARTS一直在增长 [root@master yaml]# kubectl get pods pod-liveness-exec -n default NAME READY STATUS RESTARTS AGE pod-liveness-exec 0/1 CrashLoopBackOff 4 (12s ago) 2m43s方式二:TCPSocket创建Pod-Liveness-Tcpsocket.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-liveness-tcpsocket namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 livenessProbe: tcpSocket: port: 8080 # 尝试访问8080端口# 创建Pod [root@master yaml]# kubectl create -f Pod-Liveness-Tcpsocket.yaml pod/pod-liveness-tcpsocket created # 查看Pod详情 # 发现容器尝试访问8080端口,但是失败了 [root@master yaml]# kubectl describe pods pod-liveness-tcpsocket -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 31s default-scheduler Successfully assigned default/pod-liveness-tcpsocket to work1.host.com Normal Pulled 1s (x2 over 30s) kubelet Container image "docker.io/library/nginx:1.23.1" already present on machine Normal Created 1s (x2 over 30s) kubelet Created container nginx Normal Started 1s (x2 over 30s) kubelet Started container nginx Warning Unhealthy 1s (x3 over 21s) kubelet Liveness probe failed: dial tcp 10.244.67.89:8080: connect: connection refused Normal Killing 1s kubelet Container nginx failed liveness probe, will be restarted # 查看Pod状态 # 发现RESTARTS一直在增长 [root@master yaml]# kubectl get pods pod-liveness-tcpsocket -n default NAME READY STATUS RESTARTS AGE pod-liveness-tcpsocket 1/1 Running 4 (7s ago) 2m7s方式三:HTTPGet创建Pod-Liveness-Httpget.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-liveness-httpget namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 livenessProbe: httpGet: # 其实就是访问http://127.0.0.1:80/hello scheme: HTTP #支持的协议,http或者https port: 80 #端口号 path: /hello #URI地址# 创建Pod [root@master yaml]# kubectl create -f Pod-Liveness-Httpget.yaml pod/pod-liveness-httpget created # 查看Pod详情 [root@master yaml]# kubectl describe pod pod-liveness-httpget -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 22s default-scheduler Successfully assigned default/pod-liveness-httpget to work2.host.com Normal Pulled 22s kubelet Container image "docker.io/library/nginx:1.23.1" already present on machine Normal Created 21s kubelet Created container nginx Normal Started 21s kubelet Started container nginx Warning Unhealthy 2s (x2 over 12s) kubelet Liveness probe failed: HTTP probe failed with statuscode: 404 # 查看Pod状态 # 发现RESTARTS一直在增长 [root@master yaml]# kubectl get pod pod-liveness-httpget -n default NAME READY STATUS RESTARTS AGE pod-liveness-httpget 1/1 Running 2 (26s ago) 86s在LivenessProbe的子属性下还会发现一些其他的配置,这里简单解释一下含义:[root@master yaml]# kubectl explain pod.spec.containers.livenessProbe KIND: Pod VERSION: v1 RESOURCE: livenessProbe <Object> DESCRIPTION: Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated. More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic. FIELDS: exec <Object> Exec specifies the action to take. failureThreshold <integer> # 连续探测失败多少次才被认定为失败。默认是3。最小值是1 Minimum consecutive failures for the probe to be considered failed after having succeeded. Defaults to 3. Minimum value is 1. grpc <Object> GRPC specifies an action involving a GRPC port. This is a beta field and requires enabling GRPCContainerProbe feature gate. httpGet <Object> HTTPGet specifies the http request to perform. initialDelaySeconds <integer> # 容器启动后等待多少秒执行第一次探测 Number of seconds after the container has started before liveness probes are initiated. More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes periodSeconds <integer> # 执行探测的频率。默认是10秒,最小1秒 How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. successThreshold <integer> # 连续探测成功多少次才被认定为成功。默认是1 Minimum consecutive successes for the probe to be considered successful after having failed. Defaults to 1. Must be 1 for liveness and startup. Minimum value is 1. tcpSocket <Object> TCPSocket specifies an action involving a TCP port. terminationGracePeriodSeconds <integer> Optional duration in seconds the pod needs to terminate gracefully upon probe failure. The grace period is the duration in seconds after the processes running in the pod are sent a termination signal and the time when the processes are forcibly halted with a kill signal. Set this value longer than the expected cleanup time for your process. If this value is nil, the pod's terminationGracePeriodSeconds will be used. Otherwise, this value overrides the value provided by the pod spec. Value must be non-negative integer. The value zero indicates stop immediately via the kill signal (no opportunity to shut down). This is a beta field and requires enabling ProbeTerminationGracePeriod feature gate. Minimum value is 1. spec.terminationGracePeriodSeconds is used if unset. timeoutSeconds <integer> # 探测超时时间。默认1秒,最小1秒 Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes 设置探测详细时间参照下面配置apiVersion: v1 kind: Pod metadata: name: pod-liveness-httpget namespace: dev spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 livenessProbe: httpGet: scheme: HTTP port: 80 path: / initialDelaySeconds: 30 # 容器启动后30s开始探测 timeoutSeconds: 5 # 探测超时时间为5s重启策略在容器探测livenessProbe中一旦探测出现了问题,Kubernetes就会对容器所在的Pod进行重启,重启的方式是由pod的重启策略决定的,Pod的重启策略有三种,分别如下:Always :容器失效时,自动重启该容器,这也是默认值。OnFailure : 容器终止运行且退出码不为0时重启Never : 不论状态为何,都不重启该容器重启策略适用于pod对象中的所有容器,首次需要重启的容器,将在其需要时立即进行重启,随后再次需要重启的操作将由kubelet延迟一段时间后进行,且反复的重启操作的延迟时长以此为10s、20s、40s、80s、160s和300s,300s是最大延迟时长。创建Pod-Restartpolicy.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-restartpolicy namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 ports: - name: nginx-port containerPort: 80 livenessProbe: httpGet: scheme: HTTP port: 80 path: /hello restartPolicy: Never # 设置重启策略为Never# 创建Pod [root@master yaml]# kubectl create -f Pod-Restartpolicy.yaml pod/pod-restartpolicy created # 查看Pod详情,发现nginx容器的健康检查失败 [root@master yaml]# kubectl describe pods pod-restartpolicy -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 49s default-scheduler Successfully assigned default/pod-restartpolicy to work1.host.com Normal Pulled 48s kubelet Container image "docker.io/library/nginx:1.23.1" already present on machine Normal Created 48s kubelet Created container nginx Normal Started 48s kubelet Started container nginx Warning Unhealthy 19s (x3 over 39s) kubelet Liveness probe failed: HTTP probe failed with statuscode: 404 Normal Killing 19s kubelet Stopping container nginx # 过一会之后,查看pod的状态,发现重启次数一直是0 [root@master yaml]# kubectl get pods pod-restartpolicy -n default NAME READY STATUS RESTARTS AGE pod-restartpolicy 0/1 Completed 0 2m7sPod调度调度方式在默认情况下,一个Pod在哪个Node节点上运行,是由Scheduler组件采用相应的算法计算出来的,这个过程是不受人工控制的。但是在实际使用中,这并不满足的需求,因为很多情况下,控制某些Pod到达某些节点上,这就需要了解kubernetes对Pod的调度规则,kubernetes提供了四大类调度方式:自动调度:运行在哪个节点上完全由Scheduler经过一系列的算法计算得出定向调度:NodeName、NodeSelector亲和性调度:NodeAffinity、PodAffinity、PodAntiAffinity污点(容忍)调度:Taints、Toleration定向调度定向调度,指的是利用在pod上声明nodeName或者nodeSelector,以此将Pod调度到期望的node节点上。注意,这里的调度是强制的,这就意味着即使要调度的目标Node不存在,也会向上面进行调度,只不过pod运行失败而已NodeNameNodeName用于强制约束将Pod调度到指定的Name的Node节点上。这种方式,其实是直接跳过Scheduler的调度逻辑,直接将Pod调度到指定名称的节点。创建一个Pod-Nodename.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-nodename namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 nodeName: node1 # 指定调度到node1节点上# 创建Pod [root@master yaml]# kubectl create -f Pod-Nodename.yaml pod/pod-nodename created # 查看Pod具体状态和调度节点 # 发现Pod调度到了node1节点上,但是实则我的集群是没有这个节点的所以导致一直无法正常运行 [root@master yaml]# kubectl get pods pod-nodename -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-nodename 0/1 Pending 0 10s <none> node1 <none> <none> # 修改文件的nodeName为"work1.host.com"并更新配置 [root@master yaml]# vim Pod-Nodename.yaml [root@master yaml]# kubectl apply -f Pod-Nodename.yaml pod/pod-nodename created # 再次查看Pod的具体状态和调度节点 # 发现已经成功调度到其他节点并运行成功 [root@master yaml]# kubectl get pods pod-nodename -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-nodename 1/1 Running 0 34s 10.244.67.91 work1.host.com <none> <none>NodeSelectorNodeSelector用于将pod调度到添加了指定标签的node节点上。它是通过kubernetes的label-selector机制实现的,也就是说,在pod创建之前,会由scheduler使用MatchNodeSelector调度策略进行label匹配,找出目标node,然后将pod调度到目标节点,该匹配规则是强制约束。# 给节点创建标签 # 给work1.host.com节点创建了一个nodeenv=pro标签 # 给work2.host.com节点创建了一个nodeenv=test标签 [root@master yaml]# kubectl label nodes work1.host.com nodeenv=pro node/work1.host.com labeled [root@master yaml]# kubectl label nodes work2.host.com nodeenv=test node/work2.host.com labeled创建Pod-Nodeselector.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-nodeselector namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 nodeSelector: nodeenv: pro # 指定调度到具有nodeenv=pro标签的节点上# 创建Pod [root@master yaml]# kubectl create -f Pod-Nodeselector.yaml pod/pod-nodeselector created # 查看Pod的具体状态和调度节点 [root@master yaml]# kubectl get pods pod-nodeselector -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-nodeselector 1/1 Running 0 51s 10.244.67.92 work1.host.com <none> <none> # 之后删除pod,修改nodeSelector的值为nodeenv: pro2 (不存在打有此标签的节点) [root@master yaml]# kubectl delete -f Pod-Nodeselector.yaml pod "pod-nodeselector" deleted [root@master yaml]# vim Pod-Nodeselector.yaml [root@master yaml]# kubectl create -f Pod-Nodeselector.yaml pod/pod-nodeselector created # 再次查看Pod的具体状态和调度节点 # 发现调度节的值为<none> [root@master yaml]# kubectl get pods pod-nodeselector -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-nodeselector 0/1 Pending 0 43s <none> <none> <none> <none> # 通过查看Pod详情,发现node selector匹配失败的提示 [root@master yaml]# kubectl describe pods pod-nodeselector -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 118s default-scheduler 0/3 nodes are available: 1 node(s) had untolerated taint {node-role.kubernetes.io/master: }, 3 node(s) didn't match Pod's node affinity/selector. preemption: 0/3 nodes are available: 3 Preemption is not helpful for scheduling.亲和性调度使用定向调度进行调度时,如果出现没有满足条件的Node那么Pod就会不被运行,为了解决这个问题,Kubernetes在NodeSelector的基础之上的进行了扩展,通过配置的形式实现优先选择满足条件的Node进行调度,如果没有也可以调度到不满足条件的节点上,使其更加灵活。Affinity主要分为三类:nodeAffinity(node亲和性): 以node为目标,解决pod可以调度到哪些node的问题podAffinity(pod亲和性) : 以pod为目标,解决pod可以和哪些已存在的pod部署在同一个拓扑域中的问题podAntiAffinity(pod反亲和性) : 以pod为目标,解决pod不能和哪些已存在pod部署在同一个拓扑域中的问题关于亲和性(反亲和性)使用场景的说明:亲和性:如果两个应用频繁交互,那就有必要利用亲和性让两个应用的尽可能的靠近,这样可以减少因网络通信而带来的性能损耗。反亲和性:当应用的采用多副本部署时,有必要采用反亲和性让各个应用实例打散分布在各个node上,这样可以提高服务的高可用性。NodeAffinityNodeAffinity的可配置项如下:pod.spec.affinity.nodeAffinity requiredDuringSchedulingIgnoredDuringExecution Node节点必须满足指定的所有规则才可以,相当于硬限制 nodeSelectorTerms 节点选择列表 matchFields 按节点字段列出的节点选择器要求列表 matchExpressions 按节点标签列出的节点选择器要求列表(推荐) key 键 values 值 operator 关系符 支持Exists, DoesNotExist, In, NotIn, Gt, Lt preferredDuringSchedulingIgnoredDuringExecution 优先调度到满足指定的规则的Node,相当于软限制 (倾向) preference 一个节点选择器项,与相应的权重相关联 matchFields 按节点字段列出的节点选择器要求列表 matchExpressions 按节点标签列出的节点选择器要求列表(推荐) key 键 values 值 operator 关系符 支持In, NotIn, Exists, DoesNotExist, Gt, Lt weight 倾向权重,在范围1-100。关系符的使用说明: - matchExpressions: - key: nodeenv # 匹配存在标签的key为nodeenv的节点 operator: Exists - key: nodeenv # 匹配标签的key为nodeenv,且value是"xxx"或"yyy"的节点 operator: In values: ["xxx","yyy"] - key: nodeenv # 匹配标签的key为nodeenv,且value大于"xxx"的节点 operator: Gt values: "xxx"requiredDuringSchedulingIgnoredDuringExecution创建Pod-Nodeaffinity-Required.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-nodeaffinity-required namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 affinity: #亲和性设置 nodeAffinity: #设置node亲和性 requiredDuringSchedulingIgnoredDuringExecution: # 硬限制 nodeSelectorTerms: - matchExpressions: # 匹配env的值在["xxx","yyy"]中的标签 - key: nodeenv operator: In values: ["xxx","yyy"]# 创建Pod [root@master yaml]# kubectl create -f Pod-Nodeaffinity-Required.yaml pod/pod-nodeaffinity-required created # 查看Pod状态 # 发现Pod的NODE一直为<none> [root@master yaml]# kubectl get pods pod-nodeaffinity-required -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-nodeaffinity-required 0/1 Pending 0 21s <none> <none> <none> <none> # 查看Pod详情 # 发现提示node选择失败 [root@master yaml]# kubectl describe pod pod-nodeaffinity-required -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 105s default-scheduler 0/3 nodes are available: 1 node(s) had untolerated taint {node-role.kubernetes.io/master: }, 3 node(s) didn't match Pod's node affinity/selector. preemption: 0/3 nodes are available: 3 Preemption is not helpful for scheduling. # 删除Pod [root@master yaml]# kubectl delete -f Pod-Nodeaffinity-Required.yaml pod "pod-nodeaffinity-required" deleted # 修改Pod-Nodeaffinity-Required.yaml文件 # 将values: ["xxx","yyy"]------> ["pro","yyy"],并启动 [root@master yaml]# vim Pod-Nodeaffinity-Required.yaml [root@master yaml]# kubectl create -f Pod-Nodeaffinity-Required.yaml pod/pod-nodeaffinity-required created # 查看Pod信息 # 发现Pod已经成功调度到work1.host.com节点上 [root@master yaml]# kubectl get pods pod-nodeaffinity-required -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-nodeaffinity-required 1/1 Running 0 79s 10.244.67.107 work1.host.com <none> <none>requiredDuringSchedulingIgnoredDuringExecution创建Pod-Nodeaffinity-Preferred.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-nodeaffinity-preferred namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 affinity: #亲和性设置 nodeAffinity: #设置node亲和性 preferredDuringSchedulingIgnoredDuringExecution: # 软限制 - weight: 1 preference: matchExpressions: # 匹配env的值在["xxx","yyy"]中的标签(当前环境没有) - key: nodeenv operator: In values: ["xxx","yyy"]# 创建Pod [root@master yaml]# kubectl create -f Pod-Nodeaffinity-Preferred.yaml pod/pod-nodeaffinity-preferred created # 查看Pod状态 # 发现Pod成功调度 [root@master yaml]# kubectl get pod pod-nodeaffinity-preferred -n default NAME READY STATUS RESTARTS AGE pod-nodeaffinity-preferred 1/1 Running 0 27sNodeAffinity规则设置的注意事项: 1 如果同时定义了nodeSelector和nodeAffinity,那么必须两个条件都得到满足,Pod才能运行在指定的Node上 2 如果nodeAffinity指定了多个nodeSelectorTerms,那么只需要其中一个能够匹配成功即可 3 如果一个nodeSelectorTerms中有多个matchExpressions ,则一个节点必须满足所有的才能匹配成功 4 如果一个pod所在的Node在Pod运行期间其标签发生了改变,不再符合该Pod的节点亲和性需求,则系统将忽略此变化PodAffinityPodAffinity主要实现以运行的Pod为参照,实现让新创建的Pod跟参照pod在一个区域的功能。PodAffinity的可配置项如下pod.spec.affinity.podAffinity requiredDuringSchedulingIgnoredDuringExecution 硬限制 namespaces 指定参照pod的namespace topologyKey 指定调度作用域 labelSelector 标签选择器 matchExpressions 按节点标签列出的节点选择器要求列表(推荐) key 键 values 值 operator 关系符 支持In, NotIn, Exists, DoesNotExist. matchLabels 指多个matchExpressions映射的内容 preferredDuringSchedulingIgnoredDuringExecution 软限制 podAffinityTerm 选项 namespaces topologyKey labelSelector matchExpressions key 键 values 值 operator matchLabels weight 倾向权重,在范围1-100topologyKey用于指定调度时作用域,例如: 如果指定为kubernetes.io/hostname,那就是以Node节点为区分范围 如果指定为beta.kubernetes.io/os,则以Node节点的操作系统类型来区分requiredDuringSchedulingIgnoredDuringExecution创建一个参照Pod的清单Pod-Podaffinity-Target.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-podaffinity-target namespace: default labels: podenv: pro #设置标签 spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 nodeName: work1.host.com # 将目标pod名确指定到work1.host.com上# 创建Pod [root@master yaml]# kubectl create -f Pod-Podaffinity-Target.yaml pod/pod-podaffinity-target created # 查看Pod状态和调度节点 [root@master yaml]# kubectl get pods pod-podaffinity-target -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-podaffinity-target 1/1 Running 0 19m 10.244.67.108 work1.host.com <none> <none>创建Pod-Podaffinity-Required.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-podaffinity-required namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 affinity: #亲和性设置 podAffinity: #设置pod亲和性 requiredDuringSchedulingIgnoredDuringExecution: # 硬限制 - labelSelector: matchExpressions: # 匹配env的值在["xxx","yyy"]中的标签 - key: podenv operator: In values: ["xxx","yyy"] topologyKey: kubernetes.io/hostname上面的配置为匹配标签podenv=xxx或者podenv=yyy的容器的同一节点,现在还没有这样的Pod,下面运行测试一下# 创建Pod [root@master yaml]# kubectl create -f Pod-Podaffinity-Required.yaml pod/pod-podaffinity-required created # 查看Pod状态 # 发现创建失败 [root@master yaml]# kubectl get pods pod-podaffinity-required -n default NAME READY STATUS RESTARTS AGE pod-podaffinity-required 0/1 Pending 0 41s # 查看Pod详情 # 发现NODE节点调度失败 [root@master yaml]# kubectl describe pods pod-podaffinity-required -n default ...... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 85s default-scheduler 0/3 nodes are available: 1 node(s) had untolerated taint {node-role.kubernetes.io/master: }, 3 node(s) didn't match pod affinity rules. preemption: 0/3 nodes are available: 3 Preemption is not helpful for scheduling. # 删除Pod [root@master yaml]# kubectl delete -f Pod-Podaffinity-Required.yaml pod "pod-podaffinity-required" deleted # 修改Pod-Podaffinity-Required.yaml的values: ["xxx","yyy"]为values:["pro","yyy"] # 再次创建Pod [root@master yaml]# vim Pod-Podaffinity-Required.yaml [root@master yaml]# kubectl create -f Pod-Podaffinity-Required.yaml pod/pod-podaffinity-required created # 再次查看Pod状态 # 发现Pod已经成调度到参照Pod的节点 [root@master yaml]# kubectl get pods pod-podaffinity-required -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-podaffinity-required 1/1 Running 0 61s 10.244.67.109 work1.host.com <none> <none>PodAffinity的 preferredDuringSchedulingIgnoredDuringExecution,不再演示。PodAntiAffinityPodAntiAffinity主要实现以运行的Pod为参照,让新创建的Pod跟参照pod不在一个区域中的功能。PodAntiAffinty的配置方式适合PodAffinty是一样的,测试方法如下# 继续使用PodAffinity的Pod为参照Pod [root@master yaml]# kubectl get pods -n default -o wide --show-labels NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES LABELS pod-podaffinity-target 1/1 Running 0 28m 10.244.67.108 work1.host.com <none> <none> podenv=pro创建Pod-Podantiaffinity-Required.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-podantiaffinity-required namespace: default spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 affinity: #亲和性设置 podAntiAffinity: #设置pod亲和性 requiredDuringSchedulingIgnoredDuringExecution: # 硬限制 - labelSelector: matchExpressions: # 匹配podenv的值在["pro"]中的标签 - key: podenv operator: In values: ["pro"] topologyKey: kubernetes.io/hostname上面配置为新Pod必须要与拥有标签nodeenv=pro的pod不在同一Node上,运行测试一下# 创建Pod [root@master yaml]# kubectl create -f Pod-Podantiaffinity-Required.yaml pod/pod-podantiaffinity-required created # 查看Pod状态 # 发现Pod调度到了work2.host.com节点 [root@master yaml]# kubectl get pods pod-podantiaffinity-required -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-podantiaffinity-required 1/1 Running 0 2m13s 10.244.52.230 work2.host.com <none> <none>污点和容忍污点(Taints)前面的调度方式都是站在Pod的角度上,通过在Pod上添加属性,来确定Pod是否要调度到指定的Node上,其实我们也可以站在Node的角度上,通过在Node上添加污点属性,来决定是否允许Pod调度过来。Node被设置上污点之后就和Pod之间存在了一种相斥的关系,进而拒绝Pod调度进来,甚至可以将已经存在的Pod驱逐出去。污点的格式为:key=value:effect, key和value是污点的标签,effect描述污点的作用,支持如下三个选项:PreferNoSchedule:kubernetes将尽量避免把Pod调度到具有该污点的Node上,除非没有其他节点可调度NoSchedule:kubernetes将不会把Pod调度到具有该污点的Node上,但不会影响当前Node上已存在的PodNoExecute:kubernetes将不会把Pod调度到具有该污点的Node上,同时也会将Node上已存在的Pod驱离# 设置污点 kubectl taint nodes <节点> key=value:effect # 去除污点 kubectl taint nodes <节点> key:effect- # 去除所有污点 kubectl taint nodes <节点> key- # 查看污点 kubectl describe node <节点> ...... Taints: <none> ......已NoSchedule为例,创建Pod-Taints-Noschedule.yaml,内容如下apiVersion: v1 kind: Pod metadata: name: pod-taints-noschedule namespace: default labels: app: pod spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1# 为work1.host.com创建污点 [root@master yaml]# kubectl taint nodes work1.host.com region=qingdao:NoSchedule node/work1.host.com tainted # 为work2.host.com创建污点 [root@master yaml]# kubectl taint nodes work2.host.com region=beijing:NoSchedule node/work2.host.com tainted # 创建Pod [root@master yaml]# kubectl create -f Pod-Taints-Noschedule.yaml pod/pod-taints-noschedule created # 查看Pod状态 # 发现Pod未被调度到节点上面 [root@master yaml]# kubectl get pod -n default pod-taints-noschedule -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-taints-noschedule 0/1 Pending 0 38s <none> <none> <none> <none> # 查看Pod详情 # 发现集群3台NODE都有污点不能调度 [root@master yaml]# kubectl describe pod -n default pod-taints-noschedule Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 108s default-scheduler 0/3 nodes are available: 1 node(s) had untolerated taint {node-role.kubernetes.io/master: }, 1 node(s) had untolerated taint {region: beijing}, 1 node(s) had untolerated taint {region: qingdao}. preemption: 0/3 nodes are available: 3 Preemption is not helpful for scheduling.容忍(Toleration)污点就是拒绝,容忍就是忽略,Node通过污点拒绝pod调度上去,Pod通过容忍忽略拒绝。配置模板[root@master yaml]# kubectl explain pod.spec.tolerations ...... FIELDS: key # 对应着要容忍的污点的键,空意味着匹配所有的键 value # 对应着要容忍的污点的值 operator # key-value的运算符,支持Equal和Exists(默认) effect # 对应污点的effect,空意味着匹配所有影响 tolerationSeconds # 容忍时间, 当effect为NoExecute时生效,表示pod在Node上的停留时间创建Pod-Toleration.yaml,内容如下 apiVersion: v1 kind: Pod metadata: name: pod-toleration namespace: default labels: app: pod spec: containers: - name: nginx image: docker.io/library/nginx:1.23.1 tolerations: # 添加容忍 - key: "region" # 要容忍的污点的key operator: "Equal" # 操作符equal等于 value: "beijing" # 容忍的污点的value effect: "NoSchedule" # 添加容忍的规则,这里必须和标记的污点规则相同# 创建Pod [root@master yaml]# kubectl create -f Pod-Toleration.yaml pod/pod-toleration created # 查看Pod状态 # 发现成功调度到work2.host.com节点 [root@master yaml]# kubectl get pod pod-toleration -n default -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-toleration 1/1 Running 0 6s 10.244.52.232 work2.host.com <none> <none> Kubernetes-容器编排引擎(资源管理) https://blog.boychai.xyz/index.php/archives/25/ 2022-08-28T10:37:00+00:00 什么是资源?K8s中所有的内容都抽象为资源,资源实例化之后,叫做对象。资源列表工作负载类Pod、ReplicaSet、Deployment、StatefulSet、DaemonSet、Job、CronJob(ReplicationController在v1.11版本被废弃)服务发现和负载均衡类Service、Ingress、...存储类Volume、CSI配置类ConfigMap、Secret、DownwardAPI集群类Namespace、Node、Role、ClusterRole、RoleBinding、ClusterRoleBinding元数据类HPA、PodTemplate、LimitRange资源清单什么是资源清单?在K8S中,一般使用yaml格式的文件来创建符合我们预期期望的pod,这样的yaml文件我们一般称为资源清单。资源清单格式资源清单格式apiVersion: group/apiversion kind: metadata: spec: status:apiVersion:如果没有给定group名称,那么默认为croe,可以使用kubectl api-versions 获取当前k8s版本上所有的apiVersion版本信息(每个版本可能不同),也可以通过kubectl explain 资源名称|grep VERSION来获取相应资源的apiversionkind:资源类别metadata:资源元数据spec:期望的状态(disired state)status:当前状态,本字段有kubernetes自身维护,用户不能去定义清单格式帮助以pod资源为例,想要查看pod资源的资源清单格式可以使用一下命令kubectl explain pod使用上面命令只能看到一级配置,想要看二级的,例如metadata、spec,可以使用一下命令kubectl explain pod.metadata kubectl explain pod.specNamespace什么是Namespace?Namespace也称为命名空间是kubernetes系统中的一种非常重要资源,它的主要作用是用来实现多套环境的资源隔离或者多租户的资源隔离。作用默认情况下,kubernetes集群中的所有的Pod都是可以相互访问的。但是在实际中,可能不想让两个Pod之间进行互相的访问,那此时就可以将两个Pod划分到不同的namespace下。kubernetes通过将集群内部的资源分配到不同的Namespace中,可以形成逻辑上的"组",以方便不同的组的资源进行隔离使用和管理。可以通过kubernetes的授权机制,将不同的namespace交给不同租户进行管理,这样就实现了多租户的资源隔离。此时还能结合kubernetes的资源配额机制,限定不同租户能占用的资源,例如CPU使用量、内存使用量等等,来实现租户可用资源的管理。管理列出全部的命名空间kubectl get ns创建命名空间kubectl create ns dev删除命名空间kubectl delete ns dev资源清单apiVersion: v1 kind: Namespace metadata: name: dev创建:kubectl create -f ns-dev.yaml删除:kubectl delete -f ns-dev.yaml资源管理资源管理方式命令式对象管理:直接使用命令去操作kubernetes资源命令式对象配置:通过命令配置和配置文件去操作kubernetes资源声明式对象配置:通过apply命令和配置文件去操作kubernetes资源命令式对象管理格式kubectl命令就是kubernetes集权管理的命令行工具,通过它能够对集群本身进行管理,并能够在集群上进行容器化应用的安装部署。命令语法如下:kubectl [command] [type] [name] [flags]comand:指定要对资源执行的操作,例如create、get、deletetype:指定资源类型,比如deployment、pod、servicename:指定资源的名称,名称大小写敏感flags:指定额外的可选参数command基本命令命令命令作用create创建一个资源edit编辑一个资源get获取一个资源patch更新一个资源delete删除一个资源explain显示资源文档运行调试命令命令作用run在集群中运行一个指定的镜像expose暴露资源为Servicedescribe显示资源内部信息logs输出容器在Pod中的日志attach进入运行中的容器exec执行容器中的一个命令cp在Pod和内外复制文件rollout管理资源的发布scale扩(缩)容Pod的数量autoscale自动调整Pod的数量其他命令命令命令作用apply通过文件对资源进行创建或更新label更新资源上的标签cluster-info显示集群信息version显示当前Client和Server的版本type资源资源类型,这里不进行列举了,上面已经说过。命令式对象配置命令式对象配置就是使用命令配合资源清单来使用资源清单创建好之后使用下面命令进行操作创建资源:kubectl create -f 资源清单查看资源:kubectl get -f 资源清单删除资源:kubectl delete -f 资源清单声明式对象配置声明式对象配置跟命令式对象配置很相似,但是它只有一个命令apply。和命令式对象配置的区别就在于命令式是用来创建删除的,而声明式是用来修改的,当资源清单修改后可以使用下面命令对资源对进行更新更新资源:kubectl apply -f 资源清单 Kubernetes-容器编排引擎(安装-Kubeadm-Containerd-1.24.0) https://blog.boychai.xyz/index.php/archives/23/ 2022-07-31T12:32:00+00:00 准备开始一台兼容的 Linux 主机。Kubernetes 项目为基于 Debian 和 Red Hat 的 Linux 发行版以及一些不提供包管理器的发行版提供通用的指令每台机器 2 GB 或更多的 RAM (如果少于这个数字将会影响你应用的运行内存)2 CPU 核或更多集群中的所有机器的网络彼此均能相互连接(公网和内网都可以)节点之中不可以有重复的主机名、MAC 地址或 product_uuid。请参见这里了解更多详细信息。开启机器上的某些端口。请参见这里 了解更多详细信息。禁用交换分区。为了保证 kubelet 正常工作,你 必须 禁用交换分区。环境主机名系统硬件环境master.host.comrocky8.52核CPU,2G内存关闭selinux和防火墙,可使用主机名通信work1.host.comrocky8.52核CPU,2G内存关闭selinux和防火墙,可使用主机名通信work2.host.comrocky8.52核CPU,2G内存关闭selinux和防火墙,可使用主机名通信初始化主机一下操作所有主机都做安装配置Containerdcurl -o /etc/yum.repos.d/docker.repo https://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo yum -y install containerd.io containerd config default | sudo tee /etc/containerd/config.toml sed -i 's/SystemdCgroup = false/SystemdCgroup = true/g' /etc/containerd/config.toml systemctl enable --now containerd关闭SWAP分区sudo swapoff -a sudo sed -ri 's/.*swap.*/#&/' /etc/fstab允许 iptables 检查桥接流量并配置内核转发modprobe br_netfilter cat <<EOF | sudo tee /etc/modules-load.d/k8s.conf br_netfilter EOF cat <<EOF | sudo tee /etc/sysctl.d/k8s.conf net.bridge.bridge-nf-call-ip6tables = 1 net.bridge.bridge-nf-call-iptables = 1 net.ipv4.ip_forward = 1 EOF sudo sysctl --system配置IPVSservice有基于iptables和基于ipvs两种代理模型。基于ipvs的性能要高一些。需要手动载入才能使用ipvs模块yum install -y ipset ipvsadm cat > /etc/sysconfig/modules/ipvs.modules <<EOF #!/bin/bash modprobe -- ip_vs modprobe -- ip_vs_rr modprobe -- ip_vs_wrr modprobe -- ip_vs_sh modprobe -- nf_conntrack_ipv4 EOF chmod +x /etc/sysconfig/modules/ipvs.modules /bin/bash /etc/sysconfig/modules/ipvs.modules如果出现以下报错则执行下面内容modprobe: FATAL: Module nf_conntrack_ipv4 not found in directory /lib/modules/4.18.0-348.el8.0.2.x86_64sed -i 's/nf_conntrack_ipv4/nf_conntrack/g' /etc/sysconfig/modules/ipvs.modules /bin/bash /etc/sysconfig/modules/ipvs.modules安装Kubernetes相关软件工具cat <<EOF > /etc/yum.repos.d/kubernetes.repo [kubernetes] name=Kubernetes baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64/ enabled=1 gpgcheck=1 repo_gpgcheck=1 gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg https://mirrors.aliyun.com/kubernetes/yum/doc/rpm-package-key.gpg EOF yum install -y kubelet-1.24.0 kubeadm-1.24.0 kubectl-1.24.0 systemctl enable --now kubelet安装KubernetesMASTER节点生成kubeadm配置文件:sudo kubeadm config print init-defaults > kubeadm.yaml编辑kubeadm.yaml并修改下面内容advertiseAddress: 改成自己的ip nodeRegistration下的name字段:改成自己的主机名 imageRepository: registry.aliyuncs.com/google_containers在networking段添加pod的网段:podSubnet: 10.244.0.0/16修改后内容如下:$ cat kubeadm.yaml apiVersion: kubeadm.k8s.io/v1beta3 bootstrapTokens: - groups: - system:bootstrappers:kubeadm:default-node-token token: abcdef.0123456789abcdef ttl: 24h0m0s usages: - signing - authentication kind: InitConfiguration localAPIEndpoint: advertiseAddress: 192.168.0.109 bindPort: 6443 nodeRegistration: criSocket: unix:///var/run/containerd/containerd.sock imagePullPolicy: IfNotPresent name: master.host.com taints: null --- apiServer: timeoutForControlPlane: 4m0s apiVersion: kubeadm.k8s.io/v1beta3 certificatesDir: /etc/kubernetes/pki clusterName: kubernetes controllerManager: {} dns: {} etcd: local: dataDir: /var/lib/etcd imageRepository: registry.aliyuncs.com/google_containers kind: ClusterConfiguration kubernetesVersion: 1.24.0 networking: dnsDomain: cluster.local serviceSubnet: 10.96.0.0/12 podSubnet: 10.244.0.0/16 scheduler: {}下载Kubernetes所需镜像:$ kubeadm config --config kubeadm.yaml images pull [config/images] Pulled registry.aliyuncs.com/google_containers/kube-apiserver:v1.24.0 [config/images] Pulled registry.aliyuncs.com/google_containers/kube-controller-manager:v1.24.0 [config/images] Pulled registry.aliyuncs.com/google_containers/kube-scheduler:v1.24.0 [config/images] Pulled registry.aliyuncs.com/google_containers/kube-proxy:v1.24.0 [config/images] Pulled registry.aliyuncs.com/google_containers/pause:3.7 [config/images] Pulled registry.aliyuncs.com/google_containers/etcd:3.5.3-0 [config/images] Pulled registry.aliyuncs.com/google_containers/coredns:v1.8.6在意一下pause镜像的的版本名称我这里是registry.aliyuncs.com/google_containers/pause:3.7修改containerd的配置文件/etc/containerd/config.toml,把里面的sandbox_image的值改为pause镜像的全称加版本$ cat /etc/containerd/config.toml |grep sandbox sandbox_image = "registry.aliyuncs.com/google_containers/pause:3.7"重启Containerd:systemctl restart containerd初始化master节点:kubeadm init --config kubeadm.yaml注意:修改containerd的sandbox_image配置是全部的主机都要修改初始化成功之后会打印下面的内容 Your Kubernetes control-plane has initialized successfully! To start using your cluster, you need to run the following as a regular user: mkdir -p $HOME/.kube sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config sudo chown $(id -u):$(id -g) $HOME/.kube/config Alternatively, if you are the root user, you can run: export KUBECONFIG=/etc/kubernetes/admin.conf You should now deploy a pod network to the cluster. Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at: https://kubernetes.io/docs/concepts/cluster-administration/addons/ Then you can join any number of worker nodes by running the following on each as root: kubeadm join 192.168.0.4:6443 --token abcdef.0123456789abcdef \ --discovery-token-ca-cert-hash sha256:91b1d4502e8950ece37fbc591160007f5e2a3311ff0ebe05112d24851ca082a9其中下面内容需要自己去执行o start using your cluster, you need to run the following as a regular user: mkdir -p $HOME/.kube sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config sudo chown $(id -u):$(id -g) $HOME/.kube/config Alternatively, if you are the root user, you can run: export KUBECONFIG=/etc/kubernetes/admin.conf 之后这段内容是加入集群的命令,work节点可以通过下面命令来加入集群Then you can join any number of worker nodes by running the following on each as root: kubeadm join 192.168.0.4:6443 --token abcdef.0123456789abcdef \ --discovery-token-ca-cert-hash sha256:91b1d4502e8950ece37fbc591160007f5e2a3311ff0ebe05112d24851ca082a9 WORK节点WORK节点执行master节点返回的加入集群命令加入集群,出现下面内容即加入成功kubeadm join 192.168.0.4:6443 --token abcdef.0123456789abcdef \ --discovery-token-ca-cert-hash sha256:91b1d4502e8950ece37fbc591160007f5e2a3311ff0ebe05112d24851ca082a9 This node has joined the cluster: * Certificate signing request was sent to apiserver and a response was received. * The Kubelet was informed of the new secure connection details. Run 'kubectl get nodes' on the control-plane to see this node join the cluster. 网络插件Calico选择网络插件可参考官方文档进行选择本文选用Calico网络插件在master节点下载calico的yaml文件curl https://projectcalico.docs.tigera.io/archive/v3.22/manifests/calico.yaml -O找到下面两行内容进行取消注释并修改value值# - name: CALICO_IPV4POOL_CIDR # value: "192.168.0.0/16"value值应为开始创建master节点时的pod网络10.244.0.0/16,修改后为- name: CALICO_IPV4POOL_CIDR value: "10.244.0.0/16"之后进行创建,创建方法如下$ sudu kubectl apply -f calico.yaml configmap/calico-config unchanged customresourcedefinition.apiextensions.k8s.io/bgpconfigurations.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/bgppeers.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/blockaffinities.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/caliconodestatuses.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/clusterinformations.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/felixconfigurations.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/globalnetworkpolicies.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/globalnetworksets.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/hostendpoints.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/ipamblocks.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/ipamconfigs.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/ipamhandles.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/ippools.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/ipreservations.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/kubecontrollersconfigurations.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/networkpolicies.crd.projectcalico.org configured customresourcedefinition.apiextensions.k8s.io/networksets.crd.projectcalico.org configured clusterrole.rbac.authorization.k8s.io/calico-kube-controllers unchanged clusterrolebinding.rbac.authorization.k8s.io/calico-kube-controllers unchanged clusterrole.rbac.authorization.k8s.io/calico-node unchanged clusterrolebinding.rbac.authorization.k8s.io/calico-node unchanged daemonset.apps/calico-node created serviceaccount/calico-node created deployment.apps/calico-kube-controllers created serviceaccount/calico-kube-controllers created Warning: policy/v1beta1 PodDisruptionBudget is deprecated in v1.21+, unavailable in v1.25+; use policy/v1 PodDisruptionBudget poddisruptionbudget.policy/calico-kube-controllers created执行完成没有报错之后可以运行kubectl get node来查看节点的联通状态,当STATUS全都变成Ready即部署成功$ kubectl get node NAME STATUS ROLES AGE VERSION master.host.com Ready control-plane 43m v1.24.3 work1.host.com Ready <none> 39m v1.24.3 work2.host.com Ready <none> 39m v1.24.3问题出现报错以及问题欢迎在评论区讨论