k8s安装kube-promethues(0.7版本)

发布时间 2023-09-14 14:05:43作者: 山有扶苏QWQ

k8s安装kube-promethues(0.7版本)

一.检查本地k8s版本,下载对应安装包

kubectl version

image-20230913170838353

如图可见是1.19版本

进入kube-promethus下载地址,查找自己的k8s版本适合哪一个kube-promethues版本。

image-20230913171851704

然后下载自己合适的版本

#还可以通过如下地址,在服务器上直接下已经打包好的包。或者复制地址到浏览器下载后上传到服务器。
wget https://github.com/prometheus-operator/kube-prometheus/archive/refs/tags/v0.7.0.tar.gz

本次安装是手动上传的

image-20230913172052227

tar -zxvf kube-prometheus-0.7.0.tar.gz

二.安装前准备

1.文件分类整理

我们cd到对应目录可以看见,初始的安装文件很乱。

cd kube-prometheus-0.7.0/manifests/

image-20230913172527923

新建目录,然后把对应的安装文件归类。

# 创建文件夹
mkdir -p node-exporter alertmanager grafana kube-state-metrics prometheus serviceMonitor adapter

# 移动 yaml 文件,进行分类到各个文件夹下
mv *-serviceMonitor* serviceMonitor/
mv grafana-* grafana/
mv kube-state-metrics-* kube-state-metrics/
mv alertmanager-* alertmanager/
mv node-exporter-* node-exporter/
mv prometheus-adapter* adapter/
mv prometheus-* prometheus

分类后的目录树如下

.
├── adapter
│   ├── prometheus-adapter-apiService.yaml
│   ├── prometheus-adapter-clusterRole.yaml
│   ├── prometheus-adapter-clusterRoleAggregatedMetricsReader.yaml
│   ├── prometheus-adapter-clusterRoleBinding.yaml
│   ├── prometheus-adapter-clusterRoleBindingDelegator.yaml
│   ├── prometheus-adapter-clusterRoleServerResources.yaml
│   ├── prometheus-adapter-configMap.yaml
│   ├── prometheus-adapter-deployment.yaml
│   ├── prometheus-adapter-roleBindingAuthReader.yaml
│   ├── prometheus-adapter-service.yaml
│   └── prometheus-adapter-serviceAccount.yaml
├── alertmanager
│   ├── alertmanager-alertmanager.yaml
│   ├── alertmanager-secret.yaml
│   ├── alertmanager-service.yaml
│   └── alertmanager-serviceAccount.yaml
├── grafana
│   ├── grafana-dashboardDatasources.yaml
│   ├── grafana-dashboardDefinitions.yaml
│   ├── grafana-dashboardSources.yaml
│   ├── grafana-deployment.yaml
│   ├── grafana-pvc.yaml
│   ├── grafana-service.yaml
│   └── grafana-serviceAccount.yaml
├── kube-state-metrics
│   ├── kube-state-metrics-clusterRole.yaml
│   ├── kube-state-metrics-clusterRoleBinding.yaml
│   ├── kube-state-metrics-deployment.yaml
│   ├── kube-state-metrics-service.yaml
│   └── kube-state-metrics-serviceAccount.yaml
├── node-exporter
│   ├── node-exporter-clusterRole.yaml
│   ├── node-exporter-clusterRoleBinding.yaml
│   ├── node-exporter-daemonset.yaml
│   ├── node-exporter-service.yaml
│   └── node-exporter-serviceAccount.yaml
├── prometheus
│   ├── prometheus-clusterRole.yaml
│   ├── prometheus-clusterRoleBinding.yaml
│   ├── prometheus-prometheus.yaml
│   ├── prometheus-roleBindingConfig.yaml
│   ├── prometheus-roleBindingSpecificNamespaces.yaml
│   ├── prometheus-roleConfig.yaml
│   ├── prometheus-roleSpecificNamespaces.yaml
│   ├── prometheus-rules.yaml
│   ├── prometheus-service.yaml
│   └── prometheus-serviceAccount.yaml
├── serviceMonitor
│   ├── alertmanager-serviceMonitor.yaml
│   ├── grafana-serviceMonitor.yaml
│   ├── kube-state-metrics-serviceMonitor.yaml
│   ├── node-exporter-serviceMonitor.yaml
│   ├── prometheus-adapter-serviceMonitor.yaml
│   ├── prometheus-operator-serviceMonitor.yaml
│   ├── prometheus-serviceMonitor.yaml
│   ├── prometheus-serviceMonitorApiserver.yaml
│   ├── prometheus-serviceMonitorCoreDNS.yaml
│   ├── prometheus-serviceMonitorKubeControllerManager.yaml
│   ├── prometheus-serviceMonitorKubeScheduler.yaml
│   └── prometheus-serviceMonitorKubelet.yaml
└── setup
    ├── 0namespace-namespace.yaml
    ├── prometheus-operator-0alertmanagerConfigCustomResourceDefinition.yaml
    ├── prometheus-operator-0alertmanagerCustomResourceDefinition.yaml
    ├── prometheus-operator-0podmonitorCustomResourceDefinition.yaml
    ├── prometheus-operator-0probeCustomResourceDefinition.yaml
    ├── prometheus-operator-0prometheusCustomResourceDefinition.yaml
    ├── prometheus-operator-0prometheusruleCustomResourceDefinition.yaml
    ├── prometheus-operator-0servicemonitorCustomResourceDefinition.yaml
    ├── prometheus-operator-0thanosrulerCustomResourceDefinition.yaml
    ├── prometheus-operator-clusterRole.yaml
    ├── prometheus-operator-clusterRoleBinding.yaml
    ├── prometheus-operator-deployment.yaml
    ├── prometheus-operator-service.yaml
    └── prometheus-operator-serviceAccount.yaml

8 directories, 68 files

2.查看K8s集群是否安装NFS持久化存储,如果没有则需要安装配置

kubectl get sc

image-20230913173316518

此截图显示已经安装。下面是NFS的安装和部署方法

1).安装NFS服务

Ubuntu:

sudo apt update
sudo apt install nfs-kernel-server

Centos:

yum update
yum -y install nfs-utils
# 创建或使用用已有的文件夹作为nfs文件存储点
mkdir -p /home/data/nfs/share
vi /etc/exports

写入如下内容

/home/data/nfs/share *(rw,no_root_squash,sync,no_subtree_check)

image-20230913174358481

# 配置生效并查看是否生效
exportfs -r
exportfs

image-20230913174639129

# 启动rpcbind、nfs服务
#Centos
systemctl restart rpcbind && systemctl enable rpcbind
systemctl restart nfs && systemctl enable nfs
#Ubuntu
systemctl restart rpcbind && systemctl enable rpcbind
systemctl start nfs-kernel-server && systemctl enable nfs-kernel-server

# 查看 RPC 服务的注册状况
rpcinfo -p localhost

image-20230913175507036

# showmount测试
showmount -e localhost

image-20230913175649184

以上都没有问题则说明安装成功

2).k8s注册nfs服务

新建storageclass-nfs.yaml文件,粘贴如下内容:

## 创建了一个存储类
apiVersion: storage.k8s.io/v1
kind: StorageClass                  #存储类的资源名称
metadata:
  name: nfs-storage                 #存储类的名称,自定义
  annotations:
    storageclass.kubernetes.io/is-default-class: "true"          #注解,是否是默认的存储,注意:KubeSphere默认就需要个默认存储,因此这里注解要设置为“默认”的存储系统,表示为"true",代表默认。
provisioner: k8s-sigs.io/nfs-subdir-external-provisioner         #存储分配器的名字,自定义
parameters:
  archiveOnDelete: "true"  ## 删除pv的时候,pv的内容是否要备份

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nfs-client-provisioner
  labels:
    app: nfs-client-provisioner
  # replace with namespace where provisioner is deployed
  namespace: default
spec:
  replicas: 1                 #只运行一个副本应用
  strategy:                   #描述了如何用新的POD替换现有的POD
    type: Recreate            #Recreate表示重新创建Pod
  selector:        #选择后端Pod
    matchLabels:
      app: nfs-client-provisioner
  template:
    metadata:
      labels:
        app: nfs-client-provisioner
    spec:
      serviceAccountName: nfs-client-provisioner          #创建账户
      containers:
        - name: nfs-client-provisioner         
          image: registry.cn-hangzhou.aliyuncs.com/lfy_k8s_images/nfs-subdir-external-provisioner:v4.0.2      #使用NFS存储分配器的镜像
          # resources:
          #    limits:
          #      cpu: 10m
          #    requests:
          #      cpu: 10m
          volumeMounts:
            - name: nfs-client-root           #定义个存储卷,
              mountPath: /persistentvolumes   #表示挂载容器内部的路径
          env:
            - name: PROVISIONER_NAME          #定义存储分配器的名称
              value: k8s-sigs.io/nfs-subdir-external-provisioner         #需要和上面定义的保持名称一致
            - name: NFS_SERVER                                       #指定NFS服务器的地址,你需要改成你的NFS服务器的IP地址
              value: 192.168.0.0 ## 指定自己nfs服务器地址
            - name: NFS_PATH                                
              value: /home/data/nfs/share  ## nfs服务器共享的目录            #指定NFS服务器共享的目录
      volumes:
        - name: nfs-client-root           #存储卷的名称,和前面定义的保持一致
          nfs:
            server: 192.168.0.0            #NFS服务器的地址,和上面保持一致,这里需要改为你的IP地址
            path: /home/data/nfs/share               #NFS共享的存储目录,和上面保持一致
--- 
apiVersion: v1
kind: ServiceAccount                 #创建个SA账号
metadata:
  name: nfs-client-provisioner        #和上面的SA账号保持一致
  # replace with namespace where provisioner is deployed
  namespace: default
---
#以下就是ClusterRole,ClusterRoleBinding,Role,RoleBinding都是权限绑定配置,不在解释。直接复制即可。
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: nfs-client-provisioner-runner
rules:
  - apiGroups: [""]
    resources: ["nodes"]
    verbs: ["get", "list", "watch"]
  - apiGroups: [""]
    resources: ["persistentvolumes"]
    verbs: ["get", "list", "watch", "create", "delete"]
  - apiGroups: [""]
    resources: ["persistentvolumeclaims"]
    verbs: ["get", "list", "watch", "update"]
  - apiGroups: ["storage.k8s.io"]
    resources: ["storageclasses"]
    verbs: ["get", "list", "watch"]
  - apiGroups: [""]
    resources: ["events"]
    verbs: ["create", "update", "patch"]
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: run-nfs-client-provisioner
subjects:
  - kind: ServiceAccount
    name: nfs-client-provisioner
    # replace with namespace where provisioner is deployed
    namespace: default
roleRef:
  kind: ClusterRole
  name: nfs-client-provisioner-runner
  apiGroup: rbac.authorization.k8s.io
---
kind: Role
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: leader-locking-nfs-client-provisioner
  # replace with namespace where provisioner is deployed
  namespace: default
rules:
  - apiGroups: [""]
    resources: ["endpoints"]
    verbs: ["get", "list", "watch", "create", "update", "patch"]
---
kind: RoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: leader-locking-nfs-client-provisioner
  # replace with namespace where provisioner is deployed
  namespace: default
subjects:
  - kind: ServiceAccount
    name: nfs-client-provisioner
    # replace with namespace where provisioner is deployed
    namespace: default
roleRef:
  kind: Role
  name: leader-locking-nfs-client-provisioner
  apiGroup: rbac.authorization.k8s.io

需要修改的就只有服务器地址和共享的目录

创建StorageClass

kubectl apply -f storageclass-nfs.yaml

# 查看是否存在
kubectl get sc

image-20230913180723582

3.修改Prometheus 持久化

vi prometheus/prometheus-prometheus.yaml

在文件末尾新增:

...
  serviceMonitorSelector: {}
  version: v2.11.0
  retention: 3d
  storage:
    volumeClaimTemplate:
      spec:
        storageClassName: nfs-storage
        resources:
          requests:
            storage: 5Gi

4.修改grafana持久化配置

#新增garfana的PVC配置文件
vi grafana/grafana-pvc.yaml

完整内容如下:

kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: grafana
  namespace: monitoring  #---指定namespace为monitoring
spec:
  storageClassName: nfs-storage #---指定StorageClass
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 5Gi

接着修改 grafana-deployment.yaml 文件设置持久化配置,顺便修改Garfana的镜像版本(有些模板不支持7.5以下的Grafana),应用上面的 PVC

vi grafana/grafana-deployment.yaml

修改内容如下:

      serviceAccountName: grafana
      volumes:
      - name: grafana-storage       # 新增持久化配置
        persistentVolumeClaim:
          claimName: grafana        # 设置为创建的PVC名称
#      - emptyDir: {}               # 注释旧的注释
#        name: grafana-storage
      - name: grafana-datasources
        secret:
          secretName: grafana-datasources

之前的镜像版本

image-20230914114930730

修改后的

image-20230914115002739

5.修改 promethus和Grafana的Service 端口设置

修改 Prometheus Service

vi prometheus/prometheus-service.yaml

修改为如下内容:

apiVersion: v1
kind: Service
metadata:
  labels:
    prometheus: k8s
  name: prometheus-k8s
  namespace: monitoring
spec:
  type: NodePort
  ports:
  - name: web
    port: 9090
    targetPort: web
    nodePort: 32101
  selector:
    app: prometheus
    prometheus: k8s
  sessionAffinity: ClientIP

修改 Grafana Service

vi grafana/grafana-service.yaml

修改为如下内容:

apiVersion: v1
kind: Service
metadata:
  labels:
    app: grafana
  name: grafana
  namespace: monitoring
spec:
  type: NodePort
  ports:
  - name: http
    port: 3000
    targetPort: http
    nodePort: 32102
  selector:
    app: grafana

三.安装Prometheus

1.安装promethues-operator

首先保证在manifests目录下

image-20230914092333906

开始安装 Operator:

kubectl apply -f setup/

查看 Pod,等 pod 全部ready在进行下一步:

kubectl get pods -n monitoring

image-20230914092736130

2.安装其他所有组件

#依次执行
kubectl apply -f adapter/
kubectl apply -f alertmanager/
kubectl apply -f node-exporter/
kubectl apply -f kube-state-metrics/
kubectl apply -f grafana/
kubectl apply -f prometheus/
kubectl apply -f serviceMonitor/

然后查看pod是否创建成功,并等待所有pod处于Running状态

kubectl get pods -n monitoring

image-20230914092943671

3.验证是否安装成功

如果知道集群节点地址就可以直接ip:32101访问Prometheus,如果不知道则可以访问Rancher管理界面,命名空间选择monitoring。在Services中找到,prometheus-k8s和grafana然后鼠标点击目标端口就可以访问。

image-20230914094037745

在Prometheus界面随便测试一个函数,查看是否能够正常使用。

image-20230914094623849

然后登录Grafana

image-20230914114135455

默认用户名和密码是admin/admin,第一次登陆会提示修改密码。进入Grafana后,导入模板测试。推荐的模板ID有,12884和13105

image-20230914115045741

image-20230914115329083

image-20230914115349005

效果图:

image-20230914115451862