kubernetes的最新版本已经到了1.20.x，利用假期时间搭建了最新的k8s v1.20.2版本，截止我整理此文为止，发现官方最新的release已经更新到了v1.20.4。
1、概述
1.1 在k8s中部署Prometheus监控的方法
通常在k8s中部署prometheus监控可以采取的方法有以下三种
- 通过yaml手动部署
- operator部署
- 通过helm chart部署
1.2 什么是Prometheus Operator
Prometheus Operator的本职就是一组用户自定义的CRD资源以及Controller的实现，Prometheus Operator负责监听这些自定义资源的变化，并且根据这些资源的定义自动化的完成如Prometheus Server自身以及配置的自动化管理工作。以下是Prometheus Operator的架构图
图片来源：
https://raw.githubusercontent.com/prometheus-operator/prometheus-operator/master/Documentation/user-guides/images/architecture.png
1.3 为什么用Prometheus Operator
由于Prometheus本身没有提供管理配置的AP接口（尤其是管理监控目标和管理警报规则），也没有提供好用的多实例管理手段，因此这一块往往要自己写一些代码或脚本。为了简化这类应用程序的管理复杂度，CoreOS率先引入了Operator的概念，并且首先推出了针对在Kubernetes下运行和管理Etcd的Etcd Operator。并随后推出了Prometheus Operator
1.4 kube-prometheus项目介绍
prometheus-operator官方地址：https://github.com/prometheus-operator/prometheus-operator
kube-prometheus官方地址：https://github.com/prometheus-operator/kube-prometheus
两个项目的关系：前者只包含了Prometheus Operator，后者既包含了Operator，又包含了Prometheus相关组件的部署及常用的Prometheus自定义监控，具体包含下面的组件
- The Prometheus Operator：创建CRD自定义的资源对象
- Highly available Prometheus：创建高可用的Prometheus
- Highly available Alertmanager：创建高可用的告警组件
- Prometheus node-exporter：创建主机的监控组件
- Prometheus Adapter for Kubernetes Metrics APIs：创建自定义监控的指标工具（例如可以通过nginx的request来进行应用的自动伸缩）
- kube-state-metrics：监控k8s相关资源对象的状态指标
- Grafana：进行图像展示
2、环境介绍
本文的k8s环境是通过kubeadm搭建的v 1.20.2版本，由1master+2node组合
持久化存储为storageclass动态存储，底层由ceph-rbd提供
➜ kubectl version -o yaml
clientVersion:
buildDate: "2020-12-08T17:59:43Z"
compiler: gc
gitCommit: af46c47ce925f4c4ad5cc8d1fca46c7b77d13b38
gitTreeState: clean
gitVersion: v1.20.0
goVersion: go1.15.5
major: "1"
minor: "20"
platform: darwin/amd64
serverVersion:
buildDate: "2021-01-13T13:20:00Z"
compiler: gc
gitCommit: faecb196815e248d3ecfb03c680a4507229c2a56
gitTreeState: clean
gitVersion: v1.20.2
goVersion: go1.15.5
major: "1"
minor: "20"
platform: linux/amd64
➜ kubectl get nodes
NAME STATUS ROLES AGE VERSION
k8s-m-01 Ready control-plane,master 11d v1.20.2
k8s-n-01 Ready <none> 11d v1.20.2
k8s-n-02 Ready <none> 11d v1.20.2
➜ manifests kubectl get sc
NAME PROVISIONER RECLAIMPOLICY VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE
dynamic-ceph-rbd (default) ceph.com/rbd Delete Immediate false 7d23h
kube-prometheus的兼容性说明（https://github.com/prometheus-operator/kube-prometheus#kubernetes-compatibility-matrix），按照兼容性说明，部署的是最新的release-0.7版本
| kube-prometheus stack | Kubernetes 1.16 | Kubernetes 1.17 | Kubernetes 1.18 | Kubernetes 1.19 | Kubernetes 1.20 |
|---|---|---|---|---|---|
release-0.4 |
✔ (v1.16.5+) | ✔ | ✗ | ✗ | ✗ |
release-0.5 |
✗ | ✗ | ✔ | ✗ | ✗ |
release-0.6 |
✗ | ✗ | ✔ | ✔ | ✗ |
release-0.7 |
✗ | ✗ | ✗ | ✔ | ✔ |
HEAD |
✗ | ✗ | ✗ | ✔ | ✔ |
3、清单准备
从官方的地址获取最新的release-0.7分支，或者直接打包下载release-0.7
➜ git clone https://github.com/prometheus-operator/kube-prometheus.git
➜ git checkout release-0.7
或者
➜ wget -c https://github.com/prometheus-operator/kube-prometheus/archive/v0.7.0.zip
默认下载下来的文件较多，建议把文件进行归类处理，将相关yaml文件移动到对应目录下
➜ cd kube-prometheus/manifests
➜ mkdir -p serviceMonitor prometheus adapter node-exporter kube-state-metrics grafana alertmanager operator other
最终结构如下
➜ manifests tree .
.
├── 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-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
├── operator
│ ├── 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
├── other
├── 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
9 directories, 67 files
修改yaml，增加prometheus和grafana的持久化存储
manifests/prometheus/prometheus-prometheus.yaml
...
serviceMonitorSelector: {}
version: v2.22.1
retention: 3d
storage:
volumeClaimTemplate:
spec:
storageClassName: dynamic-ceph-rbd
resources:
requests:
storage: 5Gi
manifests/grafana/grafana-deployment.yaml
...
serviceAccountName: grafana
volumes:
# - emptyDir: {}
# name: grafana-storage
- name: grafana-storage
persistentVolumeClaim:
claimName: grafana-data
新增grafana的pvc，manifests/other/grafana-pvc.yaml
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
name: grafana-data
namespace: monitoring
annotations:
volume.beta.kubernetes.io/storage-class: "dynamic-ceph-rbd"
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: 5Gi
4、开始部署
部署清单
➜ kubectl create -f other/grafana-pvc.yaml
➜ kubectl create -f operator/
➜ kubectl create -f adapter/ -f alertmanager/ -f grafana/ -f kube-state-metrics/ -f node-exporter/ -f prometheus/ -f serviceMonitor/
查看状态
➜ kubectl get po,svc -n monitoring
NAME READY STATUS RESTARTS AGE
pod/alertmanager-main-0 2/2 Running 0 15m
pod/alertmanager-main-1 2/2 Running 0 10m
pod/alertmanager-main-2 2/2 Running 0 15m
pod/grafana-d69dcf947-wnspk 1/1 Running 0 22m
pod/kube-state-metrics-587bfd4f97-bffqv 3/3 Running 0 22m
pod/node-exporter-2vvhv 2/2 Running 0 22m
pod/node-exporter-7nsz5 2/2 Running 0 22m
pod/node-exporter-wggpp 2/2 Running 0 22m
pod/prometheus-adapter-69b8496df6-cjw6w 1/1 Running 0 23m
pod/prometheus-k8s-0 2/2 Running 1 75s
pod/prometheus-k8s-1 2/2 Running 0 9m33s
pod/prometheus-operator-7649c7454f-nhl72 2/2 Running 0 28m
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/alertmanager-main ClusterIP 10.1.189.238 <none> 9093/TCP 23m
service/alertmanager-operated ClusterIP None <none> 9093/TCP,9094/TCP,9094/UDP 23m
service/grafana ClusterIP 10.1.29.30 <none> 3000/TCP 23m
service/kube-state-metrics ClusterIP None <none> 8443/TCP,9443/TCP 23m
service/node-exporter ClusterIP None <none> 9100/TCP 23m
service/prometheus-adapter ClusterIP 10.1.75.64 <none> 443/TCP 23m
service/prometheus-k8s ClusterIP 10.1.111.121 <none> 9090/TCP 23m
service/prometheus-operated ClusterIP None <none> 9090/TCP 14m
service/prometheus-operator ClusterIP None <none> 8443/TCP 28m
为prometheus、grafana、alertmanager创建ingress
manifests/other/ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: prom-ingress
namespace: monitoring
annotations:
kubernetes.io/ingress.class: "nginx"
prometheus.io/http_probe: "true"
spec:
rules:
- host: alert.k8s-1.20.2.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: alertmanager-main
port:
number: 9093
- host: grafana.k8s-1.20.2.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: grafana
port:
number: 3000
- host: prom.k8s-1.20.2.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: prometheus-k8s
port:
number: 9090
5、解决ControllerManager、Scheduler监控问题
默认安装后访问prometheus，会发现有以下有三个报警：
Watchdog、KubeControllerManagerDown、KubeSchedulerDown
Watchdog是一个正常的报警，这个告警的作用是：如果alermanger或者prometheus本身挂掉了就发不出告警了，因此一般会采用另一个监控来监控prometheus，或者自定义一个持续不断的告警通知，哪一天这个告警通知不发了，说明监控出现问题了。prometheus operator已经考虑了这一点，本身携带一个watchdog，作为对自身的监控。
如果需要关闭，删除或注释掉Watchdog部分
prometheus-rules.yaml
...
- name: general.rules
rules:
- alert: TargetDown
annotations:
message: 'xxx'
expr: 100 * (count(up == 0) BY (job, namespace, service) / count(up) BY (job, namespace, service)) > 10
for: 10m
labels:
severity: warning
# - alert: Watchdog
# annotations:
# message: |
# This is an alert meant to ensure that the entire alerting pipeline is functional.
# This alert is always firing, therefore it should always be firing in Alertmanager
# and always fire against a receiver. There are integrations with various notification
# mechanisms that send a notification when this alert is not firing. For example the
# "DeadMansSnitch" integration in PagerDuty.
# expr: vector(1)
# labels:
# severity: none
KubeControllerManagerDown、KubeSchedulerDown的解决
原因是因为在prometheus-serviceMonitorKubeControllerManager.yaml中有如下内容，但默认安装的集群并没有给系统kube-controller-manager组件创建svc
selector:
matchLabels:
k8s-app: kube-controller-manager
修改kube-controller-manager的监听地址
# vim /etc/kubernetes/manifests/kube-controller-manager.yaml
...
spec:
containers:
- command:
- kube-controller-manager
- --allocate-node-cidrs=true
- --authentication-kubeconfig=/etc/kubernetes/controller-manager.conf
- --authorization-kubeconfig=/etc/kubernetes/controller-manager.conf
- --bind-address=0.0.0.0
# netstat -lntup|grep kube-contro
tcp6 0 0 :::10257 :::* LISTEN 38818/kube-controll
创建一个service和endpoint，以便serviceMonitor监听
other/kube-controller-namager-svc-ep.yaml
apiVersion: v1
kind: Service
metadata:
name: kube-controller-manager
namespace: kube-system
labels:
k8s-app: kube-controller-manager
spec:
type: ClusterIP
clusterIP: None
ports:
- name: https-metrics
port: 10257
targetPort: 10257
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: kube-controller-manager
namespace: kube-system
labels:
k8s-app: kube-controller-manager
subsets:
- addresses:
- ip: 172.16.1.71
ports:
- name: https-metrics
port: 10257
protocol: TCP
kube-scheduler同理，修改kube-scheduler的监听地址
# vim /etc/kubernetes/manifests/kube-scheduler.yaml
...
spec:
containers:
- command:
- kube-scheduler
- --authentication-kubeconfig=/etc/kubernetes/scheduler.conf
- --authorization-kubeconfig=/etc/kubernetes/scheduler.conf
- --bind-address=0.0.0.0
# netstat -lntup|grep kube-sched
tcp6 0 0 :::10259 :::* LISTEN 100095/kube-schedul
创建一个service和endpoint，以便serviceMonitor监听
kube-scheduler-svc-ep.yaml
apiVersion: v1
kind: Service
metadata:
name: kube-scheduler
namespace: kube-system
labels:
k8s-app: kube-scheduler
spec:
type: ClusterIP
clusterIP: None
ports:
- name: https-metrics
port: 10259
targetPort: 10259
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: kube-scheduler
namespace: kube-system
labels:
k8s-app: kube-scheduler
subsets:
- addresses:
- ip: 172.16.1.71
ports:
- name: https-metrics
port: 10259
protocol: TCP
再次查看prometheus的alert界面，全部恢复正常
登录到grafana，查看相关图像展示
至此，通过kube-prometheus部署k8s监控已经基本完成了，后面再分享自定义监控和告警、告警通知、高可用、规模化部署等相关内容
参考：https://github.com/prometheus-operator/kube-prometheus