作者Double冬

写在前面

之前部署web网站的时候,架构图中有一环节是监控部分,并且搭建一套有效的监控平台对于运维来说非常之重要,只有这样才能更有效率的保证我们的服务器和服务的稳定运行,常见的开源监控软件有好几种,如zabbix、Nagios、open-flcon还有prometheus,每一种有着各自的优劣势,感兴趣的童鞋可以自行百度,但是与k8s集群监控,相对于而已更加友好的是Prometheus,今天我们就看看如何部署一套Prometheus全方位监控K8S

主要内容


  • 1.Prometheus架构
  • 2.K8S监控指标及实现思路
  • 3.在K8S平台部署Prometheus
  • 4.基于K8S服务发现的配置解析
  • 5.在K8S平台部署Grafana
  • 6.监控K8S集群中Pod、Node、资源对象
  • 7.使用Grafana可视化展示Prometheus监控数据
  • 8.告警规则与告警通知

1 Prometheus架构

Prometheus 是什么

Prometheus(普罗米修斯)是一个最初在SoundCloud上构建的监控系统。自2012年成为社区开源项目,拥有非常活跃的开发人员和用户社区。为强调开源及独立维护,Prometheus于2016年加入云原生云计算基金会(CNCF),成为继Kubernetes之后的第二个托管项目。

官网地址:

​https://prometheus.io​

​https://github.com/prometheus​

Prometheus 组成及架构

k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim


  • Prometheus Server:收集指标和存储时间序列数据,并提供查询接口

  • ClientLibrary:客户端库

  • Push Gateway:短期存储指标数据。主要用于临时性的任务

  • Exporters:采集已有的第三方服务监控指标并暴露metrics

  • Alertmanager:告警


Web UI:简单的Web控制台

数据模型

Prometheus将所有数据存储为时间序列;具有相同度量名称以及标签属于同一个指标。
每个时间序列都由度量标准名称和一组键值对(也成为标签)唯一标识。
时间序列格式:



{=, …}

示例:api_http_requests_total{method=”POST”, handler=”/messages”}

作业和实例

实例:可以抓取的目标称为实例(Instances)

作业:具有相同目标的实例集合称为作业(Job)

scrape_configs:

-job_name: ‘prometheus’

static_configs:

-targets: [‘localhost:9090’]

-job_name: ‘node’

static_configs:

-targets: [‘192.168.1.10:9090’]

2 K8S监控指标及实现思路

k8S监控指标

Kubernetes本身监控


  • Node资源利用率
  • Node数量
  • Pods数量(Node)
  • 资源对象状态

Pod监控


  • Pod数量(项目)
  • 容器资源利用率
  • 应用程序
    Prometheus监控K8S实现的架构
    k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_02

监控指标

具体实现

举例

Pod性能

cAdvisor

容器CPU

Node性能

node-exporter 节点CPU

内存利用率

K8S资源对象

kube-state-metrics

Pod/Deployment/Service

服务发现:

​https://prometheus.io/docs/prometheus/latest/configuration/configuration/#kubernetes_sd_config​

3 在K8S平台部署Prometheus

3.1集群环境




ip地址

角色

备注

192.168.73.136

nfs


192.168.73.138

k8s-master


192.168.73.139

k8s-node01


192.168.73.140

k8s-node02


192.168.73.135

k8s-node03



3.2 项目地址

可以直接选择git clone项目代码,也可以后面自己编写,后面的操作也会有实现代码

[root@k8s-master src]# git clone https://github.com/zhangdongdong7/k8s-prometheus.git
Cloning into 'k8s-prometheus'...
remote: Enumerating objects: 3, done.
remote: Counting objects: 100% (3/3), done.
remote: Total 3 (delta 0), reused 0 (delta 0), pack-reused 0
Unpacking objects: 100% (3/3), done.
[root@k8s-master src]# cd k8s-prometheus/
[root@k8s-master k8s-prometheus]# ls
alertmanager-configmap.yaml kube-state-metrics-rbac.yaml prometheus-rbac.yaml
alertmanager-deployment.yaml kube-state-metrics-service.yaml prometheus-rules.yaml
alertmanager-pvc.yaml node_exporter-0.17.0.linux-amd64.tar.gz prometheus-service.yaml
alertmanager-service.yaml node_exporter.sh prometheus-statefulset-static-pv.yaml
grafana.yaml OWNERS prometheus-statefulset.yaml
kube-state-metrics-deployment.yaml prometheus-configmap.yaml README.md

3.3 使用RBAC进行授权

RBAC(Role-Based Access Control,基于角色的访问控制):负责完成授权(Authorization)工作。

编写授权yaml

[root@k8s-master prometheus-k8s]# vim prometheus-rbac.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: prometheus
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
name: prometheus
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
- ""
resources:
- nodes
- nodes/metrics
- services
- endpoints
- pods
verbs:
- get
- list
- watch
- apiGroups:
- ""
resources:
- configmaps
verbs:
- get
- nonResourceURLs:
- "/metrics"
verbs:
- get
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
name: prometheus
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: prometheus
subjects:
- kind: ServiceAccount
name: prometheus
namespace: kube-system

创建

[root@k8s-master prometheus-k8s]# kubectl apply -f prometheus-rbac.yaml

3.4 配置管理

使用Configmap保存不需要加密配置信息

其中需要把nodes中ip地址根据自己的地址进行修改,其他不需要改动

[root@k8s-master prometheus-k8s]# vim prometheus-configmap.yaml
# Prometheus configuration format https://prometheus.io/docs/prometheus/latest/configuration/configuration/
apiVersion: v1
kind: ConfigMap #
metadata:
name: prometheus-config
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: EnsureExists
data:
prometheus.yml: |
rule_files:
- /etc/config/rules/*.rules

scrape_configs:
- job_name: prometheus
static_configs:
- targets:
- localhost:9090

- job_name: kubernetes-nodes
scrape_interval: 30s
static_configs:
- targets:
- 192.168.73.135:9100 #ip地址根据自己的地址进行修改
- 192.168.73.138:9100
- 192.168.73.139:9100
- 192.168.73.140:9100

- job_name: kubernetes-apiservers
kubernetes_sd_configs:
- role: endpoints
relabel_configs:
- action: keep
regex: default;kubernetes;https
source_labels:
- __meta_kubernetes_namespace
- __meta_kubernetes_service_name
- __meta_kubernetes_endpoint_port_name
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
insecure_skip_verify: true
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

- job_name: kubernetes-nodes-kubelet
kubernetes_sd_configs:
- role: node
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
insecure_skip_verify: true
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

- job_name: kubernetes-nodes-cadvisor
kubernetes_sd_configs:
- role: node
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __metrics_path__
replacement: /metrics/cadvisor
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
insecure_skip_verify: true
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

- job_name: kubernetes-service-endpoints
kubernetes_sd_configs:
- role: endpoints
relabel_configs:
- action: keep
regex: true
source_labels:
- __meta_kubernetes_service_annotation_prometheus_io_scrape
- action: replace
regex: (https?)
source_labels:
- __meta_kubernetes_service_annotation_prometheus_io_scheme
target_label: __scheme__
- action: replace
regex: (.+)
source_labels:
- __meta_kubernetes_service_annotation_prometheus_io_path
target_label: __metrics_path__
- action: replace
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
source_labels:
- __address__
- __meta_kubernetes_service_annotation_prometheus_io_port
target_label: __address__
- action: labelmap
regex: __meta_kubernetes_service_label_(.+)
- action: replace
source_labels:
- __meta_kubernetes_namespace
target_label: kubernetes_namespace
- action: replace
source_labels:
- __meta_kubernetes_service_name
target_label: kubernetes_name

- job_name: kubernetes-services
kubernetes_sd_configs:
- role: service
metrics_path: /probe
params:
module:
- http_2xx
relabel_configs:
- action: keep
regex: true
source_labels:
- __meta_kubernetes_service_annotation_prometheus_io_probe
- source_labels:
- __address__
target_label: __param_target
- replacement: blackbox
target_label: __address__
- source_labels:
- __param_target
target_label: instance
- action: labelmap
regex: __meta_kubernetes_service_label_(.+)
- source_labels:
- __meta_kubernetes_namespace
target_label: kubernetes_namespace
- source_labels:
- __meta_kubernetes_service_name
target_label: kubernetes_name

- job_name: kubernetes-pods
kubernetes_sd_configs:
- role: pod
relabel_configs:
- action: keep
regex: true
source_labels:
- __meta_kubernetes_pod_annotation_prometheus_io_scrape
- action: replace
regex: (.+)
source_labels:
- __meta_kubernetes_pod_annotation_prometheus_io_path
target_label: __metrics_path__
- action: replace
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
source_labels:
- __address__
- __meta_kubernetes_pod_annotation_prometheus_io_port
target_label: __address__
- action: labelmap
regex: __meta_kubernetes_pod_label_(.+)
- action: replace
source_labels:
- __meta_kubernetes_namespace
target_label: kubernetes_namespace
- action: replace
source_labels:
- __meta_kubernetes_pod_name
target_label: kubernetes_pod_name
alerting:
alertmanagers:
- static_configs:
- targets: ["alertmanager:80"]

创建

[root@k8s-master prometheus-k8s]# kubectl apply -f prometheus-configmap.yaml

3.5 有状态部署prometheus

这里使用storageclass进行动态供给,给prometheus的数据进行持久化,具体实现办法,可以查看之前的文章《k8s中的NFS动态存储供给》,除此之外可以使用静态供给的prometheus-statefulset-static-pv.yaml进行持久化

[root@k8s-master prometheus-k8s]# vim prometheus-statefulset.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: prometheus
namespace: kube-system
labels:
k8s-app: prometheus
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
version: v2.2.1
spec:
serviceName: "prometheus"
replicas: 1
podManagementPolicy: "Parallel"
updateStrategy:
type: "RollingUpdate"
selector:
matchLabels:
k8s-app: prometheus
template:
metadata:
labels:
k8s-app: prometheus
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ''
spec:
priorityClassName: system-cluster-critical
serviceAccountName: prometheus
initContainers:
- name: "init-chown-data"
image: "busybox:latest"
imagePullPolicy: "IfNotPresent"
command: ["chown", "-R", "65534:65534", "/data"]
volumeMounts:
- name: prometheus-data
mountPath: /data
subPath: ""
containers:
- name: prometheus-server-configmap-reload
image: "jimmidyson/configmap-reload:v0.1"
imagePullPolicy: "IfNotPresent"
args:
- --volume-dir=/etc/config
- --webhook-url=http://localhost:9090/-/reload
volumeMounts:
- name: config-volume
mountPath: /etc/config
readOnly: true
resources:
limits:
cpu: 10m
memory: 10Mi
requests:
cpu: 10m
memory: 10Mi


- name: prometheus-server
image: "prom/prometheus:v2.2.1"
imagePullPolicy: "IfNotPresent"
args:
- --config.file=/etc/config/prometheus.yml
- --storage.tsdb.path=/data
- --web.console.libraries=/etc/prometheus/console_libraries
- --web.console.templates=/etc/prometheus/consoles
- --web.enable-lifecycle
ports:
- containerPort: 9090
readinessProbe:
httpGet:
path: /-/ready
port: 9090
initialDelaySeconds: 30
timeoutSeconds: 30
livenessProbe:
httpGet:
path: /-/healthy
port: 9090
initialDelaySeconds: 30
timeoutSeconds: 30
# based on 10 running nodes with 30 pods each
resources:
limits:
cpu: 200m
memory: 1000Mi
requests:
cpu: 200m
memory: 1000Mi


volumeMounts:
- name: config-volume
mountPath: /etc/config
- name: prometheus-data
mountPath: /data
subPath: ""
- name: prometheus-rules
mountPath: /etc/config/rules


terminationGracePeriodSeconds: 300
volumes:
- name: config-volume
configMap:
name: prometheus-config
- name: prometheus-rules
configMap:
name: prometheus-rules


volumeClaimTemplates:
- metadata:
name: prometheus-data
spec:
storageClassName: managed-nfs-storage #存储类根据自己的存储类名字修改
accessModes:
- ReadWriteOnce
resources:
requests:
storage: "16Gi"

创建

[root@k8s-master prometheus-k8s]# kubectl apply -f prometheus-statefulset.yaml

检查状态

[root@k8s-master prometheus-k8s]# kubectl get pod -n kube-system
NAME READY STATUS RESTARTS AGE
coredns-5bd5f9dbd9-wv45t 1/1 Running 1 8d
kubernetes-dashboard-7d77666777-d5ng4 1/1 Running 5 14d
prometheus-0 2/2 Running 6 14d

可以看到一个prometheus-0的pod,这就刚才使用statefulset控制器进行的有状态部署,两个容器的状态为Runing则是正常,如果不为Runing可以使用kubectl describe pod  prometheus-0 -n kube-system查看报错详情

3.6 创建service暴露访问端口

此处使用nodePort固定一个访问端口,不适用随机端口,便于访问

[root@k8s-master prometheus-k8s]# vim prometheus-service.yaml
kind: Service
apiVersion: v1
metadata:
name: prometheus
namespace: kube-system
labels:
kubernetes.io/name: "Prometheus"
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
spec:
type: NodePort
ports:
- name: http
port: 9090
protocol: TCP
targetPort: 9090
nodePort: 30090 #固定的对外访问的端口
selector:
k8s-app: prometheus

创建

[root@k8s-master prometheus-k8s]# kubectl apply -f prometheus-service.yaml

检查

[root@k8s-master prometheus-k8s]# kubectl get pod,svc -n kube-system
NAME READY STATUS RESTARTS AGE
pod/coredns-5bd5f9dbd9-wv45t 1/1 Running 1 8dpod/kubernetes-dashboard-7d77666777-d5ng4 1/1 Running 5 14dpod/prometheus-0 2/2 Running 6 14dNAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/kube-dns ClusterIP 10.0.0.2 <none> 53/UDP,53/TCP 13dservice/kubernetes-dashboard NodePort 10.0.0.127 <none> 443:30001/TCP 16dservice/prometheus NodePort 10.0.0.33 <none> 9090:30090/TCP 13d

3.7 web访问

使用任意一个NodeIP加端口进行访问,访问地址:http://NodeIP:Port ,此例就是:http://192.168.73.139:30090

访问成功的界面如图所示:

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_03

4 在K8S平台部署Grafana

通过上面的web访问,可以看出prometheus自带的UI界面是没有多少功能的,可视化展示的功能不完善,不能满足日常的监控所需,因此常常我们需要再结合Prometheus+Grafana的方式来进行可视化的数据展示

官网地址:

​https://github.com/kubernetes/kubernetes/tree/master/cluster/addons/prometheus​

​https://grafana.com/grafana/download​

刚才下载的项目中已经写好了Grafana的yaml,根据自己的环境进行修改

4.1 使用StatefulSet部署grafana

[root@k8s-master prometheus-k8s]# vim grafana.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: grafana
namespace: kube-system
spec:
serviceName: "grafana"
replicas: 1
selector:
matchLabels:
app: grafana
template:
metadata:
labels:
app: grafana
spec:
containers:
- name: grafana
image: grafana/grafana
ports:
- containerPort: 3000
protocol: TCP
resources:
limits:
cpu: 100m
memory: 256Mi
requests:
cpu: 100m
memory: 256Mi
volumeMounts:
- name: grafana-data
mountPath: /var/lib/grafana
subPath: grafana
securityContext:
fsGroup: 472
runAsUser: 472
volumeClaimTemplates:
- metadata:
name: grafana-data
spec:
storageClassName: managed-nfs-storage #和prometheus使用同一个存储类
accessModes:
- ReadWriteOnce
resources:
requests:
storage: "1Gi"


---


apiVersion: v1
kind: Service
metadata:
name: grafana
namespace: kube-system
spec:
type: NodePort
ports:
- port : 80
targetPort: 3000
nodePort: 30091
selector:
app: grafana

4.2 Grafana的web访问

使用任意一个NodeIP加端口进行访问,访问地址:http://NodeIP:Port ,此例就是:http://192.168.73.139:30091

成功访问界面如下,会需要进行账号密码登陆,默认账号密码都为admin,登陆之后会让修改密码

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_04

登陆之后的界面如下

k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim_05

第一步需要进行数据源添加,点击create your first data source数据库图标,根据下图所示进行添加即可

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_06

第二步,添加完了之后点击底部的绿色的Save&Test,会成功提示Data sourse is working,则表示数据源添加成功

4.3 监控K8S集群中Pod、Node、资源对象数据的方法


1)Pod
kubelet的节点使用cAdvisor提供的metrics接口获取该节点所有Pod和容器相关的性能指标数据,安装kubelet默认就开启了
暴露接口地址:
​https://NodeIP:10255/metrics/cadvisor​​​​https://NodeIP:10250/metrics/cadvisor​

2)Node
需要使用node_exporter收集器采集节点资源利用率。
​https://github.com/prometheus/node_exporter​​使用文档:https://prometheus.io/docs/guides/node-exporter/

  • 使用node_exporter.sh脚本分别在所有服务器上部署node_exporter收集器,不需要修改可直接运行脚本


[root@k8s-master prometheus-k8s]# cat node_exporter.sh #!/bin/bashwget https://github.com/prometheus/node_exporter/releases/download/v0.17.0/node_exporter-0.17.0.linux-amd64.tar.gz


tar zxf node_exporter-0.17.0.linux-amd64.tar.gz
mv node_exporter-0.17.0.linux-amd64 /usr/local/node_exporter


cat <<EOF >/usr/lib/systemd/system/node_exporter.service
[Unit]
Description=https://prometheus.io


[Service]
Restart=on-failure
ExecStart=/usr/local/node_exporter/node_exporter --collector.systemd --collector.systemd.unit-whitelist=(docker|kubelet|kube-proxy|flanneld).service


[Install]
WantedBy=multi-user.target
EOF


systemctl daemon-reload
systemctl enable node_exporter
systemctl restart node_exporter
[root@k8s-master prometheus-k8s]# ./node_exporter.sh

  • 检测node_exporter的进程,是否生效
[root@k8s-master prometheus-k8s]# ps -ef|grep node_exporter
root 6227 1 0 Oct08 ? 00:06:43 /usr/local/node_exporter/node_exporter --collector.systemd --collector.systemd.unit-whitelist=(docker|kubelet|kube-proxy|flanneld).service
root 118269 117584 0 23:27 pts/0 00:00:00 grep --color=auto node_exporter


3)资源对象
kube-state-metrics采集了k8s中各种资源对象的状态信息,只需要在master节点部署就行
​https://github.com/kubernetes/kube-state-metrics​

  1. 创建rbac的yaml对metrics进行授权


[root@k8s-master prometheus-k8s]# vim kube-state-metrics-rbac.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: kube-state-metrics
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: kube-state-metrics
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups: [""]
resources:
- configmaps
- secrets
- nodes
- pods
- services
- resourcequotas
- replicationcontrollers
- limitranges
- persistentvolumeclaims
- persistentvolumes
- namespaces
- endpoints
verbs: ["list", "watch"]
- apiGroups: ["extensions"]
resources:
- daemonsets
- deployments
- replicasets
verbs: ["list", "watch"]
- apiGroups: ["apps"]
resources:
- statefulsets
verbs: ["list", "watch"]
- apiGroups: ["batch"]
resources:
- cronjobs
- jobs
verbs: ["list", "watch"]
- apiGroups: ["autoscaling"]
resources:
- horizontalpodautoscalers
verbs: ["list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: kube-state-metrics-resizer
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups: [""]
resources:
- pods
verbs: ["get"]
- apiGroups: ["extensions"]
resources:
- deployments
resourceNames: ["kube-state-metrics"]
verbs: ["get", "update"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: kube-state-metrics
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: kube-state-metrics
subjects:
- kind: ServiceAccount
name: kube-state-metrics
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: kube-state-metrics
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: kube-state-metrics-resizer
subjects:
- kind: ServiceAccount
name: kube-state-metrics
namespace: kube-system
[root@k8s-master prometheus-k8s]# kubectl apply -f kube-state-metrics-rbac.yaml
  1. 编写Deployment和ConfigMap的yaml进行metrics pod部署,不需要进行修改
[root@k8s-master prometheus-k8s]# cat kube-state-metrics-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: kube-state-metrics
namespace: kube-system
labels:
k8s-app: kube-state-metrics
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
version: v1.3.0
spec:
selector:
matchLabels:
k8s-app: kube-state-metrics
version: v1.3.0
replicas: 1
template:
metadata:
labels:
k8s-app: kube-state-metrics
version: v1.3.0
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ''
spec:
priorityClassName: system-cluster-critical
serviceAccountName: kube-state-metrics
containers:
- name: kube-state-metrics
image: lizhenliang/kube-state-metrics:v1.3.0
ports:
- name: http-metrics
containerPort: 8080
- name: telemetry
containerPort: 8081
readinessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 5
timeoutSeconds: 5
- name: addon-resizer
image: lizhenliang/addon-resizer:1.8.3
resources:
limits:
cpu: 100m
memory: 30Mi
requests:
cpu: 100m
memory: 30Mi
env:
- name: MY_POD_NAME
valueFrom:
fieldRef:
fieldPath: metadata.name
- name: MY_POD_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
volumeMounts:
- name: config-volume
mountPath: /etc/config
command:
- /pod_nanny
- --config-dir=/etc/config
- --container=kube-state-metrics
- --cpu=100m
- --extra-cpu=1m
- --memory=100Mi
- --extra-memory=2Mi
- --threshold=5
- --deployment=kube-state-metrics
volumes:
- name: config-volume
configMap:
name: kube-state-metrics-config
---
# Config map for resource configuration.
apiVersion: v1
kind: ConfigMap
metadata:
name: kube-state-metrics-config
namespace: kube-system
labels:
k8s-app: kube-state-metrics
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
data:
NannyConfiguration: |-
apiVersion: nannyconfig/v1alpha1
kind: NannyConfiguration
[root@k8s-master prometheus-k8s]# kubectl apply -f kube-state-metrics-deployment.yaml

      2.编写Service的yaml对metrics进行端口暴露

[root@k8s-master prometheus-k8s]# cat kube-state-metrics-service.yaml
apiVersion: v1
kind: Service
metadata:
name: kube-state-metrics
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/name: "kube-state-metrics"
annotations:
prometheus.io/scrape: 'true'
spec:
ports:
- name: http-metrics
port: 8080
targetPort: http-metrics
protocol: TCP
- name: telemetry
port: 8081
targetPort: telemetry
protocol: TCP
selector:
k8s-app: kube-state-metrics
[root@k8s-master prometheus-k8s]# kubectl apply -f kube-state-metrics-service.yaml

     3.检查pod和svc的状态,可以看到正常运行了pod/kube-state-metrics-7c76bdbf68-kqqgd 和对外暴露了8080和8081端口

[root@k8s-master prometheus-k8s]# kubectl get pod,svc -n kube-system
NAME READY STATUS RESTARTS AGE
pod/alertmanager-5d75d5688f-fmlq6 2/2 Running 0 9dpod/coredns-5bd5f9dbd9-wv45t 1/1 Running 1 9dpod/grafana-0 1/1 Running 2 15dpod/kube-state-metrics-7c76bdbf68-kqqgd 2/2 Running 6 14dpod/kubernetes-dashboard-7d77666777-d5ng4 1/1 Running 5 16dpod/prometheus-0 2/2 Running 6 15dNAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/alertmanager ClusterIP 10.0.0.207 <none> 80/TCP 13dservice/grafana NodePort 10.0.0.74 <none> 80:30091/TCP 15dservice/kube-dns ClusterIP 10.0.0.2 <none> 53/UDP,53/TCP 14dservice/kube-state-metrics ClusterIP 10.0.0.194 <none> 8080/TCP,8081/TCP 14dservice/kubernetes-dashboard NodePort 10.0.0.127 <none> 443:30001/TCP 17dservice/prometheus NodePort 10.0.0.33 <none> 9090:30090/TCP 14d[root@k8s-master prometheus-k8s]#

5 使用Grafana可视化展示Prometheus监控数据

通常在使用Prometheus采集数据的时候我们需要监控K8S集群中Pod、Node、资源对象,因此我们需要安装对应的插件和资源采集器来提供api进行数据获取,在4.3中我们已经配置好,我们也可以使用Prometheus的UI界面中的Staus菜单下的Target中的各个采集器的状态情况,如图所示:

k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim_07

k8s实战之部署Prometheus+Grafana可视化监控告警平台_github_08

只有当我们各个Target的状态都是UP状态时,我们可以使用自带的的界面去获取到某一监控项的相关的数据,如图所示:

k8s实战之部署Prometheus+Grafana可视化监控告警平台_github_09

从上面的图中可以看出Prometheus的界面可视化展示的功能较单一,不能满足需求,因此我们需要结合Grafana来进行可视化展示Prometheus监控数据,在上一章节,已经成功部署了Granfana,因此需要在使用的时候添加dashboard和Panel来设计展示相关的监控项,但是实际上在Granfana社区里面有很多成熟的模板,我们可以直接使用,然后根据自己的环境修改Panel中的查询语句来获取数据

​https://grafana.com/grafana/dashboards​

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_10


推荐模板:



集群资源监控的模板号:3119,如图所示进行添加




k8s实战之部署Prometheus+Grafana可视化监控告警平台_github_11



k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim_12

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_13

当模板添加之后如果某一个Panel不显示数据,可以点击Panel上的编辑,查询PromQL语句,然后去Prometheus自己的界面上进行调试PromQL语句是否可以获取到值,最后调整之后的监控界面如图所示

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_14


k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim_15



资源状态监控:6417
同理,添加资源状态的监控模板,然后经过调整之后的监控界面如图所示,可以获取到k8s中各种资源状态的监控展示


k8s实战之部署Prometheus+Grafana可视化监控告警平台_github_16



Node监控:9276
同理,添加资源状态的监控模板,然后经过调整之后的监控界面如图所示,可以获取到各个node上的基本情况



k8s实战之部署Prometheus+Grafana可视化监控告警平台_github_17



6 在K8S中部署Alertmanager

6.1 部署Alertmanager的实现步骤

k8s实战之部署Prometheus+Grafana可视化监控告警平台_github_18

6.2 部署告警

我们以Email来进行实现告警信息的发送


  1. 首先需要准备一个发件邮箱,开启stmp发送功能
  2. 使用configmap存储告警规则,编写报警规则的yaml文件,可根据自己的实际情况进行修改和添加报警的规则,prometheus比zabbix就麻烦在这里,所有的告警规则需要自己去定义

[root@k8s-master prometheus-k8s]# vim prometheus-rules.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-rules
namespace: kube-system
data:
general.rules: |
groups:
- name: general.rules
rules:
- alert: InstanceDown
expr: up == 0
for: 1m
labels:
severity: error
annotations:
summary: "Instance {{ $labels.instance }} 停止工作"
description: "{{ $labels.instance }} job {{ $labels.job }} 已经停止5分钟以上."
node.rules: |
groups:
- name: node.rules
rules:
- alert: NodeFilesystemUsage
expr: 100 - (node_filesystem_free_bytes{fstype=~"ext4|xfs"} / node_filesystem_size_bytes{fstype=~"ext4|xfs"} * 100) > 80
for: 1m
labels:
severity: warning
annotations:
summary: "Instance {{ $labels.instance }} : {{ $labels.mountpoint }} 分区使用率过高"
description: "{{ $labels.instance }}: {{ $labels.mountpoint }} 分区使用大于80% (当前值: {{ $value }})"


- alert: NodeMemoryUsage
expr: 100 - (node_memory_MemFree_bytes+node_memory_Cached_bytes+node_memory_Buffers_bytes) / node_memory_MemTotal_bytes * 10
0 > 80
for: 1m
labels:
severity: warning
annotations:
summary: "Instance {{ $labels.instance }} 内存使用率过高"
description: "{{ $labels.instance }}内存使用大于80% (当前值: {{ $value }})"


- alert: NodeCPUUsage
expr: 100 - (avg(irate(node_cpu_seconds_total{mode="idle"}[5m])) by (instance) * 100) > 60
for: 1m
labels:
severity: warning
annotations:
summary: "Instance {{ $labels.instance }} CPU使用率过高"
description: "{{ $labels.instance }}CPU使用大于60% (当前值: {{ $value }})"
[root@k8s-master prometheus-k8s]# kubectl apply -f prometheus-rules.yaml

     3.编写告警configmap的yaml文件部署,增加alertmanager告警配置,进行配置邮箱发送地址

[root@k8s-master prometheus-k8s]# vim alertmanager-configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: alertmanager-config
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: EnsureExists
data:
alertmanager.yml: |
global:
resolve_timeout: 5m
smtp_smarthost: 'xxx.com.cn:25' #登陆邮件进行查看
smtp_from: 'xxx@126.com.cn' #根据自己申请的发件邮箱进行配置
smtp_auth_username: 'xxx@qq.com.cn'
smtp_auth_password: 'xxxxx'


receivers:
- name: default-receiver
email_configs:
- to: "zhangdongdong27459@goldwind.com.cn"


route:
group_interval: 1m
group_wait: 10s
receiver: default-receiver
repeat_interval: 1m
[root@k8s-master prometheus-k8s]# kubectl apply -f alertmanager-configmap.yaml

     4.创建PVC进行数据持久化,我这个yaml文件使用的跟Prometheus安装时用的存储类来进行自动供给,需要根据自己的实际情况修改

[root@k8s-master prometheus-k8s]# vim alertmanager-pvc.yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: alertmanager
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: EnsureExists
spec:
storageClassName: managed-nfs-storage
accessModes:
- ReadWriteOnce
resources:
requests:
storage: "2Gi"
[root@k8s-master prometheus-k8s]# kubectl apply -f alertmanager-pvc.yaml

      5.编写deployment的yaml来部署alertmanager的pod

[root@k8s-master prometheus-k8s]# vim alertmanager-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: alertmanager
namespace: kube-system
labels:
k8s-app: alertmanager
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
version: v0.14.0
spec:
replicas: 1
selector:
matchLabels:
k8s-app: alertmanager
version: v0.14.0
template:
metadata:
labels:
k8s-app: alertmanager
version: v0.14.0
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ''
spec:
priorityClassName: system-cluster-critical
containers:
- name: prometheus-alertmanager
image: "prom/alertmanager:v0.14.0"
imagePullPolicy: "IfNotPresent"
args:
- --config.file=/etc/config/alertmanager.yml
- --storage.path=/data
- --web.external-url=/
ports:
- containerPort: 9093
readinessProbe:
httpGet:
path: /#/status
port: 9093
initialDelaySeconds: 30
timeoutSeconds: 30
volumeMounts:
- name: config-volume
mountPath: /etc/config
- name: storage-volume
mountPath: "/data"
subPath: ""
resources:
limits:
cpu: 10m
memory: 50Mi
requests:
cpu: 10m
memory: 50Mi
- name: prometheus-alertmanager-configmap-reload
image: "jimmidyson/configmap-reload:v0.1"
imagePullPolicy: "IfNotPresent"
args:
- --volume-dir=/etc/config
- --webhook-url=http://localhost:9093/-/reload
volumeMounts:
- name: config-volume
mountPath: /etc/config
readOnly: true
resources:
limits:
cpu: 10m
memory: 10Mi
requests:
cpu: 10m
memory: 10Mi
volumes:
- name: config-volume
configMap:
name: alertmanager-config
- name: storage-volume
persistentVolumeClaim:
claimName: alertmanager
[root@k8s-master prometheus-k8s]# kubectl apply -f alertmanager-deployment.yaml

        6.创建 alertmanager的service对外暴露的端口

[root@k8s-master prometheus-k8s]# vim alertmanager-service.yaml
apiVersion: v1
kind: Service
metadata:
name: alertmanager
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/name: "Alertmanager"
spec:
ports:
- name: http
port: 80
protocol: TCP
targetPort: 9093
selector:
k8s-app: alertmanager
type: "ClusterIP"
[root@k8s-master prometheus-k8s]# kubectl apply -f alertmanager-service.yaml

     7.检测部署状态,可以发现pod/alertmanager-5d75d5688f-fmlq6和service/alertmanager正常运行

[root@k8s-master prometheus-k8s]# kubectl get pod,svc -n kube-system -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pod/alertmanager-5d75d5688f-fmlq6 2/2 Running 4 10d 172.17.15.2 192.168.73.140 <none> <none>
pod/coredns-5bd5f9dbd9-qxvmz 1/1 Running 0 42m 172.17.33.2 192.168.73.138 <none> <none>
pod/grafana-0 1/1 Running 3 16d 172.17.31.2 192.168.73.139 <none> <none>
pod/kube-state-metrics-7c76bdbf68-hv56m 2/2 Running 0 23h 172.17.15.3 192.168.73.140 <none> <none>
pod/kubernetes-dashboard-7d77666777-d5ng4 1/1 Running 6 17d 172.17.31.4 192.168.73.139 <none> <none>
pod/prometheus-0 2/2 Running 8 16d 172.17.83.2 192.168.73.135 <none> <none>


NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
service/alertmanager ClusterIP 10.0.0.207 <none> 80/TCP 14d k8s-app=alertmanager
service/grafana NodePort 10.0.0.74 <none> 80:30091/TCP 16d app=grafana
service/kube-dns ClusterIP 10.0.0.2 <none> 53/UDP,53/TCP 42m k8s-app=kube-dns
service/kube-state-metrics ClusterIP 10.0.0.194 <none> 8080/TCP,8081/TCP 15d k8s-app=kube-state-metrics
service/kubernetes-dashboard NodePort 10.0.0.127 <none> 443:30001/TCP 18d k8s-app=kubernetes-dashboard
service/prometheus NodePort 10.0.0.33 <none> 9090:30090/TCP 15d k8s-app=prometheus

6.3 测试告警发送

登录prometheus默认的web界面,选择Alert菜单,则可以看到刚才我们使用prometheus-rules.yaml定义的的四个告警规则

k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim_19

因为告警规则中定义了一个InstanceDown 的实例,所以我们可以停掉138服务器上的kubelet,来测试是否可以收到报警邮件发送


[root@k8s-master prometheus-k8s]# kubectl get node
NAME STATUS ROLES AGE VERSION
192.168.73.135 Ready <none> 18d v1.15.2
192.168.73.138 Ready <none> 17d v1.15.2
192.168.73.139 Ready <none> 19d v1.15.2
192.168.73.140 Ready <none> 19d v1.15.2
[root@k8s-master prometheus-k8s]# systemctl stop kubelet
[root@k8s-master prometheus-k8s]# kubectl get node
NAME STATUS ROLES AGE VERSION
192.168.73.135 NotReady <none> 18d v1.15.2
192.168.73.138 Ready <none> 17d v1.15.2
192.168.73.139 Ready <none> 19d v1.15.2
192.168.73.140   Ready      <none>   19d   v1.15.2

稍微等一会,我们再刷新刚才的web上的告警规则界面,可以发现InstanceDown 的实例颜色变成粉红色了,并且显示2 active

k8s实战之部署Prometheus+Grafana可视化监控告警平台_数据_20

根据规则等待五分钟之后,我们去刷新刚才配置的告警收件箱,收到了一个封InstanceDown 的邮件提醒,邮件的发送间隔时间可以在alertmanager-configmap.yaml配置文件中进行设置,恢复刚才停止的kubelet,将不会收到告警邮件提醒

k8s实战之部署Prometheus+Grafana可视化监控告警平台_vim_21

如果各位大佬看到这里,相信已经对于如何在k8s集群中部署一套Prometheus监控平台来可视化进行数据的展示和告警有了一定了解,读万卷书,不如行万里路,还是希望大家能够自己多去实操

在此特别鸣谢李振良老师的指导,感兴趣的同学可以去腾旭课堂搜他相关的课程

写的不好,有问题欢迎大家一起讨论学习

写在最后


- 如果各位大佬看到这里,相信已经对于如何在k8s集群中部署一套Prometheus监控平台来可视化进行数据的展示和告警有了一定了解,读万卷书,不如行万里路,还是希望大家能够自己多去实操

- 在此特别鸣谢李振良老师的指导,感兴趣的同学可以去腾讯课堂搜他相关的课程

-写的不好,有问题欢迎大家一起讨论学习