Kubernetes 集群部署 Prometheus 和 Grafana
实验环境
控制节点/master01 192.168.110.10
工作节点/node01 192.168.110.20
工作节点/node02 192.168.110.30
node-exporter 安装
#创建监控 namespace
kubectl create ns monitor-sa
#部署 node-exporter
mkdir /opt/prometheus
cd /opt/prometheus/
vim node-export.yaml
---
apiVersion: apps/v1
kind: DaemonSet #可以保证 k8s 集群的每个节点都运行完全一样的 pod
metadata:
name: node-exporter
namespace: monitor-sa
labels:
name: node-exporter
spec:
selector:
matchLabels:
name: node-exporter
template:
metadata:
labels:
name: node-exporter
spec:
hostPID: true
hostIPC: true
hostNetwork: true
containers:
- name: node-exporter
image: prom/node-exporter:v0.16.0
ports:
- containerPort: 9100
resources:
requests:
cpu: 0.15 #这个容器运行至少需要0.15核cpu
securityContext:
privileged: true #开启特权模式
args:
- --path.procfs
- /host/proc
- --path.sysfs
- /host/sys
- --collector.filesystem.ignored-mount-points
- '"^/(sys|proc|dev|host|etc)($|/)"'
volumeMounts:
- name: dev
mountPath: /host/dev
- name: proc
mountPath: /host/proc
- name: sys
mountPath: /host/sys
- name: rootfs
mountPath: /rootfs
tolerations:
- key: "node-role.kubernetes.io/master"
operator: "Exists"
effect: "NoSchedule"
volumes:
- name: proc
hostPath:
path: /proc
- name: dev
hostPath:
path: /dev
- name: sys
hostPath:
path: /sys
- name: rootfs
hostPath:
path: /
kubectl apply -f node-export.yaml
kubectl get pods -n monitor-sa -o wide
[root@master01 prometheus]# kubectl get pods -n monitor-sa -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
node-exporter-4mjm8 1/1 Running 5 3m40s 192.168.110.30 192.168.110.30 <none> <none>
node-exporter-kzbpv 1/1 Running 5 3m40s 192.168.110.20 192.168.110.20 <none> <none>
通过 node-exporter 采集数据
node-exporter 默认的监听端口是 9100，可以执行 curl http://主机ip:9100/metrics 获取到主机的所有监控数据
curl -Ls http://192.168.110.20:9100/metrics | grep node_cpu_seconds
curl -Ls http://192.168.110.20:9100/metrics | grep node_load
[root@node02 ~]# curl -Ls http://192.168.110.20:9100/metrics | grep node_cpu_seconds
# HELP node_cpu_seconds_total Seconds the cpus spent in each mode.
# TYPE node_cpu_seconds_total counter
node_cpu_seconds_total{cpu="0",mode="idle"} 67314.31
node_cpu_seconds_total{cpu="0",mode="iowait"} 5.25
... ...
node_cpu_seconds_total{cpu="3",mode="system"} 768.89
node_cpu_seconds_total{cpu="3",mode="user"} 143.63
[root@node02 ~]# curl -Ls http://192.168.110.20:9100/metrics | grep node_load
# HELP node_load1 1m load average.
# TYPE node_load1 gauge
node_load1 0.41
# HELP node_load15 15m load average.
# TYPE node_load15 gauge
node_load15 0.75
# HELP node_load5 5m load average.
# TYPE node_load5 gauge
node_load5 0.62
Prometheus 安装和配置
创建 sa 账号，对 sa 做 rbac 授权
#创建一个 sa 账号 monitor
kubectl create serviceaccount monitor -n monitor-sa
#把 sa 账号 monitor 通过 clusterrolebing 绑定到 clusterrole 上
kubectl create clusterrolebinding monitor-clusterrolebinding -n monitor-sa --clusterrole=cluster-admin --serviceaccount=monitor-sa:monitor
创建一个 configmap 存储卷，用来存放 prometheus 配置信息
vim prometheus-cfg.yaml
---
kind: ConfigMap
apiVersion: v1
metadata:
labels:
app: prometheus
name: prometheus-config
namespace: monitor-sa
data:
prometheus.yml: |
global: #指定prometheus的全局配置，比如采集间隔，抓取超时时间等
scrape_interval: 15s #采集目标主机监控数据的时间间隔，默认为1m
scrape_timeout: 10s #数据采集超时时间，默认10s
evaluation_interval: 1m #触发告警生成alert的时间间隔，默认是1m
scrape_configs: #配置数据源，称为target，每个target用job_name命名。又分为静态配置和服务发现
- job_name: 'kubernetes-node'
kubernetes_sd_configs: # *_sd_configs 指定的是k8s的服务发现
- role: node #使用node角色，它使用默认的kubelet提供的http端口来发现集群中每个node节点
relabel_configs: #重新标记
- source_labels: [__address__] #配置的原始标签，匹配地址
regex: '(.*):10250' #匹配带有10250端口的url
replacement: '${1}:9100' #把匹配到的ip:10250的ip保留
target_label: __address__ #新生成的url是${1}获取到的ip:9100
action: replace #动作替换
- action: labelmap
regex: __meta_kubernetes_node_label_(.+) #匹配到下面正则表达式的标签会被保留,如果不做regex正则的话，默认只是会显示instance标签
- job_name: 'kubernetes-node-cadvisor' #抓取cAdvisor数据，是获取kubelet上/metrics/cadvisor接口数据来获取容器的资源使用情况
kubernetes_sd_configs:
- role: node
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- action: labelmap #把匹配到的标签保留
regex: __meta_kubernetes_node_label_(.+) #保留匹配到的具有__meta_kubernetes_node_label的标签
- target_label: __address__ #获取到的地址：__address__="192.168.80.20:10250"
replacement: kubernetes.default.svc:443 #把获取到的地址替换成新的地址kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+) #把原始标签中__meta_kubernetes_node_name值匹配到
target_label: __metrics_path__ #获取__metrics_path__对应的值
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
#把metrics替换成新的值api/v1/nodes/<node_name>/proxy/metrics/cadvisor
#${1}是__meta_kubernetes_node_name获取到的值
#最后通过https://<apiserver_address>/api/v1/nodes/<node_name>/proxy/metrics/cadvisor来获取对应节点cadvisor监控数据
- job_name: 'kubernetes-apiserver'
kubernetes_sd_configs:
- role: endpoints #使用k8s中的endpoint服务发现，采集apiserver 6443端口获取到的数据
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name] #[endpoint这个对象的名称空间,endpoint对象的服务名,exnpoint的端口名称]
action: keep #采集满足条件的实例，其他实例不采集
regex: default;kubernetes;https #正则匹配到的默认空间下的service名字是kubernetes，协议是https的endpoint类型保留下来
- job_name: 'kubernetes-service-endpoints'
kubernetes_sd_configs:
- role: endpoints
relabel_configs:
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
action: keep
regex: true
#重新打标仅抓取到的具有"prometheus.io/scrape: true"的annotation的端点， 意思是说如果某个service具有prometheus.io/scrape = true的annotation声明则抓取，annotation本身也是键值结构， 所以这里的源标签设置为键，而regex设置值true，当值匹配到regex设定的内容时则执行keep动作也就是保留，其余则丢弃。
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
action: replace
target_label: __scheme__
regex: (https?)
#重新设置scheme，匹配源标签__meta_kubernetes_service_annotation_prometheus_io_scheme也就是prometheus.io/scheme annotation，如果源标签的值匹配到regex，则把值替换为__scheme__对应的值。
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
action: replace
target_label: __metrics_path__
regex: (.+)
#应用中自定义暴露的指标，也许你暴露的API接口不是/metrics这个路径，那么你可以在这个POD对应的service中做一个 "prometheus.io/path = /mymetrics" 声明，上面的意思就是把你声明的这个路径赋值给__metrics_path__， 其实就是让prometheus来获取自定义应用暴露的metrices的具体路径， 不过这里写的要和service中做好约定，如果service中这样写 prometheus.io/app-metrics-path: '/metrics' 那么你这里就要__meta_kubernetes_service_annotation_prometheus_io_app_metrics_path这样写。
- source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
action: replace
target_label: __address__
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
#暴露自定义的应用的端口，就是把地址和你在service中定义的 "prometheus.io/port = <port>" 声明做一个拼接， 然后赋值给__address__，这样prometheus就能获取自定义应用的端口，然后通过这个端口再结合__metrics_path__来获取指标，如果__metrics_path__值不是默认的/metrics那么就要使用上面的标签替换来获取真正暴露的具体路径。
- action: labelmap #保留下面匹配到的标签
regex: __meta_kubernetes_service_label_(.+)
- source_labels: [__meta_kubernetes_namespace]
action: replace #替换__meta_kubernetes_namespace变成kubernetes_namespace
target_label: kubernetes_namespace
- source_labels: [__meta_kubernetes_service_name]
action: replace
target_label: kubernetes_name
kubectl apply -f prometheus-cfg.yaml
通过 deployment 部署 prometheus
#将 prometheus 调度到 node1 节点，在 node1 节点创建 prometheus 数据存储目录
mkdir /data && chmod 777 /data
#通过 deployment 部署 prometheus
vim prometheus-deploy.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus-server
namespace: monitor-sa
labels:
app: prometheus
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
component: server
#matchExpressions:
#- {key: app, operator: In, values: [prometheus]}
#- {key: component, operator: In, values: [server]}
template:
metadata:
labels:
app: prometheus
component: server
annotations:
prometheus.io/scrape: 'false'
spec:
nodeName: 192.168.110.20 #指定pod调度到哪个节点上
serviceAccountName: monitor
containers:
- name: prometheus
image: prom/prometheus:v2.2.1
imagePullPolicy: IfNotPresent
command:
- prometheus
- --config.file=/etc/prometheus/prometheus.yml
- --storage.tsdb.path=/prometheus #数据存储目录
- --storage.tsdb.retention=720h #数据保存时长
- --web.enable-lifecycle #开启热加载
ports:
- containerPort: 9090
protocol: TCP
volumeMounts:
- mountPath: /etc/prometheus/prometheus.yml
name: prometheus-config
subPath: prometheus.yml
- mountPath: /prometheus/
name: prometheus-storage-volume
volumes:
- name: prometheus-config
configMap:
name: prometheus-config
items:
- key: prometheus.yml
path: prometheus.yml
mode: 0644
- name: prometheus-storage-volume
hostPath:
path: /data
type: Directory
kubectl apply -f prometheus-deploy.yaml
kubectl get pods -o wide -n monitor-sa
[root@master01 prometheus]# kubectl get pods -o wide -n monitor-sa
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
node-exporter-4mjm8 1/1 Running 5 15m 192.168.110.30 192.168.110.30 <none> <none>
node-exporter-kzbpv 1/1 Running 5 15m 192.168.110.20 192.168.110.20 <none> <none>
prometheus-server-75fb7f8fc6-9rrl7 0/1 Pending 0 49s <none> node01 <none> <none>
给 prometheus pod 创建一个 service
vim prometheus-svc.yaml
---
apiVersion: v1
kind: Service
metadata:
name: prometheus
namespace: monitor-sa
labels:
app: prometheus
spec:
type: NodePort
ports:
- port: 9090
targetPort: 9090
protocol: TCP
nodePort: 31000
selector:
app: prometheus
component: server
kubectl apply -f prometheus-svc.yaml
kubectl get pods -o wide -n monitor-sa
kubectl get svc -n monitor-sa
[root@master01 prometheus]# kubectl get pods -o wide -n monitor-sa
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
node-exporter-7lfl8 1/1 Running 9 2d12h 192.168.110.20 192.168.110.20 <none> <none>
node-exporter-hnpm2 1/1 Running 0 2d12h 192.168.110.30 192.168.110.30 <none> <none>
prometheus-server-84b77ffcf8-mj5rp 1/1 Running 0 5m22s 10.244.60.102 192.168.110.20 <none> <none>
[root@master01 prometheus]# kubectl get svc -n monitor-sa
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
prometheus NodePort 10.0.0.113 <none> 9090:31000/TCP 5d5h
如发现镜像拉取失败导致无法建立 pod 检查docker 版本，要使用19.xx.x-22.xx.x 版
通过上面可以看到 service 在 node 节点上映射的端口是 31000，这样我们访问 k8s 集群的 node 节点的 ip:31000，就可以访问到 prometheus 的 web ui 界面了。
浏览器访问 http://192.168.110.20:31000
点击页面的Status->Targets，如看到所有 Target 状态都为 UP，说明我们配置的服务发现可以正常采集数据
查询 K8S 集群中一分钟之内每个 Pod 的 CPU 使用率
sum by (name)( rate(container_cpu_usage_seconds_total{image!=“”, name!=“”}[1m] ) )
Prometheus 配置热加载
为了每次修改配置文件可以热加载prometheus，也就是不停止prometheus就可以使配置生效。想要使配置生效可用如下热加载命令：
kubectl get pods -n monitor-sa -o wide -l app=prometheus
[root@master01 prometheus]# kubectl get pods -n monitor-sa -o wide -l app=prometheus
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
prometheus-server-84b77ffcf8-mj5rp 1/1 Running 0 13m 10.244.60.102 192.168.110.20 <none> <none>
想要使配置生效可用如下命令热加载
curl -X POST -Ls http://10.244.60.102:9090/-/reload
查看 log
kubectl logs -n monitor-sa prometheus-server-84b77ffcf8-mj5rp | grep "Loading configuration file"
[root@master01 prometheus]# kubectl logs -n monitor-sa prometheus-server-84b77ffcf8-mj5rp | grep "Loading configuration file"
level=info ts=2025-02-19T14:18:55.772194011Z caller=main.go:588 msg="Loading configuration file" filename=/etc/prometheus/prometheus.yml
一般热加载速度比较慢，可以暴力重启prometheus，如修改上面的 prometheus-cfg.yaml 文件之后，可用如下命令：
可执行先强制删除，然后再通过 apply 更新
kubectl delete -f prometheus-cfg.yaml
kubectl delete -f prometheus-deploy.yaml
kubectl apply -f prometheus-cfg.yaml
kubectl apply -f prometheus-deploy.yaml
Grafana 安装
部署
vim grafana.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: monitoring-grafana
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
task: monitoring
k8s-app: grafana
template:
metadata:
labels:
task: monitoring
k8s-app: grafana
spec:
containers:
- name: grafana
image: grafana/grafana:5.0.4
ports:
- containerPort: 3000
protocol: TCP
volumeMounts:
- mountPath: /etc/ssl/certs
name: ca-certificates
readOnly: true
- mountPath: /var
name: grafana-storage
env:
- name: INFLUXDB_HOST
value: monitoring-influxdb
- name: GF_SERVER_HTTP_PORT
value: "3000"
# The following env variables are required to make Grafana accessible via
# the kubernetes api-server proxy. On production clusters, we recommend
# removing these env variables, setup auth for grafana, and expose the grafana
# service using a LoadBalancer or a public IP.
- name: GF_AUTH_BASIC_ENABLED
value: "false"
- name: GF_AUTH_ANONYMOUS_ENABLED
value: "true"
- name: GF_AUTH_ANONYMOUS_ORG_ROLE
value: Admin
- name: GF_SERVER_ROOT_URL
# If you're only using the API Server proxy, set this value instead:
# value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
value: /
volumes:
- name: ca-certificates
hostPath:
path: /etc/ssl/certs
- name: grafana-storage
emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
labels:
# For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
# If you are NOT using this as an addon, you should comment out this line.
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: monitoring-grafana
name: monitoring-grafana
namespace: kube-system
spec:
# In a production setup, we recommend accessing Grafana through an external Loadbalancer
# or through a public IP.
# type: LoadBalancer
# You could also use NodePort to expose the service at a randomly-generated port
# type: NodePort
ports:
- port: 80
targetPort: 3000
selector:
k8s-app: grafana
type: NodePort
kubectl apply -f grafana.yaml
kubectl get pods -n kube-system -l task=monitoring -o wide
kubectl get svc -n kube-system | grep grafana
[root@master01 prometheus]# kubectl get pods -n kube-system -l task=monitoring -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
monitoring-grafana-fd8554c5c-nffvn 1/1 Running 0 3m6s 10.244.60.107 192.168.110.20 <none> <none>
[root@master01 prometheus]# kubectl get svc -n kube-system | grep grafana monitoring-grafana NodePort 10.0.0.231 <none> 80:35196/TCP 3m12s
Grafana 配置
浏览器访问http://192.168.110.20:35196 ，登陆 grafana
开始配置 grafana 的 web 界面：选择 Add data source
【Name】设置成 Prometheus
【Type】选择 Prometheus
【URL】设置成 http://prometheus.monitor-sa.svc:9090 #使用service的集群内部端口配置服务端地址
点击 【Save & Test】
导入监控模板
官方链接搜索：https://grafana.com/dashboards?dataSource=prometheus&search=kubernetes
监控 node 状态
点击左侧+号选择【Import】
点击【Upload .json File】导入 node_exporter.json 模板
【Prometheus】选择 Prometheus
点击【Import】
监控 容器 状态
点击左侧+号选择【Import】
点击【Upload Upload .json File】导入 docker 模板
【Prometheus】选择 Prometheus
点击【Import】
k8s 部署 kube-state-metrics 组件
（1）安装 kube-state-metrics 组件
#创建 sa，并对 sa 授权
vim kube-state-metrics-rbac.yaml
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: kube-state-metrics
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: kube-state-metrics
rules:
- apiGroups: [""]
resources: ["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: ClusterRoleBinding
metadata:
name: kube-state-metrics
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: kube-state-metrics
subjects:
- kind: ServiceAccount
name: kube-state-metrics
namespace: kube-system
kubectl apply -f kube-state-metrics-rbac.yaml
#安装 kube-state-metrics 组件和 service
vim kube-state-metrics-deploy.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: kube-state-metrics
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
app: kube-state-metrics
template:
metadata:
labels:
app: kube-state-metrics
spec:
serviceAccountName: kube-state-metrics
containers:
- name: kube-state-metrics
image: quay.io/coreos/kube-state-metrics:v1.9.0
ports:
- containerPort: 8080
---
apiVersion: v1
kind: Service
metadata:
annotations:
prometheus.io/scrape: 'true'
name: kube-state-metrics
namespace: kube-system
labels:
app: kube-state-metrics
spec:
ports:
- name: kube-state-metrics
port: 8080
protocol: TCP
selector:
app: kube-state-metrics
kubectl apply -f kube-state-metrics-deploy.yaml
kubectl get pods,svc -n kube-system -l app=kube-state-metrics
[root@master01 prometheus]# kubectl get pods,svc -n kube-system -l app=kube-state-metrics
NAME READY STATUS RESTARTS AGE
pod/kube-state-metrics-58d4957bc5-2vx5j 1/1 Running 0 9s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/kube-state-metrics ClusterIP 10.0.0.41 <none> 8080/TCP 9s
（2）Grafana 配置
#监控 k8s 群集状态
点击左侧+号选择【Import】
点击【Upload .json File】导入 kubernetes-cluster-prometheus_rev4.json 模板
【Prometheus】选择 Prometheus
点击【Import】
监控 k8s 群集性能状态
点击左侧+号选择【Import】
点击【Upload .json File】导入 kubernetes-cluster-monitoring-via-prometheus_rev3.json 模板
【Prometheus】选择 Prometheus
点击【Import】
