1.创建命名空间
新建一个yaml文件命名为monitor-namespace.yaml，写入如下内容：
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
执行如下命令创建monitoring命名空间：
kubectl create -f monitor-namespace.yaml
2.创建ClusterRole
你需要对上面创建的命名空间分配集群的读取权限，以便Prometheus可以通过Kubernetes的API获取集群的资源目标。
新建一个yaml文件命名为cluster-role.yaml，写入如下内容：
apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRole metadata: name: prometheus rules: - apiGroups: [""] resources: - nodes - nodes/proxy - services - endpoints - pods verbs: ["get", "list", "watch"] - apiGroups: - extensions resources: - ingresses verbs: ["get", "list", "watch"] - nonResourceURLs: ["/metrics"] verbs: ["get"] --- apiVersion: rbac.authorization.k8s.io/v1beta1 kind: ClusterRoleBinding metadata: name: prometheus roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: prometheus subjects: - kind: ServiceAccount name: default namespace: monitoring
执行如下命令创建:
kubectl create -f cluster-role.yaml
3.创建Config Map
我们需要创建一个Config Map保存后面创建Prometheus容器用到的一些配置，这些配置包含了从Kubernetes集群中动态发现pods和运行中的服务。
新建一个yaml文件命名为config-map.yaml，写入如下内容：
apiVersion: v1 kind: ConfigMap metadata: name: prometheus-server-conf labels: name: prometheus-server-conf namespace: monitoring data: prometheus.yml: |- global: scrape_interval: 5s evaluation_interval: 5s scrape_configs: - job_name: 'kubernetes-apiservers' kubernetes_sd_configs: - role: endpoints 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] action: keep regex: default;kubernetes;https - job_name: 'kubernetes-nodes' scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token kubernetes_sd_configs: - role: node relabel_configs: - action: labelmap regex: __meta_kubernetes_node_label_(.+) - target_label: __address__ replacement: kubernetes.default.svc:443 - source_labels: [__meta_kubernetes_node_name] regex: (.+) target_label: __metrics_path__ replacement: /api/v1/nodes/${1}/proxy/metrics - job_name: 'kubernetes-pods' kubernetes_sd_configs: - role: pod relabel_configs: - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape] action: keep regex: true - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path] action: replace target_label: __metrics_path__ regex: (.+) - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port] action: replace regex: ([^:]+)(?::d+)?;(d+) replacement: $1:$2 target_label: __address__ - action: labelmap regex: __meta_kubernetes_pod_label_(.+) - source_labels: [__meta_kubernetes_namespace] action: replace target_label: kubernetes_namespace - source_labels: [__meta_kubernetes_pod_name] action: replace target_label: kubernetes_pod_name - job_name: 'kubernetes-cadvisor' scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token kubernetes_sd_configs: - role: node relabel_configs: - action: labelmap regex: __meta_kubernetes_node_label_(.+) - target_label: __address__ replacement: kubernetes.default.svc:443 - source_labels: [__meta_kubernetes_node_name] regex: (.+) target_label: __metrics_path__ replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor - 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 - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme] action: replace target_label: __scheme__ regex: (https?) - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path] action: replace target_label: __metrics_path__ regex: (.+) - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port] action: replace target_label: __address__ regex: ([^:]+)(?::d+)?;(d+) replacement: $1:$2 - action: labelmap regex: __meta_kubernetes_service_label_(.+) - source_labels: [__meta_kubernetes_namespace] action: replace target_label: kubernetes_namespace - source_labels: [__meta_kubernetes_service_name] action: replace target_label: kubernetes_name
执行如下命令进行创建:
kubectl create -f config-map.yaml -n monitoring
4.创建Deployment模式的Prometheus
apiVersion: extensions/v1beta1 kind: Deployment metadata: name: prometheus-deployment namespace: monitoring spec: replicas: 1 template: metadata: labels: app: prometheus-server spec: containers: - name: prometheus image: prom/prometheus:v2.3.2 args: - "--config.file=/etc/prometheus/prometheus.yml" - "--storage.tsdb.path=/prometheus/" ports: - containerPort: 9090 volumeMounts: - name: prometheus-config-volume mountPath: /etc/prometheus/ - name: prometheus-storage-volume mountPath: /prometheus/ volumes: - name: prometheus-config-volume configMap: defaultMode: 420 name: prometheus-server-conf - name: prometheus-storage-volume emptyDir: {}
使用如下命令部署:
kubectl create -f prometheus-deployment.yaml --namespace=monitoring
部署完成后通过dashboard能够看到如下的界面：
5.连接Prometheus
这里有两种方式
1.通过kubectl命令进行端口代理
2.针对Prometheus的POD暴露一个服务，推荐此种方式
首先新建一个yaml文件命名为prometheus-service.yaml，写入如下内容：
apiVersion: v1 kind: Service metadata: name: prometheus-service spec: selector: app: prometheus-server type: NodePort ports: - port: 9090 targetPort: 9090 nodePort: 30909
执行如下命令创建服务:
kubectl create -f prometheus-service.yaml --namespace=monitoring
通过以下命令查看Service的状态，我们可以看到暴露的端口是30909：
kubectl get svc -n monitoring NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE prometheus-service NodePort 10.101.186.82 <none> 9090:30909/TCP 100m
现在可以通过浏览器访问【http://虚拟机IP:30909】，看到如下界面，现在可以点击 status –> Targets，马上就可以看到所有Kubernetes集群上的Endpoint通过服务发现的方式自动连接到了Prometheus。：
我们还可以通过图形化界面查看内存：
OK，到这里Prometheus部署就算完成了，但是数据的统计明显不够直观，所以我们需要使用Grafana来构建更加友好的监控页面。
6.搭建Grafana
新建以下yaml文件：grafana-dashboard-provider.yaml
apiVersion: v1 kind: ConfigMap metadata: name: grafana-dashboard-provider namespace: monitoring data: default-dashboard.yaml: | - name: 'default' org_id: 1 folder: '' type: file options: folder: /var/lib/grafana/dashboards
grafana.yaml：
apiVersion: extensions/v1beta1 kind: Deployment metadata: name: grafana namespace: monitoring labels: app: grafana component: core spec: replicas: 1 template: metadata: labels: app: grafana component: core spec: containers: - image: grafana/grafana:5.0.0 name: grafana ports: - containerPort: 3000 resources: limits: cpu: 100m memory: 100Mi requests: cpu: 100m memory: 100Mi volumeMounts: - name: grafana-persistent-storage mountPath: /var - name: grafana-dashboard-provider mountPath: /etc/grafana/provisioning/dashboards volumes: - name: grafana-dashboard-provider configMap: name: grafana-dashboard-provider - name: grafana-persistent-storage emptyDir: {}
grafana-service.yaml：
apiVersion: v1 kind: Service metadata: labels: name: grafana name: grafana namespace: monitoring spec: type: NodePort selector: app: grafana ports: - protocol: TCP port: 3000 targetPort: 3000 nodePort: 30300
执行如下命令进行创建：
kubectl apply -f grafana-dashboard-provider.yaml kubectl apply -f grafana.yaml kubectl apply -f grafana-service.yaml
部署完成后通过Kubernetes Dashboard可以看到:
根据服务暴露出来的端口30300通过浏览器访问【http://虚拟机IP:30300】看到如下界面：
输入用户名和密码（admin/admin）即可登录。
接着我们配置数据源：
然后导入Dashboards：
将JSON文件上传
grafana-dashboard.json （百度云链接 https://pan.baidu.com/s/1YtfD3s1U_d6Yon67qjihmw 密码：n25f）
然后点击导入：
然后就可以看到Kubernetes集群的监控数据了：
还有一个资源统计的Dashboards：
kubernetes-resources-usage-dashboard.json
OK，Prometheus的监控搭建到此结束。