Joe Blog
文档说明
实验环境：kubernetes Version v1.10.9 网络CNI：fannel 存储CSI: NFS Dynamic Class DNS: CoreDNS
背景
在学习Prometheus Operator 的部署，Prometheus 在代码上就已经对 Kubernetes 有了原生的支持，可以通过服务发现的形式来自动监控集群，因此我们可以使用另外一种更加高级的方式来部署 Prometheus：Operator 框架。
Prometheus-Operator的架构图：
上图是Prometheus-Operator官方提供的架构图，其中Operator是最核心的部分，作为一个控制器，他会去创建Prometheus、ServiceMonitor、AlertManager以及PrometheusRule4个CRD资源对象，然后会一直监控并维持这4个资源对象的状态。
其中创建的prometheus这种资源对象就是作为Prometheus Server存在，而ServiceMonitor就是exporter的各种抽象，exporter前面我们已经学习了，是用来提供专门提供metrics数据接口的工具，Prometheus就是通过ServiceMonitor提供的metrics数据接口去 pull 数据的，当然alertmanager这种资源对象就是对应的AlertManager的抽象，而PrometheusRule是用来被Prometheus实例使用的报警规则文件。
这样我们要在集群中监控什么数据，就变成了直接去操作 Kubernetes 集群的资源对象了，是不是方便很多了。上图中的 Service 和 ServiceMonitor 都是 Kubernetes 的资源，一个 ServiceMonitor 可以通过 labelSelector 的方式去匹配一类 Service，Prometheus 也可以通过 labelSelector 去匹配多个ServiceMonitor。
安装Operator
$ git clone https://github.com/coreos/prometheus-operator
$ cd contrib/kube-prometheus/manifests/
$ ls
00namespace-namespace.yaml node-exporter-clusterRole.yaml
0prometheus-operator-0alertmanagerCustomResourceDefinition.yaml node-exporter-daemonset.yaml
......
prometheus-serviceMonitorKubelet.yaml进行简单的修改，因为默认情况下，这个 ServiceMonitor 是关联的 kubelet 的10250端口去采集的节点数据，而我们前面说过为了安全，这个 metrics 数据已经迁移到10255这个只读端口上,我们只需要将文件中的https-metrics更改成http-metrics即可
root@k8s-master-1:~/k8s_manifests/prometheus-operator# cat prometheus-serviceMonitorKubelet.yaml
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
labels:
k8s-app: kubelet
name: kubelet
namespace: monitoring
spec:
endpoints:
- bearerTokenFile: /var/run/secrets/kubernetes.io/serviceaccount/token
honorLabels: true
interval: 30s
port: http-metrics
scheme: http
tlsConfig:
insecureSkipVerify: true
- bearerTokenFile: /var/run/secrets/kubernetes.io/serviceaccount/token
honorLabels: true
interval: 30s
path: /metrics/cadvisor
port: http-metrics
scheme: http
tlsConfig:
insecureSkipVerify: true
jobLabel: k8s-app
namespaceSelector:
matchNames:
- kube-system
selector:
matchLabels:
k8s-app: kubelet
修改完成后，直接在该文件夹下面执行创建资源命令即可：
root@k8s-master-1:~/k8s_manifests/prometheus-operator# kubectl apply -f .
root@k8s-master-1:~/k8s_manifests/prometheus-operator# ls
00namespace-namespace.yaml grafana-dashboardDefinitions.yaml node-exporter-clusterRole.yaml prometheus-clusterRoleBinding.yaml
0prometheus-operator-0alertmanagerCustomResourceDefinition.yaml grafana-dashboardSources.yaml node-exporter-clusterRoleBinding.yaml prometheus-k8s-ingress.yaml
0prometheus-operator-0prometheusCustomResourceDefinition.yaml grafana-deployment.yaml node-exporter-daemonset-017.yaml prometheus-kubeSchedulerService.yaml
0prometheus-operator-0prometheusruleCustomResourceDefinition.yaml grafana-ingress.yaml node-exporter-daemonset.yaml prometheus-prometheus.yaml
0prometheus-operator-0servicemonitorCustomResourceDefinition.yaml grafana-service.yaml node-exporter-service.yaml prometheus-roleBindingConfig.yaml
0prometheus-operator-clusterRole.yaml grafana-serviceAccount.yaml node-exporter-serviceAccount.yaml prometheus-roleBindingSpecificNamespaces.yaml
0prometheus-operator-clusterRoleBinding.yaml kube-controller-manager-endpoints.yaml node-exporter-serviceMonitor.yaml prometheus-roleConfig.yaml
0prometheus-operator-deployment.yaml kube-controller-manager-service.yaml prometheus-adapter-apiService.yaml prometheus-roleSpecificNamespaces.yaml
0prometheus-operator-service.yaml kube-scheduler-endpoints.yaml prometheus-adapter-clusterRole.yaml prometheus-rules.yaml
0prometheus-operator-serviceAccount.yaml kube-scheduler-service.yaml prometheus-adapter-clusterRoleBinding.yaml prometheus-service.yaml
0prometheus-operator-serviceMonitor.yaml kube-state-metrics-clusterRole.yaml prometheus-adapter-clusterRoleBindingDelegator.yaml prometheus-serviceAccount.yaml
alertmanager-alertmanager.yaml kube-state-metrics-clusterRoleBinding.yaml prometheus-adapter-clusterRoleServerResources.yaml prometheus-serviceMonitor.yaml
alertmanager-secret.yaml kube-state-metrics-deployment.yaml prometheus-adapter-configMap.yaml prometheus-serviceMonitorApiserver.yaml
alertmanager-service.yaml kube-state-metrics-role.yaml prometheus-adapter-deployment.yaml prometheus-serviceMonitorCoreDNS.yaml
alertmanager-serviceAccount.yaml kube-state-metrics-roleBinding.yaml prometheus-adapter-roleBindingAuthReader.yaml prometheus-serviceMonitorKubeControllerManager.yaml
alertmanager-serviceMonitor.yaml kube-state-metrics-service.yaml prometheus-adapter-service.yaml prometheus-serviceMonitorKubeScheduler.yaml
coredns-metrics-service.yaml kube-state-metrics-serviceAccount.yaml prometheus-adapter-serviceAccount.yaml prometheus-serviceMonitorKubelet.yaml
grafana-dashboardDatasources.yaml kube-state-metrics-serviceMonitor.yaml prometheus-clusterRole.yaml
部署完成后，会创建一个名为monitoring的 namespace，所以资源对象对将部署在改命名空间下面，此外 Operator 会自动创建4个 CRD 资源对象：
root@k8s-master-1:~/k8s_manifests/prometheus-operator# kubectl get crd |grep coreos
alertmanagers.monitoring.coreos.com 17d
prometheuses.monitoring.coreos.com 17d
prometheusrules.monitoring.coreos.com 17d
servicemonitors.monitoring.coreos.com 17d
可以在 monitoring 命名空间下面查看所有的 Pod，其中 alertmanager 和 prometheus 是用 StatefulSet 控制器管理的，其中还有一个比较核心的 prometheus-operator 的 Pod，用来控制其他资源对象和监听对象变化的
root@k8s-master-1:~/k8s_manifests/prometheus-operator# kubectl get pods -n monitoring
NAME READY STATUS RESTARTS AGE
alertmanager-main-0 2/2 Running 4 17d
alertmanager-main-1 2/2 Running 6 17d
alertmanager-main-2 2/2 Running 4 17d
grafana-6d6c4d998d-v9djh 1/1 Running 0 8d
kube-state-metrics-5c5c6f7f8f-frwpk 4/4 Running 0 14d
loki-5c5d8d7d7d-gcvcx 1/1 Running 0 8d
loki-grafana-996d8c8fc-shm29 1/1 Running 0 8d
loki-promtail-cpqq9 1/1 Running 0 8d
loki-promtail-k786c 1/1 Running 0 8d
loki-promtail-lmmn2 1/1 Running 0 8d
loki-promtail-xlb8b 1/1 Running 0 8d
node-exporter-8gdh4 2/2 Running 2 14d
node-exporter-cdmbk 2/2 Running 0 14d
node-exporter-pqzbf 2/2 Running 0 14d
node-exporter-x4968 2/2 Running 0 14d
prometheus-adapter-69466cc54b-vgqpg 1/1 Running 2 17d
prometheus-k8s-0 3/3 Running 8 13d
prometheus-k8s-1 3/3 Running 3 11d
prometheus-operator-56954c76b5-rjlbq 1/1 Running 0 14d
root@k8s-master-1:~/k8s_manifests/prometheus-operator# kubectl get svc -n monitoring
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
alertmanager-main ClusterIP 10.68.209.89 <none> 9093/TCP 17d
alertmanager-operated ClusterIP None <none> 9093/TCP,6783/TCP 17d
grafana ClusterIP 10.68.149.168 <none> 3000/TCP 17d
kube-state-metrics ClusterIP None <none> 8443/TCP,9443/TCP 17d
loki ClusterIP 10.68.118.118 <none> 3100/TCP 8d
loki-grafana ClusterIP 10.68.77.53 <none> 80/TCP 8d
node-exporter ClusterIP None <none> 9100/TCP 17d
prometheus-adapter ClusterIP 10.68.217.16 <none> 443/TCP 17d
prometheus-k8s ClusterIP 10.68.193.174 <none> 9090/TCP 17d
prometheus-operated ClusterIP None <none> 9090/TCP 17d
prometheus-operator ClusterIP None <none> 8080/TCP 17d
部署Ingress 允许外部访问
root@k8s-master-1:~/k8s_manifests/prometheus-operator# cat grafana-ingress.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: grafana-ui
namespace: monitoring
spec:
rules:
- host: grafana.k8s.io
http:
paths:
- backend:
serviceName: grafana
servicePort: service
path: /
status:
loadBalancer: {}
监控二进制组件
由于当前集群的部署方式，Master的核心组件Kube-scheduler和kube-controller-manager是通过二进制文件启动，而不是以Pod的形式，这是一个非常重要的概念
就和 ServiceMonitor 的定义有关系了，我们先来查看下 kube-scheduler 组件对应的 ServiceMonitor 资源的定义：(prometheus-serviceMonitorKubeScheduler.yaml)
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
labels:
k8s-app: kube-scheduler
name: kube-scheduler
namespace: monitoring
spec:
endpoints:
- interval: 30s
port: http-metrics
jobLabel: k8s-app
namespaceSelector:
matchNames:
- kube-system
selector:
matchLabels:
k8s-app: kube-scheduler
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
labels:
k8s-app: kube-controller-manager
name: kube-controller-manager
namespace: monitoring
spec:
endpoints:
- interval: 30s
metricRelabelings:
- action: drop
regex: etcd_(debugging|disk|request|server).*
sourceLabels:
- __name__
port: http-metrics
jobLabel: k8s-app
namespaceSelector:
matchNames:
- kube-system
selector:
matchLabels:
k8s-app: kube-controller-manager
上面是一个典型的 ServiceMonitor 资源文件的声明方式，上面我们通过selector.matchLabels在 kube-system 这个命名空间下面匹配具有k8s-app=kube-scheduler这样的 Service，但是我们系统中根本就没有对应的 Service，所以我们需要手动创建一个 Service：
kube-controller-manager-service.yaml
kube-scheduler-service.yaml
apiVersion: v1
kind: Service
metadata:
labels:
k8s-app: kube-scheduler
name: kube-scheduler
namespace: kube-system
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10251
protocol: TCP
targetPort: 10251
apiVersion: v1
kind: Service
metadata:
namespace: kube-system
name: kube-controller-manager
labels:
k8s-app: kube-controller-manager
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10252
targetPort: 10252
protocol: TCP
kube-controller-manager.service 监听的地址改成0.0.0.0 ExecStart=/opt/kube/bin/kube-controller-manager
–address=0.0.0.0
–master=http://0.0.0.0:8080
kube-scheduler.service 监听的地址改成0.0.0.0 ExecStart=/opt/kube/bin/kube-scheduler
–address=0.0.0.0
–master=http://0.0.0.0:8080 \
Prometheus 的Targets监控
Grafana Dashboard
