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本节重点介绍 :

• 服务发现的应用
• 3种采集的k8s服务发现role
  • 容器基础资源指标 role :node
  • k8s服务组件指标 role :endpoint
  • 部署在pod中业务埋点指标 role :pod

服务发现的应用

• 所有组件将自身指标暴露在各自的服务端口上，prometheus通过pull过来拉取指标
• 但是prometheus需要知道各个目标的地址是多少，而且需要及时感知他们的变化
• 所以采用服务发现是最好的解决方式

容器基础资源指标

• 我们可以看到prometheus采用k8s服务发现，其中role :node 代表发现所有的node。

- job_name: kubernetes-nodes-cadvisorkubernetes_sd_configs:- role: node

• 其中的原理是通过监听k8s node，一旦node加入(扩容)，node离开(缩容)，prometheus可以及时收到node的信息
• 通过访问节点的cadvisor指标path如node_ip:10250/metrics/cadvisor获取到相关指标
• 通过prometheus的target展示页面(/targets)可以看到cadvisor node发现的结果，
• target结果
• 
• discovery 结果
• 

k8s服务组件指标

kube-scheduler

• 采集配置如下

- job_name: kube-schedulerkubernetes_sd_configs:- role: endpointskubeconfig_file: ""follow_redirects: true

• 采用k8s服务发现，其中role :endpoints 代表发现所有的endpoints
• endpoint 可以理解为service向其发送流量的对象的IP地址
• 在之前我们创建的控制平面暴露的service中，kube-scheduler的配置如下

---
apiVersion: v1
kind: Service
metadata:namespace: kube-systemname: kube-schedulerlabels:k8s-app: kube-scheduler
spec:selector:component: kube-schedulerports:- name: http-metricsport: 10259targetPort: 10259protocol: TCP

• 那么对应的endpoint可以describe到，就是下面所示的172.20.70.205:10259

[root@k8s-master01 ~]# kubectl describe svc kube-scheduler -n kube-system  
Name:              kube-scheduler
Namespace:         kube-system
Labels:            k8s-app=kube-scheduler
Annotations:       <none>
Selector:          component=kube-scheduler
Type:              ClusterIP
IP Families:       <none>
IP:                10.96.208.114
IPs:               10.96.208.114
Port:              http-metrics  10259/TCP
TargetPort:        10259/TCP
Endpoints:         172.20.70.205:10259
Session Affinity:  None
Events:            <none>

• 这个和prometheus kube-scheduler target页面是一致的
• 

kube-controller-manager

• 采集配置如下

- job_name: kube-controller-managerkubernetes_sd_configs:- role: endpointskubeconfig_file: ""follow_redirects: true

• 采用k8s服务发现，其中role :endpoints 代表发现所有的endpoints
• 在之前我们创建的控制平面暴露的service中，kube-controller-manager的配置如下

---
apiVersion: v1
kind: Service
metadata:namespace: kube-systemname: kube-controller-managerlabels:k8s-app: kube-controller-manager
spec:selector:component: kube-controller-managerports:- name: http-metricsport: 10257targetPort: 10257protocol: TCP

• 那么对应的endpoint可以describe到，就是下面所示的172.20.70.205:10257

[root@k8s-master01 ~]# kubectl describe svc kube-controller-manager -n kube-system                              
Name:              kube-controller-manager
Namespace:         kube-system
Labels:            k8s-app=kube-controller-manager
Annotations:       <none>
Selector:          component=kube-controller-manager
Type:              ClusterIP
IP Families:       <none>
IP:                10.96.35.204
IPs:               10.96.35.204
Port:              http-metrics  10257/TCP
TargetPort:        10257/TCP
Endpoints:         172.20.70.205:10257
Session Affinity:  None
Events:            <none>

• 这个和prometheus kube-controller-manager target页面是一致的

kube-etcd

• 采集配置如下

- job_name: kube-etcdkubernetes_sd_configs:- role: endpointskubeconfig_file: ""follow_redirects: true

• 采用k8s服务发现，其中role :endpoints 代表发现所有的endpoints
• 在之前我们创建的控制平面暴露的service中，kube-etcd的配置如下

---
apiVersion: v1
kind: Service
metadata:namespace: kube-systemname: kube-etcdlabels:k8s-app: kube-etcd
spec:selector:component: etcdtier: control-planeports:- name: http-metricsport: 2379targetPort: 2379protocol: TCP

• 那么对应的endpoint可以describe到，就是下面所示的172.20.70.205:2379

[root@prome-master01 ~]# kubectl describe  svc kube-etcd -n kube-system
Name:              kube-etcd
Namespace:         kube-system
Labels:            k8s-app=kube-etcd
Annotations:       <none>
Selector:          component=etcd,tier=control-plane
Type:              ClusterIP
IP Family Policy:  SingleStack
IP Families:       IPv4
IP:                10.96.136.217
IPs:               10.96.136.217
Port:              http-metrics  2379/TCP
TargetPort:        2379/TCP
Endpoints:         192.168.3.200:2379
Session Affinity:  None
Events:            <none>

• 这个和prometheus kube-etcd target页面是一致的
• 

部署在pod中业务埋点指标

• 采集配置如下

- job_name: kubernetes-podskubernetes_sd_configs:- role: podkubeconfig_file: ""follow_redirects: true

• 采用k8s服务发现，其中role :pods 代表发现所有的pods，相当于执行kubectl get pod -A

[root@k8s-master01 ~]# kubectl get pod -A
NAMESPACE         NAME                                           READY   STATUS    RESTARTS   AGE
calico-system     calico-kube-controllers-854b9dcf89-gct84       1/1     Running   5          139d
calico-system     calico-node-58m74                              1/1     Running   7          139d
calico-system     calico-node-8pwz5                              1/1     Running   1          42d
calico-system     calico-typha-56958ddd97-9zpd2                  1/1     Running   2          42d
calico-system     calico-typha-56958ddd97-gnt8k                  1/1     Running   8          139d
default           grafana-d5d85bcd6-f74ch                        1/1     Running   0          4d5h
default           grafana-d5d85bcd6-l44mx                        1/1     Running   0          4d5h
default           ink8s-pod-metrics-deployment-85d9795d6-95lsp   1/1     Running   0          20h
ingress-nginx     ingress-nginx-controller-6cb6fdd64b-p4s65      1/1     Running   0          4d5h
kube-admin        k8s-mon-daemonset-z6sfw                        1/1     Running   1          42d
kube-admin        k8s-mon-deployment-6d7d58bdc8-rxj42            1/1     Running   0          4d5h
kube-system       coredns-68b9d7b887-ckwgh                       1/1     Running   2          139d
kube-system       coredns-68b9d7b887-vfmft                       1/1     Running   2          139d
kube-system       etcd-k8s-master01                              1/1     Running   7          125d
kube-system       kube-apiserver-k8s-master01                    1/1     Running   2          74d
kube-system       kube-controller-manager-k8s-master01           1/1     Running   66         136d
kube-system       kube-proxy-kc258                               1/1     Running   1          42d
kube-system       kube-proxy-zx87g                               1/1     Running   2          139d
kube-system       kube-scheduler-k8s-master01                    1/1     Running   64         83d
kube-system       kube-state-metrics-564668c858-dnmnh            1/1     Running   0          4d3h
kube-system       metrics-server-7dbf6c4558-zwp5m                1/1     Running   0          4d5h
kube-system       prometheus-0                                   2/2     Running   0          4d3h
tigera-operator   tigera-operator-cf6b69777-mlgk9                1/1     Running   85         139d

• 然后访问的时候pod的ip，因为在k8s中是pod之间网络是扁平的，所以prometheus的pod可以访问到其他的pod
• target结果
• 
• discovery结果
• 

本节重点总结 :

• 服务发现的应用
• 3种采集的k8s服务发现role
  • 容器基础资源指标 role :node
  • k8s服务组件指标 role :endpoint
  • 部署在pod中业务埋点指标 role :pod