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-cadvisor
kubernetes_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
- job_name: kube-scheduler
kubernetes_sd_configs:
- role: endpoints
kubeconfig_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-system
name: kube-scheduler
labels:
k8s-app: kube-scheduler
spec:
selector:
component: kube-scheduler
ports:
- name: http-metrics
port: 10259
targetPort: 10259
protocol: 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 ~]
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
- job_name: kube-controller-manager
kubernetes_sd_configs:
- role: endpoints
kubeconfig_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-system
name: kube-controller-manager
labels:
k8s-app: kube-controller-manager
spec:
selector:
component: kube-controller-manager
ports:
- name: http-metrics
port: 10257
targetPort: 10257
protocol: 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 ~]
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
- job_name: kube-etcd
kubernetes_sd_configs:
- role: endpoints
kubeconfig_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-system
name: kube-etcd
labels:
k8s-app: kube-etcd
spec:
selector:
component: etcd
tier: control-plane
ports:
- name: http-metrics
port: 2379
targetPort: 2379
protocol: 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 ~]
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
- job_name: kubernetes-pods
kubernetes_sd_configs:
- role: pod
kubeconfig_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 ~]
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
