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