标签：ring master ef6 删除 cli insecure 日志 dep 抽象
Operator是CoreOS公司开发，用于扩展kubernetes API或特定应用程序的控制器，它用来创建、配置、管理复杂的有状态应用，例如数据库，监控系统。其中Prometheus-Operator就是其中一个重要的项目。
其架构图如下：
其中核心部分是Operator，它会去创建Prometheus、ServiceMonitor、AlertManager、PrometheusRule这4个CRD对象，然后会一直监控并维护这4个对象的状态。
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。
注意集群版本的坑，自己先到Github上下载对应的版本。
我们使用源码来安装，首先克隆源码到本地：
# git clone https://github.com/coreos/kube-prometheus.git
我们进入kube-prometheus/manifests/setup，就可以直接创建CRD对象：
# cd kube-prometheus/manifests/setup
# kubectl apply -f .
然后在上层目录创建资源清单：
# cd kube-prometheus/manifests
# kubectl apply -f .
可以看到创建如下的CRD对象：
# kubectl get crd | grep coreos
alertmanagers.monitoring.coreos.com 2019-12-02T03:03:37Z
podmonitors.monitoring.coreos.com 2019-12-02T03:03:37Z
prometheuses.monitoring.coreos.com 2019-12-02T03:03:37Z
prometheusrules.monitoring.coreos.com 2019-12-02T03:03:37Z
servicemonitors.monitoring.coreos.com 2019-12-02T03:03:37Z
查看创建的pod：
# kubectl get pod -n monitoring
NAME READY STATUS RESTARTS AGE
alertmanager-main-0 2/2 Running 0 2m37s
alertmanager-main-1 2/2 Running 0 2m37s
alertmanager-main-2 2/2 Running 0 2m37s
grafana-77978cbbdc-886cc 1/1 Running 0 2m46s
kube-state-metrics-7f6d7b46b4-vrs8t 3/3 Running 0 2m45s
node-exporter-5552n 2/2 Running 0 2m45s
node-exporter-6snb7 2/2 Running 0 2m45s
prometheus-adapter-68698bc948-6s5f2 1/1 Running 0 2m45s
prometheus-k8s-0 3/3 Running 1 2m27s
prometheus-k8s-1 3/3 Running 1 2m27s
prometheus-operator-6685db5c6-4tdhp 1/1 Running 0 2m52s
查看创建的Service：
# kubectl get svc -n monitoring
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
alertmanager-main ClusterIP 10.68.97.247 <none> 9093/TCP 3m51s
alertmanager-operated ClusterIP None <none> 9093/TCP,9094/TCP,9094/UDP 3m41s
grafana ClusterIP 10.68.234.173 <none> 3000/TCP 3m50s
kube-state-metrics ClusterIP None <none> 8443/TCP,9443/TCP 3m50s
node-exporter ClusterIP None <none> 9100/TCP 3m50s
prometheus-adapter ClusterIP 10.68.109.201 <none> 443/TCP 3m50s
prometheus-k8s ClusterIP 10.68.9.232 <none> 9090/TCP 3m50s
prometheus-operated ClusterIP None <none> 9090/TCP 3m31s
prometheus-operator ClusterIP None <none> 8080/TCP 3m57s
我们看到我们常用的prometheus和grafana都是clustorIP，我们要外部访问可以配置为NodePort类型或者用ingress。比如配置为ingress：
prometheus-ingress.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: prometheus-ingress
namespace: monitoring
annotations:
kubernetes.io/ingress.class: "traefik"
spec:
rules:
- host: prometheus.joker.com
http:
paths:
- path:
backend:
serviceName: prometheus-k8s
servicePort: 9090
grafana-ingress.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: grafana-ingress
namespace: monitoring
annotations:
kubernetes.io/ingress.class: "traefik"
spec:
rules:
- host: grafana.joker.com
http:
paths:
- path:
backend:
serviceName: grafana
servicePort: 3000
但是我们这里由于没有域名进行备案，我们就用NodePort类型。修改后如下：
# kubectl get svc -n monitoring
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
grafana NodePort 10.68.234.173 <none> 3000:39807/TCP 3h1m 3h1m
prometheus-k8s NodePort 10.68.9.232 <none> 9090:20547/TCP 3h1m
然后就可以正常在浏览器访问了。
我们可以看到大部分的配置都是正常的，只有两三个没有管理到对应的监控目标，比如 kube-controller-manager 和 kube-scheduler 这两个系统组件，这就和 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 # 每30s获取一次信息
port: http-metrics # 对应service的端口名
jobLabel: k8s-app
namespaceSelector: # 表示去匹配某一命名空间中的service，如果想从所有的namespace中匹配用any: true
matchNames:
- kube-system
selector: # 匹配的 Service 的labels，如果使用mathLabels，则下面的所有标签都匹配时才会匹配该service，如果使用matchExpressions，则至少匹配一个标签的service都会被选择
matchLabels:
k8s-app: kube-scheduler
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：（prometheus-kubeSchedulerService.yaml）
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: 10251
targetPort: 10251
protocol: TCP
10251是
kube-scheduler组件 metrics 数据所在的端口，10252是kube-controller-manager组件的监控数据所在端口。
其中最重要的是上面 labels 和 selector 部分，labels 区域的配置必须和我们上面的 ServiceMonitor 对象中的 selector 保持一致，selector下面配置的是component=kube-scheduler，为什么会是这个 label 标签呢，我们可以去 describe 下 kube-scheduelr 这个 Pod：
$ kubectl describe pod kube-scheduler-master -n kube-system
Name: kube-scheduler-master
Namespace: kube-system
Node: master/10.151.30.57
Start Time: Sun, 05 Aug 2018 18:13:32 +0800
Labels: component=kube-scheduler
tier=control-plane
......
我们可以看到这个 Pod 具有component=kube-scheduler和tier=control-plane这两个标签，而前面这个标签具有更唯一的特性，所以使用前面这个标签较好，这样上面创建的 Service 就可以和我们的 Pod 进行关联了，直接创建即可：
$ kubectl create -f prometheus-kubeSchedulerService.yaml
$ kubectl get svc -n kube-system -l k8s-app=kube-scheduler
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kube-scheduler ClusterIP 10.102.119.231 <none> 10251/TCP 18m
创建完成后，隔一小会儿后去 prometheus 查看 targets 下面 kube-scheduler 的状态：
promethus kube-scheduler error
我们可以看到现在已经发现了 target，但是抓取数据结果出错了，这个错误是因为我们集群是使用 kubeadm 搭建的，其中 kube-scheduler 默认是绑定在127.0.0.1上面的，而上面我们这个地方是想通过节点的 IP 去访问，所以访问被拒绝了，我们只要把 kube-scheduler 绑定的地址更改成0.0.0.0即可满足要求，由于 kube-scheduler 是以静态 Pod 的形式运行在集群中的，所以我们只需要更改静态 Pod 目录下面对应的 YAML 文件即可：
$ ls /etc/kubernetes/manifests/
etcd.yaml kube-apiserver.yaml kube-controller-manager.yaml kube-scheduler.yaml
将 kube-scheduler.yaml 文件中-command的--address地址更改成0.0.0.0：
containers:
- command:
- kube-scheduler
- --leader-elect=true
- --kubeconfig=/etc/kubernetes/scheduler.conf
- --address=0.0.0.0
修改完成后我们将该文件从当前文件夹中移除，隔一会儿再移回该目录，就可以自动更新了，然后再去看 prometheus 中 kube-scheduler 这个 target 是否已经正常了：
promethues-operator-kube-scheduler
大家可以按照上面的方法尝试去修复下 kube-controller-manager 组件的监控。
很多时候我们并不是把所有资源都部署在集群内的，经常有比如ectd，kube-scheduler等都部署在集群外。其监控流程和上面大致一样，唯一的区别就是在定义Service的时候，其EndPoints是需要我们自己去定义的。
（1）、定义Service和EndPoints
prometheus-KubeSchedulerService.yaml
apiVersion: v1
kind: Service
metadata:
name: kube-scheduler
namespace: kube-system
labels:
k8s-app: kube-scheduler
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10251
targetPort: 10251
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: kube-scheduler
namespace: kube-system
labels:
k8s-app: kube-scheduler
subsets:
- addresses:
- ip: 172.16.0.33
ports:
- name: http-metrics
port: 10251
protocol: TCP
（2）、定义ServiceMonitor
prometheus-serviceMonitorKubeScheduler.yaml
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: kube-scheduler
namespace: monitoring
labels:
k8s-app: kube-scheduler
spec:
endpoints:
- interval: 30s
port: http-metrics
jobLabel: k8s-app
namespaceSelector:
matchNames:
- kube-system
selector:
matchLabels:
k8s-app: kube-scheduler
然后我们就可以看到其监控上了：
（1）、配置Service和EndPoints，
prometheus-KubeControllerManagerService.yaml
apiVersion: v1
kind: Service
metadata:
name: kube-controller-manager
namespace: kube-system
labels:
k8s-app: kube-controller-manager
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10252
targetPort: 10252
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: kube-controller-manager
namespace: kube-system
labels:
k8s-app: kube-controller-manager
subsets:
- addresses:
- ip: 172.16.0.33
ports:
- name: http-metrics
port: 10252
protocol: TCP
（2）、配置ServiceMonitor
prometheus-serviceMonitorKubeControllerManager.yaml
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
很多情况下，我们的etcd都需要进行SSL认证的，所以首先需要将用到的证书保存到集群中去。
（根据自己集群证书的位置修改）
kubectl -n monitoring create secret generic etcd-certs --from-file=/etc/kubernetes/pki/etcd/healthcheck-client.crt --from-file=/etc/kubernetes/pki/etcd/healthcheck-client.key --from-file=/etc/kubernetes/pki/etcd/ca.crt
然后将上面创建的 etcd-certs 对象配置到 prometheus 资源对象中，直接更新 prometheus 资源对象即可：
# kubectl edit prometheus k8s -n monitoring
添加如下的 secrets 属性：
nodeSelector:
beta.kubernetes.io/os: linux
replicas: 2
secrets:
- etcd-certs
更新完成后，我们就可以在 Prometheus 的 Pod 中获取到上面创建的 etcd 证书文件了，具体的路径我们可以进入 Pod 中查看：
# kubectl exec -it prometheus-k8s-0 -n monitoring -- /bin/sh
Defaulting container name to prometheus.
Use ‘kubectl describe pod/prometheus-k8s-0 -n monitoring‘ to see all of the containers in this pod.
/prometheus $ ls /etc/prometheus/secrets/etcd-certs/
ca.crt healthcheck-client.crt healthcheck-client.key
/prometheus $
（1）、创建ServiceMonitor
prometheus-serviceMonitorEtcd.yamlns
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: k8s-etcd
namespace: monitoring
labels:
k8s-app: k8s-etcd
spec:
jobLabel: k8s-app
endpoints:
- port: port
interval: 30s
scheme: https
tlsConfig:
caFile: /etc/prometheus/secrets/etcd-certs/ca.crt
certFile: /etc/prometheus/secrets/etcd-certs/healthcheck-client.crt
keyFile: /etc/prometheus/secrets/etcd-certs/healthcheck-client.key
insecureSkipVerify: true
selector:
matchLabels:
k8s-app: k8s-etcd
namespaceSelector:
matchNames:
- kube-system
上面我们在 monitoring 命名空间下面创建了名为 k8s-etcd 的 ServiceMonitor 对象，基本属性和前面章节中的一致，匹配 kube-system 这个命名空间下面的具有 k8s-app=k8s-etcd 这个 label 标签的 Service，jobLabel 表示用于检索 job 任务名称的标签，和前面不太一样的地方是 endpoints 属性的写法，配置上访问 etcd 的相关证书，endpoints 属性下面可以配置很多抓取的参数，比如 relabel、proxyUrl，tlsConfig 表示用于配置抓取监控数据端点的 tls 认证，由于证书 serverName 和 etcd 中签发的可能不匹配，所以加上了 insecureSkipVerify=true.
然后创建这个配置清单：
# kubectl apply -f prometheus-serviceMonitorEtcd.yaml
（2）、创建Service
apiVersion: v1
kind: Service
metadata:
name: k8s-etcd
namespace: kube-system
labels:
k8s-app: k8s-etcd
spec:
type: ClusterIP
clusterIP: None
ports:
- name: port
port: 2379
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: k8s-etcd
namespace: kube-system
labels:
k8s-app: k8s-etcd
subsets:
- addresses:
- ip: 172.16.0.33
ports:
- name: port
port: 2379
protocol: TCP
然后在Grafana中导入3070的面板。
我们创建一个 PrometheusRule 资源对象后，会自动在上面的 prometheus-k8s-rulefiles-0 目录下面生成一个对应的
如下配置Ectd报警规则：
prometheus-etcdRule.yaml
apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
name: etcd-rules
namespace: monitoring
labels:
prometheus: k8s
role: alert-rules
spec:
groups:
- name: etcd
rules:
- alert: EtcdClusterUnavailable
annotations:
summary: etcd cluster small
description: If one more etcd peer goes down the cluster will be unavailable
expr: |
count(up{job="etcd"} == 0) > (count(up{job="etcd"}) / 2 - 1)
for: 3m
labels:
severity: critical
然后我们创建这个配置清单：
# kubectl apply -f prometheus-etcdRule.yaml
prometheusrule.monitoring.coreos.com/etcd-rules created
然后我们刷新页面，就可以看到已经生效了
首先我们将 alertmanager-main 这个 Service 改为 NodePort 类型的 Service，修改完成后我们可以在页面上的 status 路径下面查看 AlertManager 的配置信息:
# kubectl get svc -n monitoring
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
alertmanager-main NodePort 10.68.97.247 <none> 9093:21936/TCP 5h31m
然后在浏览器查看：
这些配置信息实际上是来自于我们之前在kube-prometheus/manifests目录下面创建的 alertmanager-secret.yaml 文件：
apiVersion: v1
data:
alertmanager.yaml: Imdsb2JhbCI6CiAgInJlc29sdmVfdGltZW91dCI6ICI1bSIKInJlY2VpdmVycyI6Ci0gIm5hbWUiOiAibnVsbCIKInJvdXRlIjoKICAiZ3JvdXBfYnkiOgogIC0gImpvYiIKICAiZ3JvdXBfaW50ZXJ2YWwiOiAiNW0iCiAgImdyb3VwX3dhaXQiOiAiMzBzIgogICJyZWNlaXZlciI6ICJudWxsIgogICJyZXBlYXRfaW50ZXJ2YWwiOiAiMTJoIgogICJyb3V0ZXMiOgogIC0gIm1hdGNoIjoKICAgICAgImFsZXJ0bmFtZSI6ICJXYXRjaGRvZyIKICAgICJyZWNlaXZlciI6ICJudWxsIg==
kind: Secret
metadata:
name: alertmanager-main
namespace: monitoring
type: Opaque
可以将 alertmanager.yaml 对应的 value 值做一个 base64 解码：
# echo "Imdsb2JhbCI6CiAgInJlc29sdmVfdGltZW91dCI6ICI1bSIKInJlY2VpdmVycyI6Ci0gIm5hbWUiOiAibnVsbCIKInJvdXRlIjoKICAiZ3JvdXBfYnkiOgogIC0gImpvYiIKICAiZ3JvdXBfaW50ZXJ2YWwiOiAiNW0iCiAgImdyb3VwX3dhaXQiOiAiMzBzIgogICJyZWNlaXZlciI6ICJudWxsIgogICJyZXBlYXRfaW50ZXJ2YWwiOiAiMTJoIgogICJyb3V0ZXMiOgogIC0gIm1hdGNoIjoKICAgICAgImFsZXJ0bmFtZSI6ICJXYXRjaGRvZyIKICAgICJyZWNlaXZlciI6ICJudWxsIg==" | base64 -d
"global":
"resolve_timeout": "5m"
"receivers":
- "name": "null"
"route":
"group_by":
- "job"
"group_interval": "5m"
"group_wait": "30s"
"receiver": "null"
"repeat_interval": "12h"
"routes":
- "match":
"alertname": "Watchdog"
"receiver": "null"
可以看到上面的内容和我们在网页上查到的是一致的。
如果要配置报警媒介，就可以修改这个模板：
alertmanager.yaml
global:
resolve_timeout: 5m
smtp_smarthost: ‘smtp.163.com:465‘
smtp_from: ‘fmbankops@163.com‘
smtp_auth_username: ‘fmbankops@163.com‘
smtp_auth_password: ‘<邮箱密码>‘
smtp_hello: ‘163.com‘
smtp_require_tls: false
route:
group_by: [‘job‘, ‘severity‘]
group_wait: 30s
group_interval: 5m
repeat_interval: 12h
receiver: default
routes:
- receiver: webhook
match:
alertname: CoreDNSDown
receivers:
- name: ‘default‘
email_configs:
- to: ‘517554016@qq.com‘
send_resolved: true
- name: ‘webhook‘
webhook_configs:
- url: ‘http://dingtalk-hook.kube-ops:5000‘ # 这是我们自定义的webhook
send_resolved: true
然后我们更新secret对象：
# 先将之前的 secret 对象删除
$ kubectl delete secret alertmanager-main -n monitoring
secret "alertmanager-main" deleted
$ kubectl create secret generic alertmanager-main --from-file=alertmanager.yaml -n monitoring
secret "alertmanager-main" created
然后就会收到报警信息：
我们在实际应用中会部署非常多的service和pod，如果要一个一个手动的添加监控将会是一个非常重复，浪费时间的工作，这时候就需要使用自动发现机制。我们在手动搭建Prometheus的过程中曾配置过自动发现service，其主要的配置文件如下：
- 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
要想自动被发现，只需要在service的配置清单中加上annotations:??prometheus.io/scrape=true。
我们将上面的文件保存为prometheus-additional.yaml，然后用这个文件创建一个secret。
# kubectl -n monitoring create secret generic additional-config --from-file=prometheus-additional.yaml
secret/additional-config created
然后我们在prometheus的配置清单中添加这个配置：
cat prometheus-prometheus.yaml
apiVersion: monitoring.coreos.com/v1
kind: Prometheus
metadata:
labels:
prometheus: k8s
name: k8s
namespace: monitoring
spec:
alerting:
alertmanagers:
- name: alertmanager-main
namespace: monitoring
port: web
baseImage: quay.io/prometheus/prometheus
nodeSelector:
kubernetes.io/os: linux
podMonitorSelector: {}
replicas: 2
resources:
requests:
memory: 400Mi
ruleSelector:
matchLabels:
prometheus: k8s
role: alert-rules
securityContext:
fsGroup: 2000
runAsNonRoot: true
runAsUser: 1000
additionalScrapeConfigs:
name: additional-config
key: prometheus-additional.yaml
serviceAccountName: prometheus-k8s
serviceMonitorNamespaceSelector: {}
serviceMonitorSelector: {}
version: v2.11.0
然后更新一下prometheus的配置：
# kubectl apply -f prometheus-prometheus.yaml
prometheus.monitoring.coreos.com/k8s configured
然后我们查看prometheus的日志，发现很多错误：
# kubectl logs -f prometheus-k8s-0 prometheus -n monitoring
从日志可以看出，其提示的是权限问题，在kubernetes中涉及到权限问题一般就是RBAC中配置问题，我们查看prometheus的配置清单发现其使用了一个prometheus-k8s的ServiceAccount:
而其绑定的是一个叫prometheus-k8s的ClusterRole:
# kubectl get clusterrole prometheus-k8s -n monitoring -o yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
annotations:
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"rbac.authorization.k8s.io/v1","kind":"ClusterRole","metadata":{"annotations":{},"name":"prometheus-k8s"},"rules":[{"apiGroups":[""],"resources":["nodes/metrics"],"verbs":["get"]},{"nonResourceURLs":["/metrics"],"verbs":["get"]}]}
creationTimestamp: "2019-12-02T03:03:44Z"
name: prometheus-k8s
resourceVersion: "1128592"
selfLink: /apis/rbac.authorization.k8s.io/v1/clusterroles/prometheus-k8s
uid: 4f87ca47-7769-432b-b96a-1b826b28003d
rules:
- apiGroups:
- ""
resources:
- nodes/metrics
verbs:
- get
- nonResourceURLs:
- /metrics
verbs:
- get
从上面可以知道，这个clusterrole并没有service和pod的一些相关权限。接下来我们修改这个clusterrole。
prometheus-clusterRole.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: prometheus-k8s
rules:
- apiGroups:
- ""
resources:
- nodes/metrics
- configmaps
verbs:
- get
- apiGroups:
- ""
resources:
- nodes
- pods
- services
- endpoints
- nodes/proxy
verbs:
- get
- list
- watch
- nonResourceURLs:
- /metrics
verbs:
- get
然后我们更新这个资源清单：
# kubectl apply -f prometheus-clusterRole.yaml
clusterrole.rbac.authorization.k8s.io/prometheus-k8s configured
然后等待一段时间我们可以发现自动发现成功。
提示：配置自动发现，首先annotations里需要配置prometheus.io/scrape=true，其次你的应用要有exporter去收集信息，比如我们如下的redis配置：
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: redis
namespace: kube-ops
spec:
template:
metadata:
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "9121"
labels:
app: redis
spec:
containers:
- name: redis
image: redis:4
resources:
requests:
cpu: 100m
memory: 100Mi
ports:
- containerPort: 6379
- name: redis-exporter
image: oliver006/redis_exporter:latest
resources:
requests:
cpu: 100m
memory: 100Mi
ports:
- containerPort: 9121
---
kind: Service
apiVersion: v1
metadata:
name: redis
namespace: kube-ops
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "9121"
spec:
selector:
app: redis
ports:
- name: redis
port: 6379
targetPort: 6379
- name: prom
port: 9121
targetPort: 9121
如果我们直接git clone下来的，不做任何修改，Prometheus虽然使用的是statefuleSet，但是其用的存储卷是emptyDir，在删除Pod或者重建Pod，原始数据是会丢失的。所以在真实环境我们需要对其进行持久化，首先创建storageClass，如果是用NFS做持久化，详见第四章持久化存储中的storageClass部分。我们这里依然用的NFS做持久化。
创建StorageClass：
prometheus-storage.yaml
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: prometheus-storage
provisioner: rookieops/nfs
其中provisioner需要指定我们在创建nfs-client-provisioner中指定的名字，不能随意修改。
配置prometheus的配置清单：
prometheus-prometheus.yaml
apiVersion: monitoring.coreos.com/v1
kind: Prometheus
metadata:
labels:
prometheus: k8s
name: k8s
namespace: monitoring
spec:
alerting:
alertmanagers:
- name: alertmanager-main
namespace: monitoring
port: web
storage:
volumeClaimTemplate:
spec:
storageClassName: prometheus-storage
resources:
requests:
storage: 20Gi
baseImage: quay.io/prometheus/prometheus
nodeSelector:
kubernetes.io/os: linux
podMonitorSelector: {}
replicas: 2
resources:
requests:
memory: 400Mi
ruleSelector:
matchLabels:
prometheus: k8s
role: alert-rules
securityContext:
fsGroup: 2000
runAsNonRoot: true
runAsUser: 1000
additionalScrapeConfigs:
name: additional-config
key: prometheus-additional.yaml
serviceAccountName: prometheus-k8s
serviceMonitorNamespaceSelector: {}
serviceMonitorSelector: {}
version: v2.11.0
然后就可以正常使用持久化了，建议在部署之初就做更改。
标签：ring master ef6 删除 cli insecure 日志 dep 抽象
原文地址：https://www.cnblogs.com/coolops/p/13168684.html
