参考:
https://blog.csdn.net/qq_41475058/article/details/88976393
https://blog.51cto.com/ylw6006/2084403

https://www.kubernetes.org.cn/3418.html
https://blog.qikqiak.com/post/kubernetes-monitor-prometheus-grafana/
https://github.com/giantswarm/kubernetes-prometheus/tree/master/manifests
https://segmentfault.com/a/1190000013245394

监控p8s(较全):
https://www.kancloud.cn/huyipow/prometheus/527093

Promethus的持久化:
https://blog.csdn.net/wenwst/article/details/76624019?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromBaidu-19&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromBaidu-19


什么是Prometheus?
Prometheus是由SoundCloud开发的开源监控报警系统和时序列数据库(TSDB)。Prometheus使用Go语言开发,是Google BorgMon监控系统的开源版本。
2016年由Google发起Linux基金会旗下的原生云基金会(Cloud Native Computing Foundation), 将Prometheus纳入其下第二大开源项目。
Prometheus目前在开源社区相当活跃。
Prometheus和Heapster(Heapster是K8S的一个子项目,用于获取集群的性能数据。)相比功能更完善、更全面。Prometheus性能也足够支撑上万台规模的集群。
Prometheus的特点
多维度数据模型。
灵活的查询语言。
不依赖分布式存储,单个服务器节点是自主的。
通过基于HTTP的pull方式采集时序数据。
可以通过中间网关进行时序列数据推送。
通过服务发现或者静态配置来发现目标服务对象。
支持多种多样的图表和界面展示,比如Grafana等。
官网地址:https://prometheus.io/
架构图

 

 

 

基本原理
Prometheus的基本原理是通过HTTP协议周期性抓取被监控组件的状态,任意组件只要提供对应的HTTP接口就可以接入监控。不需要任何SDK或者其他的集成过程。这样做非常适合做虚拟化环境监控系统,比如VM、Docker、Kubernetes等。输出被监控组件信息的HTTP接口被叫做exporter 。目前互联网公司常用的组件大部分都有exporter可以直接使用,比如Varnish、Haproxy、Nginx、MySQL、Linux系统信息(包括磁盘、内存、CPU、网络等等)。
服务过程
Prometheus Daemon负责定时去目标上抓取metrics(指标)数据,每个抓取目标需要暴露一个http服务的接口给它定时抓取。Prometheus支持通过配置文件、文本文件、Zookeeper、Consul、DNS SRV Lookup等方式指定抓取目标。Prometheus采用PULL的方式进行监控,即服务器可以直接通过目标PULL数据或者间接地通过中间网关来Push数据。
Prometheus在本地存储抓取的所有数据,并通过一定规则进行清理和整理数据,并把得到的结果存储到新的时间序列中。
Prometheus通过PromQL和其他API可视化地展示收集的数据。Prometheus支持很多方式的图表可视化,例如Grafana、自带的Promdash以及自身提供的模版引擎等等。Prometheus还提供HTTP API的查询方式,自定义所需要的输出。
PushGateway支持Client主动推送metrics到PushGateway,而Prometheus只是定时去Gateway上抓取数据。
Alertmanager是独立于Prometheus的一个组件,可以支持Prometheus的查询语句,提供十分灵活的报警方式。
三大套件
Server 主要负责数据采集和存储,提供PromQL查询语言的支持。
Alertmanager 警告管理器,用来进行报警。
Push Gateway 支持临时性Job主动推送指标的中间网关。
各个组件的功能
1、node-exporter组件负责收集节点上的metrics监控数据,并将数据推送给prometheus
2、prometheus负责存储这些数据
3、grafana将这些数据通过网页以图形的形式展现给用户

Prometheus的特点:
1、多维数据模型(时序列数据由metric名和一组key/value组成)
2、在多维度上灵活的查询语言(PromQl)
3、不依赖分布式存储,单主节点工作.
4、通过基于HTTP的pull方式采集时序数据
5、可以通过中间网关进行时序列数据推送(pushing)
6、目标服务器可以通过发现服务或者静态配置实现
7、多种可视化和仪表盘支持

prometheus 相关组件,Prometheus生态系统由多个组件组成,其中许多是可选的:
1、Prometheus 主服务,用来抓取和存储时序数据
2、client library 用来构造应用或 exporter 代码 (go,java,python,ruby)
3、push 网关可用来支持短连接任务
4、可视化的dashboard (两种选择,promdash 和 grafana.目前主流选择是 grafana.)
4、一些特殊需求的数据出口(用于HAProxy, StatsD, Graphite等服务)
5、实验性的报警管理端(alartmanager,单独进行报警汇总,分发,屏蔽等 )

现在我们正式开始部署工作。
一、环境介绍
操作系统环境:centos linux 7.3 64bit
K8S软件版本: 1.10.4(采用二进制方式部署)
Master节点IP: 192.168.3.25/24
Node节点IP: 192.168.3.26/24

二、Node Exporter部署
1、在k8s集群的所有节点上下载所需要的image

docker pull prom/node-exporter
docker pull prom/prometheus:v2.0.0
docker pull grafana/grafana:4.2.0

2、采用daemonset方式部署node-exporter组件
node-exporter的pod和service都是9100端口,然后映射到宿主机的31672端口

[root@k8s-master-101 prometheus]# cat node-exporter.yaml
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
name: node-exporter
namespace: kube-system
labels:
k8s-app: node-exporter
spec:
template:
metadata:
labels:
k8s-app: node-exporter
spec:
containers:
- image: prom/node-exporter
name: node-exporter
ports:
- containerPort: 9100
protocol: TCP
name: http
---
apiVersion: v1
kind: Service
metadata:
labels:
k8s-app: node-exporter
name: node-exporter
namespace: kube-system
spec:
ports:
- name: http
port: 9100
nodePort: 31672
protocol: TCP
type: NodePort
selector:
k8s-app: node-exporter

3、创建pod和service
kubectl create -f node-exporter.yaml
[root@master prometheus]# kubectl get pod -n kube-system
NAME READY STATUS RESTARTS AGE
node-exporter-dkk7n 1/1 Running 0 1m
node-exporter-p29d9 1/1 Running 0 1m
4、访问测试
Node-exporter对应的nodeport端口为31672,通过访问http://192.168.3.25:31672/metrics 可以看到对应的metrics

 

 

 

三、部署prometheus组件

1、rbac文件
[root@k8s-master-101 prometheus]# cat rbac-setup.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: prometheus
rules:
- apiGroups: [""]
resources:
- nodes
- nodes/proxy
- services
- endpoints
- pods
verbs: ["get", "list", "watch"]
- apiGroups:
- extensions
resources:
- ingresses
verbs: ["get", "list", "watch"]
- nonResourceURLs: ["/metrics"]
verbs: ["get"]
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: prometheus
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: prometheus
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: prometheus
subjects:
- kind: ServiceAccount
name: prometheus
namespace: kube-system

2、以configmap的形式管理prometheus组件的配置文件
[root@k8s-master-101 prometheus]# cat configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-config
namespace: kube-system
data:
prometheus.yml: |
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:

- job_name: 'kubernetes-apiservers'
kubernetes_sd_configs:
- role: endpoints
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
action: keep
regex: default;kubernetes;https

- job_name: 'kubernetes-nodes'
kubernetes_sd_configs:
- role: node
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics

- job_name: 'kubernetes-cadvisor'
kubernetes_sd_configs:
- role: node
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor

- 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

- job_name: 'kubernetes-services'
kubernetes_sd_configs:
- role: service
metrics_path: /probe
params:
module: [http_2xx]
relabel_configs:
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_probe]
action: keep
regex: true
- source_labels: [__address__]
target_label: __param_target
- target_label: __address__
replacement: blackbox-exporter.example.com:9115
- source_labels: [__param_target]
target_label: instance
- action: labelmap
regex: __meta_kubernetes_service_label_(.+)
- source_labels: [__meta_kubernetes_namespace]
target_label: kubernetes_namespace
- source_labels: [__meta_kubernetes_service_name]
target_label: kubernetes_name

- job_name: 'kubernetes-ingresses'
kubernetes_sd_configs:
- role: ingress
relabel_configs:
- source_labels: [__meta_kubernetes_ingress_annotation_prometheus_io_probe]
action: keep
regex: true
- source_labels: [__meta_kubernetes_ingress_scheme,__address__,__meta_kubernetes_ingress_path]
regex: (.+);(.+);(.+)
replacement: ${1}://${2}${3}
target_label: __param_target
- target_label: __address__
replacement: blackbox-exporter.example.com:9115
- source_labels: [__param_target]
target_label: instance
- action: labelmap
regex: __meta_kubernetes_ingress_label_(.+)
- source_labels: [__meta_kubernetes_namespace]
target_label: kubernetes_namespace
- source_labels: [__meta_kubernetes_ingress_name]
target_label: kubernetes_name

- job_name: 'kubernetes-pods'
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
action: keep
regex: true
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
action: replace
target_label: __metrics_path__
regex: (.+)
- source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
action: replace
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
target_label: __address__
- action: labelmap
regex: __meta_kubernetes_pod_label_(.+)
- source_labels: [__meta_kubernetes_namespace]
action: replace
target_label: kubernetes_namespace
- source_labels: [__meta_kubernetes_pod_name]
action: replace
target_label: kubernetes_pod_name
3、Prometheus deployment 文件
[root@k8s-master-101 prometheus]# cat prometheus.deploy.yml
---
apiVersion: apps/v1beta2
kind: Deployment
metadata:
labels:
name: prometheus-deployment
name: prometheus
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
template:
metadata:
labels:
app: prometheus
spec:
containers:
- image: prom/prometheus:v2.0.0
name: prometheus
command:
- "/bin/prometheus"
args:
- "--config.file=/etc/prometheus/prometheus.yml"
- "--storage.tsdb.path=/prometheus"
- "--storage.tsdb.retention=24h"
ports:
- containerPort: 9090
protocol: TCP
volumeMounts:
- mountPath: "/prometheus"
name: data
- mountPath: "/etc/prometheus"
name: config-volume
resources:
requests:
cpu: 100m
memory: 100Mi
limits:
cpu: 500m
memory: 2500Mi
serviceAccountName: prometheus
volumes:
- name: data
emptyDir: {}
- name: config-volume
configMap:
name: prometheus-config
4、Prometheus service文件
容器的9090端口和service的9090端口
宿主机的30003端口
[root@k8s-master-101 prometheus]# cat prometheus.svc.yml
---
kind: Service
apiVersion: v1
metadata:
labels:
app: prometheus
name: prometheus
namespace: kube-system
spec:
type: NodePort
ports:
- port: 9090
targetPort: 9090
nodePort: 30003
selector:
app: prometheus
5、创建相应对象
# kubectl create -f rbac-setup.yaml
# kubectl create -f configmap.yaml
# kubectl create -f prometheus.deploy.yml
# kubectl create -f prometheus.svc.yml
[root@master ~]# kubectl get pod -n kube-system

root@master ~]# kubectl get svc -n kube-system

 

6、测试访问,prometheus对应的nodeport端口为30003,通过访问http://[node ip]:30003/targets

可以看到prometheus已经成功连接上了k8s的apiserver

 

 

可以在prometheus的WEB界面上提供了基本的查询K8S集群中每个POD的CPU使用情况,查询条件如下:
sum by (pod_name)( rate(container_cpu_usage_seconds_total{image!="", pod_name!=""}[1m] ) )

 

 

上述的查询有出现数据,说明node-exporter往prometheus中写入数据正常,接下来我们就可以部署grafana组件,实现更友好的webui展示数据了。
三、部署grafana组件
1、grafana deployment配置文件
[root@k8s-master-101 prometheus]# cat grafana-deploy.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: grafana-core
namespace: kube-system
labels:
app: grafana
component: core
spec:
replicas: 1
template:
metadata:
labels:
app: grafana
component: core
spec:
containers:
- image: grafana/grafana:4.2.0
name: grafana-core
imagePullPolicy: IfNotPresent
# env:
resources:
# keep request = limit to keep this container in guaranteed class
limits:
cpu: 100m
memory: 100Mi
requests:
cpu: 100m
memory: 100Mi
env:
# The following env variables set up basic auth twith the default admin user and admin password.
- name: GF_AUTH_BASIC_ENABLED
value: "true"
- name: GF_AUTH_ANONYMOUS_ENABLED
value: "false"
# - name: GF_AUTH_ANONYMOUS_ORG_ROLE
# value: Admin
# does not really work, because of template variables in exported dashboards:
# - name: GF_DASHBOARDS_JSON_ENABLED
# value: "true"
readinessProbe:
httpGet:
path: /login
port: 3000
# initialDelaySeconds: 30
# timeoutSeconds: 1
volumeMounts:
- name: grafana-persistent-storage
mountPath: /var
volumes:
- name: grafana-persistent-storage
emptyDir: {}
2、grafana service配置文件
[root@k8s-master-101 prometheus]# cat grafana-svc.yaml
apiVersion: v1
kind: Service
metadata:
name: grafana
namespace: kube-system
labels:
app: grafana
component: core
spec:
type: NodePort
ports:
- port: 3000
selector:
app: grafana
component: core
3、grafana ingress配置文件
[root@k8s-master-101 prometheus]# cat grafana-ing.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: grafana
namespace: kube-system
spec:
rules:
- host: k8s.grafana
http:
paths:
- path: /
backend:
serviceName: grafana
servicePort: 3000
通过访问traefik的webui可以看到k8s.grafana服务发布成功

 

 

4、通过上述文件构建pod和serivce
kubectl create -f grafana-deploy.yaml
kubectl create -f grafana-svc.yaml
kubectl create -f grafana-ing.yaml
[root@master ~]# kubectl get svc -n kube-system

 

 

5、配置数据源为prometheus(访问IP:21667)
访问测试:默认用户名和密码都是admin
Add data中选择
Name: Prometheus
Type: Prometheus
url: http://prometheus.kube-system.svc.cluster.local:9090

6、导入面板之后就可以看到对应的监控数据了

 

 

添加模版的地址:
https://grafana.com/grafana/dashboards