原理相信大家看了好多了直接上部署过程！
创建一个monitoring命名空间由于存放prometheus相关的容器
Monitoring.yaml
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
Kubectl apply -f monitoring
部署node-exporter指标
Node-export.yaml
---
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
name: node-exporter
namespace: monitoring
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: monitoring
annotations:
prometheus.io/scrape: 'true'
spec:
ports:
- name: http
port: 9100
nodePort: 9100
protocol: TCP
type: NodePort
selector:
k8s-app: node-exporter
kubectl apply -f node-export.yaml #创建node-exporter容器
注意此处的prometheus.io/scrape: “true” (用于后续的kube-state-metrics endpoints使用)
部署kube-state-meteics指标
文件太多…请自行clone：https://github.com/kubernetes/kube-state-metrics
Yaml文件在$pwd/kubernetes下
部署prometheus
prometheus-configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-config
namespace: kube-system
data:
prometheus.yml: |
global:
scrape_interval: 15s
evaluation_interval: 15s
rule_files:
- /etc/prometheus/rules.yml
alerting:
alertmanagers:
- static_configs:
- targets: ["alertmanager:9093"]
scrape_configs:
- job_name: 'kubernetes-apiservers'
kubernetes_sd_configs:
- role: endpoints
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
action: keep
regex: default;kubernetes;https
- job_name: 'kubernetes-nodes'
kubernetes_sd_configs:
- role: node
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${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
prometheus-configmap-rules.yaml 规则根据自己需求定义
Prometheus.deployment.yaml
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
- mountPath: "/etc/prometheus/rules"
name: rules
resources:
requests:
cpu: 100m
memory: 100Mi
limits:
cpu: 500m
memory: 2500Mi
serviceAccountName: prometheus
volumes:
- name: data
emptyDir: {}
- name: config-volume
configMap:
name: prometheus-config
- name: rules
configMap:
name: prometheus-rules
---
kind: Service
apiVersion: v1
metadata:
labels:
app: prometheus
annotations:
prometheus.io/scrape: "true"
name: prometheus
namespace: monitoring
spec:
type: NodePort
ports:
- port: 9090
targetPort: 9090
protocol: TCP
nodePort: 9090
selector:
app: prometheus
Kubectl apply -f prometheus-configmap.yaml
Kubectl apply -f prometheus-configmap-rules.yaml
Kubectl apply -f prometheus.deployment.yaml
部署alertmanager
Alertmanager-mail.yaml
---
kind: ConfigMap
apiVersion: v1
metadata:
name: alertmanager
namespace: monitoring
data:
alertmanager.yml: |-
global:
smtp_smarthost: ###邮箱服务端
smtp_from: ###发件人邮箱
smtp_auth_username: ###发件人邮箱认证
smtp_auth_password:
smtp_require_tls: false
route:
group_by: [] ###自定义
group_wait: 30s
group_interval: 5m
repeat_interval: 10m
receiver: ###自定义接收名称
receivers:
- name: ###需与receiver的值对应
email_configs:
- to: '' ###收件人邮箱
Alertmanager.deployment.yaml
---
apiVersion: apps/v1beta2
kind: Deployment
metadata:
labels:
name: alertmanager-deployment
name: alertmanager
namespace: monitoring
spec:
replicas: 1
selector:
matchLabels:
app: alertmanager
template:
metadata:
labels:
app: alertmanager
spec:
containers:
- image: prom/alertmanager:v0.16.1
name: alertmanager
ports:
- containerPort: 9093
protocol: TCP
volumeMounts:
- mountPath: "/alertmanager"
name: data
- mountPath: "/etc/alertmanager"
name: config-volume
resources:
requests:
cpu: 50m
memory: 50Mi
limits:
cpu: 200m
memory: 200Mi
volumes:
- name: data
emptyDir: {}
- name: config-volume
configMap:
name: alertmanager
---
apiVersion: v1
kind: Service
metadata:
labels:
app: alertmanager
annotations:
prometheus.io/scrape: 'true'
name: alertmanager
namespace: monitoring
spec:
type: NodePort
ports:
- port: 9093
targetPort: 9093
nodePort: 9093
selector:
app: alertmanager
Kubectl apply -f alertmanager-mail.yaml
Kubectl apply -f alertmanager.deployment.yaml
prometheus和alertmanager部署完成，可通过web页面访问prometheus和alertmanager
Prometheus访问地址：http://IP:9090
Alertmanager访问地址：http://IP:9093
prometheus 去status --> targets 查看我们添加配置
可以明确的看到我们添加的node-exporter和kube-state-metrics都被检测到,结合我们的rules测试一下报警及邮件发送
Rules的报警过程分为Active --> Pending --> Firing ,当rules的状态为Firing时,才会将报警信息发送给Alertmanager.
当rules变为红色,这时他就会想报警信息发给alertmanager,alertmanager就会发送邮箱报警了
部署grafana
grafana-deploy.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: grafana-core
namespace: monitoring
# 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/lib/grafana
volumes:
- name: grafana-persistent-storage
emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
name: grafana
namespace: monitoring
labels:
app: grafana
component: core
spec:
type: NodePort
ports:
- port: 3000
nodePort: 3000
selector:
app: grafana
component: core
Kubectl apply -f grafana-deploy.yaml
访问grafana：http://IP:3000
看到登录页面,点击登录
点击Add data source,添加数据源(url为prometheus地址)
然后点击Dashboards --> import 输入1621
点击load,选择事先创建好的数据源prometheus
点击import即可看到动态dashboard
至此,部署完成！
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