grafana jvm中文 grafana alertlist

k8s监控实战-grafana出图_alert告警

目录

• k8s监控实战-grafana出图_alert告警

• 1 使用炫酷的grafana出图

• 1.1 部署grafana

• 1.1.1 准备镜像
• 1.1.2 准备rbac资源清单
• 1.1.3 准备dp资源清单
• 1.1.4 准备svc资源清单
• 1.1.5 准备ingress资源清单
• 1.1.6 域名解析
• 1.1.7 应用资源配置清单

• 1.2 使用grafana出图

• 1.2.1 浏览器访问验证
• 1.2.2 进入容器安装插件
• 1.2.3 配置数据源
• 1.2.4 添加K8S集群信息
• 1.2.5 查看k8s集群数据和图表

• 2 配置alert告警插件

• 2.1 部署alert插件

• 2.1.1 准备docker镜像
• 2.1.2 准备cm资源清单
• 2.1.3 准备dp资源清单
• 2.1.4 准备svc资源清单
• 2.1.5 应用资源配置清单

• 2.2 K8S使用alert报警

• 2.2.1 k8s创建基础报警规则文件
• 2.2.2 K8S 更新配置
• 2.2.3 测试告警

1 使用炫酷的grafana出图

prometheus的dashboard虽然号称拥有多种多样的图表,但是实在太简陋了,一般都用专业的grafana工具来出图
grafana官方dockerhub地址grafana官方github地址grafana官网

1.1 部署grafana

1.1.1 准备镜像

docker pull grafana/grafana:5.4.2
docker tag  6f18ddf9e552 harbor.zq.com/infra/grafana:v5.4.2
docker push harbor.zq.com/infra/grafana:v5.4.2

准备目录

mkdir /data/k8s-yaml/grafana
cd    /data/k8s-yaml/grafana

1.1.2 准备rbac资源清单

cat >rbac.yaml <<'EOF'
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: grafana
rules:
- apiGroups:
  - "*"
  resources:
  - namespaces
  - deployments
  - pods
  verbs:
  - get
  - list
  - watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/cluster-service: "true"
  name: grafana
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: grafana
subjects:
- kind: User
  name: k8s-node
EOF

1.1.3 准备dp资源清单

cat >dp.yaml <<'EOF'
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  labels:
    app: grafana
    name: grafana
  name: grafana
  namespace: infra
spec:
  progressDeadlineSeconds: 600
  replicas: 1
  revisionHistoryLimit: 7
  selector:
    matchLabels:
      name: grafana
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  template:
    metadata:
      labels:
        app: grafana
        name: grafana
    spec:
      containers:
      - name: grafana
        image: harbor.zq.com/infra/grafana:v5.4.2
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 3000
          protocol: TCP
        volumeMounts:
        - mountPath: /var/lib/grafana
          name: data
      imagePullSecrets:
      - name: harbor
      securityContext:
        runAsUser: 0
      volumes:
      - nfs:
          server: hdss7-200
          path: /data/nfs-volume/grafana
        name: data
EOF

创建frafana数据目录

mkdir /data/nfs-volume/grafana

1.1.4 准备svc资源清单

cat >svc.yaml <<'EOF'
apiVersion: v1
kind: Service
metadata:
  name: grafana
  namespace: infra
spec:
  ports:
  - port: 3000
    protocol: TCP
    targetPort: 3000
  selector:
    app: grafana
EOF

1.1.5 准备ingress资源清单

cat >ingress.yaml <<'EOF'
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  name: grafana
  namespace: infra
spec:
  rules:
  - host: grafana.zq.com
    http:
      paths:
      - path: /
        backend:
          serviceName: grafana
          servicePort: 3000
EOF

1.1.6 域名解析

vi /var/named/zq.com.zone
grafana            A    10.4.7.10

systemctl restart named

1.1.7 应用资源配置清单

kubectl apply -f http://k8s-yaml.zq.com/grafana/rbac.yaml
kubectl apply -f http://k8s-yaml.zq.com/grafana/dp.yaml
kubectl apply -f http://k8s-yaml.zq.com/grafana/svc.yaml
kubectl apply -f http://k8s-yaml.zq.com/grafana/ingress.yaml

1.2 使用grafana出图

1.2.1 浏览器访问验证

访问http://grafana.zq.com,默认用户名密码admin/admin
能成功访问表示安装成功
进入后立即修改管理员密码为admin123

1.2.2 进入容器安装插件

grafana确认启动好以后,需要进入grafana容器内部,安装以下插件

kubectl -n infra exec  -it grafana-d6588db94-xr4s6 /bin/bash
# 以下命令在容器内执行
grafana-cli plugins install grafana-kubernetes-app
grafana-cli plugins install grafana-clock-panel
grafana-cli plugins install grafana-piechart-panel
grafana-cli plugins install briangann-gauge-panel
grafana-cli plugins install natel-discrete-panel

1.2.3 配置数据源

添加数据源,依次点击：左侧锯齿图标-->add data source-->Prometheus

添加完成后重启grafana

kubectl -n infra delete pod grafana-7dd95b4c8d-nj5cx

1.2.4 添加K8S集群信息

启用K8S插件,依次点击：左侧锯齿图标-->Plugins-->kubernetes-->Enable

新建cluster,依次点击：左侧K8S图标-->New Cluster

1.2.5 查看k8s集群数据和图表

添加完需要稍等几分钟，在没有取到数据之前，会报http forbidden，没关系，等一会就好。大概2-5分钟。

点击Cluster Dashboard

2 配置alert告警插件

2.1 部署alert插件

2.1.1 准备docker镜像

docker pull docker.io/prom/alertmanager:v0.14.0
docker tag  23744b2d645c harbor.zq.com/infra/alertmanager:v0.14.0
docker push harbor.zq.com/infra/alertmanager:v0.14.0

准备目录

mkdir /data/k8s-yaml/alertmanager
cd /data/k8s-yaml/alertmanager

2.1.2 准备cm资源清单

cat >cm.yaml <<'EOF'
apiVersion: v1
kind: ConfigMap
metadata:
  name: alertmanager-config
  namespace: infra
data:
  config.yml: |-
    global:
      # 在没有报警的情况下声明为已解决的时间
      resolve_timeout: 5m
      # 配置邮件发送信息
      smtp_smarthost: 'smtp.163.com:25'
      smtp_from: '[e-mail]'
      smtp_auth_username: '[e-mail]'
      smtp_auth_password: 'xxxxxx'
      smtp_require_tls: false
    templates:   
      - '/etc/alertmanager/*.tmpl'
    # 所有报警信息进入后的根路由，用来设置报警的分发策略
    route:
      # 这里的标签列表是接收到报警信息后的重新分组标签，例如，接收到的报警信息里面有许多具有 cluster=A 和 alertname=LatncyHigh 这样的标签的报警信息将会批量被聚合到一个分组里面
      group_by: ['alertname', 'cluster']
      # 当一个新的报警分组被创建后，需要等待至少group_wait时间来初始化通知，这种方式可以确保您能有足够的时间为同一分组来获取多个警报，然后一起触发这个报警信息。
      group_wait: 30s

  # 当第一个报警发送后，等待'group_interval'时间来发送新的一组报警信息。
  group_interval: 5m

  # 如果一个报警信息已经发送成功了，等待'repeat_interval'时间来重新发送他们
  repeat_interval: 5m

  # 默认的receiver：如果一个报警没有被一个route匹配，则发送给默认的接收器
  receiver: default

receivers:
- name: 'default'
  email_configs:
  - to: '[e-mail]'
    send_resolved: true
    html: '{{ template "email.to.html" . }}' 
    headers: { Subject: " {{ .CommonLabels.instance }} {{ .CommonAnnotations.summary }}" }

email.tmpl: |
{{ define "email.to.html" }}
{{- if gt (len .Alerts.Firing) 0 -}}
{{ range .Alerts }}
告警程序: prometheus_alert <br>
告警级别: {{ .Labels.severity }} <br>
告警类型: {{ .Labels.alertname }} <br>
故障主机: {{ .Labels.instance }} <br>
告警主题: {{ .Annotations.summary }} <br>
触发时间: {{ .StartsAt.Format "2006-01-02 15:04:05" }} <br>
{{ end }}{{ end -}}

{{- if gt (len .Alerts.Resolved) 0 -}}
{{ range .Alerts }}
告警程序: prometheus_alert <br>
告警级别: {{ .Labels.severity }} <br>
告警类型: {{ .Labels.alertname }} <br>
故障主机: {{ .Labels.instance }} <br>
告警主题: {{ .Annotations.summary }} <br>
触发时间: {{ .StartsAt.Format "2006-01-02 15:04:05" }} <br>
恢复时间: {{ .EndsAt.Format "2006-01-02 15:04:05" }} <br>
{{ end }}{{ end -}}

{{- end }}

EOF

2.1.3 准备dp资源清单

cat >dp.yaml <<'EOF'
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: alertmanager
  namespace: infra
spec:
  replicas: 1
  selector:
    matchLabels:
      app: alertmanager
  template:
    metadata:
      labels:
        app: alertmanager
    spec:
      containers:
      - name: alertmanager
        image: harbor.zq.com/infra/alertmanager:v0.14.0
        args:
          - "--config.file=/etc/alertmanager/config.yml"
          - "--storage.path=/alertmanager"
        ports:
        - name: alertmanager
          containerPort: 9093
        volumeMounts:
        - name: alertmanager-cm
          mountPath: /etc/alertmanager
      volumes:
      - name: alertmanager-cm
        configMap:
          name: alertmanager-config
      imagePullSecrets:
      - name: harbor
EOF

2.1.4 准备svc资源清单

cat >svc.yaml <<'EOF'
apiVersion: v1
kind: Service
metadata:
  name: alertmanager
  namespace: infra
spec:
  selector: 
    app: alertmanager
  ports:
    - port: 80
      targetPort: 9093
EOF

2.1.5 应用资源配置清单

kubectl apply -f http://k8s-yaml.zq.com/alertmanager/cm.yaml
kubectl apply -f http://k8s-yaml.zq.com/alertmanager/dp.yaml
kubectl apply -f http://k8s-yaml.zq.com/alertmanager/svc.yaml

2.2 K8S使用alert报警

2.2.1 k8s创建基础报警规则文件

cat >/data/nfs-volume/prometheus/etc/rules.yml <<'EOF'
groups:
- name: hostStatsAlert
  rules:
  - alert: hostCpuUsageAlert
    expr: sum(avg without (cpu)(irate(node_cpu{mode!='idle'}[5m]))) by (instance) > 0.85
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "{{ $labels.instance }} CPU usage above 85% (current value: {{ $value }}%)"
  - alert: hostMemUsageAlert
    expr: (node_memory_MemTotal - node_memory_MemAvailable)/node_memory_MemTotal > 0.85
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "{{ $labels.instance }} MEM usage above 85% (current value: {{ $value }}%)"
  - alert: OutOfInodes
    expr: node_filesystem_free{fstype="overlay",mountpoint ="/"} / node_filesystem_size{fstype="overlay",mountpoint ="/"} * 100 < 10
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Out of inodes (instance {{ $labels.instance }})"
      description: "Disk is almost running out of available inodes (< 10% left) (current value: {{ $value }})"
  - alert: OutOfDiskSpace
    expr: node_filesystem_free{fstype="overlay",mountpoint ="/rootfs"} / node_filesystem_size{fstype="overlay",mountpoint ="/rootfs"} * 100 < 10
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Out of disk space (instance {{ $labels.instance }})"
      description: "Disk is almost full (< 10% left) (current value: {{ $value }})"
  - alert: UnusualNetworkThroughputIn
    expr: sum by (instance) (irate(node_network_receive_bytes[2m])) / 1024 / 1024 > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual network throughput in (instance {{ $labels.instance }})"
      description: "Host network interfaces are probably receiving too much data (> 100 MB/s) (current value: {{ $value }})"
  - alert: UnusualNetworkThroughputOut
    expr: sum by (instance) (irate(node_network_transmit_bytes[2m])) / 1024 / 1024 > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual network throughput out (instance {{ $labels.instance }})"
      description: "Host network interfaces are probably sending too much data (> 100 MB/s) (current value: {{ $value }})"
  - alert: UnusualDiskReadRate
    expr: sum by (instance) (irate(node_disk_bytes_read[2m])) / 1024 / 1024 > 50
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk read rate (instance {{ $labels.instance }})"
      description: "Disk is probably reading too much data (> 50 MB/s) (current value: {{ $value }})"
  - alert: UnusualDiskWriteRate
    expr: sum by (instance) (irate(node_disk_bytes_written[2m])) / 1024 / 1024 > 50
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk write rate (instance {{ $labels.instance }})"
      description: "Disk is probably writing too much data (> 50 MB/s) (current value: {{ $value }})"
  - alert: UnusualDiskReadLatency
    expr: rate(node_disk_read_time_ms[1m]) / rate(node_disk_reads_completed[1m]) > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk read latency (instance {{ $labels.instance }})"
      description: "Disk latency is growing (read operations > 100ms) (current value: {{ $value }})"
  - alert: UnusualDiskWriteLatency
    expr: rate(node_disk_write_time_ms[1m]) / rate(node_disk_writes_completedl[1m]) > 100
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Unusual disk write latency (instance {{ $labels.instance }})"
      description: "Disk latency is growing (write operations > 100ms) (current value: {{ $value }})"
- name: http_status
  rules:
  - alert: ProbeFailed
    expr: probe_success == 0
    for: 1m
    labels:
      severity: error
    annotations:
      summary: "Probe failed (instance {{ $labels.instance }})"
      description: "Probe failed (current value: {{ $value }})"
  - alert: StatusCode
    expr: probe_http_status_code <= 199 OR probe_http_status_code >= 400
    for: 1m
    labels:
      severity: error
    annotations:
      summary: "Status Code (instance {{ $labels.instance }})"
      description: "HTTP status code is not 200-399 (current value: {{ $value }})"
  - alert: SslCertificateWillExpireSoon
    expr: probe_ssl_earliest_cert_expiry - time() < 86400 * 30
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "SSL certificate will expire soon (instance {{ $labels.instance }})"
      description: "SSL certificate expires in 30 days (current value: {{ $value }})"
  - alert: SslCertificateHasExpired
    expr: probe_ssl_earliest_cert_expiry - time()  <= 0
    for: 5m
    labels:
      severity: error
    annotations:
      summary: "SSL certificate has expired (instance {{ $labels.instance }})"
      description: "SSL certificate has expired already (current value: {{ $value }})"
  - alert: BlackboxSlowPing
    expr: probe_icmp_duration_seconds > 2
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Blackbox slow ping (instance {{ $labels.instance }})"
      description: "Blackbox ping took more than 2s (current value: {{ $value }})"
  - alert: BlackboxSlowRequests
    expr: probe_http_duration_seconds > 2 
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Blackbox slow requests (instance {{ $labels.instance }})"
      description: "Blackbox request took more than 2s (current value: {{ $value }})"
  - alert: PodCpuUsagePercent
    expr: sum(sum(label_replace(irate(container_cpu_usage_seconds_total[1m]),"pod","$1","container_label_io_kubernetes_pod_name", "(.*)"))by(pod) / on(pod) group_right kube_pod_container_resource_limits_cpu_cores *100 )by(container,namespace,node,pod,severity) > 80
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Pod cpu usage percent has exceeded 80% (current value: {{ $value }}%)"
EOF

2.2.2 K8S 更新配置

在prometheus配置文件中追加配置：

cat >>/data/nfs-volume/prometheus/etc/prometheus.yml <<'EOF'
alerting:
  alertmanagers:
    - static_configs:
        - targets: ["alertmanager"]
rule_files:
 - "/data/etc/rules.yml"
EOF

重载配置：

curl -X POST http://prometheus.zq.com/-/reload

以上这些就是我们的告警规则

2.2.3 测试告警

把test命名空间里的dubbo-demo-service给停掉

blackbox里信息已报错,alert里面项目变黄了

等到alert中项目变为红色的时候就开会发邮件告警

如果需要自己定制告警规则和告警内容，需要研究一下promql，自己修改配置文件。