##### Consul字段设计说明 - 所有数据存在一个名为`blackbox_exporter`的Services项中,每个监控目标为一个子Service。 - 每个Service包含一个Tag,会自动配置为meta中的`module`的值,作为Prometheus自动发现的tags。 - 每个Service使用Meta的kv保存监控目标的明细:`module`,`company`,`project`,`env`,`name`,`instance`,分别表示:监控类型,公司部门,项目,环境,名称,实例url - **前5个字段合并即为consul的serviceID,作为唯一监控项标识** - **建议监控类型字段:`meta内的module`,`blackbox-exporter配置中的module`及`Prometheus的job名`使用同一命名。** ### 配置Prometheus ##### 基于Consul实现Prometheus的自动发现功能配置 - 根据Consul每个service的tag来把监控目标关联到Prometheus的JOB。 - 把Consul每个service的Meta的KV关联到Prometheus每个指标的标签。 - 根据每个指标的标签来对监控目标分类,分组,方便管理维护。 **以下配置的同一个job的`job_name`,`module`,`tags`使用同一命名,关联job,module与consul的tags** 参考配置:2XX,4XX,TCP类型的监控,注意JOB名称不要与已有的重复。 ```yaml vi prometheus.yml #####blackbox_exporter##### - job_name: 'http_2xx' metrics_path: /probe params: module: [http_2xx] consul_sd_configs: - server: 'x.x.x.x:8500' token: 'xxx-xxx-xxx-xxx' services: ['blackbox_exporter'] tags: ['http_2xx'] relabel_configs: - source_labels: ["__meta_consul_service_metadata_instance"] target_label: __param_target - source_labels: ["__meta_consul_service_metadata_company"] target_label: company - source_labels: ["__meta_consul_service_metadata_env"] target_label: env - source_labels: ["__meta_consul_service_metadata_name"] target_label: name - source_labels: ["__meta_consul_service_metadata_project"] target_label: project - source_labels: [__param_target] target_label: instance - target_label: __address__ replacement: 127.0.0.1:9115 - job_name: 'http_4xx' metrics_path: /probe params: module: [http_4xx] consul_sd_configs: - server: 'x.x.x.x:8500' token: 'xxx-xxx-xxx-xxx' services: ['blackbox_exporter'] tags: ['http_4xx'] relabel_configs: - source_labels: ["__meta_consul_service_metadata_instance"] target_label: __param_target - source_labels: ["__meta_consul_service_metadata_company"] target_label: company - source_labels: ["__meta_consul_service_metadata_env"] target_label: env - source_labels: ["__meta_consul_service_metadata_name"] target_label: name - source_labels: ["__meta_consul_service_metadata_project"] target_label: project - source_labels: [__param_target] target_label: instance - target_label: __address__ replacement: 127.0.0.1:9115 - job_name: 'tcp_connect' metrics_path: /probe params: module: [tcp_connect] consul_sd_configs: - server: 'x.x.x.x:8500' token: 'xxx-xxx-xxx-xxx' services: ['blackbox_exporter'] tags: ['tcp_connect'] relabel_configs: - source_labels: ["__meta_consul_service_metadata_instance"] target_label: __param_target - source_labels: ["__meta_consul_service_metadata_company"] target_label: company - source_labels: ["__meta_consul_service_metadata_env"] target_label: env - source_labels: ["__meta_consul_service_metadata_name"] target_label: name - source_labels: ["__meta_consul_service_metadata_project"] target_label: project - source_labels: [__param_target] target_label: instance - target_label: __address__ replacement: 127.0.0.1:9115 ``` ### 配置Blackbox_Exporter 参考配置:2XX,4XX,TCP类型的监控,注意模块名称不要与已有的重复。 ``` cat blackbox.yml modules: http_2xx: prober: http http: valid_status_codes: - 200 - 301 - 302 - 303 no_follow_redirects: true preferred_ip_protocol: ip4 ip_protocol_fallback: false http_4xx: prober: http http: valid_status_codes: - 401 - 403 - 404 preferred_ip_protocol: ip4 ip_protocol_fallback: false tcp_connect: prober: tcp ``` ### 批量导入脚本 在units目录下`instance.list`中写入监控目标的信息:JOB名称,公司/部门,项目,环境,名称,实例url,每行一个,空格分隔。 **注意:前5个字段组合起来必须唯一,作为一个监控项的ID。** 修改units目录下导入脚本中的consul_token和consul_url,保存后执行input.py,即可导入所有监控目标到Consul,并符合Prometheus的自动发现配置。 ### 导入Blackbox Exporter Dashboard - 支持Grafana 8,基于blackbox_exporter 0.19.0设计 - 采用图表+曲线图方式展示TCP,ICMP,HTTPS的服务状态,各阶段请求延时,HTTPS证书信息等 - 优化展示效果,支持监控目标的分组、分类级联展示,多服务同时对比展示。 ``` 导入ID:9965 详细URL:https://grafana.com/grafana/dashboards/9965 ``` ### Prometheus 站点监控告警规则 ``` - name: Domain rules: - alert: 站点可用性 expr: probe_success == 0 for: 1m labels: alertype: domain severity: critical annotations: description: "{{$labels.env}}_{{ $labels.name }}({{ $labels.project }}):站点无法访问\n> {{ $labels.instance }}" - alert: 站点1h可用性低于80% expr: sum_over_time(probe_success[1h])/count_over_time(probe_success[1h]) * 100 < 80 for: 3m labels: alertype: domain severity: warning annotations: description: "{{$labels.env}}_{{ $labels.name }}({{ $labels.project }}):站点1h可用性:{{ $value | humanize }}%\n> {{ $labels.instance }}" - alert: 站点状态异常 expr: (probe_success == 0 and probe_http_status_code > 499) or probe_http_status_code == 0 for: 1m labels: alertype: domain severity: warning annotations: description: "{{$labels.env}}_{{ $labels.name }}({{ $labels.project }}):站点状态异常:{{$value}}\n> {{ $labels.instance }}" - alert: 站点耗时过高 expr: probe_duration_seconds > 0.5 for: 2m labels: alertype: domain severity: warning annotations: description: "{{$labels.env}}_{{ $labels.name }}({{ $labels.project }}):当前站点耗时:{{$value | humanize}}s\n> {{ $labels.instance }}" - alert: SSL证书有效期 expr: (probe_ssl_earliest_cert_expiry-time()) / 3600 / 24 < 15 for: 2m labels: alertype: domain severity: warning annotations: description: "{{$labels.env}}_{{ $labels.name }}({{ $labels.project }}):证书有效期剩余{{ $value | humanize }}天\n> {{ $labels.instance }}" ```