怎么自己做网站游戏,网站开发语言啥意思,黄骅市长,创业融资平台prometheus将监控到的异常事件发送给Alertmanager#xff0c;然后Alertmanager将报警信息发送到邮箱等设备。可以从下图看出#xff0c;push alerts是由Prometheus发起的。 安装Alertmanager config文件
[rootmaster prometheus]# cat alertmanager-cm.yaml
kind: ConfigMa…prometheus将监控到的异常事件发送给Alertmanager然后Alertmanager将报警信息发送到邮箱等设备。可以从下图看出push alerts是由Prometheus发起的。 安装Alertmanager config文件
[rootmaster prometheus]# cat alertmanager-cm.yaml
kind: ConfigMap
apiVersion: v1
metadata:name: alertmanagernamespace: monitor-sa
data:alertmanager.yml: |-global:resolve_timeout: 1msmtp_smarthost: smtp.qq.com:465smtp_from: 147359****qq.comsmtp_auth_username: 1123345555smtp_auth_password: pytoinoomgvxiaagsmtp_require_tls: falseroute:group_by: [alertname]group_wait: 10sgroup_interval: 10srepeat_interval: 10mreceiver: default-receiverreceivers:- name: default-receiveremail_configs:- to: xisdgsgs163.comsend_resolved: true随后生效可以查看configmap清单。
[rootmaster prometheus]# kubectl get configmap -n monitor-sa
NAME DATA AGE
alertmanager 1 2m8s
kube-root-ca.crt 1 2d10h
prometheus-config 1 36h报警流程
Prometheus的处理
数据采集Prometheus Server 定期从配置的监控目标比如某个 HTTP 接口采集数据。采集间隔由 scrape_interval 控制。Pending 状态当警报条件首次被满足时警报会进入“Pending”状态。这是一个预备状态用于确保问题是持续存在的而不是暂时性的或偶然的。for 语句在警报规则中定义了需要持续触发该条件多长时间后警报才会进入下一个状态。Firing 状态如果问题在设定的 for 时间内持续存在警报状态会转变为“Firing”。这意味着警报被认为是有效的需要通知到相关人员或系统。报警发送进入“Firing”状态后警报信息会发送到 Alertmanager。
Alertmanager 的处理
Alertmanager 接收到 FIRING 状态的报警后会根据报警信息进行分组并根据配置的 group_wait 延迟一段时间后开始处理报警。
Prometheus报警规则
从上面的流程可以看出来报警规则是Prometheus设置的。设置一个config文件
[rootmaster ~]# cat prometheus-alertmanager-cfg.yaml
kind: ConfigMap
apiVersion: v1
metadata:labels:app: prometheusname: prometheus-confignamespace: monitor-sa
data:prometheus.yml: |rule_files:- /etc/prometheus/rules.ymlalerting:alertmanagers:- static_configs:- targets: [localhost:9093]global:scrape_interval: 15sscrape_timeout: 10sevaluation_interval: 1mscrape_configs:- job_name: kubernetes-nodekubernetes_sd_configs:- role: noderelabel_configs:- source_labels: [__address__]regex: (.*):10250replacement: ${1}:9100target_label: __address__action: replace- action: labelmapregex: __meta_kubernetes_node_label_(.)- job_name: kubernetes-node-cadvisorkubernetes_sd_configs:- role: nodescheme: httpstls_config:ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crtbearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/tokenrelabel_configs:- action: labelmapregex: __meta_kubernetes_node_label_(.)- target_label: __address__replacement: kubernetes.default.svc:443- source_labels: [__meta_kubernetes_node_name]regex: (.)target_label: __metrics_path__replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor- job_name: kubernetes-apiserverkubernetes_sd_configs:- role: endpointsscheme: httpstls_config:ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crtbearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/tokenrelabel_configs:- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]action: keepregex: default;kubernetes;https- job_name: kubernetes-service-endpointskubernetes_sd_configs:- role: endpointsrelabel_configs:- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]action: keepregex: true- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]action: replacetarget_label: __scheme__regex: (https?)- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]action: replacetarget_label: __metrics_path__regex: (.)- source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]action: replacetarget_label: __address__regex: ([^:])(?::\d)?;(\d)replacement: $1:$2- action: labelmapregex: __meta_kubernetes_service_label_(.)- source_labels: [__meta_kubernetes_namespace]action: replacetarget_label: kubernetes_namespace- source_labels: [__meta_kubernetes_service_name]action: replacetarget_label: kubernetes_name - job_name: kubernetes-podskubernetes_sd_configs:- role: podrelabel_configs:- action: keepregex: truesource_labels:- __meta_kubernetes_pod_annotation_prometheus_io_scrape- action: replaceregex: (.)source_labels:- __meta_kubernetes_pod_annotation_prometheus_io_pathtarget_label: __metrics_path__- action: replaceregex: ([^:])(?::\d)?;(\d)replacement: $1:$2source_labels:- __address__- __meta_kubernetes_pod_annotation_prometheus_io_porttarget_label: __address__- action: labelmapregex: __meta_kubernetes_pod_label_(.)- action: replacesource_labels:- __meta_kubernetes_namespacetarget_label: kubernetes_namespace- action: replacesource_labels:- __meta_kubernetes_pod_nametarget_label: kubernetes_pod_name- job_name: kubernetes-schedulescrape_interval: 5sstatic_configs:- targets: [192.168.40.180:10251]- job_name: kubernetes-controller-managerscrape_interval: 5sstatic_configs:- targets: [192.168.40.180:10252]- job_name: kubernetes-kube-proxyscrape_interval: 5sstatic_configs:- targets: [192.168.40.180:10249,192.168.40.181:10249]- job_name: kubernetes-etcdscheme: httpstls_config:ca_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/ca.crtcert_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.crtkey_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.keyscrape_interval: 5sstatic_configs:- targets: [192.168.40.180:2379]data: prometheus.yml: | rule_files: - /etc/prometheus/rules.yml alerting: alertmanagers: - static_configs: - targets: [localhost:9093] 这一段是基本配置信息配置Prometheus的文件路径以及在报警的时候prometheus是向localhost的9093端口报警我们将会把alartManager安装到与Prometheus相同的pod因此使用localhost就可以通信。 - job_name: kubernetes-schedule scrape_interval: 5s static_configs: - targets: [192.168.40.180:10251] - job_name: kubernetes-controller-manager scrape_interval: 5s static_configs: - targets: [192.168.40.180:10252] - job_name: kubernetes-kube-proxy scrape_interval: 5s static_configs: - targets: [192.168.40.180:10249,192.168.40.181:10249] - job_name: kubernetes-etcd scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/ca.crt cert_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.crt key_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.key scrape_interval: 5s static_configs: - targets: [192.168.40.180:2379] 相比于CSDN 中的Prometheus 规则这里新增了一些关于kube-controller和scheduler的规则但是需要查看具体的开放端口还要把这里的地址改为本机地址。
但是由于现在controller和scheduler已经不开放metrics端口所以现在无法通过Prometheus监听。
这里需要额外的精力解决。 rules.yml: |groups:- name: examplerules:- alert: kube-proxy的cpu使用率大于80%expr: rate(process_cpu_seconds_total{job~kubernetes-kube-proxy}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%- alert: kube-proxy的cpu使用率大于90%expr: rate(process_cpu_seconds_total{job~kubernetes-kube-proxy}[1m]) * 100 90for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%- alert: scheduler的cpu使用率大于80%expr: rate(process_cpu_seconds_total{job~kubernetes-schedule}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%- alert: scheduler的cpu使用率大于90%expr: rate(process_cpu_seconds_total{job~kubernetes-schedule}[1m]) * 100 90for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%- alert: controller-manager的cpu使用率大于80%expr: rate(process_cpu_seconds_total{job~kubernetes-controller-manager}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%- alert: controller-manager的cpu使用率大于90%expr: rate(process_cpu_seconds_total{job~kubernetes-controller-manager}[1m]) * 100 0for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%- alert: apiserver的cpu使用率大于80%expr: rate(process_cpu_seconds_total{job~kubernetes-apiserver}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%- alert: apiserver的cpu使用率大于90%expr: rate(process_cpu_seconds_total{job~kubernetes-apiserver}[1m]) * 100 90for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%- alert: etcd的cpu使用率大于80%expr: rate(process_cpu_seconds_total{job~kubernetes-etcd}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%- alert: etcd的cpu使用率大于90%expr: rate(process_cpu_seconds_total{job~kubernetes-etcd}[1m]) * 100 90for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%- alert: kube-state-metrics的cpu使用率大于80%expr: rate(process_cpu_seconds_total{k8s_app~kube-state-metrics}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过80%value: {{ $value }}%threshold: 80% - alert: kube-state-metrics的cpu使用率大于90%expr: rate(process_cpu_seconds_total{k8s_app~kube-state-metrics}[1m]) * 100 0for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过90%value: {{ $value }}%threshold: 90% - alert: coredns的cpu使用率大于80%expr: rate(process_cpu_seconds_total{k8s_app~kube-dns}[1m]) * 100 80for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过80%value: {{ $value }}%threshold: 80% - alert: coredns的cpu使用率大于90%expr: rate(process_cpu_seconds_total{k8s_app~kube-dns}[1m]) * 100 90for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过90%value: {{ $value }}%threshold: 90% - alert: kube-proxy打开句柄数600expr: process_open_fds{job~kubernetes-kube-proxy} 600for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数600value: {{ $value }}- alert: kube-proxy打开句柄数1000expr: process_open_fds{job~kubernetes-kube-proxy} 1000for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数1000value: {{ $value }}- alert: kubernetes-schedule打开句柄数600expr: process_open_fds{job~kubernetes-schedule} 600for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数600value: {{ $value }}- alert: kubernetes-schedule打开句柄数1000expr: process_open_fds{job~kubernetes-schedule} 1000for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数1000value: {{ $value }}- alert: kubernetes-controller-manager打开句柄数600expr: process_open_fds{job~kubernetes-controller-manager} 600for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数600value: {{ $value }}- alert: kubernetes-controller-manager打开句柄数1000expr: process_open_fds{job~kubernetes-controller-manager} 1000for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数1000value: {{ $value }}- alert: kubernetes-apiserver打开句柄数600expr: process_open_fds{job~kubernetes-apiserver} 600for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数600value: {{ $value }}- alert: kubernetes-apiserver打开句柄数1000expr: process_open_fds{job~kubernetes-apiserver} 1000for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数1000value: {{ $value }}- alert: kubernetes-etcd打开句柄数600expr: process_open_fds{job~kubernetes-etcd} 600for: 2slabels:severity: warnningannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数600value: {{ $value }}- alert: kubernetes-etcd打开句柄数1000expr: process_open_fds{job~kubernetes-etcd} 1000for: 2slabels:severity: criticalannotations:description: {{$labels.instance}}的{{$labels.job}}打开句柄数1000value: {{ $value }}- alert: corednsexpr: process_open_fds{k8s_app~kube-dns} 600for: 2slabels:severity: warnning annotations:description: 插件{{$labels.k8s_app}}({{$labels.instance}}): 打开句柄数超过600value: {{ $value }}- alert: corednsexpr: process_open_fds{k8s_app~kube-dns} 1000for: 2slabels:severity: criticalannotations:description: 插件{{$labels.k8s_app}}({{$labels.instance}}): 打开句柄数超过1000value: {{ $value }}- alert: kube-proxyexpr: process_virtual_memory_bytes{job~kubernetes-kube-proxy} 2000000000for: 2slabels:severity: warnningannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2Gvalue: {{ $value }}- alert: schedulerexpr: process_virtual_memory_bytes{job~kubernetes-schedule} 2000000000for: 2slabels:severity: warnningannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2Gvalue: {{ $value }}- alert: kubernetes-controller-managerexpr: process_virtual_memory_bytes{job~kubernetes-controller-manager} 2000000000for: 2slabels:severity: warnningannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2Gvalue: {{ $value }}- alert: kubernetes-apiserverexpr: process_virtual_memory_bytes{job~kubernetes-apiserver} 2000000000for: 2slabels:severity: warnningannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2Gvalue: {{ $value }}- alert: kubernetes-etcdexpr: process_virtual_memory_bytes{job~kubernetes-etcd} 2000000000for: 2slabels:severity: warnningannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2Gvalue: {{ $value }}- alert: kube-dnsexpr: process_virtual_memory_bytes{k8s_app~kube-dns} 2000000000for: 2slabels:severity: warnningannotations:description: 插件{{$labels.k8s_app}}({{$labels.instance}}): 使用虚拟内存超过2Gvalue: {{ $value }}- alert: HttpRequestsAvgexpr: sum(rate(rest_client_requests_total{job~kubernetes-kube-proxy|kubernetes-kubelet|kubernetes-schedule|kubernetes-control-manager|kubernetes-apiservers}[1m])) 1000for: 2slabels:team: adminannotations:description: 组件{{$labels.job}}({{$labels.instance}}): TPS超过1000value: {{ $value }}threshold: 1000 - alert: Pod_restartsexpr: kube_pod_container_status_restarts_total{namespace~kube-system|default|monitor-sa} 0for: 2slabels:severity: warnningannotations:description: 在{{$labels.namespace}}名称空间下发现{{$labels.pod}}这个pod下的容器{{$labels.container}}被重启,这个监控指标是由{{$labels.instance}}采集的value: {{ $value }}threshold: 0- alert: Pod_waitingexpr: kube_pod_container_status_waiting_reason{namespace~kube-system|default} 1for: 2slabels:team: adminannotations:description: 空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.pod}}下的{{$labels.container}}启动异常等待中value: {{ $value }}threshold: 1 - alert: Pod_terminatedexpr: kube_pod_container_status_terminated_reason{namespace~kube-system|default|monitor-sa} 1for: 2slabels:team: adminannotations:description: 空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.pod}}下的{{$labels.container}}被删除value: {{ $value }}threshold: 1- alert: Etcd_leaderexpr: etcd_server_has_leader{jobkubernetes-etcd} 0for: 2slabels:team: adminannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 当前没有leadervalue: {{ $value }}threshold: 0- alert: Etcd_leader_changesexpr: rate(etcd_server_leader_changes_seen_total{jobkubernetes-etcd}[1m]) 0for: 2slabels:team: adminannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 当前leader已发生改变value: {{ $value }}threshold: 0- alert: Etcd_failedexpr: rate(etcd_server_proposals_failed_total{jobkubernetes-etcd}[1m]) 0for: 2slabels:team: adminannotations:description: 组件{{$labels.job}}({{$labels.instance}}): 服务失败value: {{ $value }}threshold: 0- alert: Etcd_db_total_sizeexpr: etcd_debugging_mvcc_db_total_size_in_bytes{jobkubernetes-etcd} 10000000000for: 2slabels:team: adminannotations:description: 组件{{$labels.job}}({{$labels.instance}})db空间超过10Gvalue: {{ $value }}threshold: 10G- alert: Endpoint_readyexpr: kube_endpoint_address_not_ready{namespace~kube-system|default} 1for: 2slabels:team: adminannotations:description: 空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.endpoint}}不可用value: {{ $value }}threshold: 1- name: 物理节点状态-监控告警rules:- alert: 物理节点cpu使用率expr: 100-avg(irate(node_cpu_seconds_total{modeidle}[5m])) by(instance)*100 90for: 2slabels:severity: ccriticalannotations:summary: {{ $labels.instance }}cpu使用率过高description: {{ $labels.instance }}的cpu使用率超过90%,当前使用率[{{ $value }}],需要排查处理 - alert: 物理节点内存使用率expr: (node_memory_MemTotal_bytes - (node_memory_MemFree_bytes node_memory_Buffers_bytes node_memory_Cached_bytes)) / node_memory_MemTotal_bytes * 100 90for: 2slabels:severity: criticalannotations:summary: {{ $labels.instance }}内存使用率过高description: {{ $labels.instance }}的内存使用率超过90%,当前使用率[{{ $value }}],需要排查处理- alert: InstanceDownexpr: up 0for: 2slabels:severity: criticalannotations: summary: {{ $labels.instance }}: 服务器宕机description: {{ $labels.instance }}: 服务器延时超过2分钟- alert: 物理节点磁盘的IO性能expr: 100-(avg(irate(node_disk_io_time_seconds_total[1m])) by(instance)* 100) 60for: 2slabels:severity: criticalannotations:summary: {{$labels.mountpoint}} 流入磁盘IO使用率过高description: {{$labels.mountpoint }} 流入磁盘IO大于60%(目前使用:{{$value}})- alert: 入网流量带宽expr: ((sum(rate (node_network_receive_bytes_total{device!~tap.*|veth.*|br.*|docker.*|virbr*|lo*}[5m])) by (instance)) / 100) 102400for: 2slabels:severity: criticalannotations:summary: {{$labels.mountpoint}} 流入网络带宽过高description: {{$labels.mountpoint }}流入网络带宽持续5分钟高于100M. RX带宽使用率{{$value}}- alert: 出网流量带宽expr: ((sum(rate (node_network_transmit_bytes_total{device!~tap.*|veth.*|br.*|docker.*|virbr*|lo*}[5m])) by (instance)) / 100) 102400for: 2slabels:severity: criticalannotations:summary: {{$labels.mountpoint}} 流出网络带宽过高description: {{$labels.mountpoint }}流出网络带宽持续5分钟高于100M. RX带宽使用率{{$value}}- alert: TCP会话expr: node_netstat_Tcp_CurrEstab 1000for: 2slabels:severity: criticalannotations:summary: {{$labels.mountpoint}} TCP_ESTABLISHED过高description: {{$labels.mountpoint }} TCP_ESTABLISHED大于1000%(目前使用:{{$value}}%)- alert: 磁盘容量expr: 100-(node_filesystem_free_bytes{fstype~ext4|xfs}/node_filesystem_size_bytes {fstype~ext4|xfs}*100) 80for: 2slabels:severity: criticalannotations:summary: {{$labels.mountpoint}} 磁盘分区使用率过高description: {{$labels.mountpoint }} 磁盘分区使用大于80%(目前使用:{{$value}}%)可以看到报警信息有critical和warning两种。这里面的指标都来自于Prometheus监控到的指标。
