k8s与监控--解读prometheus监控kubernetes的配置文件

简介: 前言 Prometheus 是一个开源和社区驱动的监控&报警&时序数据库的项目。来源于谷歌BorgMon项目。现在最常见的Kubernetes容器管理系统中,通常会搭配Prometheus进行监控。主要监控: Node:如主机CPU,内存,网络吞吐和带宽占用,磁盘I/O和磁盘使用等指标。

前言

Prometheus 是一个开源和社区驱动的监控&报警&时序数据库的项目。来源于谷歌BorgMon项目。现在最常见的Kubernetes容器管理系统中,通常会搭配Prometheus进行监控。主要监控:

  • Node:如主机CPU,内存,网络吞吐和带宽占用,磁盘I/O和磁盘使用等指标。node-exporter采集。
  • 容器关键指标:集群中容器的CPU详细状况,内 存详细状况,Network,FileSystem和Subcontainer等。通过cadvisor采集。
  • Kubernetes集群上部署的应用:监控部署在Kubernetes集群上的应用。主要是pod,service,ingress和endpoint。通过black-box和kube-apiserver的接口采集。

prometheus自身提供了一些资源的自动发现功能,下面是我从官方github上截图,罗列了目前提供的资源发现:

图片描述
由上图可知prometheus自身提供了自动发现kubernetes的监控目标的功能。相应,配置文件官方也提供了一份,今天我们就解读一下该配置文件。

配置文件解读

首先直接上官方的配置文件:

# A scrape configuration for running Prometheus on a Kubernetes cluster.
# This uses separate scrape configs for cluster components (i.e. API server, node)
# and services to allow each to use different authentication configs.
#
# Kubernetes labels will be added as Prometheus labels on metrics via the
# `labelmap` relabeling action.
#
# If you are using Kubernetes 1.7.2 or earlier, please take note of the comments
# for the kubernetes-cadvisor job; you will need to edit or remove this job.

# Scrape config for API servers.
#
# Kubernetes exposes API servers as endpoints to the default/kubernetes
# service so this uses `endpoints` role and uses relabelling to only keep
# the endpoints associated with the default/kubernetes service using the
# default named port `https`. This works for single API server deployments as
# well as HA API server deployments.
scrape_configs:
- job_name: 'kubernetes-apiservers'

 kubernetes_sd_configs:
 - role: endpoints

 # Default to scraping over https. If required, just disable this or change to
 # `http`.
 scheme: https

 # This TLS & bearer token file config is used to connect to the actual scrape
 # endpoints for cluster components. This is separate to discovery auth
 # configuration because discovery & scraping are two separate concerns in
 # Prometheus. The discovery auth config is automatic if Prometheus runs inside
 # the cluster. Otherwise, more config options have to be provided within the
 # <kubernetes_sd_config>.
 tls_config:
 ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
 # If your node certificates are self-signed or use a different CA to the
 # master CA, then disable certificate verification below. Note that
 # certificate verification is an integral part of a secure infrastructure
 # so this should only be disabled in a controlled environment. You can
 # disable certificate verification by uncommenting the line below.
 #
 # insecure_skip_verify: true
 bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

 # Keep only the default/kubernetes service endpoints for the https port. This
 # will add targets for each API server which Kubernetes adds an endpoint to
 # the default/kubernetes service.
 relabel_configs:
 - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
 action: keep
 regex: default;kubernetes;https

# Scrape config for nodes (kubelet).
#
# Rather than connecting directly to the node, the scrape is proxied though the
# Kubernetes apiserver. This means it will work if Prometheus is running out of
# cluster, or can't connect to nodes for some other reason (e.g. because of
# firewalling).
- job_name: 'kubernetes-nodes'

 # Default to scraping over https. If required, just disable this or change to
 # `http`.
 scheme: https

 # This TLS & bearer token file config is used to connect to the actual scrape
 # endpoints for cluster components. This is separate to discovery auth
 # configuration because discovery & scraping are two separate concerns in
 # Prometheus. The discovery auth config is automatic if Prometheus runs inside
 # the cluster. Otherwise, more config options have to be provided within the
 # <kubernetes_sd_config>.
 tls_config:
 ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
 bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

 kubernetes_sd_configs:
 - role: node

 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

# Scrape config for Kubelet cAdvisor.
#
# This is required for Kubernetes 1.7.3 and later, where cAdvisor metrics
# (those whose names begin with 'container_') have been removed from the
# Kubelet metrics endpoint. This job scrapes the cAdvisor endpoint to
# retrieve those metrics.
#
# In Kubernetes 1.7.0-1.7.2, these metrics are only exposed on the cAdvisor
# HTTP endpoint; use "replacement: /api/v1/nodes/${1}:4194/proxy/metrics"
# in that case (and ensure cAdvisor's HTTP server hasn't been disabled with
# the --cadvisor-port=0 Kubelet flag).
#
# This job is not necessary and should be removed in Kubernetes 1.6 and
# earlier versions, or it will cause the metrics to be scraped twice.
- job_name: 'kubernetes-cadvisor'

 # Default to scraping over https. If required, just disable this or change to
 # `http`.
 scheme: https

 # This TLS & bearer token file config is used to connect to the actual scrape
 # endpoints for cluster components. This is separate to discovery auth
 # configuration because discovery & scraping are two separate concerns in
 # Prometheus. The discovery auth config is automatic if Prometheus runs inside
 # the cluster. Otherwise, more config options have to be provided within the
 # <kubernetes_sd_config>.
 tls_config:
 ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
 bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

 kubernetes_sd_configs:
 - role: node

 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

# Scrape config for service endpoints.
#
# The relabeling allows the actual service scrape endpoint to be configured
# via the following annotations:
#
# * `prometheus.io/scrape`: Only scrape services that have a value of `true`
# * `prometheus.io/scheme`: If the metrics endpoint is secured then you will need
# to set this to `https` & most likely set the `tls_config` of the scrape config.
# * `prometheus.io/path`: If the metrics path is not `/metrics` override this.
# * `prometheus.io/port`: If the metrics are exposed on a different port to the
# service then set this appropriately.
- 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

# Example scrape config for probing services via the Blackbox Exporter.
#
# The relabeling allows the actual service scrape endpoint to be configured
# via the following annotations:
#
# * `prometheus.io/probe`: Only probe services that have a value of `true`
- job_name: 'kubernetes-services'

 metrics_path: /probe
 params:
 module: [http_2xx]

 kubernetes_sd_configs:
 - role: service

 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

# Example scrape config for probing ingresses via the Blackbox Exporter.
#
# The relabeling allows the actual ingress scrape endpoint to be configured
# via the following annotations:
#
# * `prometheus.io/probe`: Only probe services that have a value of `true`
- job_name: 'kubernetes-ingresses'

 metrics_path: /probe
 params:
 module: [http_2xx]

 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

# Example scrape config for pods
#
# The relabeling allows the actual pod scrape endpoint to be configured via the
# following annotations:
#
# * `prometheus.io/scrape`: Only scrape pods that have a value of `true`
# * `prometheus.io/path`: If the metrics path is not `/metrics` override this.
# * `prometheus.io/port`: Scrape the pod on the indicated port instead of the
# pod's declared ports (default is a port-free target if none are declared).
- 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

当然该配置文件,是在prometheus部署在k8s中生效的,即in-cluster模式。

kubernetes-apiservers

该项主要是让prometheus程序可以访问kube-apiserver,进而进行服务发现。看一下服务发现的代码可以看出,主要服务发现:node,service,ingress,pod。

 switch d.role {
 case "endpoints":
 var wg sync.WaitGroup

 for _, namespace := range namespaces {
 elw := cache.NewListWatchFromClient(rclient, "endpoints", namespace, nil)
 slw := cache.NewListWatchFromClient(rclient, "services", namespace, nil)
 plw := cache.NewListWatchFromClient(rclient, "pods", namespace, nil)
 eps := NewEndpoints(
 log.With(d.logger, "role", "endpoint"),
 cache.NewSharedInformer(slw, &apiv1.Service{}, resyncPeriod),
 cache.NewSharedInformer(elw, &apiv1.Endpoints{}, resyncPeriod),
 cache.NewSharedInformer(plw, &apiv1.Pod{}, resyncPeriod),
 )
 go eps.endpointsInf.Run(ctx.Done())
 go eps.serviceInf.Run(ctx.Done())
 go eps.podInf.Run(ctx.Done())

 for !eps.serviceInf.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 for !eps.endpointsInf.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 for !eps.podInf.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 wg.Add(1)
 go func() {
 defer wg.Done()
 eps.Run(ctx, ch)
 }()
 }
 wg.Wait()
 case "pod":
 var wg sync.WaitGroup
 for _, namespace := range namespaces {
 plw := cache.NewListWatchFromClient(rclient, "pods", namespace, nil)
 pod := NewPod(
 log.With(d.logger, "role", "pod"),
 cache.NewSharedInformer(plw, &apiv1.Pod{}, resyncPeriod),
 )
 go pod.informer.Run(ctx.Done())

 for !pod.informer.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 wg.Add(1)
 go func() {
 defer wg.Done()
 pod.Run(ctx, ch)
 }()
 }
 wg.Wait()
 case "service":
 var wg sync.WaitGroup
 for _, namespace := range namespaces {
 slw := cache.NewListWatchFromClient(rclient, "services", namespace, nil)
 svc := NewService(
 log.With(d.logger, "role", "service"),
 cache.NewSharedInformer(slw, &apiv1.Service{}, resyncPeriod),
 )
 go svc.informer.Run(ctx.Done())

 for !svc.informer.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 wg.Add(1)
 go func() {
 defer wg.Done()
 svc.Run(ctx, ch)
 }()
 }
 wg.Wait()
 case "ingress":
 var wg sync.WaitGroup
 for _, namespace := range namespaces {
 ilw := cache.NewListWatchFromClient(reclient, "ingresses", namespace, nil)
 ingress := NewIngress(
 log.With(d.logger, "role", "ingress"),
 cache.NewSharedInformer(ilw, &extensionsv1beta1.Ingress{}, resyncPeriod),
 )
 go ingress.informer.Run(ctx.Done())

 for !ingress.informer.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 wg.Add(1)
 go func() {
 defer wg.Done()
 ingress.Run(ctx, ch)
 }()
 }
 wg.Wait()
 case "node":
 nlw := cache.NewListWatchFromClient(rclient, "nodes", api.NamespaceAll, nil)
 node := NewNode(
 log.With(d.logger, "role", "node"),
 cache.NewSharedInformer(nlw, &apiv1.Node{}, resyncPeriod),
 )
 go node.informer.Run(ctx.Done())

 for !node.informer.HasSynced() {
 time.Sleep(100 * time.Millisecond)
 }
 node.Run(ctx, ch)

 default:
 level.Error(d.logger).Log("msg", "unknown Kubernetes discovery kind", "role", d.role)
 } 

kubernetes-nodes

发现node以后,通过/api/v1/nodes/${1}/proxy/metrics来获取node的metrics。

kubernetes-cadvisor

cadvisor已经被集成在kubelet中,所以发现了node就相当于发现了cadvisor。通过 /api/v1/nodes/${1}/proxy/metrics/cadvisor采集容器指标。

kubernetes-services和kubernetes-ingresses

该两种资源监控方式差不多,都是需要安装black-box,然后类似于探针去定时访问,根据返回的http状态码来判定service和ingress的服务可用性。
PS:不过我自己在这里和官方的稍微有点区别,

- target_label: __address__ replacement: blackbox-exporter.example.com:9115

官方大致是需要我们要创建black-box 的ingress从外部访问,这样从效率和安全性都不是最合适的。所以我一般都是直接内部dns访问。如下

- target_label: __address__
 replacement: blackbox-exporter.kube-system:9115

当然看源码可以发现,并不是所有的service和ingress都会健康监测,如果需要将服务进行健康监测,那么你部署应用的yaml文件加一些注解。例如:
对于service和ingress:
需要加注解:prometheus.io/scrape: 'true'

apiVersion: v1 kind: Service metadata: annotations: prometheus.io/scrape: 'true' name: prometheus-node-exporter namespace: kube-system labels: app: prometheus component: node-exporter spec: clusterIP: None ports: - name: prometheus-node-exporter port: 9100 protocol: TCP selector: app: prometheus component: node-exporter type: ClusterIP

kubernetes-pods

对于pod的监测也是需要加注解:

  • prometheus.io/scrape,为true则会将pod作为监控目标。
  • prometheus.io/path,默认为/metrics
  • prometheus.io/port , 端口

所以看到此处可以看出,该job并不是监控pod的指标,pod已经通过前面的cadvisor采集。此处是对pod中应用的监控。写过exporter的人应该对这个概念非常清楚。通俗讲,就是你pod中的应用提供了prometheus的监控功能,加上对应的注解,那么该应用的metrics会定时被采集走。

kubernetes-service-endpoints

对于服务的终端节点,也需要加注解:

  • prometheus.io/scrape,为true则会将pod作为监控目标。
  • prometheus.io/path,默认为/metrics
  • prometheus.io/port , 端口
  • prometheus.io/scheme 默认http,如果为了安全设置了https,此处需要改为https

这个基本上同上的。采集service-endpoints的metrics。

个人认为:如果某些部署应用只有pod没有service,那么这种情况只能在pod上加注解,通过kubernetes-pods采集metrics。如果有service,那么就无需在pod加注解了,直接在service上加即可。毕竟service-endpoints最终也会落到pod上。

总结

配置项总结

  • kubernetes-service-endpoints和kubernetes-pods采集应用中metrics,当然并不是所有的都提供了metrics接口。
  • kubernetes-ingresses 和kubernetes-services 健康监测服务和ingress健康的状态
  • kubernetes-cadvisor 和 kubernetes-nodes,通过发现node,监控node 和容器的cpu等指标

自动发现源码

参考client-go和prometheus自动发现k8s,这种监听k8s集群中资源的变化,使用informer实现,不要轮询kube-apiserver接口。

本文转自SegmentFault-k8s与监控--解读prometheus监控kubernetes的配置文件

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