k8s与监控--解读prometheus监控kubernetes的配置文件

摘要：前言是一个开源和社区驱动的监控报警时序数据库的项目。集群上部署的应用监控部署在集群上的应用。通过和的接口采集。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。对于服务的终端节点，也需要加注解，为则会将作为监控目标。

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：

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。

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
  # .
  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
  # .
  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
  # .
  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。

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)
    }   

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

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。

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

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。

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。

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

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。

该配置文件需要部署一些组件来支持prometheus对k8s的监控，例如black-exporter。因为要自动发现，获取集群的一些信息，所以也要做rbac的授权。具体参考：
github