Kubernetes高可用性监控：Thanos的部署

今天药忘吃喽~ 2022-12-04 01:27 324阅读 0赞

> **原文发表于[kubernetes中文社区][kubernetes]，为作者原创翻译 ，原文地址**
> 
> **更多kubernetes文章，请多关注[kubernetes中文社区][kubernetes]**

**目录**

介绍

对Prometheus高可用性的需求

实现

Thanos架构

Thanos包含以下组件：

重复数据删除

Thanos搭建

先决条件

组件部署

部署Prometheus中的ServiceAccount资源对象，分别创建Clusterrole和Clusterrolebinding

部署Prometheus配置文件configmap.yaml

部署prometheus-rules的configmap 这将创建我们的警报规则，该警报规则将中继到alertmanager进行交付

部署Prometheus的StatefulSet资源

部署Prometheus服务

部署Thanos Querier

部署Thanos Store Gateway

部署Thanos Ruler

部署Alertmanager

部署Kubestate指标

部署Node-Exporter Daemonset

部署Grafana

部署Ingress对象

结论

--------------------

# 介绍 #

## 对Prometheus高可用性的需求 ##

在过去的几个月中，Kubernetes的采用已经增长了很多倍，现在很明显，Kubernetes是容器编排的事实标准。

同时，监视是任何基础架构的重要方面。Prometheus被认为是监视容器应用和非容器应用的绝佳选择。我们应该确保监视系统具有高可用性和高度可扩展性，以适应不断增长的基础架构的需求，尤其是在Kubernetes的情况下。

因此，今天，我们将部署Prometheus集群，它不仅可以抵抗节点故障，而且还可以确保数据归档以备将来参考。我们的集群也具有很大的可扩展性，以至于我们可以在同一监控系统内跨越多个Kubernetes集群。

当前方案

大多数Prometheus部署都使用具备持久性存储的Pod，而Prometheus使用联邦进行扩展。但是，并非所有数据都可以使用联邦进行聚合，在添加其他服务器时，通常需要一种机制来管理Prometheus配置。

解决方案

Thanos旨在解决上述问题。在Thanos的帮助下，我们不仅可以扩展Prometheus实例，并能够消除重复数据，还可以将数据归档在GCS或S3等持久性存储中。

# 实现 #

## Thanos架构 ##

### ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70][] ###

## Thanos包含以下组件： ##

*  Thanos Sidecar：这是在Prometheus运行的主要组件。它读取并存储object store中的数据。此外，它管理Prometheus的配置和生命周期。为了区分每个Prometheus实例，Sidecar组件将外部标签注入Prometheus配置中。Sidecar组件能够在Prometheus服务器的PromQL接口上运行查询。Sidecar组件还侦听Thanos gRPC协议，并在gRPC查询和REST查询之间转换。
 *  Thanos Store：此组件在object store中的历史数据之上实现Store API。它主要充当API网关，因此不需要大量的本地磁盘空间。它在启动时加入Thanos集群，并公布它可以访问的数据。它会在本地磁盘上保留有关所有远程块的少量信息，并使它与object store保持同步。通常，在重新启动时可以安全地删除此数据，但会增加启动时间。
 *  Thanos Query：是个查询组件，负责侦听HTTP并将查询转换为Thanos gRPC格式。它汇总了来自不同来源的查询结果，并且可以从Sidecar和Store中读取数据。在高可用性设置中，它甚至可以对重复数据进行删除。

### 重复数据删除 ###

Prometheus是有状态的，不允许复制其数据库。这意味着通过运行多个Prometheus副本来增强高可用性并不是最佳选择。

简单的负载平衡将不起作用，例如，在发生崩溃后，副本可能已启动，但是查询此类副本将导致其关闭期间的间隙很小。你有第二个副本可能正在运行，但是又可能在另一时间关闭（例如，滚动重启），因此在这些副本上进行负载平衡将无法正常工作。

*  相反，Thanos Querier从两个副本中提取数据，并对这些信号进行重复数据删除，从而帮助Querier使用者填补了空白。
 *  Thanos Compact：是Thanos的压缩器组件，它采用Prometheus 2.0存储引擎的压缩过程，来阻止数据存储在object store中。通常，它以单例方式部署。 它还负责数据的向下采样(downsampling)-40小时后执行5m的向下采样，而10天后执行1h的向下采样。
 *  Thanos Ruler：它基本上与Prometheus的rules具有相同的作用。唯一的区别是它可以与Thanos组件进行通信。

# Thanos搭建 #

## 先决条件 ##

为了完全理解本教程，需要以下内容：

1.  Kubernetes的工作原理和熟练使用Kubectl
2.  Kubernetes集群至少有3个节点（在本演示中，使用GKE集群）
3.  实现Ingress Controller和Ingress对象（出于演示目的，使用Nginx Ingress Controller）。尽管这不是强制性的，但强烈建议你这样做以减少外部端点创建的数量。
4.  创建供Thanos组件访问object store的凭证（在本例中为GCS存储）
5.  创建2个GCS存储，并将其命名为prometheus-long-term和thanos-ruler
6.  创建一个角色为“ 存储对象管理员”的服务帐户
7.  将密钥文件下载保存为JSON格式，并将其命名为thanos-gcs-credentials.json
8.  使用secret创建kubernetes密钥 kubectl create secret generic thanos-gcs-credentials --from-file=thanos-gcs-credentials.json -n monitoring

## 组件部署 ##

### 部署Prometheus中的ServiceAccount资源对象，分别创建Clusterrole和Clusterrolebinding ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: monitoring
      namespace: monitoring
    ---
    apiVersion: rbac.authorization.k8s.io/v1beta1
    kind: ClusterRole
    metadata:
      name: monitoring
      namespace: monitoring
    rules:
    - apiGroups: [""]
      resources:
      - nodes
      - nodes/proxy
      - services
      - endpoints
      - pods
      verbs: ["get", "list", "watch"]
    - apiGroups: [""]
      resources:
      - configmaps
      verbs: ["get"]
    - nonResourceURLs: ["/metrics"]
      verbs: ["get"]
    ---
    apiVersion: rbac.authorization.k8s.io/v1beta1
    kind: ClusterRoleBinding
    metadata:
      name: monitoring
    subjects:
      - kind: ServiceAccount
        name: monitoring
        namespace: monitoring
    roleRef:
      kind: ClusterRole
      Name: monitoring
      apiGroup: rbac.authorization.k8s.io
    ---

上述清单创建监控命名空间和服务ServiceAccount。

### 部署Prometheus配置文件configmap.yaml ###

apiVersion: v1
    kind: ConfigMap
    metadata:
      name: prometheus-server-conf
      labels:
        name: prometheus-server-conf
      namespace: monitoring
    data:
      prometheus.yaml.tmpl: |-
        global:
          scrape_interval: 5s
          evaluation_interval: 5s
          external_labels:
            cluster: prometheus-ha
            # Each Prometheus has to have unique labels.
            replica: $(POD_NAME)
    
        rule_files:
          - /etc/prometheus/rules/*rules.yaml
    
        alerting:
    
          # We want our alerts to be deduplicated
          # from different replicas.
          alert_relabel_configs:
          - regex: replica
            action: labeldrop
    
          alertmanagers:
            - scheme: http
              path_prefix: /
              static_configs:
                - targets: ['alertmanager:9093']
    
        scrape_configs:
        - job_name: kubernetes-nodes-cadvisor
          scrape_interval: 10s
          scrape_timeout: 10s
          scheme: https
          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_(.+)
            # Only for Kubernetes ^1.7.3.
            # See: https://github.com/prometheus/prometheus/issues/2916
            - target_label: __address__
              replacement: kubernetes.default.svc:443
            - source_labels: [__meta_kubernetes_node_name]
              regex: (.+)
              target_label: __metrics_path__
              replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
          metric_relabel_configs:
            - action: replace
              source_labels: [id]
              regex: '^/machine\.slice/machine-rkt\\x2d([^\\]+)\\.+/([^/]+)\.service$'
              target_label: rkt_container_name
              replacement: '${2}-${1}'
            - action: replace
              source_labels: [id]
              regex: '^/system\.slice/(.+)\.service$'
              target_label: systemd_service_name
              replacement: '${1}'
    
        - job_name: 'kubernetes-pods'
          kubernetes_sd_configs:
            - role: pod
          relabel_configs:
            - 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
            - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
              action: keep
              regex: true
            - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scheme]
              action: replace
              target_label: __scheme__
              regex: (https?)
            - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
              action: replace
              target_label: __metrics_path__
              regex: (.+)
            - source_labels: [__address__, __meta_kubernetes_pod_prometheus_io_port]
              action: replace
              target_label: __address__
              regex: ([^:]+)(?::\d+)?;(\d+)
              replacement: $1:$2
    
    
        - job_name: 'kubernetes-apiservers'
          kubernetes_sd_configs:
            - role: endpoints
          scheme: https 
          tls_config:
            ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
          bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
          relabel_configs:
            - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
              action: keep
              regex: default;kubernetes;https
    
        - job_name: 'kubernetes-service-endpoints'
          kubernetes_sd_configs:
            - role: endpoints
          relabel_configs:
            - 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
            - 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

上面的Configmap创建Prometheus配置文件模板。Thanos sidecar组件将读取此配置文件模板，并将生成实际的配置文件，而该配置文件又将由在同一容器中运行的Prometheus容器使用。

在配置文件中添加external\_labels部分非常重要，以使Querier可以基于该部分对重复数据进行删除。

### 部署prometheus-rules的configmap 这将创建我们的警报规则，该警报规则将中继到alertmanager进行交付 ###

apiVersion: v1
    kind: ConfigMap
    metadata:
      name: prometheus-rules
      labels:
        name: prometheus-rules
      namespace: monitoring
    data:
      alert-rules.yaml: |-
        groups:
          - name: Deployment
            rules:
            - alert: Deployment at 0 Replicas
              annotations:
                summary: Deployment {
       {$labels.deployment}} in {
       {$labels.namespace}} is currently having no pods running
              expr: |
                sum(kube_deployment_status_replicas{pod_template_hash=""}) by (deployment,namespace)  < 1
              for: 1m
              labels:
                team: devops
    
            - alert: HPA Scaling Limited  
              annotations: 
                summary: HPA named {
       {$labels.hpa}} in {
       {$labels.namespace}} namespace has reached scaling limited state
              expr: | 
                (sum(kube_hpa_status_condition{condition="ScalingLimited",status="true"}) by (hpa,namespace)) == 1
              for: 1m
              labels: 
                team: devops
    
            - alert: HPA at MaxCapacity 
              annotations: 
                summary: HPA named {
       {$labels.hpa}} in {
       {$labels.namespace}} namespace is running at Max Capacity
              expr: | 
                ((sum(kube_hpa_spec_max_replicas) by (hpa,namespace)) - (sum(kube_hpa_status_current_replicas) by (hpa,namespace))) == 0
              for: 1m
              labels: 
                team: devops
    
          - name: Pods
            rules:
            - alert: Container restarted
              annotations:
                summary: Container named {
       {$labels.container}} in {
       {$labels.pod}} in {
       {$labels.namespace}} was restarted
              expr: |
                sum(increase(kube_pod_container_status_restarts_total{namespace!="kube-system",pod_template_hash=""}[1m])) by (pod,namespace,container) > 0
              for: 0m
              labels:
                team: dev
    
            - alert: High Memory Usage of Container 
              annotations: 
                summary: Container named {
       {$labels.container}} in {
       {$labels.pod}} in {
       {$labels.namespace}} is using more than 75% of Memory Limit
              expr: | 
                ((( sum(container_memory_usage_bytes{image!="",container_name!="POD", namespace!="kube-system"}) by (namespace,container_name,pod_name)  / sum(container_spec_memory_limit_bytes{image!="",container_name!="POD",namespace!="kube-system"}) by (namespace,container_name,pod_name) ) * 100 ) < +Inf ) > 75
              for: 5m
              labels: 
                team: dev
    
            - alert: High CPU Usage of Container 
              annotations: 
                summary: Container named {
       {$labels.container}} in {
       {$labels.pod}} in {
       {$labels.namespace}} is using more than 75% of CPU Limit
              expr: | 
                ((sum(irate(container_cpu_usage_seconds_total{image!="",container_name!="POD", namespace!="kube-system"}[30s])) by (namespace,container_name,pod_name) / sum(container_spec_cpu_quota{image!="",container_name!="POD", namespace!="kube-system"} / container_spec_cpu_period{image!="",container_name!="POD", namespace!="kube-system"}) by (namespace,container_name,pod_name) ) * 100)  > 75
              for: 5m
              labels: 
                team: dev
    
          - name: Nodes
            rules:
            - alert: High Node Memory Usage
              annotations:
                summary: Node {
       {$labels.kubernetes_io_hostname}} has more than 80% memory used. Plan Capcity
              expr: |
                (sum (container_memory_working_set_bytes{id="/",container_name!="POD"}) by (kubernetes_io_hostname) / sum (machine_memory_bytes{}) by (kubernetes_io_hostname) * 100) > 80
              for: 5m
              labels:
                team: devops
    
            - alert: High Node CPU Usage
              annotations:
                summary: Node {
       {$labels.kubernetes_io_hostname}} has more than 80% allocatable cpu used. Plan Capacity.
              expr: |
                (sum(rate(container_cpu_usage_seconds_total{id="/", container_name!="POD"}[1m])) by (kubernetes_io_hostname) / sum(machine_cpu_cores) by (kubernetes_io_hostname)  * 100) > 80
              for: 5m
              labels:
                team: devops
    
            - alert: High Node Disk Usage
              annotations:
                summary: Node {
       {$labels.kubernetes_io_hostname}} has more than 85% disk used. Plan Capacity.
              expr: |
                (sum(container_fs_usage_bytes{device=~"^/dev/[sv]d[a-z][1-9]$",id="/",container_name!="POD"}) by (kubernetes_io_hostname) / sum(container_fs_limit_bytes{container_name!="POD",device=~"^/dev/[sv]d[a-z][1-9]$",id="/"}) by (kubernetes_io_hostname)) * 100 > 85
              for: 5m
              labels:
                team: devops

### 部署Prometheus的StatefulSet资源 ###

apiVersion: storage.k8s.io/v1beta1
    kind: StorageClass
    metadata:
      name: fast
      namespace: monitoring
    provisioner: kubernetes.io/gce-pd
    allowVolumeExpansion: true
    ---
    apiVersion: apps/v1beta1
    kind: StatefulSet
    metadata:
      name: prometheus
      namespace: monitoring
    spec:
      replicas: 3
      serviceName: prometheus-service
      template:
        metadata:
          labels:
            app: prometheus
            thanos-store-api: "true"
        spec:
          serviceAccountName: monitoring
          containers:
            - name: prometheus
              image: prom/prometheus:v2.4.3
              args:
                - "--config.file=/etc/prometheus-shared/prometheus.yaml"
                - "--storage.tsdb.path=/prometheus/"
                - "--web.enable-lifecycle"
                - "--storage.tsdb.no-lockfile"
                - "--storage.tsdb.min-block-duration=2h"
                - "--storage.tsdb.max-block-duration=2h"
              ports:
                - name: prometheus
                  containerPort: 9090
              volumeMounts:
                - name: prometheus-storage
                  mountPath: /prometheus/
                - name: prometheus-config-shared
                  mountPath: /etc/prometheus-shared/
                - name: prometheus-rules
                  mountPath: /etc/prometheus/rules
            - name: thanos
              image: quay.io/thanos/thanos:v0.8.0
              args:
                - "sidecar"
                - "--log.level=debug"
                - "--tsdb.path=/prometheus"
                - "--prometheus.url=http://127.0.0.1:9090"
                - "--objstore.config={type: GCS, config: {bucket: prometheus-long-term}}"
                - "--reloader.config-file=/etc/prometheus/prometheus.yaml.tmpl"
                - "--reloader.config-envsubst-file=/etc/prometheus-shared/prometheus.yaml"
                - "--reloader.rule-dir=/etc/prometheus/rules/"
              env:
                - name: POD_NAME
                  valueFrom:
                    fieldRef:
                      fieldPath: metadata.name
                - name : GOOGLE_APPLICATION_CREDENTIALS
                  value: /etc/secret/thanos-gcs-credentials.json
              ports:
                - name: http-sidecar
                  containerPort: 10902
                - name: grpc
                  containerPort: 10901
              livenessProbe:
                  httpGet:
                    port: 10902
                    path: /-/healthy
              readinessProbe:
                httpGet:
                  port: 10902
                  path: /-/ready
              volumeMounts:
                - name: prometheus-storage
                  mountPath: /prometheus
                - name: prometheus-config-shared
                  mountPath: /etc/prometheus-shared/
                - name: prometheus-config
                  mountPath: /etc/prometheus
                - name: prometheus-rules
                  mountPath: /etc/prometheus/rules
                - name: thanos-gcs-credentials
                  mountPath: /etc/secret
                  readOnly: false
          securityContext:
            fsGroup: 2000
            runAsNonRoot: true
            runAsUser: 1000
          volumes:
            - name: prometheus-config
              configMap:
                defaultMode: 420
                name: prometheus-server-conf
            - name: prometheus-config-shared
              emptyDir: {}
            - name: prometheus-rules
              configMap:
                name: prometheus-rules
            - name: thanos-gcs-credentials
              secret:
                secretName: thanos-gcs-credentials
      volumeClaimTemplates:
      - metadata:
          name: prometheus-storage
          namespace: monitoring
        spec:
          accessModes: [ "ReadWriteOnce" ]
          storageClassName: fast
          resources:
            requests:
              storage: 20Gi

上面提供的清单，重要的是要了解以下几个方面：

1.  Prometheus部署为具有3个副本的StatefulSet，每个副本动态地配置自己的持久存储卷。
2.  Thanos sidecar容器使用我们在上面创建的模板文件，生成Prometheus配置信息。
3.  Thanos需要处理数据压缩，因此我们需要设置--storage.tsdb.min-block-duration = 2h和--storage.tsdb.max-block-duration = 2h
4.  PrometheusStatefulSet被打上thanos-store-api：true的标签， 因此每个headless 服务都会发现每个Pod，我们将在下面的Service资源中创建它。Thanos Querier将使用此headless服务来查询所有Prometheus实例中的数据。我们还将相同的标签(thanos-store-api：true)应用于Thanos Store和Thanos Ruler组件，以便Querier也会发现它们并将其用于查询指标。
5.  使用GOOGLE\_APPLICATION\_CREDENTIALS环境变量提供了GCS存储凭据路径。这个凭据是我们创建secret获得的。

### 部署Prometheus服务 ###

apiVersion: v1
    kind: Service
    metadata: 
      name: prometheus-0-service
      annotations: 
        prometheus.io/scrape: "true"
        prometheus.io/port: "9090"
      namespace: monitoring
      labels:
        name: prometheus
    spec:
      selector: 
        statefulset.kubernetes.io/pod-name: prometheus-0
      ports: 
        - name: prometheus 
          port: 8080
          targetPort: prometheus
    ---
    apiVersion: v1
    kind: Service
    metadata: 
      name: prometheus-1-service
      annotations: 
        prometheus.io/scrape: "true"
        prometheus.io/port: "9090"
      namespace: monitoring
      labels:
        name: prometheus
    spec:
      selector: 
        statefulset.kubernetes.io/pod-name: prometheus-1
      ports: 
        - name: prometheus 
          port: 8080
          targetPort: prometheus
    ---
    apiVersion: v1
    kind: Service
    metadata: 
      name: prometheus-2-service
      annotations: 
        prometheus.io/scrape: "true"
        prometheus.io/port: "9090"
      namespace: monitoring
      labels:
        name: prometheus
    spec:
      selector: 
        statefulset.kubernetes.io/pod-name: prometheus-2
      ports: 
        - name: prometheus 
          port: 8080
          targetPort: prometheus
    ---
    #This service creates a srv record for querier to find about store-api's
    apiVersion: v1
    kind: Service
    metadata:
      name: thanos-store-gateway
      namespace: monitoring
    spec:
      type: ClusterIP
      clusterIP: None
      ports:
        - name: grpc
          port: 10901
          targetPort: grpc
      selector:
        thanos-store-api: "true"

我们为StatefulSet中的每个Prometheus Pod创建了不同的服务，这不是必需的，这些仅用于调试目的。上面已经解释了headless服务名称为thanos-store-gateway的目的。稍后我们将使用ingress 对象暴露Prometheus服务。

### 部署Thanos Querier ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: thanos-querier
      namespace: monitoring
      labels:
        app: thanos-querier
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: thanos-querier
      template:
        metadata:
          labels:
            app: thanos-querier
        spec:
          containers:
          - name: thanos
            image: quay.io/thanos/thanos:v0.8.0
            args:
            - query
            - --log.level=debug
            - --query.replica-label=replica
            - --store=dnssrv+thanos-store-gateway:10901
            ports:
            - name: http
              containerPort: 10902
            - name: grpc
              containerPort: 10901
            livenessProbe:
              httpGet:
                port: http
                path: /-/healthy
            readinessProbe:
              httpGet:
                port: http
                path: /-/ready
    ---
    apiVersion: v1
    kind: Service
    metadata:
      labels:
        app: thanos-querier
      name: thanos-querier
      namespace: monitoring
    spec:
      ports:
      - port: 9090
        protocol: TCP
        targetPort: http
        name: http
      selector:
        app: thanos-querier

Thanos Querier是Thanos部署的主要组件之一。请注意以下几点：

1.  容器参数--store=dnssrv+thanos-store-gateway:10901有助于从度量标准数据中发现所有组件。
2.  thanos-querier服务提供了一个Web界面来运行PromQL查询。它还可以选择在多个Prometheus群集之间删除重复数据。
3.  Thanos Querier也是Grafana等所有仪表板的数据源。

### 部署Thanos Store Gateway ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: apps/v1beta1
    kind: StatefulSet
    metadata:
      name: thanos-store-gateway
      namespace: monitoring
      labels:
        app: thanos-store-gateway
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: thanos-store-gateway
      serviceName: thanos-store-gateway
      template:
        metadata:
          labels:
            app: thanos-store-gateway
            thanos-store-api: "true"
        spec:
          containers:
            - name: thanos
              image: quay.io/thanos/thanos:v0.8.0
              args:
              - "store"
              - "--log.level=debug"
              - "--data-dir=/data"
              - "--objstore.config={type: GCS, config: {bucket: prometheus-long-term}}"
              - "--index-cache-size=500MB"
              - "--chunk-pool-size=500MB"
              env:
                - name : GOOGLE_APPLICATION_CREDENTIALS
                  value: /etc/secret/thanos-gcs-credentials.json
              ports:
              - name: http
                containerPort: 10902
              - name: grpc
                containerPort: 10901
              livenessProbe:
                httpGet:
                  port: 10902
                  path: /-/healthy
              readinessProbe:
                httpGet:
                  port: 10902
                  path: /-/ready
              volumeMounts:
                - name: thanos-gcs-credentials
                  mountPath: /etc/secret
                  readOnly: false
          volumes:
            - name: thanos-gcs-credentials
              secret:
                secretName: thanos-gcs-credentials
    ---

这将创建存储组件，该组件存储服务从object store到Querier的指标信息。

### 部署Thanos Ruler ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: v1
    kind: ConfigMap
    metadata:
      name: thanos-ruler-rules
      namespace: monitoring
    data:
      alert_down_services.rules.yaml: |
        groups:
        - name: metamonitoring
          rules:
          - alert: PrometheusReplicaDown
            annotations:
              message: Prometheus replica in cluster {
       {$labels.cluster}} has disappeared from Prometheus target discovery.
            expr: |
              sum(up{cluster="prometheus-ha", instance=~".*:9090", job="kubernetes-service-endpoints"}) by (job,cluster) < 3
            for: 15s
            labels:
              severity: critical
    ---
    apiVersion: apps/v1beta1
    kind: StatefulSet
    metadata:
      labels:
        app: thanos-ruler
      name: thanos-ruler
      namespace: monitoring
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: thanos-ruler
      serviceName: thanos-ruler
      template:
        metadata:
          labels:
            app: thanos-ruler
            thanos-store-api: "true"
        spec:
          containers:
            - name: thanos
              image: quay.io/thanos/thanos:v0.8.0
              args:
                - rule
                - --log.level=debug
                - --data-dir=/data
                - --eval-interval=15s
                - --rule-file=/etc/thanos-ruler/*.rules.yaml
                - --alertmanagers.url=http://alertmanager:9093
                - --query=thanos-querier:9090
                - "--objstore.config={type: GCS, config: {bucket: thanos-ruler}}"
                - --label=ruler_cluster="prometheus-ha"
                - --label=replica="$(POD_NAME)"
              env:
                - name : GOOGLE_APPLICATION_CREDENTIALS
                  value: /etc/secret/thanos-gcs-credentials.json
                - name: POD_NAME
                  valueFrom:
                    fieldRef:
                      fieldPath: metadata.name
              ports:
                - name: http
                  containerPort: 10902
                - name: grpc
                  containerPort: 10901
              livenessProbe:
                httpGet:
                  port: http
                  path: /-/healthy
              readinessProbe:
                httpGet:
                  port: http
                  path: /-/ready
              volumeMounts:
                - mountPath: /etc/thanos-ruler
                  name: config
                - name: thanos-gcs-credentials
                  mountPath: /etc/secret
                  readOnly: false
          volumes:
            - configMap:
                name: thanos-ruler-rules
              name: config
            - name: thanos-gcs-credentials
              secret:
                secretName: thanos-gcs-credentials
    ---
    apiVersion: v1
    kind: Service
    metadata:
      labels:
        app: thanos-ruler
      name: thanos-ruler
      namespace: monitoring
    spec:
      ports:
        - port: 9090
          protocol: TCP
          targetPort: http
          name: http
      selector:
        app: thanos-ruler

现在，在与我们的工作负载相同的名称空间中的输入以下命令，能够查看到thanos-store-gateway对应有哪些Pod ：

root@my-shell-95cb5df57-4q6w8:/# nslookup thanos-store-gateway
    Server:     10.63.240.10
    Address:    10.63.240.10#53
    
    Name:   thanos-store-gateway.monitoring.svc.cluster.local
    Address: 10.60.25.2
    Name:   thanos-store-gateway.monitoring.svc.cluster.local
    Address: 10.60.25.4
    Name:   thanos-store-gateway.monitoring.svc.cluster.local
    Address: 10.60.30.2
    Name:   thanos-store-gateway.monitoring.svc.cluster.local
    Address: 10.60.30.8
    Name:   thanos-store-gateway.monitoring.svc.cluster.local
    Address: 10.60.31.2
    
    root@my-shell-95cb5df57-4q6w8:/# exit

上面返回的IP对应于我们的Prometheus中的Pod（thanos-store和thanos-ruler）。

可以通过以下命令验证

$ kubectl get pods -o wide -l thanos-store-api="true"
    NAME                     READY   STATUS    RESTARTS   AGE    IP           NODE                              NOMINATED NODE   READINESS GATES
    prometheus-0             2/2     Running   0          100m   10.60.31.2   gke-demo-1-pool-1-649cbe02-jdnv   <none>           <none>
    prometheus-1             2/2     Running   0          14h    10.60.30.2   gke-demo-1-pool-1-7533d618-kxkd   <none>           <none>
    prometheus-2             2/2     Running   0          31h    10.60.25.2   gke-demo-1-pool-1-4e9889dd-27gc   <none>           <none>
    thanos-ruler-0           1/1     Running   0          100m   10.60.30.8   gke-demo-1-pool-1-7533d618-kxkd   <none>           <none>
    thanos-store-gateway-0   1/1     Running   0          14h    10.60.25.4   gke-demo-1-pool-1-4e9889dd-27gc   <none>           <none>

### 部署Alertmanager ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    kind: ConfigMap
    apiVersion: v1
    metadata:
      name: alertmanager
      namespace: monitoring
    data:
      config.yml: |-
        global:
          resolve_timeout: 5m
          slack_api_url: "<your_slack_hook>"
          victorops_api_url: "<your_victorops_hook>"
    
        templates:
        - '/etc/alertmanager-templates/*.tmpl'
        route:
          group_by: ['alertname', 'cluster', 'service']
          group_wait: 10s
          group_interval: 1m
          repeat_interval: 5m  
          receiver: default 
          routes:
          - match:
              team: devops
            receiver: devops
            continue: true 
          - match: 
              team: dev
            receiver: dev
            continue: true
    
        receivers:
        - name: 'default'
    
        - name: 'devops'
          victorops_configs:
          - api_key: '<YOUR_API_KEY>'
            routing_key: 'devops'
            message_type: 'CRITICAL'
            entity_display_name: '{
       { .CommonLabels.alertname }}'
            state_message: 'Alert: {
       { .CommonLabels.alertname }}. Summary:{
       { .CommonAnnotations.summary }}. RawData: {
       { .CommonLabels }}'
          slack_configs:
          - channel: '#k8-alerts'
            send_resolved: true
    
    
        - name: 'dev'
          victorops_configs:
          - api_key: '<YOUR_API_KEY>'
            routing_key: 'dev'
            message_type: 'CRITICAL'
            entity_display_name: '{
       { .CommonLabels.alertname }}'
            state_message: 'Alert: {
       { .CommonLabels.alertname }}. Summary:{
       { .CommonAnnotations.summary }}. RawData: {
       { .CommonLabels }}'
          slack_configs:
          - channel: '#k8-alerts'
            send_resolved: true
    
    ---
    apiVersion: extensions/v1beta1
    kind: Deployment
    metadata:
      name: alertmanager
      namespace: monitoring
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: alertmanager
      template:
        metadata:
          name: alertmanager
          labels:
            app: alertmanager
        spec:
          containers:
          - name: alertmanager
            image: prom/alertmanager:v0.15.3
            args:
              - '--config.file=/etc/alertmanager/config.yml'
              - '--storage.path=/alertmanager'
            ports:
            - name: alertmanager
              containerPort: 9093
            volumeMounts:
            - name: config-volume
              mountPath: /etc/alertmanager
            - name: alertmanager
              mountPath: /alertmanager
          volumes:
          - name: config-volume
            configMap:
              name: alertmanager
          - name: alertmanager
            emptyDir: {}
    ---
    apiVersion: v1
    kind: Service
    metadata:
      annotations:
        prometheus.io/scrape: 'true'
        prometheus.io/path: '/metrics'
      labels:
        name: alertmanager
      name: alertmanager
      namespace: monitoring
    spec:
      selector:
        app: alertmanager
      ports:
      - name: alertmanager
        protocol: TCP
        port: 9093
        targetPort: 9093

alertmanager将根据Prometheus规则生成所有的警报。

### 部署Kubestate指标 ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: rbac.authorization.k8s.io/v1 
    # kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
    kind: ClusterRoleBinding
    metadata:
      name: kube-state-metrics
    roleRef:
      apiGroup: rbac.authorization.k8s.io
      kind: ClusterRole
      name: kube-state-metrics
    subjects:
    - kind: ServiceAccount
      name: kube-state-metrics
      namespace: monitoring
    ---
    apiVersion: rbac.authorization.k8s.io/v1
    # kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
    kind: ClusterRole
    metadata:
      name: kube-state-metrics
    rules:
    - apiGroups: [""]
      resources:
      - configmaps
      - secrets
      - nodes
      - pods
      - services
      - resourcequotas
      - replicationcontrollers
      - limitranges
      - persistentvolumeclaims
      - persistentvolumes
      - namespaces
      - endpoints
      verbs: ["list", "watch"]
    - apiGroups: ["extensions"]
      resources:
      - daemonsets
      - deployments
      - replicasets
      verbs: ["list", "watch"]
    - apiGroups: ["apps"]
      resources:
      - statefulsets
      verbs: ["list", "watch"]
    - apiGroups: ["batch"]
      resources:
      - cronjobs
      - jobs
      verbs: ["list", "watch"]
    - apiGroups: ["autoscaling"]
      resources:
      - horizontalpodautoscalers
      verbs: ["list", "watch"]
    ---
    apiVersion: rbac.authorization.k8s.io/v1
    # kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
    kind: RoleBinding
    metadata:
      name: kube-state-metrics
      namespace: monitoring
    roleRef:
      apiGroup: rbac.authorization.k8s.io
      kind: Role
      name: kube-state-metrics-resizer
    subjects:
    - kind: ServiceAccount
      name: kube-state-metrics
      namespace: monitoring
    ---
    apiVersion: rbac.authorization.k8s.io/v1
    # kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
    kind: Role
    metadata:
      namespace: monitoring
      name: kube-state-metrics-resizer
    rules:
    - apiGroups: [""]
      resources:
      - pods
      verbs: ["get"]
    - apiGroups: ["extensions"]
      resources:
      - deployments
      resourceNames: ["kube-state-metrics"]
      verbs: ["get", "update"]
    ---
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: kube-state-metrics
      namespace: monitoring
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: kube-state-metrics
      namespace: monitoring
    spec:
      selector:
        matchLabels:
          k8s-app: kube-state-metrics
      replicas: 1
      template:
        metadata:
          labels:
            k8s-app: kube-state-metrics
        spec:
          serviceAccountName: kube-state-metrics
          containers:
          - name: kube-state-metrics
            image: quay.io/mxinden/kube-state-metrics:v1.4.0-gzip.3
            ports:
            - name: http-metrics
              containerPort: 8080
            - name: telemetry
              containerPort: 8081
            readinessProbe:
              httpGet:
                path: /healthz
                port: 8080
              initialDelaySeconds: 5
              timeoutSeconds: 5
          - name: addon-resizer
            image: k8s.gcr.io/addon-resizer:1.8.3
            resources:
              limits:
                cpu: 150m
                memory: 50Mi
              requests:
                cpu: 150m
                memory: 50Mi
            env:
              - name: MY_POD_NAME
                valueFrom:
                  fieldRef:
                    fieldPath: metadata.name
              - name: MY_POD_NAMESPACE
                valueFrom:
                  fieldRef:
                    fieldPath: metadata.namespace
            command:
              - /pod_nanny
              - --container=kube-state-metrics
              - --cpu=100m
              - --extra-cpu=1m
              - --memory=100Mi
              - --extra-memory=2Mi
              - --threshold=5
              - --deployment=kube-state-metrics
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: kube-state-metrics
      namespace: monitoring
      labels:
        k8s-app: kube-state-metrics
      annotations:
        prometheus.io/scrape: 'true'
    spec:
      ports:
      - name: http-metrics
        port: 8080
        targetPort: http-metrics
        protocol: TCP
      - name: telemetry
        port: 8081
        targetPort: telemetry
        protocol: TCP
      selector:
        k8s-app: kube-state-metrics

需要使用Kubestate指标来中继一些重要的容器指标，这些指标不是kubelet本身公开的，因此不能直接用于Prometheus。

### 部署Node-Exporter Daemonset ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: extensions/v1beta1
    kind: DaemonSet
    metadata:
      name: node-exporter
      namespace: monitoring
      labels:
        name: node-exporter
    spec:
      template:
        metadata:
          labels:
            name: node-exporter
          annotations:
             prometheus.io/scrape: "true"
             prometheus.io/port: "9100"
        spec:
          hostPID: true
          hostIPC: true
          hostNetwork: true
          containers:
            - name: node-exporter
              image: prom/node-exporter:v0.16.0
              securityContext:
                privileged: true
              args:
                - --path.procfs=/host/proc
                - --path.sysfs=/host/sys
              ports:
                - containerPort: 9100
                  protocol: TCP
              resources:
                limits:
                  cpu: 100m
                  memory: 100Mi
                requests:
                  cpu: 10m
                  memory: 100Mi
              volumeMounts:
                - name: dev
                  mountPath: /host/dev
                - name: proc
                  mountPath: /host/proc
                - name: sys
                  mountPath: /host/sys
                - name: rootfs
                  mountPath: /rootfs
          volumes:
            - name: proc
              hostPath:
                path: /proc
            - name: dev
              hostPath:
                path: /dev
            - name: sys
              hostPath:
                path: /sys
            - name: rootfs
              hostPath:
                path: /

Node-Exporter是Daemonset资源，它在每个节点上运行一个pod -exporter的容器，并公开非常重要的与节点相关的度量标准，这些度量标准可以由Prometheus实例提取。

### 部署Grafana ###

apiVersion: v1
    kind: Namespace
    metadata:
      name: monitoring
    ---
    apiVersion: storage.k8s.io/v1beta1
    kind: StorageClass
    metadata:
      name: fast
      namespace: monitoring
    provisioner: kubernetes.io/gce-pd
    allowVolumeExpansion: true
    ---
    apiVersion: apps/v1beta1
    kind: StatefulSet
    metadata:
      name: grafana
      namespace: monitoring
    spec:
      replicas: 1
      serviceName: grafana
      template:
        metadata:
          labels:
            task: monitoring
            k8s-app: grafana
        spec:
          containers:
          - name: grafana
            image: k8s.gcr.io/heapster-grafana-amd64:v5.0.4
            ports:
            - containerPort: 3000
              protocol: TCP
            volumeMounts:
            - mountPath: /etc/ssl/certs
              name: ca-certificates
              readOnly: true
            - mountPath: /var
              name: grafana-storage
            env:
            - name: GF_SERVER_HTTP_PORT
              value: "3000"
              # The following env variables are required to make Grafana accessible via
              # the kubernetes api-server proxy. On production clusters, we recommend
              # removing these env variables, setup auth for grafana, and expose the grafana
              # service using a LoadBalancer or a public IP.
            - name: GF_AUTH_BASIC_ENABLED
              value: "false"
            - name: GF_AUTH_ANONYMOUS_ENABLED
              value: "true"
            - name: GF_AUTH_ANONYMOUS_ORG_ROLE
              value: Admin
            - name: GF_SERVER_ROOT_URL
              # If you're only using the API Server proxy, set this value instead:
              # value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
              value: /
          volumes:
          - name: ca-certificates
            hostPath:
              path: /etc/ssl/certs
      volumeClaimTemplates:
      - metadata:
          name: grafana-storage
          namespace: monitoring
        spec:
          accessModes: [ "ReadWriteOnce" ]
          storageClassName: fast
          resources:
            requests:
              storage: 5Gi
    ---
    apiVersion: v1
    kind: Service
    metadata:
      labels:
        kubernetes.io/cluster-service: 'true'
        kubernetes.io/name: grafana
      name: grafana
      namespace: monitoring
    spec:
      ports:
      - port: 3000
        targetPort: 3000
      selector:
        k8s-app: grafana

这将创建我们的Grafana的Deployment和Service资源对象，该Service将 通过我们的Ingress对象公开。

为了将Thanos-Querier添加为Grafana数据源。我们可以这样做：

1.  在Grafana单击Add DataSource
2.  名称：DS\_PROMETHEUS
3.  类型：Prometheus
4.  网址：[http://thanos-querier:9090][http_thanos-querier_9090]
5.  点击Save and Test。现在，你可以构建自定义仪表板，也可以直接从grafana.net导入仪表板。仪表盘＃315和＃1471是很好的开始。

### 部署Ingress对象 ###

apiVersion: extensions/v1beta1
    kind: Ingress
    metadata:
      name: monitoring-ingress
      namespace: monitoring
      annotations:
        kubernetes.io/ingress.class: "nginx"
    spec:
      rules:
      - host: grafana.<yourdomain>.com
        http:
          paths:
          - path: /
            backend:
              serviceName: grafana
              servicePort: 3000
      - host: prometheus-0.<yourdomain>.com
        http:
          paths:
          - path: /
            backend:
              serviceName: prometheus-0-service
              servicePort: 8080
      - host: prometheus-1.<yourdomain>.com
        http:
          paths:
          - path: /
            backend:
              serviceName: prometheus-1-service
              servicePort: 8080
      - host: prometheus-2.<yourdomain>.com
        http:
          paths:
          - path: /
            backend:
              serviceName: prometheus-2-service
              servicePort: 8080
      - host: alertmanager.<yourdomain>.com
        http: 
          paths:
          - path: /
            backend:
              serviceName: alertmanager
              servicePort: 9093
      - host: thanos-querier.<yourdomain>.com
        http:
          paths:
          - path: /
            backend:
              serviceName: thanos-querier
              servicePort: 9090
      - host: thanos-ruler.<yourdomain>.com
        http:
          paths:
          - path: /
            backend:
              serviceName: thanos-ruler
              servicePort: 9090

这将有助于在Kubernetes集群之外公开我们所有的服务。记得将<yourdomain>替换为你可以访问的域名，并且可以将Ingress-Controller的服务指向该域名。

现在，您应该可以在[http://thanos-querier][http_thanos-querier].<yourdomain>.com上访问Thanos Querier 。

它看起来像这样：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 1][]

可以选择“ deldupication“ 删除重复数据。

如果单击“ Stores ”，则可以看到thanos-store-gateway服务发现的所有活动端点

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 2][]

现在，您将Thanos Querier添加为Grafana中的数据源，并开始创建仪表板

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 3][]

Kubernetes集群监控仪表板

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 4][]

Kubernetes节点监控仪表板

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 5][]

## 结论 ##

将Thanos与Prometheus集成无疑提供了水平扩展Prometheus的能力，并且由于Thanos-Querier能够从其他查询器实例中提取指标，因此你实际上可以跨集群提取指标，从而在单个仪表板上可视化它们。

我们还能够将度量标准数据存档在object store中，该object store为我们的监视系统提供了无限的存储空间，并提供了来自object store本身的度量。

但是，要实现所有这些，你需要进行大量配置。上面提供的清单已在生产环境中进行了测试。如果你有任何疑问，请随时与我们联系。

译文连接：[https://dzone.com/articles/high-availability-kubernetes-monitoring-using-prom][https_dzone.com_articles_high-availability-kubernetes-monitoring-using-prom]

[kubernetes]: https://www.kubernetes.org.cn/
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70]: /images/20221123/6c27b33fb3694c4b88d244cf0c21bb1f.png
[http_thanos-querier_9090]: http://thanos-querier:9090/
[http_thanos-querier]: http://thanos-querier/
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 1]: /images/20221123/c06d7c3ec46c4a5585d26c985de2280d.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 2]: /images/20221123/4a1837b891f84e1599ed85dac654b3f3.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 3]: /images/20221123/15a2fef0c32d44d88782300193838860.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 4]: /images/20221123/77d34aba06e44d38b652396ea3d28cf9.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ZseTkxMDkwNQ_size_16_color_FFFFFF_t_70 5]: /images/20221123/e6f76b6ec91043f4b419c4163f0adcfe.png
[https_dzone.com_articles_high-availability-kubernetes-monitoring-using-prom]: https://dzone.com/articles/high-availability-kubernetes-monitoring-using-prom