微信公众号：运维开发故事，作者：华仔

背景

之前给大家介绍了victoriametrics以及安装中的一些注意事项，今天来给大家实操一下，如何在k8s中进行安装。本次是基于云上的k8s上安装一个cluster版本的victoriametrics，需要使用到云上的负载均衡。

注：victoriametrics后续简称vm

安装准备

  • 一个k8s集群，我的k8s版本是v1.20.6

  • 在集群上准备好一个storageclass，我这里用的NFS来做的

  • operator镜像tag为v0.17.2，vmstorage、vmselect和vminsert镜像tag为v1.63.0。可提前拉取镜像保存到本地镜像仓库

安装须知

vm可以通过多种方式安装，如二进制、docker镜像以及源码。可根据场景进行选择。如果在k8s中进行安装，我们可以直接使用operator来进行安装。下面重点说一下安装过程中的一些注意事项。

  1. 一个最小的集群必须包含以下节点：

    ● 一个vmstorage单节点，另外要指定-retentionPeriod和-storageDataPath两个参数

    ● 一个vminsert单节点，要指定-storageNode=<vmstorage_host>

    ● 一个vmselect单节点，要指定-storageNode=<vmstorage_host>

    注：高可用情况下，建议每个服务至少有个两个节点

  2. 在vmselect和vminsert前面需要一个负载均衡，比如vmauth、nginx。这里我们使用云上的负载均衡。同时要求：

    ● 以/insert开头的请求必须要被路由到vminsert节点的8480端口

    ● 以/select开头的请求必须要被路由到vmselect节点的8481端口

    注：各服务的端口可以通过-httpListenAddr进行指定

  3. 建议为集群安装监控

  4. 如果是在一个主机上进行安装测试集群，vminsert、vmselect和vmstorage各自的-httpListenAddr参数必须唯一，vmstorage的-storageDataPath、-vminsertAddr、-vmselectAddr这几个参数必须有唯一的值。

  5. 当vmstorage通过-storageDataPath目录大小小于通过-storage.minFreeDiskSpaceBytes指定的可用空间时，会切换到只读模式；vminsert停止像这类节点发送数据，转而将数据发送到其他可用vmstorage节点

安装过程

安装vm

1、创建crd

# 下载安装文件
export VM_VERSION=`basename $(curl -fs -o/dev/null -w %{redirect_url} https://github.com/VictoriaMetrics/operator/releases/latest)`
wget https://github.com/VictoriaMetrics/operator/releases/download/$VM_VERSION/bundle_crd.zip
unzip  bundle_crd.zip 
kubectl apply -f release/crds

# 检查crd
[root@test opt]# kubectl get crd  |grep vm
vmagents.operator.victoriametrics.com                2022-01-05T07:26:01Z
vmalertmanagerconfigs.operator.victoriametrics.com   2022-01-05T07:26:01Z
vmalertmanagers.operator.victoriametrics.com         2022-01-05T07:26:01Z
vmalerts.operator.victoriametrics.com                2022-01-05T07:26:01Z
vmauths.operator.victoriametrics.com                 2022-01-05T07:26:01Z
vmclusters.operator.victoriametrics.com              2022-01-05T07:26:01Z
vmnodescrapes.operator.victoriametrics.com           2022-01-05T07:26:01Z
vmpodscrapes.operator.victoriametrics.com            2022-01-05T07:26:01Z
vmprobes.operator.victoriametrics.com                2022-01-05T07:26:01Z
vmrules.operator.victoriametrics.com                 2022-01-05T07:26:01Z
vmservicescrapes.operator.victoriametrics.com        2022-01-05T07:26:01Z
vmsingles.operator.victoriametrics.com               2022-01-05T07:26:01Z
vmstaticscrapes.operator.victoriametrics.com         2022-01-05T07:26:01Z
vmusers.operator.victoriametrics.com                 2022-01-05T07:26:01Z

2、安装operator

# 安装operator。记得提前修改operator的镜像地址
kubectl apply -f release/operator/

# 安装后检查operator是否正常
[root@test opt]# kubectl get po -n monitoring-system
vm-operator-76dd8f7b84-gsbfs              1/1     Running   0          25h

3、安装vmcluster operator安装完成后，需要根据自己的需求去构建自己的的cr。我这里安装一个vmcluster。先看看vmcluster安装文件

# cat vmcluster-install.yaml
apiVersion: operator.victoriametrics.com/v1beta1
kind: VMCluster
metadata:
  name: vmcluster
  namespace: monitoring-system
spec:
  replicationFactor: 1
  retentionPeriod: "4"
  vminsert:
    image:
      pullPolicy: IfNotPresent
      repository: images.huazai.com/release/vminsert
      tag: v1.63.0
    podMetadata:
      labels:
        victoriaMetrics: vminsert
    replicaCount: 1
    resources:
      limits:
        cpu: "1"
        memory: 1000Mi
      requests:
        cpu: 500m
        memory: 500Mi
  vmselect:
    cacheMountPath: /select-cache
    image:
      pullPolicy: IfNotPresent
      repository: images.huazai.com/release/vmselect
      tag: v1.63.0
    podMetadata:
      labels:
        victoriaMetrics: vmselect
    replicaCount: 1
    resources:
      limits:
        cpu: "1"
        memory: 1000Mi
      requests:
        cpu: 500m
        memory: 500Mi
    storage:
      volumeClaimTemplate:
        spec:
          accessModes:
          - ReadWriteOnce
          resources:
            requests:
              storage: 2G
          storageClassName: nfs-csi
          volumeMode: Filesystem
  vmstorage:
    image:
      pullPolicy: IfNotPresent
      repository: images.huazai.com/release/vmstorage
      tag: v1.63.0
    podMetadata:
      labels:
        victoriaMetrics: vmstorage
    replicaCount: 1
    resources:
      limits:
        cpu: "1"
        memory: 1500Mi
      requests:
        cpu: 500m
        memory: 750Mi
    storage:
      volumeClaimTemplate:
        spec:
          accessModes:
          - ReadWriteOnce
          resources:
            requests:
              storage: 20G
          storageClassName: nfs-csi
          volumeMode: Filesystem
    storageDataPath: /vm-data
 
 # install vmcluster
 kubectl apply -f vmcluster-install.yaml
 
 # 检查vmcluster install结果
[root@test opt]# kubectl get po -n monitoring-system 
NAME                                      READY   STATUS    RESTARTS   AGE
vm-operator-76dd8f7b84-gsbfs              1/1     Running   0          26h
vminsert-vmcluster-main-69766c8f4-r795w   1/1     Running   0          25h
vmselect-vmcluster-main-0                 1/1     Running   0          25h
vmstorage-vmcluster-main-0                1/1     Running   0          25h

4、创建vminsert和vmselect service

# 查看创建的svc
[root@test opt]# kubectl get svc -n monitoring-system
NAME                            TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)                      AGE
vminsert-vmcluster-main         ClusterIP   10.0.182.73    <none>        8480/TCP                     25h
vmselect-vmcluster-main         ClusterIP   None           <none>        8481/TCP                     25h
vmstorage-vmcluster-main        ClusterIP   None           <none>        8482/TCP,8400/TCP,8401/TCP   25h

# 这里为了方便不同k8s集群的数据都可以存储到该vm来，同时方便后续查询数据，
# 重新创建两个svc，类型为nodeport，分别为vminsert-lbsvc和vmselect-lbsvc.同时配置云上的lb监听8480和8481端口，后端服务器为vm所在集群的节点ip，
# 端口为vminsert-lbsvc和vmsleect-lbsvc两个service暴露出来的nodeport
# 但与vm同k8s集群的比如opentelemetry需要存储数据时，仍然可以用：
# vminsert-vmcluster-main.kube-system.svc.cluster.local:8480
# 与vm不同k8s集群的如opentelemetry存储数据时使用lb:8480

# cat vminsert-lb-svc.yaml
apiVersion: v1
kind: Service
metadata:
  labels:
    app.kubernetes.io/component: monitoring
    app.kubernetes.io/instance: vmcluster-main
    app.kubernetes.io/name: vminsert
  name: vminsert-vmcluster-main-lbsvc
  namespace: monitoring-system
spec:
  externalTrafficPolicy: Cluster
  ports:
  - name: http
    nodePort: 30135
    port: 8480
    protocol: TCP
    targetPort: 8480
  selector:
    app.kubernetes.io/component: monitoring
    app.kubernetes.io/instance: vmcluster-main
    app.kubernetes.io/name: vminsert
  sessionAffinity: None
  type: NodePort
  
# cat vmselect-lb-svc.yaml
apiVersion: v1
kind: Service
metadata:
  labels:
    app.kubernetes.io/component: monitoring
    app.kubernetes.io/instance: vmcluster-main
    app.kubernetes.io/name: vmselect
  name: vmselect-vmcluster-main-lbsvc
  namespace: monitoring-system
spec:
  externalTrafficPolicy: Cluster
  ports:
  - name: http
    nodePort: 31140
    port: 8481
    protocol: TCP
    targetPort: 8481
  selector:
    app.kubernetes.io/component: monitoring
    app.kubernetes.io/instance: vmcluster-main
    app.kubernetes.io/name: vmselect
  sessionAffinity: None
  type: NodePort
 
 # 创建svc 
 kubectl apply -f vmselect-lb-svc.yaml 
 kubectl apply -f vminsert-lb-svc.yaml
 
 # ！！配置云上lb，
 自行配置
 
# 最后检查vm相关的pod和svc

[root@test opt]# kubectl get po,svc -n monitoring-system 
NAME                                          READY   STATUS    RESTARTS   AGE
pod/vm-operator-76dd8f7b84-gsbfs              1/1     Running   0          30h
pod/vminsert-vmcluster-main-69766c8f4-r795w   1/1     Running   0          29h
pod/vmselect-vmcluster-main-0                 1/1     Running   0          29h
pod/vmstorage-vmcluster-main-0                1/1     Running   0          29h

NAME                                    TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)                      AGE
service/vminsert-vmcluster-main         ClusterIP   10.0.182.73    <none>        8480/TCP                     29h
service/vminsert-vmcluster-main-lbsvc   NodePort    10.0.255.212   <none>        8480:30135/TCP               7h54m
service/vmselect-vmcluster-main         ClusterIP   None           <none>        8481/TCP                     29h
service/vmselect-vmcluster-main-lbsvc   NodePort    10.0.45.239    <none>        8481:31140/TCP               7h54m
service/vmstorage-vmcluster-main        ClusterIP   None           <none>        8482/TCP,8400/TCP,8401/TCP   29h
安装prometheus-expoter

这里还是来安装node exporter，暴露k8s节点数据，由后续的opentelemetry来采集，并通过vminsert存储到vmstorage。数据通过vmselect来进行查询

# kubectl apply -f prometheus-node-exporter-install.yaml
apiVersion: apps/v1
kind: DaemonSet
metadata:
  labels:
    app: prometheus-node-exporter
    release: prometheus-node-exporter
  name: prometheus-node-exporter
  namespace: kube-system
spec:
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: prometheus-node-exporter
      release: prometheus-node-exporter
  template:
    metadata:
      labels:
        app: prometheus-node-exporter
        release: prometheus-node-exporter
    spec:
      containers:
      - args:
        - --path.procfs=/host/proc
        - --path.sysfs=/host/sys
        - --path.rootfs=/host/root
        - --web.listen-address=$(HOST_IP):9100
        env:
        - name: HOST_IP
          value: 0.0.0.0
        image: images.huazai.com/release/node-exporter:v1.1.2
        imagePullPolicy: IfNotPresent
        livenessProbe:
          failureThreshold: 3
          httpGet:
            path: /
            port: 9100
            scheme: HTTP
          periodSeconds: 10
          successThreshold: 1
          timeoutSeconds: 1
        name: node-exporter
        ports:
        - containerPort: 9100
          hostPort: 9100
          name: metrics
          protocol: TCP
        readinessProbe:
          failureThreshold: 3
          httpGet:
            path: /
            port: 9100
            scheme: HTTP
          periodSeconds: 10
          successThreshold: 1
          timeoutSeconds: 1
        resources:
          limits:
            cpu: 200m
            memory: 50Mi
          requests:
            cpu: 100m
            memory: 30Mi
        terminationMessagePath: /dev/termination-log
        terminationMessagePolicy: File
        volumeMounts:
        - mountPath: /host/proc
          name: proc
          readOnly: true
        - mountPath: /host/sys
          name: sys
          readOnly: true
        - mountPath: /host/root
          mountPropagation: HostToContainer
          name: root
          readOnly: true
      dnsPolicy: ClusterFirst
      hostNetwork: true
      hostPID: true
      restartPolicy: Always
      schedulerName: default-scheduler
      securityContext:
        fsGroup: 65534
        runAsGroup: 65534
        runAsNonRoot: true
        runAsUser: 65534
      serviceAccount: prometheus-node-exporter
      serviceAccountName: prometheus-node-exporter
      terminationGracePeriodSeconds: 30
      tolerations:
      - effect: NoSchedule
        operator: Exists
      volumes:
      - hostPath:
          path: /proc
          type: ""
        name: proc
      - hostPath:
          path: /sys
          type: ""
        name: sys
      - hostPath:
          path: /
          type: ""
        name: root
  updateStrategy:
    rollingUpdate:
      maxUnavailable: 1
    type: RollingUpdate

# 检查node-exporter
[root@test ~]# kubectl get po -n kube-system  |grep prometheus
prometheus-node-exporter-89wjk                 1/1     Running   0          31h
prometheus-node-exporter-hj4gh                 1/1     Running   0          31h
prometheus-node-exporter-hxm8t                 1/1     Running   0          31h
prometheus-node-exporter-nhqp6                 1/1     Running   0          31h
安装opentelemetry

prometheus node exporter安装好之后，再来安装opentelemetry(以后有机会再介绍)

# opentelemetry 配置文件。定义数据的接收、处理、导出
# 1.receivers即从哪里获取数据
# 2.processors即对获取的数据的处理
# 3.exporters即将处理过的数据导出到哪里,本次数据通过vminsert最终写入到vmstorage
# kubectl apply -f opentelemetry-install-cm.yaml
apiVersion: v1
data:
  relay: |
    exporters:
      prometheusremotewrite:
        # 我这里配置lb_ip:8480，即vminsert地址
        endpoint: http://lb_ip:8480/insert/0/prometheus
        # 不同的集群添加不同的label，比如cluster: uat/prd
        external_labels:
          cluster: uat
    extensions:
      health_check: {}
    processors:
      batch: {}
      memory_limiter:
        ballast_size_mib: 819
        check_interval: 5s
        limit_mib: 1638
        spike_limit_mib: 512
    receivers:
      prometheus:
        config:
          scrape_configs:
          - job_name: opentelemetry-collector
            scrape_interval: 10s
            static_configs:
            - targets:
              - localhost:8888
...省略...
          - job_name: kube-state-metrics
            kubernetes_sd_configs:
            - namespaces:
                names:
                - kube-system
              role: service
            metric_relabel_configs:
            - regex: ReplicaSet;([\w|\-]+)\-[0-9|a-z]+
              replacement: $$1
              source_labels:
              - created_by_kind
              - created_by_name
              target_label: created_by_name
            - regex: ReplicaSet
              replacement: Deployment
              source_labels:
              - created_by_kind
              target_label: created_by_kind
            relabel_configs:
            - action: keep
              regex: kube-state-metrics
              source_labels:
              - __meta_kubernetes_service_name
          - job_name: node-exporter
            kubernetes_sd_configs:
            - namespaces:
                names:
                - kube-system
              role: endpoints
            relabel_configs:
            - action: keep
              regex: node-exporter
              source_labels:
              - __meta_kubernetes_service_name
            - source_labels:
              - __meta_kubernetes_pod_node_name
              target_label: node
            - source_labels:
              - __meta_kubernetes_pod_host_ip
              target_label: host_ip
   ...省略...
    service:
    # 上面定义的receivors、processors、exporters以及extensions需要在这里配置，不然不起作用
      extensions:
      - health_check
      pipelines:
        metrics:
          exporters:
          - prometheusremotewrite
          processors:
          - memory_limiter
          - batch
          receivers:
          - prometheus
kind: ConfigMap
metadata:
  annotations:
    meta.helm.sh/release-name: opentelemetry-collector-hua
    meta.helm.sh/release-namespace: kube-system
  labels:
    app.kubernetes.io/instance: opentelemetry-collector-hua
    app.kubernetes.io/name: opentelemetry-collector-hua
  name: opentelemetry-collector-hua
  namespace: kube-system


# 安装opentelemetry
# kubectl apply -f  opentelemetry-install.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app.kubernetes.io/instance: opentelemetry-collector-hua
    app.kubernetes.io/name: opentelemetry-collector-hua
  name: opentelemetry-collector-hua
  namespace: kube-system
spec:
  progressDeadlineSeconds: 600
  replicas: 1
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app.kubernetes.io/instance: opentelemetry-collector-hua
      app.kubernetes.io/name: opentelemetry-collector-hua
  strategy:
    rollingUpdate:
      maxSurge: 25%
      maxUnavailable: 25%
    type: RollingUpdate
  template:
    metadata:
      labels:
        app.kubernetes.io/instance: opentelemetry-collector-hua
        app.kubernetes.io/name: opentelemetry-collector-hua
    spec:
      containers:
      - command:
        - /otelcol
        - --config=/conf/relay.yaml
        - --metrics-addr=0.0.0.0:8888
        - --mem-ballast-size-mib=819
        env:
        - name: MY_POD_IP
          valueFrom:
            fieldRef:
              apiVersion: v1
              fieldPath: status.podIP
        image: images.huazai.com/release/opentelemetry-collector:0.27.0
        imagePullPolicy: IfNotPresent
        livenessProbe:
          failureThreshold: 3
          httpGet:
            path: /
            port: 13133
            scheme: HTTP
          periodSeconds: 10
          successThreshold: 1
          timeoutSeconds: 1
        name: opentelemetry-collector-hua
        ports:
        - containerPort: 4317
          name: otlp
          protocol: TCP
        readinessProbe:
          failureThreshold: 3
          httpGet:
            path: /
            port: 13133
            scheme: HTTP
          periodSeconds: 10
          successThreshold: 1
          timeoutSeconds: 1
        resources:
          limits:
            cpu: "1"
            memory: 2Gi
          requests:
            cpu: 500m
            memory: 1Gi
        volumeMounts:
        - mountPath: /conf
        # 上面创建的给oepntelnemetry用的configmap
          name: opentelemetry-collector-configmap-hua
        - mountPath: /etc/otel-collector/secrets/etcd-cert/
          name: etcd-tls
          readOnly: true
      dnsPolicy: ClusterFirst
      restartPolicy: Always
      schedulerName: default-scheduler
      securityContext: {}
      # sa这里自行创建吧
      serviceAccount: opentelemetry-collector-hua
      serviceAccountName: opentelemetry-collector-hua
      terminationGracePeriodSeconds: 30
      volumes:
      - configMap:
          defaultMode: 420
          items:
          - key: relay
            path: relay.yaml
           # 上面创建的给oepntelnemetry用的configmap
          name: opentelemetry-collector-hua
        name: opentelemetry-collector-configmap-hua
      - name: etcd-tls
        secret:
          defaultMode: 420
          secretName: etcd-tls
          
 # 检查opentelemetry运行情况。如果opentelemetry与vm在同一个k8s集群，请写service那一套，不要使用lb(受制于云上
 # 4层监听器的后端服务器暂不能支持同时作为客户端和服务端)
 [root@kube-control-1 ~]# kubectl get po -n kube-system  |grep opentelemetry-collector-hua
opentelemetry-collector-hua-647c6c64c7-j6p4b   1/1     Running   0          8h

安装检查

所有的组件安装完成后，在浏览器输入http://lb:8481/select/0/vmui，然后在server url输入；http://lb:8481/select/0/prometheus。最后再输入对应的指标就可以查询数据了，左上角还可以开启自动刷新！图片

总结

整个安装过程还是比较简单的。一旦安装完成后，即可存储多个k8s集群的监控数据。vm是支持基于PromeQL的MetricsQL的，也能够作为grafana的数据源。想想之前需要手动在每个k8s集群单独安装prometheus，还要去配置存储，需要查询数据时，要单独打开每个集群的prometheus UI是不是显得稍微麻烦一点呢。如果你也觉得vm不错，动手试试看吧！

全文参考

  • https://github.com/VictoriaMetrics/VictoriaMetrics/tree/cluster

  • https://docs.victoriametrics.com/

  • https://opentelemetry.io/docs/

  • https://prometheus.io/docs/prometheus/latest/configuration/configuration/

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