【EFK】k8s部署ElasticSearch+Fluentd+Kibana进行日志收集

 一、为什么使用EFK

       
        EFK Stack为开发者提供了一套完整而灵活的日志管理系统。通过结合Elasticsearch的存储和搜索功能、Fluentd的采集和处理功能以及Kibana的展示和分析功能，开发者可以实现日志的收集、存储、搜索、分析和可视化。相比其他日志管理方案，EFK Stack在高性能和低资源消耗方面表现出色。特别是Fluentd和Filebeat等轻量级的日志收集工具，使得EFK Stack在资源有限或需要快速部署的场景中更具优势。  
 

• ElasticSearch：Elasticsearch是一个基于Lucene的分布式搜索和分析引擎，能够快速存储、搜索和分析大量数据。它适用于构建实时分析应用程序，并提供全文搜索、结构化搜索、分析以及分布式、多租户能力的功能。
• Fluentd：Fluentd是一个开源的数据收集器，能够从各种来源（如应用程序、服务器、消息队列等）实时地采集日志数据。它支持多种数据输入和输出的插件，可以轻松地集成到各种环境中。Fluentd在容器化环境中表现出色，特别是与Kubernetes等容器编排系统结合使用时。它能够自动发现和管理容器日志，确保日志数据的完整性和准确性。
• Kibana：Kibana是一个基于Elasticsearch的可视化分析平台，提供了丰富的图表和可视化功能。用户可以通过Kibana对日志数据进行搜索、分析和可视化，以便更好地理解应用程序的运行状态和日志信息。

 二、版本信息
 

Kubernetes版本：1.28.14
ElasticSearch版本：7.2.0
Fluentd版本：1.16
Kibana版本：7.2.0

 三、部署ES
 

       编写yaml创建ES的Service，使用有状态应用StatefulSet创建ES集群，使用NFS做PV，存储ES数据到PV中

#创建ES的Service
kind: Service
apiVersion: v1
metadata:
  name: elasticsearch
  namespace: k8s-logging
  labels:
    app: elasticsearch
spec:
  selector:
    app: elasticsearch
  clusterIP: None
  ports:
    - port: 9200
      name: rest
    - port: 9300
      name: inter-node
---
#使用statefulset部署ES
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: es-cluster
  namespace: k8s-logging
spec:
  serviceName: elasticsearch
  replicas: 2
  selector:
    matchLabels:
      app: elasticsearch
  template:
    metadata:
      labels:
        app: elasticsearch
    spec:
      tolerations:
      - key: "node-role.kubernetes.io/control-plane"
        operator: "Exists"
        effect: "NoSchedule"
      containers:
      - name: elasticsearch
        image: 192.168.119.150/k8s_repository/elasticsearch:7.2.0
        imagePullPolicy: IfNotPresent
        resources:
            limits:
              cpu: 1000m
            requests:
              cpu: 100m
        ports:
        - containerPort: 9200
          name: rest
          protocol: TCP
        - containerPort: 9300
          name: inter-node
          protocol: TCP
        volumeMounts:
        - name: esdata
          mountPath: /usr/share/elasticsearch/data
        env:
          - name: cluster.name
            value: k8s-logs
          - name: node.name
            valueFrom:
              fieldRef:
                fieldPath: metadata.name
          - name: discovery.seed_hosts
            value: "es-cluster-0.elasticsearch.k8s-logging.svc.cluster.local,es-cluster-1.elasticsearch.k8s-logging.svc.cluster.local"
          - name: cluster.initial_master_nodes
            value: "es-cluster-0,es-cluster-1"
          - name: ES_JAVA_OPTS
            value: "-Xms512m -Xmx512m"
          - name: TZ
            value: "Asia/Shanghai"
      initContainers:
      - name: fix-permissions
        image: 192.168.119.150/myrepo/busybox:stable-glibc
        imagePullPolicy: IfNotPresent
        command: ["sh", "-c", "chown -R 1000:1000 /usr/share/elasticsearch/data"]
        securityContext:
          privileged: true
        volumeMounts:
        - name: esdata
          mountPath: /usr/share/elasticsearch/data
      - name: increase-vm-max-map
        image: 192.168.119.150/myrepo/busybox:stable-glibc
        imagePullPolicy: IfNotPresent
        command: ["sysctl", "-w", "vm.max_map_count=262144"]
        securityContext:
          privileged: true
      - name: increase-fd-ulimit
        image: 192.168.119.150/myrepo/busybox:stable-glibc
        imagePullPolicy: IfNotPresent
        command: ["sh", "-c", "ulimit -n 65536"]
        securityContext:
          privileged: true
  volumeClaimTemplates:
  - metadata:
      name: esdata
    spec:
      accessModes: [ "ReadWriteOnce" ]
      resources:
        requests:
          storage: 1Gi

 

 三、部署kibana
 

     kibana是无状态应用，不需要存储数据，所以使用deployment部署kibana。同时创建kibana的Service和Ingress暴露服务

#部署kibana的service
apiVersion: v1
kind: Service
metadata:
  name: kibana
  namespace: k8s-logging
  labels:
    app: kibana
spec:
  type: NodePort
  ports:
  - port: 5601
  selector:
    app: kibana
---
#部署kibana的ingress
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: kibana-ingress
  namespace: k8s-logging
spec:
  ingressClassName: nginx
  rules:
  - host: www.mykibana.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: kibana
            port:
              number: 5601
---
#部署kibana的deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: k8s-logging
  labels:
    app: kibana
spec:
  replicas: 1
  selector:
    matchLabels:
      app: kibana
  template:
    metadata:
      labels:
        app: kibana
    spec:
      nodeSelector:
        node: master
      tolerations:
      - key: "node-role.kubernetes.io/control-plane"
        operator: "Exists"
        effect: "NoSchedule"
      containers:
      - name: kibana
        image: 192.168.119.150/k8s_repository/kibana:7.2.0
        imagePullPolicy: IfNotPresent
        resources:
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: ELASTICSEARCH_URL
            value: http://elasticsearch.k8s-logging.svc.cluster.local:9200
        ports:
        - containerPort: 5601
        volumeMounts:
        - name: tzdata
          mountPath: /etc/localtime
      volumes:
      - name: tzdata
        hostPath:
          path: /usr/share/zoneinfo/Asia/Shanghai

 

 四、部署fluentd
 

 首先创建fluentd的主配置文件

#编写fluentd的主配置文件的ConfigMap
apiVersion: v1
kind: ConfigMap
metadata:
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
  name: fluentd-es-config-main
  namespace: k8s-logging
data:
  fluent.conf: |-
    <match fluent.**>
    @type null
    </match>

    @include /fluentd/etc/config.d/*.conf

创建fluentd的子配置文件。在子配置文件中设置时间戳格式，并在子配置文件中定义使用kubernetes插件，根据日志中的pod信息查对应k8s信息，并在日志中增加k8s信息，并配置logstash格式输出

#编写fluentd的子配置文件的ConfigMap
apiVersion: v1
kind: ConfigMap
metadata:
  name: fluentd-config
  namespace: k8s-logging
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
data:
  containers.input.conf: |-
    <source>
      @id fluentd-containers.log
      @type tail
      path /var/log/containers/*.log
      pos_file /var/log/es-containers.log.pos
      time_format %Y-%m-%dT%H:%M:%S.%L%z #设置时间戳格式
      tag raw.kubernetes.*
      format json
      read_from_head false
    </source>
    <match raw.kubernetes.**>
      @id raw.kubernetes
      @type detect_exceptions
      remove_tag_prefix raw
      message log
      stream stream
      multiline_flush_interval 5
      max_bytes 500000
      max_lines 1000
    </match>
  output.conf: |-
    <filter kubernetes.**>
      @type kubernetes_metadata#使用kubernetes插件，在日志中增加k8s信息
    </filter>
    <match **>
      @id elasticsearch
      @type elasticsearch
      @log_level info
      include_tag_key true
      hosts es-cluster-0.elasticsearch:9200,es-cluster-1.elasticsearch:9200
      logstash_format true
      request_timeout    30s
      <buffer>
        @type file
        path /var/log/fluentd-buffers/kubernetes.system.buffer
        flush_mode interval
        retry_type exponential_backoff
        flush_thread_count 2
        flush_interval 5s
        retry_forever
        retry_max_interval 30
        chunk_limit_size 2M
        queue_limit_length 8
        overflow_action block
      </buffer>
    </match>  

fluentd会通过不断监听/var/log/container中的容器日志，传输日志到ES数据库中保存。我们使用DaemonSet部署fluentd，保证每个node都有fluentd收集日志。并创建RBAC，给fluentd pod查k8s数据的权限

apiVersion: v1
kind: ServiceAccount
metadata:
  name: fluentd-es
  namespace: k8s-logging
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: fluentd-es
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
  - ""
  resources:
  - "namespaces"
  - "pods"
  verbs:
  - "get"
  - "watch"
  - "list"
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: fluentd-es
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
  name: fluentd-es
  namespace: k8s-logging
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: fluentd-es
  apiGroup: ""
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: fluentd-es
  namespace: k8s-logging
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
    k8s-app: fluentd-es
spec:
  selector:
    matchLabels:
      k8s-app: fluentd-es
  template:
    metadata:
      labels:
        k8s-app: fluentd-es
    spec:
      securityContext: {}
      serviceAccount: fluentd-es
      serviceAccountName: fluentd-es
      tolerations:
      - key: "node-role.kubernetes.io/control-plane"
        operator: "Exists"
        effect: "NoSchedule"      
      containers:
      - name: fluentd
        image: 192.168.119.150/k8s_repository/fluentd-kubernetes-daemonset:v1.16
        imagePullPolicy: IfNotPresent
        env:
          - name:  FLUENT_ELASTICSEARCH_HOST
            value: "elasticsearch.k8s-logging.svc.cluster.local"
          - name:  FLUENT_ELASTICSEARCH_PORT
            value: "9200"
          - name: FLUENT_ELASTICSEARCH_SCHEME
            value: "http"
          - name: FLUENTD_SYSTEMD_CONF
            value: "disable"
          - name: TZ
            value: "Asia/Shanghai"
          - name: FLUENT_CONTAINER_TAIL_PARSER_TYPE
            value: "cri"
          - name: FLUENT_CONTAINER_TAIL_PARSER_TIME_FORMAT
            value: "%Y-%m-%dT%H:%M:%S.%L%z"
        resources:
          limits:
            memory: 512Mi
          requests:
            cpu: 100m
            memory: 200Mi
        volumeMounts:
        - name: varlog
          mountPath: /var/log
        - name: varlibdockercontainers
          mountPath: /var/lib/docker/containers
          readOnly: true
        - name: config-volume
          mountPath: /fluentd/etc/config.d
        - name: config-volume-main
          mountPath: /fluentd/etc/fluent.conf
          subPath: fluent.conf
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /var/lib/docker/containers
      - configMap:
          defaultMode: 420
          name: fluentd-config
        name: config-volume
      - configMap:
          defaultMode: 420
          items:
          - key: fluent.conf
            path: fluent.conf
          name: fluentd-es-config-main
        name: config-volume-main

 五、kibana展示数据

 
访问刚刚定义的ingress，访问kibana的web界面。

在web界面中我们可以点击侧边栏的Dev Tools，测试fluentd传输日志是否生效

 点击GET /_cat/indices?v   如果出现logstash的索引，则说明fluentd配置生效

想要用kibana展示数据，还需要配置索引，点击Management / Index Patterns，创建Index pattern

 

在界面中输入logstash-*，点击Next step 

 配置时间过滤器，选择@timestamp选项，点击Create index pattern

来到Discover界面，可以看到日志数据已经被展示出来了