TKE中部署EFK日志收集

蒋经纬

修改于 2020-06-22 10:15:52

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文章被收录于专栏：TKE学习分享TKE学习分享

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目前主流的Kubernetes中采集日志主要有两种形式

第一种：DaemonSet

通过DaemonSet在每一台Node节点上跑一个Filebeat或fluentd，然后通过挂载的形式将容器日志与该Pod关联，从而处理发送至后端存储；

优点：不会对应用与Pod有侵入性；

这种方案,要求应用输出的日志,都必须是直接输出到容器的 stdout 和 stderr 中。

第二种：SideCar

通过Sidecar的形式，每一个Pod中都包含一个Filebeat或Fluentd，从而直接将日志处理发送至后端存储。

优点：部署简单,对宿主机也非常友好；

缺点：由于是Sidecar的形式，每一个Pod下多起了一个容器，资源消耗会增多；

特殊：此种方式不仅可以实现直接输出到容器的 stdout 和 stderr 中的日志收集，也可以实现对特定文件内容的收集。

这里我们采用DaemonSet这种形式来进行日志收集系统的部署。

1、为了方便辨识区分，这里新建一个namspaces；

kubectl create namespaces ns-log

2、部署ES集群；

es-svc.yml

这里的Service采用一个clusterIP=None的Headless Service

有时不需要或不想要负载均衡，以及单独的Service IP。遇到这种情况，可以通过指定 Cluster IP（spec.clusterIP）的值为“None”来创建Headless Service。这类Service 并不会分配Cluster IP，kube-proxy 不会处理它们，而且平台也不会为它们进行负载均衡和路由。

kind: Service
apiVersion: v1
metadata:
  name: elasticsearch
  namespace: ns-log
  labels:
    app: elasticsearch
spec:
  selector:
    app: elasticsearch
  clusterIP: None
  ports:
    - port: 9200
      name: rest
    - port: 9300
      name: inter-node

由于我们是在TKE上部署elasticsearch，所以这里我们持久化存储先创建一个StorageClass。

es-statefulset.yml

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: es-cluster
  namespace: ns-log
spec:
  serviceName: elasticsearch
  replicas: 3
  selector:
    matchLabels:
      app: elasticsearch
  template:
    metadata:
      labels:
        app: elasticsearch
    spec:
      containers:
      - name: elasticsearch
        image: elasticsearch:7.7.0
        resources:
            limits:
              cpu: 1000m
            requests:
              cpu: 100m
        ports:
        - containerPort: 9200
          name: rest
          protocol: TCP
        - containerPort: 9300
          name: inter-node
          protocol: TCP
        volumeMounts:
        - name: data
          mountPath: /usr/share/elasticsearch/data
        env:
          - name: cluster.name
            value: k8s-logs
          - name: node.name
            valueFrom:
              fieldRef:
                fieldPath: metadata.name
          - name: discovery.zen.ping.unicast.hosts
            value: "es-cluster-0.elasticsearch,es-cluster-1.elasticsearch,es-cluster-2.elasticsearch"
          - name: discovery.zen.minimum_master_nodes
            value: "2"
          - name: ES_JAVA_OPTS
            value: "-Xms512m -Xmx512m"
      initContainers:
      - name: fix-permissions
        image: busybox
        command: ["sh", "-c", "chown -R 1000:1000 /usr/share/elasticsearch/data"]
        securityContext:
          privileged: true
        volumeMounts:
        - name: data
          mountPath: /usr/share/elasticsearch/data
      - name: increase-vm-max-map
        image: busybox
        command: ["sysctl", "-w", "vm.max_map_count=262144"]
        securityContext:
          privileged: true
      - name: increase-fd-ulimit
        image: busybox
        command: ["sh", "-c", "ulimit -n 65536"]
        securityContext:
          privileged: true
  volumeClaimTemplates:
  - metadata:
      name: data
      labels:
        app: elasticsearch
    spec:
      accessModes: [ "ReadWriteOnce" ]
      storageClassName: es-log
      resources:
        requests:
          storage: 50Gi

3、部署Kibana；

apiVersion: v1
kind: Service
metadata:
  name: kibana
  namespace: ns-log
  labels:
    app: kibana
spec:
  ports:
  - port: 5601
  # 由于是web界面，使用NodePort方式便于访问
  type: NodePort
  selector:
    app: kibana
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: ns-log
  labels:
    app: kibana
spec:
  selector:
    matchLabels:
      app: kibana
  template:
    metadata:
      labels:
        app: kibana
    spec:
      containers:
      - name: kibana
        image: kibana:7.7.0
        resources:
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: ELASTICSEARCH_URL
            value: http://elasticsearch:9200
        ports:
        - containerPort: 5601

4、部署fluentd；

fluentd-configmap.yml

kind: ConfigMap
apiVersion: v1
metadata:
  name: fluentd-config
  namespace: ns-log
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
data:
  system.conf: |-
    <system>
      root_dir /tmp/fluentd-buffers/
    </system>
  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.%NZ
      localtime
      tag raw.kubernetes.*
      format json
      read_from_head true
    </source>
    # Detect exceptions in the log output and forward them as one log entry.
    <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>
  system.input.conf: |-
    # Logs from systemd-journal for interesting services.
    <source>
      @id journald-docker
      @type systemd
      filters [{ "_SYSTEMD_UNIT": "docker.service" }]
      <storage>
        @type local
        persistent true
      </storage>
      read_from_head true
      tag docker
    </source>
    <source>
      @id journald-kubelet
      @type systemd
      filters [{ "_SYSTEMD_UNIT": "kubelet.service" }]
      <storage>
        @type local
        persistent true
      </storage>
      read_from_head true
      tag kubelet
    </source>
  forward.input.conf: |-
    # Takes the messages sent over TCP
    <source>
      @type forward
    </source>
  output.conf: |-
    # Enriches records with Kubernetes metadata
    <filter kubernetes.**>
      @type kubernetes_metadata
    </filter>
    <match **>
      @id elasticsearch
      @type elasticsearch
      @log_level info
      include_tag_key true
      host elasticsearch
      port 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.daemonset.yml

apiVersion: apps/v1beta2
kind: DaemonSet
metadata:
  name: fluentd-es
  namespace: ns-log
  labels:
    k8s-app: fluentd-es
    version: v2.0.4
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  selector:
    matchLabels:
      k8s-app: fluentd-es
      version: v2.0.4
  template:
    metadata:
      labels:
        k8s-app: fluentd-es
        kubernetes.io/cluster-service: "true"
        version: v2.0.4
      # This annotation ensures that fluentd does not get evicted if the node
      # supports critical pod annotation based priority scheme.
      # Note that this does not guarantee admission on the nodes (#40573).
      annotations:
        scheduler.alpha.kubernetes.io/critical-pod: ''
    spec:
      serviceAccountName: fluentd-es
      containers:
      - name: fluentd-es
        image: cnych/fluentd-elasticsearch:v2.0.4
        env:
        - name: FLUENTD_ARGS
          value: --no-supervisor -q
        resources:
          limits:
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 200Mi
        volumeMounts:
        - name: varlog
          mountPath: /var/log
        - name: varlibdockercontainers
          mountPath: /data/docker/containers
          readOnly: true
        - name: config-volume
          mountPath: /etc/fluent/config.d
      #nodeSelector:
      #  beta.kubernetes.io/fluentd-ds-ready: "true"
      tolerations:
      - key: node-role.kubernetes.io/master
        operator: Exists
        effect: NoSchedule
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /data/docker/containers
      - name: config-volume
        configMap:
          name: fluentd-config

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