kubernetes集群EFK日志框架部署

目标:在现有Kubernetes集群中搭建EFK日志框架,实现集群日志的存储与展示

环境:Kubernetes集群(kubeadm方式部署)

步骤:Kubernetes日志架构概述->Fluentd日志收集容器部署->Elasticsearch日志存储容器部署->Kibana日志展示容器部署

1.Kubernetes日志架构概述

在Kubernetes集群中,Cluster-Level Logging架构为集中查看并分析集群资源及服务日志的官方解决方案:

kubernetes集群EFK日志框架部署_第1张图片

该方案采用Node Logging Agent的方式,通过在集群每个节点上部署一个Agent代理Pod服务,收集该Node上的日志并push到后端。Agent应具备进入该节点上所有服务容器日志目录的权限。

具体在EFK方案中,logging-agent使用Fluentd,logging backend使用Elasticsearch,另为方便展示,使用kibana获取并展示es数据库数据。

2.Fluentd日志收集容器部署

Fluentd日志收集容器以DaemonSet的形式运行在Kubernetes集群中,保证集群中每个Node都会启动一个Fluentd。

在Master节点创建fluentd服务,最终会在所有Node节点上运行。

(1)配置映射文件 - fluentd-es-configmap.yaml

kind: ConfigMap
apiVersion: v1
metadata:
  name: fluentd-es-config-v0.1.4
  namespace: kube-system
  labels:
    addonmanager.kubernetes.io/mode: Reconcile
data:
  system.conf: |-
    
      root_dir /tmp/fluentd-buffers/
    
  containers.input.conf: |-
    # This configuration file for Fluentd / td-agent is used
    # to watch changes to Docker log files. The kubelet creates symlinks that
    # capture the pod name, namespace, container name & Docker container ID
    # to the docker logs for pods in the /var/log/containers directory on the host.
    # If running this fluentd configuration in a Docker container, the /var/log
    # directory should be mounted in the container.
    #
    # These logs are then submitted to Elasticsearch which assumes the
    # installation of the fluent-plugin-elasticsearch & the
    # fluent-plugin-kubernetes_metadata_filter plugins.
    # See https://github.com/uken/fluent-plugin-elasticsearch &
    # https://github.com/fabric8io/fluent-plugin-kubernetes_metadata_filter for
    # more information about the plugins.
    #
    # Example
    # =======
    # A line in the Docker log file might look like this JSON:
    #
    # {"log":"2014/09/25 21:15:03 Got request with path wombat\n",
    #  "stream":"stderr",
    #   "time":"2014-09-25T21:15:03.499185026Z"}
    #
    # The time_format specification below makes sure we properly
    # parse the time format produced by Docker. This will be
    # submitted to Elasticsearch and should appear like:
    # $ curl 'http://elasticsearch-logging:9200/_search?pretty'
    # ...
    # {
    #      "_index" : "logstash-2014.09.25",
    #      "_type" : "fluentd",
    #      "_id" : "VBrbor2QTuGpsQyTCdfzqA",
    #      "_score" : 1.0,
    #      "_source":{"log":"2014/09/25 22:45:50 Got request with path wombat\n",
    #                 "stream":"stderr","tag":"docker.container.all",
    #                 "@timestamp":"2014-09-25T22:45:50+00:00"}
    #    },
    # ...
    #
    # The Kubernetes fluentd plugin is used to write the Kubernetes metadata to the log
    # record & add labels to the log record if properly configured. This enables users
    # to filter & search logs on any metadata.
    # For example a Docker container's logs might be in the directory:
    #
    #  /var/lib/docker/containers/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b
    #
    # and in the file:
    #
    #  997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b-json.log
    #
    # where 997599971ee6... is the Docker ID of the running container.
    # The Kubernetes kubelet makes a symbolic link to this file on the host machine
    # in the /var/log/containers directory which includes the pod name and the Kubernetes
    # container name:
    #
    #    synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #    ->
    #    /var/lib/docker/containers/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b-json.log
    #
    # The /var/log directory on the host is mapped to the /var/log directory in the container
    # running this instance of Fluentd and we end up collecting the file:
    #
    #   /var/log/containers/synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #
    # This results in the tag:
    #
    #  var.log.containers.synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #
    # The Kubernetes fluentd plugin is used to extract the namespace, pod name & container name
    # which are added to the log message as a kubernetes field object & the Docker container ID
    # is also added under the docker field object.
    # The final tag is:
    #
    #   kubernetes.var.log.containers.synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #
    # And the final log record look like:
    #
    # {
    #   "log":"2014/09/25 21:15:03 Got request with path wombat\n",
    #   "stream":"stderr",
    #   "time":"2014-09-25T21:15:03.499185026Z",
    #   "kubernetes": {
    #     "namespace": "default",
    #     "pod_name": "synthetic-logger-0.25lps-pod",
    #     "container_name": "synth-lgr"
    #   },
    #   "docker": {
    #     "container_id": "997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b"
    #   }
    # }
    #
    # This makes it easier for users to search for logs by pod name or by
    # the name of the Kubernetes container regardless of how many times the
    # Kubernetes pod has been restarted (resulting in a several Docker container IDs).
    # Json Log Example:
    # {"log":"[info:2016-02-16T16:04:05.930-08:00] Some log text here\n","stream":"stdout","time":"2016-02-17T00:04:05.931087621Z"}
    # CRI Log Example:
    # 2016-02-17T00:04:05.931087621Z stdout F [info:2016-02-16T16:04:05.930-08:00] Some log text here
    
      @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
      tag raw.kubernetes.*
      read_from_head true
      
        @type multi_format
        
          format json
          time_key time
          time_format %Y-%m-%dT%H:%M:%S.%NZ
        
        
          format /^(?
      
    
    # Detect exceptions in the log output and forward them as one log entry.
    
      @id raw.kubernetes
      @type detect_exceptions
      remove_tag_prefix raw
      message log
      stream stream
      multiline_flush_interval 5
      max_bytes 500000
      max_lines 1000
    
  system.input.conf: |-
    # Example:
    # 2015-12-21 23:17:22,066 [salt.state       ][INFO    ] Completed state [net.ipv4.ip_forward] at time 23:17:22.066081
    
      @id minion
      @type tail
      format /^(?

kubectl create -f fluentd-es-configmap.yaml

(2)部署及服务文件 - fluentd-es-ds.yaml

apiVersion: v1
kind: ServiceAccount
metadata:
  name: fluentd-es
  namespace: kube-system
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
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"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
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: kube-system
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: fluentd-es
  apiGroup: ""
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: fluentd-es-v2.2.0
  namespace: kube-system
  labels:
    k8s-app: fluentd-es
    version: v2.2.0
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  selector:
    matchLabels:
      k8s-app: fluentd-es
      version: v2.2.0
  template:
    metadata:
      labels:
        k8s-app: fluentd-es
        kubernetes.io/cluster-service: "true"
        version: v2.2.0
      # 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: ''
        seccomp.security.alpha.kubernetes.io/pod: 'docker/default'
    spec:
      priorityClassName: system-node-critical
      serviceAccountName: fluentd-es
      containers:
      - name: fluentd-es
        image: gcr.io/google-containers/fluentd-elasticsearch:v2.2.0
        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: /var/lib/docker/containers
          readOnly: true
        - name: config-volume
          mountPath: /etc/fluent/config.d
      nodeSelector:
        beta.kubernetes.io/fluentd-ds-ready: "true"
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /var/lib/docker/containers
      - name: config-volume
        configMap:
          name: fluentd-es-config-v0.1.4

kubectl create -f fluentd-es-ds.yaml

此处fluentd未能成功启动,因为node节点未打上标签beta.kubernetes.io/fluentd-ds-ready=true

为所有节点打上标签:kubectl label node nodeid beta.kubernetes.io/fluentd-ds-ready=true

重新运行fluentd

kubectl apply -f fluentd-es-ds.yaml

kubectl get pods -n kube-system


3.Elasticsearch日志存储容器部署

Elasticsearch的主要作用是将日志信息进行分割,建立索引。

(1)node环境配置

kubernetes集群EFK日志框架部署_第2张图片

将max_map_count值设置为655360,防止该值低于es运行所需,导致es无法正常运行

sysctl -p应用

(2)es部署文件与服务文件

es-statefulset.yaml

# RBAC authn and authz
apiVersion: v1
kind: ServiceAccount
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
  - ""
  resources:
  - "services"
  - "namespaces"
  - "endpoints"
  verbs:
  - "get"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  namespace: kube-system
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
  name: elasticsearch-logging
  namespace: kube-system
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: elasticsearch-logging
  apiGroup: ""
---
# Elasticsearch deployment itself
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    version: v6.2.4
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  serviceName: elasticsearch-logging
  replicas: 2
  selector:
    matchLabels:
      k8s-app: elasticsearch-logging
      version: v6.2.4
  template:
    metadata:
      labels:
        k8s-app: elasticsearch-logging
        version: v6.2.4
        kubernetes.io/cluster-service: "true"
    spec:
      serviceAccountName: elasticsearch-logging
      containers:
      - image: gcr.io/google-containers/elasticsearch:v6.2.4
        name: elasticsearch-logging
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: elasticsearch-logging
          mountPath: /data
        env:
        - name: "NAMESPACE"
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
      volumes:
      - name: elasticsearch-logging
        emptyDir: {}
es-service.yaml
apiVersion: v1
kind: Service
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Elasticsearch"
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    k8s-app: elasticsearch-logging

使用kubectl create -f .部署

查看日志输出,确认es服务启动成功

kubectl logs -f pod/esname -n kube-system

kubernetes集群EFK日志框架部署_第3张图片

4.Kibana日志展示容器部署

Kibana是一个开源的分析与可视化平台,与elasticsearch配合使用,可以使用kibana搜索、查看存储在es中的数据

(1)kibana部署文件

kibana-deployment.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana-logging
  namespace: kube-system
  labels:
    k8s-app: kibana-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  replicas: 1
  selector:
    matchLabels:
      k8s-app: kibana-logging
  template:
    metadata:
      labels:
        k8s-app: kibana-logging
      annotations:
        seccomp.security.alpha.kubernetes.io/pod: 'docker/default'
    spec:
      containers:
      - name: kibana-logging
        image: docker.elastic.co/kibana/kibana-oss:6.2.4
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: ELASTICSEARCH_URL
            value: http://elasticsearch-logging:9200
          - name: SERVER_BASEPATH
            value: /api/v1/namespaces/kube-system/services/kibana-logging/proxy
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP

(2)kibana服务文件

kibana-service.yaml

apiVersion: v1
kind: Service
metadata:
  name: kibana-logging
  namespace: kube-system
  labels:
    k8s-app: kibana-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Kibana"
spec:
  ports:
  - port: 5601
    protocol: TCP
    targetPort: ui
  selector:
    k8s-app: kibana-logging

查看kibana对应的服务地址:

kubectl cluster-info


浏览器导入/etc/kubernetes/pki/ca.crt,访问:

kubernetes集群EFK日志框架部署_第4张图片

访问kibana服务地址:此时会由于没有角色权限而访问失败,可通过proxy代理暴露地址解决

kubernetes集群EFK日志框架部署_第5张图片

因此通过proxy代理将kibana服务暴露出来:

kubectl proxy --port=8080 --address=192.168.0.29 --accept-hosts=^*$

重新访问,端口改为8080:

kubernetes集群EFK日志框架部署_第6张图片

设置index-pattern为logstash-*

discover:

kubernetes集群EFK日志框架部署_第7张图片

以上,kubernetes集群EFK日志框架构建完成。


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