Collect EMQX Logs in Kubernetes

Objective

Use ELK to collect EMQX cluster logs.

Deploy ELK

ELK stands for Elasticsearch, Logstash, and Kibana (also known as the Elastic Stack):

Elasticsearch: Distributed, near-real-time search and analytics engine based on Lucene providing REST APIs to interact with data.
Logstash: Primary data flow engine for collecting, transforming, and forwarding logs from various sources to different destinations.
Kibana: Web interface for visualizing and analyzing Elasticsearch data in real time.

Deploy Single Node Elasticsearch

Deploying a single-node Elasticsearch cluster is relatively simple. You can use the following YAML configuration file to quickly deploy an Elasticsearch cluster.

Save the following content as a YAML file and deploy it using kubectl apply.

yaml

---
apiVersion: v1
kind: Service
metadata:
  name: elasticsearch-logging
  namespace: kube-logging
  labels:
    k8s-app: elasticsearch
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    k8s-app: elasticsearch
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: elasticsearch-logging
  namespace: kube-logging
  labels:
    k8s-app: elasticsearch
    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
    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-logging
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
  name: elasticsearch-logging
  namespace: kube-logging
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: elasticsearch
  apiGroup: ""
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: elasticsearch-logging
  namespace: kube-logging
  labels:
    k8s-app: elasticsearch
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  serviceName: elasticsearch-logging
  replicas: 1
  selector:
    matchLabels:
      k8s-app: elasticsearch
  template:
    metadata:
      labels:
        k8s-app: elasticsearch
    spec:
      serviceAccountName: elasticsearch-logging
      containers:
      - image: docker.io/library/elasticsearch:7.9.3
        name: elasticsearch-logging
        resources:
          limits:
            cpu: 1000m
            memory: 1Gi
          requests:
            cpu: 100m
            memory: 500Mi
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: elasticsearch-logging
          mountPath: /usr/share/elasticsearch/data/
        env:
        - name: "NAMESPACE"
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: "discovery.type"
          value: "single-node"
        - name: ES_JAVA_OPTS
          value: "-Xms512m -Xmx2g"
      # Elasticsearch requires vm.max_map_count to be at least 262144.
      # If your OS already sets up this number to a higher value, feel free
      # to remove this init container.
      initContainers:
      - name: elasticsearch-logging-init
        image: alpine:3.6
        command: ["/sbin/sysctl", "-w", "vm.max_map_count=262144"]
        securityContext:
          privileged: true
      - name: increase-fd-ulimit
        image: busybox
        imagePullPolicy: IfNotPresent
        command: ["sh", "-c", "ulimit -n 65536"]
        securityContext:
          privileged: true
      - name: elasticsearch-volume-init
        image: alpine:3.6
        command:
          -chmod
          - -R
          - "777"
          - /usr/share/elasticsearch/data/
        volumeMounts:
        - name: elasticsearch-logging
          mountPath: /usr/share/elasticsearch/data/
  volumeClaimTemplates:
  - metadata:
      name: elasticsearch-logging
    spec:
      storageClassName: ${storageClassName}
      accessModes: [ "ReadWriteOnce" ]
      resources:
        requests:
          storage: 10Gi

TIP

Use the storageClassName field to choose the appropriate StorageClass. Run kubectl get storageclass to list the StorageClasses that already exist in the Kubernetes cluster, or create a StorageClass according to your needs.

Wait for Elasticsearch to be ready.

Check the status of the Elasticsearch pod using the kubectl get command and ensure that STATUS is Running.

bash

$ kubectl get pod -n kube-logging -l "k8s-app=elasticsearch"
NAME                        READY   STATUS             RESTARTS   AGE
elasticsearch-0             1/1     Running            0          16m

Deploy Kibana

This walkthrough uses a Deployment to deploy Kibana for visualizing the collected logs, and a Service of type NodePort to expose Kibana externally.

Save the following content as a YAML file and deploy it using kubectl apply.

yaml

---
apiVersion: v1
kind: Service
metadata:
  name: kibana
  namespace: kube-logging
  labels:
    k8s-app: kibana
spec:
  type: NodePort
  ports:
  - port: 5601
    nodePort: 35601
    protocol: TCP
    targetPort: ui
  selector:
    k8s-app: kibana
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: kube-logging
  labels:
    k8s-app: kibana
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  replicas: 1
  selector:
    matchLabels:
      k8s-app: kibana
  template:
    metadata:
      labels:
        k8s-app: kibana
      annotations:
        seccomp.security.alpha.kubernetes.io/pod: 'docker/default'
    spec:
      containers:
      - name: kibana
        image: docker.io/kubeimages/kibana:7.9.3
        resources:
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          # The access address of ES
          - name: ELASTICSEARCH_HOSTS
            value: http://elasticsearch-logging:9200
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP

Wait for Kibana to be ready.

Check the status of the Kibana pod using the kubectl get command and ensure that STATUS is Running.

bash

$ kubectl get pod -n kube-logging -l "k8s-app=kibana"
NAME                        READY   STATUS             RESTARTS   AGE
kibana-b7d98644-48gtm       1/1     Running            0          17m

Finally, in your browser, navigate to http://{node_ip}:35601 to access the Kibana web interface.

Deploy Filebeat

Filebeat is a lightweight log collection component that is part of the Elastic Stack and works seamlessly with Logstash, Elasticsearch, and Kibana.

Save the following content as a YAML file and deploy it using kubectl apply.

yaml

---
apiVersion: v1
kind: ConfigMap
metadata:
  name: filebeat-config
  namespace: kube-logging
  labels:
    k8s-app: filebeat
data:
  filebeat.yml: |-
    filebeat.inputs:
    - type: container
      paths:
        # The log path of the EMQX container on the host
        - /var/log/containers/^emqx.*.log
      processors:
        - add_kubernetes_metadata:
            host: ${NODE_NAME}
            matchers:
            - logs_path:
                logs_path: "/var/log/containers/"
    output.logstash:
      hosts: ["logstash:5044"]
      enabled: true
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: filebeat
  namespace: kube-logging
  labels:
    k8s-app: filebeat
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
  name: filebeat
  labels:
    k8s-app: filebeat
rules:
- apiGroups: [""]
  resources:
  - namespaces
  - pods
  verbs:
  - get
  - watch
  - list
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
  name: filebeat
subjects:
- kind: ServiceAccount
  name: filebeat
  namespace: kube-logging
roleRef:
  kind: ClusterRole
  name: filebeat
  apiGroup: rbac.authorization.k8s.io
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: filebeat
  namespace: kube-logging
  labels:
    k8s-app: filebeat
spec:
  selector:
    matchLabels:
      k8s-app: filebeat
  template:
    metadata:
      labels:
        k8s-app: filebeat
    spec:
      serviceAccountName: filebeat
      terminationGracePeriodSeconds: 30
      containers:
      - name: filebeat
        image: docker.io/kubeimages/filebeat:7.9.3
        args: [
          "-c", "/etc/filebeat.yml",
          "-e","-httpprof","0.0.0.0:6060"
        ]
        env:
        - name: NODE_NAME
          valueFrom:
            fieldRef:
              fieldPath: spec.nodeName
        - name: ELASTICSEARCH_HOST
          value: elasticsearch
        - name: ELASTICSEARCH_PORT
          value: "9200"
        securityContext:
          runAsUser: 0
        resources:
          limits:
            memory: 1000Mi
            cpu: 1000m
          requests:
            memory: 100Mi
            cpu: 100m
        volumeMounts:
        - name: config
          mountPath: /etc/filebeat.yml
          readOnly: true
          subPath: filebeat.yml
        - name: data
          mountPath: /usr/share/filebeat/data
        - name: varlibdockercontainers
          mountPath: /data/var/
          readOnly: true
        - name: varlog
          mountPath: /var/log/
          readOnly: true
        - name: timezone
          mountPath: /etc/localtime
      volumes:
      - name: config
        configMap:
          defaultMode: 0600
          name: filebeat-config
      - name: varlibdockercontainers
        hostPath:
          path: /data/var/
      - name: varlog
        hostPath:
          path: /var/log/
      - name: inputs
        configMap:
          defaultMode: 0600
          name: filebeat-inputs
      - name: data
        hostPath:
          path: /data/filebeat-data
          type: DirectoryOrCreate
      - name: timezone
        hostPath:
          path: /etc/localtime

Wait for Filebeat to become ready.

Check the status of Filebeat pods using the kubectl get command and ensure that STATUS is Running.

bash

$ kubectl get pod -n kube-logging -l "k8s-app=filebeat"
NAME             READY   STATUS    RESTARTS   AGE
filebeat-82d2b   1/1     Running   0          45m
filebeat-vwrjn   1/1     Running   0          45m

Deploy Logstash

Logstash is used for log processing and cleaning.

In this walkthrough, we use the Beats Input plugin of Logstash to collect logs and the Ruby filter plugin to filter logs. Logstash also provides many other input and filtering plugins that you can configure according to your business needs.

Save the following content as a YAML file and deploy it using kubectl apply.

yaml

---
apiVersion: v1
kind: Service
metadata:
  name: logstash
  namespace: kube-logging
spec:
  ports:
  - port: 5044
    targetPort: beats
  selector:
    k8s-app: logstash
  clusterIP: None
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: logstash
  namespace: kube-logging
spec:
  selector:
    matchLabels:
      k8s-app: logstash
  template:
    metadata:
      labels:
        k8s-app: logstash
    spec:
      containers:
      - image: docker.io/kubeimages/logstash:7.9.3
        name: logstash
        ports:
        - containerPort: 5044
          name: beats
        command:
        - logstash
        - '-f'
        - '/etc/logstash_c/logstash.conf'
        env:
        - name: "XPACK_MONITORING_ELASTICSEARCH_HOSTS"
          value: "http://elasticsearch-logging:9200"
        volumeMounts:
        - name: config-volume
          mountPath: /etc/logstash_c/
        - name: config-yml-volume
          mountPath: /usr/share/logstash/config/
        - name: timezone
          mountPath: /etc/localtime
        resources:
          limits:
            cpu: 1000m
            memory: 2048Mi
          requests:
            cpu: 512m
            memory: 512Mi
      volumes:
      - name: config-volume
        configMap:
          name: logstash-conf
          items:
          - key: logstash.conf
            path: logstash.conf
      - name: timezone
        hostPath:
          path: /etc/localtime
      - name: config-yml-volume
        configMap:
          name: logstash-yml
          items:
          - key: logstash.yml
            path: logstash.yml
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: logstash-conf
  namespace: kube-logging
  labels:
    k8s-app: logstash
data:
  logstash.conf: |-
    input {
      beats {
        port => 5044
      }
    }
    filter {
      ruby {
        code => "
          ss = event.get('message').split(' ')
          len = ss.length()
          level = ''
          index = ''
          msg = ''
          if len == 0 || len < 2
            event.set('level','invalid')
            return
          end
          if ss[1][0] == '['
            l = ss[1].length()
            level = ss[1][1..l-2]
            index = 2
          else
            level = 'info'
            index = 0
          end
          event.set('level',level)
          for i in ss[index..len]
            msg = msg + i
            msg = msg + ' '
          end
          event.set('message',msg)
        "
      }
      if [level] == "invalid" {
        drop {}
      }
    }
    output {
      elasticsearch {
        hosts => ["http://elasticsearch-logging:9200"]
        codec => json
        index => "logstash-%{+YYYY.MM.dd}"
      }
    }
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: logstash-yml
  namespace: kube-logging
  labels:
    k8s-app: logstash
data:
  logstash.yml: |-
    http.host: "0.0.0.0"
    xpack.monitoring.elasticsearch.hosts: http://elasticsearch-logging:9200

Wait for Logstash to be ready.

Check the status of Logstash pods using the kubectl get command and ensure that STATUS is Running.

bash

$ kubectl get pod -n kube-logging -l "k8s-app=logstash"
NAME             READY   STATUS    RESTARTS   AGE
filebeat-82d2b   1/1     Running   0          45m
filebeat-vwrjn   1/1     Running   0          45m

Deploy EMQX Cluster

To deploy an EMQX cluster, please refer to the document Deploy EMQX.

Verify Log Collection

Log in to the Kibana interface, open the stack management module in the menu, and click on Index Management. You can see that log indices have already been collected.

To discover and view logs in Kibana, you need to create an index pattern. Select index patterns and click Create.

Finally, verify that the EMQX cluster logs are collected.

Kubernetes

EMQX Operator

Manage EMQX Cluster

API Reference

パスワード認証

監視

アクセスコントロール

統合

管理

OpenTelemetry との統合

エンドツーエンドトレース

プラグイン

JT/T 808 ゲートウェイ

Volcengine RTC

シナリオ

GPT-Realtime

Collect EMQX Logs in Kubernetes ​

Objective ​

Deploy ELK ​

Deploy Single Node Elasticsearch ​

Deploy Kibana ​

Deploy Filebeat ​

Deploy Logstash ​

Deploy EMQX Cluster ​

Verify Log Collection ​

Collect EMQX Logs in Kubernetes

Objective

Deploy ELK

Deploy Single Node Elasticsearch

Deploy Kibana

Deploy Filebeat

Deploy Logstash

Deploy EMQX Cluster

Verify Log Collection