一、背景

基于K8s集群的私有化交付方案中，日志收集采用了 ilogtail+logstash+kafka+es方案，其中ilogtail负责日志收集，logstash负责对数据转换，kafka负责对日志传递中的消峰进而减少es的写入压力，es用来保存日志数据。在私有化交付中本方案中涉及的中间件一般需要单独部署，但是在京东内网环境的部署考虑到kafka和es的高可用，则不推荐采用单独部署的方案。

二、新方案实践

1.新方案简介

在京东内网环境部署 K8S并 收集日志， kafka+es的替代方案考虑使用 JMQ+JES，由于JMQ的底层是基于kafaka、JES的底层基于ES，所以该替换方案理论上是可行的

2.主要架构

数据流向大致如下

应用日志 -> ilogtail -> JMQ -> logstash -> JES

3.如何使用

核心改造点汇总

ilogtail nameservers配置

增加解析JMQ域名的nameserver（京东云主机上无法直接解析.local域名） spec:     spec:       dnsPolicy: "None"       dnsConfig:         nameservers:           - x.x.x.x # 可以解析jmq域名的nameserver

ilogtail flushers配置

调整发送到JMQ到配置 apiVersion: v1kind: ConfigMapmetadata:   name: ilogtail-user-cm  namespace: elastic-systemdata:   app_stdout.yaml: |     flushers:       - Type: flusher_stdout         OnlyStdout: true       - Type: flusher_kafka_v2         Brokers:           - nameserver.jmq.jd.local:80 # jmq元数据地址         Topic: ai-middle-k8s-log-prod # jmq topic          ClientID: ai4middle4log # Kafka的用户ID（识别客户端并设置其唯一性），对应jmq的Group名称，重要‼️ （https://ilogtail.gitbook.io/ilogtail-docs/plugins/input/service-kafka#cai-ji-pei-zhi-v2）

logstash kafka&es配置

apiVersion: v1kind: ConfigMapmetadata:   name: logstash-config  namespace: elastic-system  labels:     elastic-app: logstashdata:   logstash.conf: |-     input {         kafka {                 bootstrap_servers => ["nameserver.jmq.jd.local:80"] #jmq的元数据地址                 group_id => "ai4middle4log" # jmq的Group的名称                 client_id => "ai4middle4log" # jmq的Group的名称，即jmq的省略了kafka中的client_id概念，用Group名称代替                 consumer_threads => 2                 decorate_events => true                 topics => ["ai-middle-k8s-log-prod"] # jmp的topic                 auto_offset_reset => "latest"                 codec => json { charset => "UTF-8" }         }     }     output {         elasticsearch {                 hosts => ["http://x.x.x.x:40000","http://x.x.x.x:40000","http://x.x.x.x:40000"] # es地址                 index =>  "%{[@metadata][kafka][topic]}-%{+YYYY-MM-dd}" # 索引规则                 user => "XXXXXX" #jes的用户名                 password => "xxxxx" #jes的密码                 ssl => "false"                 ssl_certificate_verification => "false"        }     }

ilogtail 的配置如下

# ilogtail-daemonset.yamlapiVersion: apps/v1kind: DaemonSetmetadata:   name: ilogtail-ds  namespace: elastic-system  labels:     k8s-app: logtail-dsspec:   selector:     matchLabels:       k8s-app: logtail-ds  template:     metadata:       labels:         k8s-app: logtail-ds    spec:       dnsPolicy: "None"       dnsConfig:         nameservers:           - x.x.x.x # （京东云主机上）可以解析jmq域名的nameserver       tolerations:         - operator: Exists                    # deploy on all nodes       containers:         - name: logtail          env:             - name: ALIYUN_LOG_ENV_TAGS       # add log tags from env               value: _node_name_|_node_ip_            - name: _node_name_              valueFrom:                 fieldRef:                   apiVersion: v1                  fieldPath: spec.nodeName            - name: _node_ip_              valueFrom:                 fieldRef:                   apiVersion: v1                  fieldPath: status.hostIP            - name: cpu_usage_limit           # iLogtails self monitor cpu limit               value: "1"             - name: mem_usage_limit           # iLogtails self monitor mem limit               value: "512"           image: dockerhub.ai.jd.local/ai-middleware/ilogtail-community-edition/ilogtail:1.3.1          imagePullPolicy: IfNotPresent          resources:             limits:               cpu: 1000m              memory: 1Gi            requests:               cpu: 400m              memory: 384Mi          volumeMounts:             - mountPath: /var/run                       # for container runtime socket               name: run            - mountPath: /logtail_host                  # for log access on the node               mountPropagation: HostToContainer              name: root              readOnly: true             - mountPath: /usr/local/ilogtail/checkpoint # for checkpoint between container restart               name: checkpoint            - mountPath: /usr/local/ilogtail/user_yaml_config.d # mount config dir               name: user-config              readOnly: true             - mountPath: /usr/local/ilogtail/apsara_log_conf.json              name: apsara-log-config              readOnly: true               subPath: apsara_log_conf.json      dnsPolicy: ClusterFirst      hostNetwork: true       volumes:         - hostPath:             path: /var/run            type: Directory          name: run        - hostPath:             path: /            type: Directory          name: root        - hostPath:             path: /etc/ilogtail-ilogtail-ds/checkpoint            type: DirectoryOrCreate          name: checkpoint        - configMap:             defaultMode: 420             name: ilogtail-user-cm          name: user-config        - configMap:             defaultMode: 420             name: ilogtail-apsara-log-config-cm          name: apsara-log-config # ilogtail-user-configmap.yamlapiVersion: v1kind: ConfigMapmetadata:   name: ilogtail-user-cm  namespace: elastic-systemdata:   app_stdout.yaml: |     enable: true     inputs:       - Type: service_docker_stdout         Stderr: true         Stdout: true         K8sNamespaceRegex: ai-train         ExternalK8sLabelTag:           platform/resource-name: k8s_label_resource-name           platform/task-identify: k8s_label_task-identify           task-id: k8s_label_task-id           run-id: k8s_label_run-id           request-id: k8s_label_request-id     processors:       - Type: processor_rename         SourceKeys:           - k8s_label_resource-name           - k8s_label_task-identify           - k8s_label_task-id           - k8s_label_run-id           - k8s_label_request-id           - _namespace_           - _image_name_           - _pod_uid_           - _pod_name_           - _container_name_           - _container_ip_           - __path__           - _source_         DestKeys:           - resource_name           - task_identify           - task_id           - run_id           - request_id           - namespace           - image_name           - pod_uid           - pod_name           - container_name           - container_ip           - path           - source     flushers:       - Type: flusher_stdout         OnlyStdout: true       - Type: flusher_kafka_v2         Brokers:           - nameserver.jmq.jd.local:80 # jmq元数据地址         Topic: ai-middle-k8s-log-prod # jmq topic          ClientID: ai4middle4log # Kafka的用户ID（识别客户端并设置其唯一性），对应jmq的Group名称，重要‼️ （https://ilogtail.gitbook.io/ilogtail-docs/plugins/input/service-kafka#cai-ji-pei-zhi-v2）   app_file_log.yaml: |     enable: true     inputs:       - Type: file_log         LogPath: /export/Logs/ai-dt-algorithm-tools         FilePattern: "*.log"         ContainerInfo:           K8sNamespaceRegex: ai-train           ExternalK8sLabelTag:             platform/resource-name: k8s_label_resource-name             platform/task-identify: k8s_label_task-identify             task-id: k8s_label_task-id             run-id: k8s_label_run-id             request-id: k8s_label_request-id     processors:       - Type: processor_add_fields        Fields:           source: file      - Type: processor_rename        SourceKeys:           - __tag__:k8s_label_resource-name          - __tag__:k8s_label_task-identify          - __tag__:k8s_label_task-id          - __tag__:k8s_label_run-id          - __tag__:k8s_label_request-id          - __tag__:_namespace_          - __tag__:_image_name_          - __tag__:_pod_uid_          - __tag__:_pod_name_          - __tag__:_container_name_          - __tag__:_container_ip_          - __tag__:__path__        DestKeys:           - resource_name          - task_identify          - task_id          - run_id          - request_id          - namespace          - image_name          - pod_uid          - pod_name          - container_name          - container_ip          - path    flushers:       - Type: flusher_stdout        OnlyStdout: true       - Type: flusher_kafka_v2        Brokers:           - nameserver.jmq.jd.local:80         Topic: ai-middle-k8s-log-prod        ClientID: ai4middle4log

logstash 的配置如下

# logstash-configmap.yaml---apiVersion: v1kind: ConfigMapmetadata:   name: logstash-config  namespace: elastic-system  labels:     elastic-app: logstashdata:   logstash.conf: |-     input {         kafka {                 bootstrap_servers => ["nameserver.jmq.jd.local:80"] #jmq的元数据地址                 #group_id => "services"                 group_id => "ai4middle4log" # jmq的Group的名称                 client_id => "ai4middle4log" # jmq的Group的名称，即jmq的省略了kafka中的client_id概念，用Group名称代替                 consumer_threads => 2                 decorate_events => true                #topics_pattern => ".*"                 topics => ["ai-middle-k8s-log-prod"] # jmp的topic                 auto_offset_reset => "latest"                 codec => json { charset => "UTF-8" }         }     }     filter {       ruby {           code => "event.set(index_date, event.get(@timestamp).time.localtime + 8*60*60)"       }       ruby {           code => "event.set(message,event.get(contents))"      }       #ruby {       #    code => "event.set(@timestamp,event.get(time).time.localtime)"       #}       mutate {           remove_field => ["contents"]           convert => ["index_date", "string"]           #convert => ["@timestamp", "string"]           gsub => ["index_date", "T.*Z",""]           #gsub => ["@timestamp", "T.*Z",""]       }     }     output {         elasticsearch {                 #hosts => ["https://ai-middle-cluster-es-http:9200"]                 hosts => ["http://x.x.x.x:40000","http://x.x.x.x:40000","http://x.x.x.x:40000"] # es地址                 index =>  "%{[@metadata][kafka][topic]}-%{+YYYY-MM-dd}" # 索引规则                 user => "XXXXXX" #jes的用户名                 password => "xxxxx" #jes的密码                 ssl => "false"                 ssl_certificate_verification => "false"                #cacert => "/usr/share/logstash/cert/ca_logstash.cer"         }         stdout {             codec => rubydebug        }     }

4.核心价值

在私有化部署的基础上通过简单改造实现了与京东内部中间件的完美融合，使得系统在高可用性上适应性更强、可用范围更广。