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  • 日志采集/分析

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    EFK

    这是一个日志收集系统,日志收集属于可观测性体系

    可观测性体系

    • 监控

      • 基础设施的维度
        • USE方法
          • CPU:
            • 利用率
            • 负载
          • 内存:
            • 利用率
            • 饱和度
            • 错误率
          • 网卡:
            • 利用率
            • 饱和度
            • 错误率
      • 应用程序的维度
        • RED方法
    • 日志

      • 操作系统维度
      • 应用维度
        • 通过日志的错误进一步完善监控
        • 通过日志排查问题
        • 行为分析
    • 链路追踪

    1. 日志系统

    1. ELK
      • ElasticSearch :日志存储系统
      • LogStash:日志采集器
      • Kibana:日志查询分析系统

    ELK现在用的少,原因是

    1. jruby(java+ruby)
    2. 语法复杂:重量级日志采集
    3. 性能差
    1. EFK

      • ElasticSearch
      • Fluneted:日志采集器
      • Kibana
    2. PLG

      • Promtail :日志采集器
      • Loki:日志存储系统
      • Grafana:日志查询分析系统

    我们这里部署的架构是

    ilogtail ---> kafka ---> logstash ---> elasticsearch ---> kibana

    使用ilogtail采集日志写入到kafka消息队列里,再由logstash从消息队列里读取日志写入到 es,最后再由kibana做展示

    至于第三个环节为什么是logstash而不是ilogtail是因为,ilogtail要往es里面写日志会需要配置es的认证密码,但我们是没有给es配置用户名和密码的,所以采用logstash

    2. 部署ElasticSearch

    2.1 创建handless服务

    [root@master EFK]# vim es-svc.yaml 
    kind: Service
    apiVersion: v1
    metadata:
      name: elasticsearch
      namespace: logging
      labels:
        app: elasticsearch
    spec:
      selector:
        app: elasticsearch
      clusterIP: None
      ports:
      - port: 9200
        name: rest
      - port: 9300
        name: inter-node
    

    2.2 创建sts

    [root@master EFK]# vim es-sts.yaml 
    apiVersion: apps/v1
    kind: StatefulSet
    metadata:
      name: es
      namespace: logging
    spec:
      serviceName: elasticsearch
      replicas: 1
      selector:
        matchLabels:
          app: elasticsearch
      template:
        metadata:
          labels:
            app: elasticsearch
        spec:
          initContainers:
            - name: initc1
              image: busybox
              command: ["sysctl","-w","vm.max_map_count=262144"]
              securityContext:
                privileged: true
            - name: initc2
              image: busybox
              command: ["sh","-c","ulimit -n 65536"]
              securityContext:
                privileged: true
            - name: initc3
              image: busybox
              command: ["sh","-c","chmod 777 /data"]
              volumeMounts:
              - name: data
                mountPath: /data
          containers:
            - name: elasticsearch
              image: swr.cn-east-3.myhuaweicloud.com/hcie_openeuler/elasticsearch:7.17.1
              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: cluster.initial_master_nodes
                  value: "es-0"
                - name: discovery.zen.minimum_master_nodes
                  value: "2"
                - name: discovery.seed_hosts
                  value: "elasticsearch"
                - name: ES_JAVA_OPTS
                  value: "-Xms512m -Xmx512m"
                - name: network.host
                  value: "0.0.0.0"
      volumeClaimTemplates:
        - metadata:
            name: data
            labels:
              app: elasticsearch
          spec:
            accessModes: ["ReadWriteOnce"]
            resources:
              requests:
                storage: 10Gi
    

    应用yaml文件

    [root@master EFK]# kubectl create ns logging
    [root@master EFK]# kubectl apply -f .
    service/elasticsearch create
    statefulset.apps/es create
    [root@master EFK]# kubectl get pods -n logging 
    NAME   READY   STATUS    RESTARTS   AGE
    es-0   1/1     Running   0          46s
    

    pod显示running就是部署好了

    3. 部署kibana

    我直接将所有需要的资源放在一个yaml文件里面

    apiVersion: v1
    kind: ConfigMap
    metadata:
      namespace: logging
      name: kibana-config
      labels:
        app: kibana
    data:
      kibana.yml: |
        server.name: kibana
        server.host: "0.0.0.0"
        i18n.locale: zh-CN
        elasticsearch:
          hosts: ${ELASTICSEARCH_HOSTS}
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: kibana
      namespace: logging
      labels:
        app: kibana
    spec:
      ports:
      - port: 5601
      type: NodePort
      selector:
        app: kibana
    
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: kibana
      namespace: logging
      labels:
        app: kibana
    spec:
      selector:
        matchLabels:
          app: kibana
      template:
        metadata:
          labels:
            app: kibana
        spec:
          containers:
          - name: kibana
            image: swr.cn-east-3.myhuaweicloud.com/hcie_openeuler/kibana:7.17.1
            imagePullPolicy: IfNotPresent
            resources:
              limits:
                cpu: 1
              requests:
                cpu: 1
            env:
            - name: ELASTICSEARCH_URL
              value: http://elasticsearch:9200    # 写handless的名字
            - name: ELASTICSEARCH_HOSTS
              value: http://elasticsearch:9200    # 写handless的名字
            ports:
            - containerPort: 5601
            volumeMounts:
            - name: config
              mountPath: /usr/share/kibana/config/kibana.yml
              readOnly: true
              subPath: kibana.yml
          volumes: 
          - name: config
            configMap:
              name: kibana-config
    

    查看端口并访问

    [root@master EFK]# kubectl get svc
    NAME            TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)             AGE
    elasticsearch   ClusterIP   None            <none>        9200/TCP,9300/TCP   17m
    kibana          NodePort    10.104.94.122   <none>        5601:30980/TCP      4m30s
    

    kibana的nodeport端口是30980,我们来访问

    这样就算部署好了,接下来需要部署日志采集工具

    4. 部署ilogtail(docker-compose)

    因为Fluentd配置复杂,所以我这里采用ilogtail来采集日志

    • ilogtail配置简单
    • 阿里开源,界面中文

    我们先使用docker-compose的方式部署,最后整个平台搭建起来之后我们再将ilogtail部署到k8s集群里

    4.1 编写docker-compose

    [root@master ilogtail]# vim docker-compose.yaml
    version: "3"
    services:
      ilogtail:
        container_name: ilogtail
        image: sls-opensource-registry.cn-shanghai.cr.aliyuncs.com/ilogtail-community-edition/ilogtail:2.0.4
        network_mode: host
        volumes:
          - /:/logtail_host:ro
          - /var/run:/var/run
          - ./checkpoing:/usr/local/ilogtail/checkpoint
          - ./config:/usr/local/ilogtail/config/local
    
    • /:我们将宿主机的整个 / ,目录挂载到容器里面,方便容器读取日志
    • checkpoint:这个相当于一个指针,指向当前读取到哪一行日志了,如果ilogtail被重启了它可以根据这个checkpoint来回到上一次读取的地方
    • config:这个就是放采集的配置文件的

    启动容器

    [root@master ilogtail]# docker-compose up -d
    [root@master ilogtail]# docker ps |grep ilogtail
    eac545d4da87        sls-opensource-registry.cn-shanghai.cr.aliyuncs.com/ilogtail-community-edition/ilogtail:2.0.4   "/usr/local/ilogtail…"   10 seconds ago      Up 9 seconds                            ilogtail
    

    这样容器就启动了

    4.2 配置ilogtail采集

    [root@master ilogtail]# cd config/
    [root@master config]# vim sample-stdout.yaml
    enable: true
    inputs:
      - Type: input_file          # 文件输入类型
        FilePaths: 
          - /logtail_host/var/log/messages
    flushers:
      - Type: flusher_stdout    # 标准输出流输出类型
        OnlyStdout: true
    [root@master config]# docker restart ilogtail
    
    • /logtail_host/var/log/messages:这里是这个地址的原因是我们将宿主机的/,挂载到了容器内的logtail_host,所以我们宿主机产生的日志会在容器的/logtail_host/var/log/messages这个目录下

    • 配置文件写好之后我们还需要重启容器让他读取配置,所以有一个restart

    4.3 查看容器采集的日志

    [root@master config]# docker logs ilogtail
    
    2024-06-30 11:16:25 {"content":"Jun 30 19:16:22 master dockerd[1467]: time=\"2024-06-30T19:16:22.251108165+08:00\" level=info msg=\"handled exit event processID=9a8df40981b3609897794e50aeb2bde805eab8a75334266d7b5c2899f61d486e containerID=61770e8f88e3c6a63e88f2a09d2683c6ccce1e13f6d4a5b6f79cc4d49094bab4 pid=125402\" module=libcontainerd namespace=moby","__time__":"1719746182"}
    2024-06-30 11:16:25 {"content":"Jun 30 19:16:23 master kubelet[1468]: E0630 19:16:23.594557    1468 kubelet_volumes.go:245] \"There were many similar errors. Turn up verbosity to see them.\" err=\"orphaned pod \\\"9d5ae64f-1341-4c15-b70f-1c8f71efc20e\\\" found, but error not a directory occurred when trying to remove the volumes dir\" numErrs=2","__time__":"1719746184"}
    

    可以看到,宿主机的日志已经被成功采集了,宿主机的日志会被封装到content里,如果没有看到输出的日志的话,需要进入到容器内部查看一个叫做ilogtail.LOG的文件,而不能使用docker logs ilogtail

    4.4 采集容器标准输出日志(可选)

    [root@master config]# cp sample-stdout.yaml docker-stdout.yaml
    # 为了避免同时输出到标准输出而导致的日志杂乱,我们临时将sample-stdout关掉
    [root@master config]# cat sample-stdout.yaml 
    enable: false                 # 将这里改为false
    inputs:
      - Type: input_file          # 文件输入类型
        FilePaths: 
          - /logtail_host/var/log/messages
    flushers:
      - Type: flusher_stdout    # 标准输出流输出类型
        OnlyStdout: true
    [root@master config]# cat docker-stdout.yaml 
    enable: true
    inputs:
      - Type: service_docker_stdout        
        Stdout: true                 # 采集标准输出
        Stderr: false                # 不采集错误输出
    flushers:
      - Type: flusher_stdout    
        OnlyStdout: true
    [root@master config]# docker restart ilogtail 
    ilogtail
    

    4.5 查看采集的容器日志

    2024-06-30 11:24:13 {"content":"2024-06-30 11:24:10 {\"content\":\"2024-06-30 11:24:07 {\\\"content\\\":\\\"2024-06-30 11:24:04.965 [INFO][66] felix/summary.go 100: Summarising 12 dataplane reconciliation loops over 1m3.4s: avg=3ms longest=12ms ()\\\",\\\"_time_\\\":\\\"2024-06-30T11:24:04.965893702Z\\\",\\\"_source_\\\":\\\"stdout\\\",\\\"_container_ip_\\\":\\\"192.168.200.200\\\",\\\"_image_name_\\\":\\\"calico/node:v3.23.5\\\",\\\"_container_name_\\\":\\\"calico-node\\\",\\\"_pod_name_\\\":\\\"calico-node-hgqzr\\\",\\\"_namespace_\\\":\\\"kube-system\\\",\\\"_pod_uid_\\\":\\\"4d0d950c-346a-4f81-817c-c19526700542\\\",\\\"__time__\\\":\\\"1719746645\\\"}\",\"_time_\":\"2024-06-30T11:24:07.968118197Z\",\"_source_\":\"stdout\",\"_container_ip_\":\"192.168.200.200\",\"_image_name_\":\"sls-opensource-registry.cn-shanghai.cr.aliyuncs.com/ilogtail-community-edition/ilogtail:2.0.4\",\"_container_name_\":\"ilogtail\",\"__time__\":\"1719746647\"}","_time_":"2024-06-30T11:24:10.971474647Z","_source_":"stdout","_container_ip_":"192.168.200.200","_image_name_":"sls-opensource-registry.cn-shanghai.cr.aliyuncs.com/ilogtail-community-edition/ilogtail:2.0.4","_container_name_":"ilogtail","__time__":"1719746650"}
    

    能够正常看见日志就说明日志采集没有问题,接下来我们部署kafka,用来接收ilogtail的日志,注意将日志采集关掉,不然你的虚拟机磁盘很快就会满

    5. 部署kafka

    kafka作为消息队列,会有消费者和生产者,生产者在这里就是ilogtail,也就是将日志写入到kafka,消费者就是logstash,从kafka里面读取日志写入到es

    5.1 kafka介绍

    Apache kafka是分布式的,基于发布/订阅的容错消息系统,主要特性如下

    • 高吞吐,低延迟:可以做到每秒百万级的吞吐量,并且延迟低(其他的消息队列基本也都可以)

    • 持久性,可靠性:消息会被持久化到本地磁盘,支持数据备份防止数据丢失,并且可以配置消息有效期,以便消费者可以多次消费

    • kafka官方不支持docker部署,我们可以使用第三方的镜像

    5.2 部署kafka(docker-compose)

    version: '3'
    services:
      zookeeper:
        image: quay.io/3330878296/zookeeper:3.8
        network_mode: host
        container_name: zookeeper-test
        volumes:
          - zookeeper_vol:/data
          - zookeeper_vol:/datalog
          - zookeeper_vol:/logs
      kafka:
        image: quay.io/3330878296/kafka:2.13-2.8.1
        network_mode: host
        container_name: kafka
        environment:
          KAFKA_ADVERTISED_HOST_NAME: "192.168.200.200"
          KAFKA_ZOOKEEPER_CONNECT: "192.168.200.200:2181"
          KAFKA_LOG_DIRS: "/kafka/logs"
        volumes:
          - kafka_vol:/kafka
        depends_on:
          - zookeeper
    volumes:
      zookeeper_vol: {}
      kafka_vol: {}
    
    • KAFKA_LOG_DIRS: "/kafka/logs":这个地方需要注意,在kafka的名词里面,他把数据叫做日志,这个地方看似是定义的日志目录,其实是kafka的数据目录

    5.3 部署kafdrop(kafka的web界面)

    [root@master kafka]# docker run -d --rm -p 9000:9000 \
        -e KAFKA_BROKERCONNECT=192.168.200.200:9092 \
        -e SERVER_SERVLET_CONTEXTPATH="/" \
        quay.io/3330878296/kafdrop
    

    部署好之后就可以使用web界面查看了,部署web界面的原因是我们将日志写入到kafka之后可以直接使用web界面查看也没有写入进去,比kafka命令行更加的直观

    在浏览器输入ip:9000

    5.4 ilogtail将日志写入到kafka

    [root@master config]# cd /root/ilogtail/config
    [root@master config]# cp sample-stdout.yaml kafka.yaml
    [root@master config]# vim kafka.yaml
    enable: true
    inputs:
      - Type: input_file         
        FilePaths:
          - /logtail_host/var/log/messages
    flushers:
      - Type: flusher_kafka_v2  
        Brokers:
          - 192.168.200.200:9092
        Topic: KafkaTopic
    [root@master config]# docker restart ilogtail
    ilogtail
    

    这个时候我们再回到web界面就会出现一个topic

    点进去可以查看有哪些日志被写入进去了

    能看见日志就没问题了,接下来部署logstash

    6. 部署logstash

    logstash会从kafka读取消息然后写入到es里面去

    6.1 部署logstash(docker-compose)

    [root@master ~]# mkdir logstash
    [root@master ~]# cd logstash
    [root@master logstash]# vim docker-compose.yaml
    version: '3'
    services:
      logstash:
        image: quay.io/3330878296/logstash:8.10.1
        container_name: logstash
        network_mode: host
        environment:
          LS_JAVA_OPTS: "-Xmx1g -Xms1g"
        volumes:
          - /etc/localtime:/etc/localtime:ro
          - /apps/logstash/config/logstash.yml:/usr/share/logstash/config/logstash.yml
          - /apps/logstash/pipeline:/usr/share/logstash/pipeline
          - /var/log:/var/log
    
    • config里面放的是logstash本身的配置文件
    • pipeline里面放的是采集/输出日志的规则

    docker-compose写好之后先不要着急启动,因为我们给他挂载的配置文件还没有启动

    现在编写配置文件

    [root@master logstash]# mkdir /apps/logstash/{config,pipeline}
    [root@master logstash]# cd /apps/logstash/config/
    [root@master config]# vim logstash.yml 
    pipeline.workers: 2
    pipeline.batch.size: 10
    pipeline.batch.delay: 5
    config.reload.automatic: true
    config.reload.interval: 60s
    

    写好这个文件之后我们启动这个logstash容器

    [root@master logstash]# /root/logstash
    [root@master logstash]# docker-compose up -d
    [root@master logstash]# docker ps |grep logstash
    60dfde4df40d        quay.io/3330878296/logstash:8.10.1                                                              "/usr/local/bin/dock…"   2 minutes ago       Up 2 minutes                                 logstash
    

    启动之后就没问题了

    6.2 输出日志到es

    Logstash官方文档地址

    我们要使用logstash输出日志到es的话就需要到pipeline里面去写一些规则

    [root@master EFK]# cd /apps/logstash/pipeline/
    [root@master pipeline]# vim logstash.conf
    input {
      kafka {
        # 指定kafka地址
        bootstrap_servers => "192.168.200.200:9092"
        # 从哪些topic获取数据,要写已经存在topic
        topics => ["KafkaTopic"]
        # 从哪个地方开始读取,earliest是从头开始读取
        auto_offset_reset => "earliest"
        codec => "json"
        # 当一个logstash中有多个input插件时,建议每个插件定义一个id
        # id => "kubernetes"
        # group_id => "kubernetes"
      }
    }
    
    
    filter {
      json {
        source => "event.original"
      }
      mutate {
        remove_field => ["event.original","event"]
      }
    }
    
    output {
      elasticsearch {
        hosts => ["http://192.168.200.200:9200"]
        index => "kubernetes-logs-%{+YYYY.mm}"
      }
    }
    
    • ​ hosts => ["http://192.168.200.200:9200"]:这个地方的9200,因为我们的logstash是用docker部署的,但是es是部署在k8s集群内部的,所以这个地方9200端口是通不了的,所以我们需要给k8s的es创建一个nodeport类型的svc,来让docker可以访问到
    [root@master EFK]# kubectl expose pod es-0 --type NodePort --port 9200 --target-port 9200
    service/es-0 exposed
    [root@master EFK]# kubectl get svc
    NAME            TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)             AGE
    elasticsearch   ClusterIP   None            <none>        9200/TCP,9300/TCP   3h38m
    es-0            NodePort    10.97.238.173   <none>        9200:32615/TCP      2s
    kibana          NodePort    10.106.1.52     <none>        5601:30396/TCP      3h38m
    

    这里他将9200映射到了本地的32615端口,所以我们将logstash的地址改到32615

    output {
      elasticsearch {
        hosts => ["http://192.168.200.200:32615"]
        index => "kubernetes-logs-%{+YYYY.mm}"
      }
    }
    

    然后重启logstash

    [root@master pipeline]# docker restart logstash 
    

    6.3 到kibana查看

    6.3.1 查看索引

    1. 点击stack management

    2. 点击索引管理,会看到有索引存在就是正常

    3. 点击索引模式,创建索引

    1. 进入discover