04-kubernetes项目交付 - 04-4-日志收集 - 《Kubernetes》

1. 日志收集方式
- 1.1. Kubernetes日志收集思路
- 1.2. 拓扑图
2. 准备业务APP
2. 部署Elasticsearch
3. 部署Kafka
- 3.1. 部署Kafka
- 3.2. 部署Kafka-manager
4. 使用filebeat
- 4.1. 制作filebeat镜像
- 4.2. 运行dubbo消费者
5. 部署logstash
- 5.1. 制作logstash镜像
- 5.2. 启动logstash
6. Kibana部署
7. 说明

1. 日志收集方式

Kubernetes的业务Pod日志有两种输出方式：一种是直接打到标准输出或者标准错误，第二种是将日志写到特定目录下的文件种。针对这两种不同场景，提供了不同的容器日志收集思路。

1.1. Kubernetes日志收集思路

1.1.1. 使用节点代理收集日志

在各个Node节点上以Deamonset方式部署log-agent-pod，将宿主机上的日志目录挂载到log-agent-pod里面，由log-agent-pod将日志发送出去。常用的log-agent是通过Fluentd实现的。

1.1.2. 使用边车模式收集日志

在每个业务Pod中，启动一个辅助容器，将主容器的日志目录挂载到辅助容器中，将主容器刷盘的日志推送出去。这种模式下，辅助容器必须要在主容器之前启动，避免主容器丢日志。常用的辅助容器是filebeat实现的。

1.1.3. 日志输出方式的转换

标准输出—>写文件：command >/logs/stdout.log 2>/logs/stderr.log
写文件—>标准输出：tail -f xxx.log
1.2. 拓扑图
本实验采用辅助容器(边车模式)收集日志到ELK集群系统，本实验先将日志写到Kafka集群，然后再通过logstash消费Kafka中的数据，并写入Elasticsearch，这种方式是异步的，虽然消息的及时性不是特别高，但是性能比直接写Elasticsearch高很高。

2. 准备业务APP

2.1. 准备Tomcat基础镜像

2.1.1. 准备Tomcat

[root@hdss7-200 src]# wget http://mirrors.tuna.tsinghua.edu.cn/apache/tomcat/tomcat-8/v8.5.50/bin/apache-tomcat-8.5.50.tar.gz
[root@hdss7-200 src]# tar -xf apache-tomcat-8.5.50.tar.gz -C docker_files/tomcat/
[root@hdss7-200 src]# cd docker_files/tomcat/
[root@hdss7-200 tomcat]# rm -fr apache-tomcat-8.5.50/webapps/* 
[root@hdss7-200 tomcat]# vim apache-tomcat-8.5.50/conf/server.xml  # 关闭AJP
       <!-- <Connector port="8009" protocol="AJP/1.3" redirectPort="8443" /> -->
[root@hdss7-200 tomcat]# vim apache-tomcat-8.5.50/conf/logging.properties
# 删除3manager和4host-manager日志
# 修改日志级别为 INFO
handlers = 1catalina.org.apache.juli.AsyncFileHandler, 2localhost.org.apache.juli.AsyncFileHandler, java.util.logging.ConsoleHandler
......
1catalina.org.apache.juli.AsyncFileHandler.level = INFO
1catalina.org.apache.juli.AsyncFileHandler.directory = ${catalina.base}/logs
1catalina.org.apache.juli.AsyncFileHandler.prefix = catalina.
1catalina.org.apache.juli.AsyncFileHandler.encoding = UTF-8
2localhost.org.apache.juli.AsyncFileHandler.level = INFO
2localhost.org.apache.juli.AsyncFileHandler.directory = ${catalina.base}/logs
2localhost.org.apache.juli.AsyncFileHandler.prefix = localhost.
2localhost.org.apache.juli.AsyncFileHandler.encoding = UTF-8
# 3manager.org.apache.juli.AsyncFileHandler.level = FINE
# 3manager.org.apache.juli.AsyncFileHandler.directory = ${catalina.base}/logs
# 3manager.org.apache.juli.AsyncFileHandler.prefix = manager.
# 3manager.org.apache.juli.AsyncFileHandler.encoding = UTF-8
# 
# 4host-manager.org.apache.juli.AsyncFileHandler.level = FINE
# 4host-manager.org.apache.juli.AsyncFileHandler.directory = ${catalina.base}/logs
# 4host-manager.org.apache.juli.AsyncFileHandler.prefix = host-manager.
# 4host-manager.org.apache.juli.AsyncFileHandler.encoding = UTF-8
java.util.logging.ConsoleHandler.level = INFO
java.util.logging.ConsoleHandler.formatter = org.apache.juli.OneLineFormatter
java.util.logging.ConsoleHandler.encoding = UTF-8
......

2.1.2. 制作Tomcat底包

From harbor.od.com/public/jre:8u112
RUN /bin/cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
ENV CATALINA_HOME /opt/tomcat
ENV LANG zh_CN.UTF-8
ADD apache-tomcat-8.5.50/ /opt/tomcat
# 配合Pormetheus使用，且在K8S集群外的情况下使用
ADD config.yml /opt/prom/config.yml
ADD jmx_javaagent-0.3.1.jar /opt/prom/jmx_javaagent-0.3.1.jar
WORKDIR /opt/tomcat
ADD entrypoint.sh /entrypoint.sh
CMD ["/entrypoint.sh"]

[root@hdss7-200 tomcat]# cat entrypoint.sh
#!/bin/bash
M_OPTS="-Duser.timezone=Asia/Shanghai -javaagent:/opt/prom/jmx_javaagent-0.3.1.jar=$(hostname -i):${M_PORT:-"12346"}:/opt/prom/config.yml"
C_OPTS=${C_OPTS} # 连接Apollo信息
MIN_HEAP=${MIN_HEAP:-"128m"}
MAX_HEAP=${MAX_HEAP:-"128m"} 
JAVA_OPTS=${JAVA_OPTS:-"-Xmn384m -Xss256k -Duser.timezone=GMT+08  -XX:+DisableExplicitGC -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:+CMSParallelRemarkEnabled -XX:+UseCMSCompactAtFullCollection -XX:CMSFullGCsBeforeCompaction=0 -XX:+CMSClassUnloadingEnabled -XX:LargePageSizeInBytes=128m -XX:+UseFastAccessorMethods -XX:+UseCMSInitiatingOccupancyOnly -XX:CMSInitiatingOccupancyFraction=80 -XX:SoftRefLRUPolicyMSPerMB=0 -XX:+PrintClassHistogram  -Dfile.encoding=UTF8 -Dsun.jnu.encoding=UTF8"}
CATALINA_OPTS=${CATALINA_OPTS}
JAVA_OPTS="${M_OPTS} ${C_OPTS} -Xms${MIN_HEAP} -Xmx${MAX_HEAP} ${JAVA_OPTS}"
sed -i -e "1a\JAVA_OPTS=\"$JAVA_OPTS\"" -e "1a\CATALINA_OPTS=\"$CATALINA_OPTS\"" /opt/tomcat/bin/catalina.sh
# 让tomcat在前台启动
cd /opt/tomcat && /opt/tomcat/bin/catalina.sh run 2>&1 >> /opt/tomcat/logs/stdout.log

[root@hdss7-200 tomcat]# vim config.yml  
rules:
  - pattern: '.*'
[root@hdss7-200 tomcat]# chmod +x entrypoint.sh
[root@hdss7-200 tomcat]# wget https://repo1.maven.org/maven2/io/prometheus/jmx/jmx_prometheus_javaagent/0.3.1/jmx_prometheus_javaagent-0.3.1.jar -O jmx_javaagent-0.3.1.jar
[root@hdss7-200 tomcat]# docker image build . -t harbor.od.com/public/tomcat:v8.5.50
[root@hdss7-200 tomcat]# docker image push harbor.od.com/public/tomcat:v8.5.50

2.2. 配置Jenkins流水线

采用参数化构建，参考： https://www.yuque.com/duduniao/ww8pmw/gp8n04#VNfSK

1.  name: git_repo
    type: string
    description: 项目在git版本仓库的地址，如 https://gitee.com/xxx/dubbo-demo-service.git

2.  name: app_name
    type: string
    description: 项目名称，如 dubbo-demo-service  

3.  name: git_ver
    type: string
    description: 项目在git仓库中对应的分支或者版本号

4.  name: maven
    type: choice
    description: 编译时使用的maven目录中的版本号部分

5.  name: mvn_cmd
    type: string
    default: mvn clean package -Dmaven.test.skip=true
    description: 执行编译所用的指令

6.  name: mvn_dir
    type: string
    default: ./
    description: 在哪个目录执行编译，由开发同事提供

7.  name: target_dir
    type: string
    default: ./target
    description: 编译的jar/war文件存放目录，由开发同事提供

8.  name: root_dir
    type: string
    default: ROOT
    description: 项目放到webapps下面的哪个目录中

9.  name: base_image
    type: choice
    default:
    description: 项目使用的jre底包

10. name: image_name
    type: string
    description: docker镜像名称，如 app/dubbo-demo-service 

11. name: add_tag
    type: string
    default:
    description: 日期-时间，和git_ver拼在一起组成镜像的tag，如: 202002011001

pipeline {
  agent any 
    stages {
    stage('pull') { //get project code from repo 
      steps {
        sh "git clone ${params.git_repo} ${params.app_name}/${env.BUILD_NUMBER} && cd ${params.app_name}/${env.BUILD_NUMBER} && git checkout ${params.git_ver}"
        }
    }
    stage('build') { //exec mvn cmd
      steps {
        sh "cd ${params.app_name}/${env.BUILD_NUMBER}  && /var/jenkins_home/maven-${params.maven}/bin/${params.mvn_cmd}"
      }
    }
    stage('unzip') { //unzip  target/*.war -c target/project_dir
      steps {
        sh "cd ${params.app_name}/${env.BUILD_NUMBER} && cd ${params.target_dir} && mkdir project_dir && unzip *.war -d ./project_dir"
      }
    }
    stage('image') { //build image and push to registry
      steps {
        writeFile file: "${params.app_name}/${env.BUILD_NUMBER}/Dockerfile", text: """FROM harbor.od.com/${params.base_image}
ADD ${params.target_dir}/project_dir /opt/tomcat/webapps/${params.root_dir}"""
        sh "cd  ${params.app_name}/${env.BUILD_NUMBER} && docker build -t harbor.od.com/${params.image_name}:${params.git_ver}_${params.add_tag} . && docker push harbor.od.com/${params.image_name}:${params.git_ver}_${params.add_tag}"
      }
    }
  }
}

2.3. 构建dubbo-demo-web

2.4. 部署微服务

当前微服务启动时，需要依赖于 Apollo、dubbo-demo-service部件。
参考：https://www.yuque.com/duduniao/ww8pmw/eaw7s4

[root@hdss7-200 ~]# cat /data/k8s-yaml/dev/dubbo-demo-consumer/deployment.yaml # 只改镜像
......
image: harbor.od.com/app/dubbo-demo-consumer:tomcat_20200209_1149
......

2. 部署Elasticsearch

Elasticsearch 是一个有状态的服务，不建议部署在Kubernetes集群中，本次实验采用单节点部署Elasticsearch，部署节点为 hdss7-12.host.com (10.4.7.12)。

[root@hdss7-12 src]# wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.8.6.tar.gz
[root@hdss7-12 src]# tar -xf elasticsearch-6.8.6.tar.gz -C /opt/release/
[root@hdss7-12 src]# ln -s /opt/release/elasticsearch-6.8.6 /opt/apps/elasticsearch

[root@hdss7-12 ~]# grep -Ev "^$|^#" /opt/apps/elasticsearch/config/elasticsearch.yml # 调整以下配置
cluster.name: elasticsearch.od.com
node.name: hdss7-12.host.com
path.data: /data/elasticsearch/data
path.logs: /data/elasticsearch/logs
bootstrap.memory_lock: true
network.host: 10.4.7.12
http.port: 9200
[root@hdss7-12 ~]# vim /opt/apps/elasticsearch/config/jvm.options # 默认1g
......
# 生产中一般不超过32G
-Xms512m
-Xmx512m
[root@hdss7-12 ~]# useradd -M es
[root@hdss7-12 ~]# mkdir -p /data/elasticsearch/{logs,data}
[root@hdss7-12 ~]# chown -R es.es /data/elasticsearch /opt/release/elasticsearch-6.8.6

[root@hdss7-12 ~]# vim /etc/security/limits.conf 
......
es hard nofile 65536
es soft fsize unlimited
es hard memlock unlimited
es soft memlock unlimited
[root@hdss7-12 ~]# echo "vm.max_map_count=262144" >> /etc/sysctl.conf ; sysctl -p

[root@hdss7-12 ~]# su es -c "/opt/apps/elasticsearch/bin/elasticsearch -d" # 启动
[root@hdss7-12 ~]# su es -c "/opt/apps/elasticsearch/bin/elasticsearch -d -p /data/elasticsearch/logs/pid" # 指定pid记录的文件
[root@hdss7-12 ~]# netstat -lntp | grep 9.00
tcp6       0      0 10.4.7.12:9200          :::*                    LISTEN      69352/java          
tcp6       0      0 10.4.7.12:9300          :::*                    LISTEN      69352/java
[root@hdss7-12 ~]# su es -c "ps aux|grep -v grep|grep java|grep elasticsearch|awk '{print \$2}'|xargs kill" # kill Pid
[root@hdss7-12 ~]# pkill -F /data/elasticsearch/logs/pid

# 添加k8s日志索引模板
[root@hdss7-12 ~]# curl -H "Content-Type:application/json" -XPUT http://10.4.7.12:9200/_template/k8s -d '{
  "template" : "k8s*",
  "index_patterns": ["k8s*"],  
  "settings": {
    "number_of_shards": 5,
    "number_of_replicas": 0
  }
}'

3. 部署Kafka

3.1. 部署Kafka

Kafka需要是有状态的服务，一般部署在Kubernetes之外，本次部署在 hdss7-11.host.com(10.4.7.11)。由于后面需要部署的Kafka-manager只支持到 2.2.0 版本，因此这次部署采用kafka_2.12-2.2.0版本，其中2.12为Scala版本号。

[root@hdss7-11 src]# wget https://archive.apache.org/dist/kafka/2.2.0/kafka_2.12-2.2.0.tgz
[root@hdss7-11 src]# tar -xf kafka_2.12-2.2.0.tgz -C /opt/release/
[root@hdss7-11 src]# ln -s /opt/release/kafka_2.12-2.2.0 /opt/apps/kafka

[root@hdss7-11 ~]# vim /opt/apps/kafka/config/server.properties
......
log.dirs=/data/kafka/logs
# 超过10000条日志强制刷盘，超过1000ms刷盘
log.flush.interval.messages=10000
log.flush.interval.ms=1000
# 填写需要连接的 zookeeper 集群地址，当前连接本地的 zk 集群。
zookeeper.connect=localhost:2181
# 新增以下两项
delete.topic.enable=true
host.name=hdss7-11.host.com
[root@hdss7-11 ~]# mkdir -p /data/kafka/logs
[root@hdss7-11 ~]# /opt/apps/kafka/bin/kafka-server-start.sh -daemon /opt/apps/kafka/config/server.properties
[root@hdss7-11 ~]# netstat -lntp|grep 121952
tcp6       0      0 10.4.7.11:9092          :::*                    LISTEN      121952/java         
tcp6       0      0 :::41211                :::*                    LISTEN      121952/java

3.2. 部署Kafka-manager

Kafka-manager是一款管理Kafka集群的软件，建议安装，github地址: https://github.com/yahoo/CMAK。如果采用交付到k8s集群，会稍微麻烦一些。

3.2.1. 镜像制作

# 这里存在几个问题：
# 1. kafka-manager 改名为 CMAK，压缩包名称和内部目录名发生了变化
# 2. sbt 编译需要下载很多依赖，因为不可描述的原因，速度非常慢，个人非VPN网络大概率失败
# 3. 因本人不具备VPN条件，编译失败。又因为第一条，这个dockerfile大概率需要修改
# 4. 生产环境中一定要自己重新做一份！
FROM hseeberger/scala-sbt

ENV ZK_HOSTS=localhost:2181 \
    KM_VERSION=2.0.0.2

RUN mkdir -p /tmp && \
    cd /tmp && \
    wget https://github.com/yahoo/kafka-manager/archive/${KM_VERSION}.tar.gz && \
    tar xf ${KM_VERSION}.tar.gz && \
    cd /tmp/kafka-manager-${KM_VERSION} && \
    sbt clean dist && \
    unzip  -d / ./target/universal/kafka-manager-${KM_VERSION}.zip && \
    rm -fr /tmp/${KM_VERSION} /tmp/kafka-manager-${KM_VERSION}

WORKDIR /kafka-manager-${KM_VERSION}
EXPOSE 9000
ENTRYPOINT ["./bin/kafka-manager","-Dconfig.file=conf/application.conf"]

[root@hdss7-200 ~]# docker image pull linuxduduniao/kafka-manager:v2.0.0.2
[root@hdss7-200 ~]# docker image tag linuxduduniao/kafka-manager:v2.0.0.2 harbor.od.com/public/kafka-manager:v2.0.0.2
[root@hdss7-200 ~]# docker image push harbor.od.com/public/kafka-manager:v2.0.0.2

3.2.2. 资源配置清单

apiVersion: apps/v1
kind: Deployment
metadata:
  name: kafka-manager
  namespace: infra
  labels: 
    name: kafka-manager
spec:
  replicas: 1
  selector:
    matchLabels: 
      app: kafka-manager
  template:
    metadata:
      labels: 
        app: kafka-manager
    spec:
      containers:
      - name: kafka-manager
        image: harbor.od.com/public/kafka-manager:v2.0.0.2
        ports:
        - containerPort: 9000
          protocol: TCP
        env:
        - name: ZK_HOSTS
          value: zk1.od.com:2181
        - name: APPLICATION_SECRET
          value: letmein

apiVersion: v1
kind: Service
metadata: 
  name: kafka-manager
  namespace: infra
spec:
  ports:
  - protocol: TCP
    port: 9000
    targetPort: 9000
  selector: 
    app: kafka-manager

apiVersion: extensions/v1beta1
kind: Ingress
metadata: 
  name: kafka-manager
  namespace: infra
spec:
  rules:
  - host: kafka-manager.od.com
    http:
      paths:
      - path: /
        backend: 
          serviceName: kafka-manager
          servicePort: 9000

3.2.3. 应用资源配置清单

[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/devops/ELK/kafka-manager/deployment.yaml
[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/devops/ELK/kafka-manager/service.yaml
[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/devops/ELK/kafka-manager/ingress.yaml

[root@hdss7-11 ~]# cat /var/named/od.com.zone
......
kafka-manager      A    10.4.7.10
[root@hdss7-11 ~]# systemctl restart named
[root@hdss7-11 ~]# host kafka-manager.od.com
kafka-manager.od.com has address 10.4.7.10

4. 使用filebeat

4.1. 制作filebeat镜像

# 当前的Dockerfile 是从老男孩教育的资料中拷贝的
# 官网有现成的docker镜像可以考虑使用: https://www.elastic.co/guide/en/beats/filebeat/current/running-on-docker.html
FROM debian:jessie

ENV FILEBEAT_VERSION=7.4.0 \
    FILEBEAT_SHA1=c63bb1e16f7f85f71568041c78f11b57de58d497ba733e398fa4b2d071270a86dbab19d5cb35da5d3579f35cb5b5f3c46e6e08cdf840afb7c347777aae5c4e11

RUN set -x && \
  apt-get update && \
  apt-get install -y wget && \
  wget https://artifacts.elastic.co/downloads/beats/filebeat/filebeat-${FILEBEAT_VERSION}-linux-x86_64.tar.gz -O /opt/filebeat.tar.gz && \
  cd /opt && \
  echo "${FILEBEAT_SHA1}  filebeat.tar.gz" | sha512sum -c - && \
  tar xzvf filebeat.tar.gz && \
  cd filebeat-* && \
  cp filebeat /bin && \
  cd /opt && \
  rm -rf filebeat* && \
  apt-get purge -y wget && \
  apt-get autoremove -y && \
  apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

COPY docker-entrypoint.sh /
ENTRYPOINT ["/docker-entrypoint.sh"]

# 因为通过wget下载filebeat速度太慢，采用windows环境中下载好的压缩包直接ADD到镜像中
FROM debian:jessie
ADD filebeat-7.4.0-linux-x86_64.tar.gz /opt/
RUN set -x && cp /opt/filebeat-*/filebeat /bin && rm -fr /opt/filebeat* 
COPY entrypoint.sh /
ENTRYPOINT ["/entrypoint.sh"]

[root@hdss7-200 filebeat]# cat entrypoint.sh 
#!/bin/bash
ENV=${ENV:-"dev"}  # 运行环境
PROJ_NAME=${PROJ_NAME:-"no-define"}  # project 名称,关系到topic
MULTILINE=${MULTILINE:-"^\d{2}"}     # 多行匹配，根据日志格式来定
KAFKA_ADDR=${KAFKA_ADDR:-'"10.4.7.11:9092"'}
cat > /etc/filebeat.yaml << EOF
filebeat.inputs:
- type: log
  fields_under_root: true
  fields:
    topic: logm-${PROJ_NAME}
  paths:
    - /logm/*.log
    - /logm/*/*.log
    - /logm/*/*/*.log
    - /logm/*/*/*/*.log
    - /logm/*/*/*/*/*.log
  scan_frequency: 120s
  max_bytes: 10485760
  multiline.pattern: '$MULTILINE'
  multiline.negate: true
  multiline.match: after
  multiline.max_lines: 100
- type: log
  fields_under_root: true
  fields:
    topic: logu-${PROJ_NAME}
  paths:
    - /logu/*.log
    - /logu/*/*.log
    - /logu/*/*/*.log
    - /logu/*/*/*/*.log
    - /logu/*/*/*/*/*.log
    - /logu/*/*/*/*/*/*.log
output.kafka:
  hosts: [${KAFKA_ADDR}]
  topic: k8s-fb-$ENV-%{[topic]}
  version: 2.0.0
  required_acks: 0
  max_message_bytes: 10485760
EOF

set -xe

if [[ "$1" == "" ]]; then
     exec filebeat  -c /etc/filebeat.yaml 
else
    exec "$@"
fi

[root@hdss7-200 filebeat]# chmod +x entrypoint.sh
[root@hdss7-200 filebeat]# docker image build . -t harbor.od.com/public/filebeat:v7.4.0
[root@hdss7-200 filebeat]# docker image push harbor.od.com/public/filebeat:v7.4.0

4.2. 运行dubbo消费者

# 本deployment修改的是 apollo 章节中 dev 环境下 dubbo-demo-consumer 服务
# 需要apollo、生产者启动
# reference: https://www.yuque.com/duduniao/ww8pmw/pvwdlq#CPLkT
apiVersion: apps/v1
kind: Deployment
metadata:
  name: dubbo-demo-consumer
  namespace: dev
  labels: 
    name: dubbo-demo-consumer
spec:
  replicas: 1
  selector:
    matchLabels: 
      name: dubbo-demo-consumer
  template:
    metadata:
      labels: 
        app: dubbo-demo-consumer
        name: dubbo-demo-consumer
    spec:
      containers:
      - name: dubbo-demo-consumer
        image: harbor.od.com/app/dubbo-demo-consumer:tomcat_20200209_1149
        ports:
        - containerPort: 8080
          protocol: TCP
        env:
        - name: C_OPTS
          value: -Denv=dev -Dapollo.meta=http://config-dev.od.com
        volumeMounts:
        - mountPath: /opt/tomcat/logs
          name: logm
      - name: filebeat
        image: harbor.od.com/public/filebeat:v7.4.0
        env:
        - name: ENV
          value: dev
        - name: PROJ_NAME
          value: dubbo-demo-consumer
        - name: KAFKA_ADDR
          value: '"10.4.7.11:9092"'
        volumeMounts:
        - mountPath: /logm
          name: logm
      volumes:
      - emptyDir: {}
        name: logm
      imagePullSecrets:
      - name: harbor

[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/dev/dubbo-demo-consumer/deployment.yaml

5. 部署logstash

5.1. 制作logstash镜像

[root@hdss7-200 ~]# docker image pull logstash:6.8.3
[root@hdss7-200 ~]# docker image tag logstash:6.8.3 harbor.od.com/public/logstash:v6.8.3
[root@hdss7-200 ~]# docker image push harbor.od.com/public/logstash:v6.8.3

5.2. 启动logstash

# 启动logstash，可以交付到k8s中，相关配置采用configmap方式挂载
# k8s在不同项目的名称空间中，可以创建不同的logstash，制定不同的索引
[root@hdss7-200 ~]# cat /etc/logstash/logstash-dev.conf
input {
  kafka {
    bootstrap_servers => "10.4.7.11:9092"
    client_id => "10.4.7.200"
    consumer_threads => 4
    group_id => "k8s_dev"
    topics_pattern => "k8s-fb-dev-.*"
  }
}

filter {
  json {
    source => "message"
  }
}

output {
  elasticsearch {
    hosts => ["10.4.7.12:9200"]
    index => "k8s-dev-%{+YYYY.MM}"
  }
}
[root@hdss7-200 ~]# docker run -d --name logstash-dev -v /etc/logstash:/etc/logstash harbor.od.com/public/logstash:v6.8.3 -f /etc/logstash/logstash-dev.conf
024fa2bda8157710212a860a68ca869ffc09fef706907ca63e8b920db394cade

6. Kibana部署

6.1. 准备镜像

[root@hdss7-200 ~]# docker pull kibana:6.8.3
[root@hdss7-200 ~]# docker image tag kibana:6.8.3 harbor.od.com/public/kibana:v6.8.3
[root@hdss7-200 ~]# docker image push harbor.od.com/public/kibana:v6.8.3

6.2. 准备资源配置清单

apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: infra
  labels: 
    name: kibana
spec:
  replicas: 1
  selector:
    matchLabels: 
      name: kibana
  template:
    metadata:
      labels: 
        app: kibana
        name: kibana
    spec:
      containers:
      - name: kibana
        image: harbor.od.com/public/kibana:v6.8.3
        ports:
        - containerPort: 5601
          protocol: TCP
        env:
        - name: ELASTICSEARCH_URL
          value: http://10.4.7.12:9200

apiVersion: v1
kind: Service
metadata: 
  name: kibana
  namespace: infra
spec:
  ports:
  - protocol: TCP
    port: 80
    targetPort: 5601
  selector: 
    app: kibana

apiVersion: extensions/v1beta1
kind: Ingress
metadata: 
  name: kibana
  namespace: infra
spec:
  rules:
  - host: kibana.od.com
    http:
      paths:
      - path: /
        backend: 
          serviceName: kibana
          servicePort: 80

6.3. 应用资源配置清单

[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/devops/ELK/kibana/deployment.yaml
[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/devops/ELK/kibana/ingress.yaml
[root@hdss7-21 ~]# kubectl apply -f http://k8s-yaml.od.com/devops/ELK/kibana/service.yaml

[root@hdss7-11 ~]# vim /var/named/od.com.zone 
......
kibana             A    10.4.7.10
[root@hdss7-11 ~]# systemctl restart named

6.4. 配置Kibana索引分组

6.5. 多环境收日志

# 环境准备分为两步
# 1. 启动测试环境(fat)中dubbo-demo-consumer(tomcat)版本pod，参考4.2
# 2. 启动收集fat日志的logstash
[root@hdss7-200 ~]# docker run -d --name logstash-fat -v /etc/logstash:/etc/logstash harbor.od.com/public/logstash:v6.8.3 -f /etc/logstash/logstash-fat.conf

[root@hdss7-21 ~]# curl http://10.4.7.12:9200/_cat/indices?v
health status index                           uuid                   pri rep docs.count docs.deleted store.size pri.store.size
green  open   k8s-dev-2020.02                 rReG1iadTqulQhzGfPH6RQ   5   0        137            0    488.3kb        488.3kb
green  open   k8s-fat-2020.02                 8TaKkfvCQzeDgSOba2-R4Q   5   0          8            0       63kb           63kb
......

7. 说明

当前实验中，仅仅是演示一种在Kubernetes环境下日志采集方案，实际生产环境下，需要对日志字段进行更加详细的补充和拆分，否则无法高效的检索和排错，一般在两个方面去实现，在filebeat输入侧添加更多的字段信息，在logstash侧进行日志字段拆分和清洗。另外还需要在ELK进行安全加固。这部分内容可以参考我的另一篇ELK博客，实现举一反三。
https://www.yuque.com/docs/share/36e6efbc-4eea-4082-973f-631eca4cdde5?# 《01-1-ELK集群安装》

04-4-日志收集