日志收集过程

收集,能够采集多种来源的日志数据(流式日志收集齐)
传输,能够稳定的吧日志传输到中央系统;ElasticSearch可以通过9200http方式传输,也可以通过

架构

在这里插入图片描述

安装elasticsearch-6.8.6

服务部署在21上

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

~]# grep -Ev "^$|^#" /opt/apps/elasticsearch/config/elasticsearch.yml # 调整以下配置
cluster.name: elasticsearch.host.com
path.data: /data/elasticsearch/data
path.logs: /data/elasticsearch/logs
bootstrap.memory_lock: true
network.host: 172.16.0.21
http.port: 9200
~]# vim /opt/apps/elasticsearch/config/jvm.options # 默认1g
......
# 生产中一般不超过32G
-Xms16g
-Xmx16g
~]# useradd -M es
~]# mkdir -p /data/elasticsearch/{logs,data}
~]# chown -R es.es /data/elasticsearch /opt/release/elasticsearch-6.8.6

## 修改es用户的内核配置
~]# vim /etc/security/limits.conf 
......
es hard nofile 65536
es soft fsize unlimited
es hard memlock unlimited
es soft memlock unlimited
~]# echo "vm.max_map_count=262144" >> /etc/sysctl.conf ; sysctl -p 

# 管理es命令
 ~]# su es -c "/opt/apps/elasticsearch/bin/elasticsearch -d" # 启动
 ~]# su es -c "/opt/apps/elasticsearch/bin/elasticsearch -d -p /data/elasticsearch/logs/pid" # 指定pid记录的文件启动es
 ~]# 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
 ~]# su es -c "ps aux|grep -v grep|grep java|grep elasticsearch|awk '{print \$2}'|xargs kill" # kill Pid
 ~]# pkill -F /data/elasticsearch/logs/pid

# 添加k8s日志索引模板
 ~]# curl -H "Content-Type:application/json" -XPUT http://172.16.0.21:9200/_template/k8s -d '{
  "template" : "k8s*",
  "index_patterns": ["k8s*"],  
  "settings": {
    "number_of_shards": 5,
    "number_of_replicas": 0
  }
}'

安装kafka

最好不要超过2.2版本,超过之后kafka_manager就不再支持

 src]# wget https://archive.apache.org/dist/kafka/2.2.0/kafka_2.12-2.2.0.tgz
 src]# tar -xf kafka_2.12-2.2.0.tgz -C /opt/release/
 src]# ln -s /opt/release/kafka_2.12-2.2.0 /opt/apps/kafka
 
 ~]# vim /opt/apps/kafka/config/server.properties
 ~]# 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
listeners=PLAINTEXT://172.16.0.21:9092
 # 启动kafka之前需要先启动zookeeper
/opt/apps/kafka/bin/zookeeper-server-start.sh -daemon /opt/apps/kafka/config/zookeeper.properties
 ~]# mkdir -p /data/kafka/logs
 ~]# /opt/apps/kafka/bin/kafka-server-start.sh -daemon /opt/apps/kafka/config/server.properties
 ~]# netstat -lntp|grep 121952
tcp6       0      0 10.4.7.11:9092          :::*                    LISTEN      121952/java         
tcp6       0      0 :::41211                :::*                    LISTEN      121952/java
# 查询kafka的topic是否创建成功
/opt/apps/kafka/bin/kafka-topics.sh --list --zookeeper localhost:2181

kafka-manager 安装

配置dockerfile
kafka-manager 改名为 CMAK,压缩包名称和内部目录名发生了变化,后续安装

# 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"]
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: 172.16.1.10:8900/public/kafka-manager:v2.0.0.2
        ports:
        - containerPort: 9000
          protocol: TCP
        env:
        - name: ZK_HOSTS
          value: zk1.host.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.host.com
    http:
      paths:
      - path: /
        backend: 
          serviceName: kafka-manager
          servicePort: 9000

安装filebeat

日志收集服务使用filebeat,因为传统的ruby收集的日志的方式十分消耗资源;其与业务服务采用边车模式运行;通过挂载卷的方式共享业务容器中的日志
ps:

  1. 在k8s的yaml文件中定义containers时,同时定义的容器就是以边车模式运行的
  2. docker的边车模式下两个容器共享了网络名称空间,USER(用户名称空间)和UTS(时间),隔离了IPC(进程空间)和文件系统
    注意点:要与elasticsearch版本一致

制作镜像

# windows环境中下载好的压缩包直接ADD到镜像中 https://artifacts.elastic.co/downloads/beats/filebeat/filebeat-7.4.0-linux-x86_64.tar.gz
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"]
filebeat]# cat docker-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:-'"172.16.0.21:9092"'}
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

docker build -t 172.16.1.10:8900/filebeat:v7.4.0 . 创建docker镜像
docker push 172.16.1.10:8900/filebeat:v7.4.0 推送镜像到仓库

在spinnaker中配置日志收集容器filebeat

  1. 配置emptydir类型的存储卷;将/logm下的文件挂载到该配置卷下;将业务容器的日志同样挂载到该存储卷下;
  2. 配置环境变量,在filebeat.yaml配置文件中的所有环境变量都可以配置到容器环境变量中,有项目名称$PROJ_NAME,环境名称$ENV,多行匹配正则规则$MULTILINE

部署logstash

版本要求:与elasticsearch一致
启动方式:开发和生产环境各使用docker run启动一份
部署步骤:

# 下载镜像
~]# docker image pull logstash:6.8.3
~]# docker image tag logstash:6.8.3 172.16.1.10:8900/logstash:6.8.3
~]# docker image push 172.16.1.10:8900/logstash:6.8.3
cat /etc/logstash/logstash-dev.conf
input {
  kafka {
    bootstrap_servers => "172.16.0.21:9092"
    client_id => "172.16.0.21"
    consumer_threads => 4
    group_id => "k8s_dev"
    topics_pattern => "k8s-fb-dev-.*"
  }
}

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

output {
  elasticsearch {
    hosts => ["172.16.0.21:9200"]
    index => "k8s-dev-%{+YYYY.MM}"
  }
}

# 运行logstash dev环境的日志收集
docker run -d --name logstash-dev -v /etc/logstash:/etc/logstash 172.16.1.10:8900/logstash:v6.8.3 -f /etc/logstash/logstash-dev.conf

kibana部署

~]# docker pull kibana:6.8.3
~]# docker image tag kibana:6.8.3 172.16.1.10:8900/kibana:6.8.3
~]# docker image push 172.16.1.10:8900/kibana:6.8.3

pd控制器资源配置清单 dp.yml文件

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: 172.16.1.10:8900/kibana:6.8.3
        ports:
        - containerPort: 5601
          protocol: TCP
        env:
        - name: ELASTICSEARCH_URL
          value: http://172.16.0.21:9200

service资源配置清单 svc.yml

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

ingress资源配置清单 ingress.yml

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

应用资源配置清单
添加kibana.host.com域名到bind9服务

kibana使用

  1. 初始化kibana,点击Explore on my own按钮;协助优化kibana,选择NO;Monitoring选项中,点击Turn On,开启监控,可以查询es的状态及索引;

  2. 在Management中,配置index,使用logstash中建立index的规则名称去匹配,之后选择kibana中默认的@timestamp时间戳规则,创建index patterns
    index patterns

  3. 看日志,选择Discover,选择器的使用

    1. 时间选择器quick,相对时间,绝对时间
    2. 环境选择器,对应建立的es-index,通过环境变量传递的
    3. 项目选择器(Filter功能的topic选项),对应topic名称,是通过环境变量传递的
    4. 关键字选择器;支持lusen的查询语法
      在这里插入图片描述
  4. 配置常用字段
    Time, message, log.file.path, hostname

  5. 落盘的日志直接filebeat收集;没有落盘的日志,统一输出重定向command >> /opt/logs/*.log 2>&1

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