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  • GO开发:用go写个日志监控系统

    日志收集系统架构

    1.项目背景

    a. 每个系统都有日志,当系统出现问题时,需要通过日志解决问题

    b. 当系统机器比较少时,登陆到服务器上查看即可满足

    c. 当系统机器规模巨大,登陆到机器上查看几乎不现实

    2.解决方案

    a. 把机器上的日志实时收集,统一的存储到中心系统

    b. 然后再对这些日志建立索引,通过搜索即可以找到对应日志

    c. 通过提供界面友好的web界面,通过web即可以完成日志搜索

    面临的问题

    a. 实时日志量非常大,每天几十亿条

    b. 日志准实时收集,延迟控制在分钟级别

    c. 能够水平可扩展

    ELK介绍

    •官网https://www.elastic.co/cn/

    • 中文指南https://www.gitbook.com/book/chenryn/elk-stack-guide-cn/details

    • ELKStack (5.0版本之后)--> ElasticStack == (ELKStack + Beats)

    • ELK Stack包含:ElasticSearch、Logstash、Kibana

    • ElasticSearch是一个搜索引擎,用来搜索、分析、存储日志。它是分布式的,也就是说可以横向扩容,可以自动发现,索引自动分片,总之很强大。文档https://www.elastic.co/guide/cn/elasticsearch/guide/current/index.html

    • Logstash用来采集日志,把日志解析为json格式交给ElasticSearch。

    • Kibana是一个数据可视化组件,把处理后的结果通过web界面展示

    • Beats在这里是一个轻量级日志采集器,其实Beats家族有5个成员

    • 早期的ELK架构中使用Logstash收集、解析日志,但是Logstash对内存、cpu、io等资源消耗比较高。相比 Logstash,Beats所占系统的CPU和内存几乎可以忽略不计

    • x-pack对ElasticStack提供了安全、警报、监控、报表、图表于一身的扩展包,是收费的

    elk

    elk方案问题

    a. 运维成本高,每增加一个日志收集,都需要手动修改配置

    b. 监控缺失,无法准确获取logstash的状态

    c. 无法做定制化开发以及维护

    日志收集系统设计

    kafka

    Kafka消息队列

    数据解耦

    a. Log Agent,日志收集客户端,用来收集服务器上的日志

    b. Kafka,高吞吐量的分布式队列,linkin开发,apache顶级开源项目

    c. ES,elasticsearch,开源的搜索引擎,提供基于http restful的web接口

    d. Hadoop,分布式计算框架,能够对大量数据进行分布式处理的平台

    zookeeper

    Zookeeper 作为一个分布式的服务框架,主要用来解决分布式集群中应用系统的一致性问题,它能提供基于类似于文件系统的目录节点树方式的数据存储, Zookeeper 作用主要是用来维护和监控存储的数据的状态变化,通过监控这些数据状态的变化,从而达到基于数据的集群管理

    简单的说,zookeeper=文件系统+通知机制

    a. 安装JDK,从oracle下载最新的SDK安装

    b. 安装zookeeper3.3.6,下载地址:http://apache.fayea.com/zookeeper/

    1)mv conf/zoo_sample.cfg conf/zoo.cfg

    2)编辑 conf/zoo.cfg,修改dataDir

    # the directory where the snapshot is stored.
    dataDir=/tmp/zookeeper/data
    # the port at which the clients will connect
    clientPort=2181
    dataLogDir=/tmp/zookeeper/log
    

    3)vim /etc/profile

    export PATH=$PATH:/usr/local/zookeeper/bin

    source /etc/profile

    运行:

    [root@greg02 zookeeper]#zkServer.sh start
    JMX enabled by default
    Using config: /usr/local/zookeeper/bin/../conf/zoo.cfg
    Starting zookeeper ... STARTED
    

    kafka

    1.打开链接:http://kafka.apache.org/downloads.html

    下载https://www.apache.org/dyn/closer.cgi?path=/kafka/0.11.0.2/kafka_2.12-0.11.0.2.tgz

    2.打开config目录下的server.properties, 修改log.dirs为D:kafka_logs,修改advertised.host.name=服务器ip

    3.启动kafka

    [root@greg02 kafka]#kafka-server-start.sh config/server.properties 
    

    kafka消费者开启

    [root@greg02 kafka]#kafka-console-consumer.sh --topic nginx_log --zookeeper 127.0.0.1 2181
    Using the ConsoleConsumer with old consumer is deprecated and will be removed in a future major release. Consider using the new consumer by passing [bootstrap-server] instead of [zookeeper].
    [2018-02-05 18:30:22,451] WARN Connected to an old server; r-o mode will be unavailable (org.apache.zookeeper.ClientCnxnSocket)
    [2018-02-05 18:30:22,597] WARN Connected to an old server; r-o mode will be unavailable (org.apache.zookeeper.ClientCnxnSocket)
    
    

    go kafka

    package main
    
    import (
       "fmt"
       "time"
       "github.com/Shopify/sarama"
    )
    
    func main() {
       config := sarama.NewConfig()
       config.Producer.RequiredAcks = sarama.WaitForAll
       config.Producer.Partitioner = sarama.NewRandomPartitioner
       config.Producer.Return.Successes = true
    
       client, err := sarama.NewSyncProducer([]string{"192.168.179.130:9092"}, config)
       if err != nil {
          fmt.Println("producer close, err:", err)
          return
       }
    
       defer client.Close()
       msg := &sarama.ProducerMessage{}
       msg.Topic = "nginx_log"
       msg.Value = sarama.StringEncoder("this is a good test, my message is good")
    
       pid, offset, err := client.SendMessage(msg)
       if err != nil {
          fmt.Println("send message failed,", err)
          return
       }
    
       fmt.Printf("pid:%v offset:%v
    ", pid, offset)
       time.Sleep(10 * time.Millisecond)
    }
    

    linux tail命令

    ​ -f 用于循环读取文件的内容,监视文件的增长

    ​ -F 与-f类似,区别在于当将监视的文件删除重建后-F仍能监视该文件内容-f则不行,-F有重试的功能,会不断重试

    package main
    
    import (
       "fmt"
       "github.com/hpcloud/tail"
       "time"
    )
    func main() {
       filename := "/root/passwd"
       tails, err := tail.TailFile(filename, tail.Config{
          ReOpen:    true,
          Follow:    true,
          //Location:  &tail.SeekInfo{Offset: 0, Whence: 2},
          MustExist: false,  
             Poll:      true,
       })
       if err != nil {
          fmt.Println("tail file err:", err)
          return
       }
       var msg *tail.Line
       var ok bool
       for true {
          msg, ok = <-tails.Lines
          if !ok {
             fmt.Printf("tail file close reopen, filename:%s
    ", tails.Filename)
             time.Sleep(100 * time.Millisecond)
             continue
          }
          fmt.Println("msg:", msg)
       }
    }
    

    配置文件库使用

    1. 初始化配置库

      iniconf, err := NewConfig("ini", "testini.conf")
      if err != nil {
          t.Fatal(err)
      }
      
    2. 读取配置项

    	•	String(key string) string
    	•	Int(key string) (int, error)
    	•	Int64(key string) (int64, error)
    	•	Bool(key string) (bool, error)
    	•	Float(key string) (float64, error)
    

    cofig的go实现

    package main
    
    import (
       "fmt"
       "github.com/astaxie/beego/config"
    )
    
    func main() {
       conf, err := config.NewConfig("ini", "./logagent.conf")
       if err != nil {
          fmt.Println("new config failed, err:", err)
          return
       }
    
       port, err := conf.Int("server::port")
       if err != nil {
          fmt.Println("read server:port failed, err:", err)
          return
       }
    
       fmt.Println("Port:", port)
       log_level := conf.String("logs::log_level")
       if len(log_level) == 0 {
          log_level = "debug"
       }
    
       fmt.Println("log_level:", log_level)
    
       log_path := conf.String("logs::log_path")
       fmt.Println("log_path:", log_path)
    }
    

    日志库的使用

    1. 配置log组件

           config := make(map[string]interface{})
      	config["filename"] = "./logs/logcollect.log"
      	config["level"] = logs.LevelDebug
      
      	configStr, err := json.Marshal(config)
      	if err != nil {
      		fmt.Println("marshal failed, err:", err)
      		return
      	}
      
    2. 初始化日志组件

      logs.SetLogger(“file”, string(configStr))
      

      写日志

      package main
      
      import (
         "encoding/json"
         "fmt"
         "github.com/astaxie/beego/logs"
      )
      
      func main() {
         config := make(map[string]interface{})
         config["filename"] = "/root/logs/logcollect.log"
         config["level"] = logs.LevelDebug
      
         configStr, err := json.Marshal(config)
         if err != nil {
            fmt.Println("marshal failed, err:", err)
            return
         }
      
         logs.SetLogger(logs.AdapterFile, string(configStr))
      
         logs.Debug("this is a test, my name is %s", "stu01")
         logs.Trace("this is a trace, my name is %s", "stu02")
         logs.Warn("this is a warn, my name is %s", "stu03")
      }
      
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  • 原文地址:https://www.cnblogs.com/ningxin18/p/8416816.html
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