基于docker-compose编排elk6.6+filebeat6.6.2+kafka2.1.1部署日志收集平台

#需求：
做一个收集Nginx的access log和error log并绘制图表
#解决方案
采用filebeat6.6.2在Nginx应用服务器上收集日志，经过kafka2.1.1（zookeeper集群）消息队列中间件传入到logstash进行过滤解析，然后存储到elasticsearch，最终由kibana进行查询和制图。并且elk、filebeat和kafka都采用docker的方式进行部署，采用docker-compose进行编排方便线上的维护

使用filebeat的原因：对比logstash，filebeat更加轻量，且消耗资源更少

采用kafka作为中间件原因：避免直接传入logstash引起的io瓶颈，同时具有较高吞吐量，而且比较稳定，处理消息的效率很高

PS：当看到kibana正常load数据的时候，有几点感触
1.一定要好好看elk和filebeat的官方文档，知道filebeat的output和logstash的input的各个参数使用
2.使用docker部署kafka & zookeeper会有个坑，可能也是楼主对docker网络和kafka不熟悉的原因造成的

#实际场景

应用程序	虚拟机IP
Nginx	10.150.33.123

#部署情况

应用程序	虚拟机IP	备注	端口
Nginx	10.150.33.123	日志文件位于/var/log/nginx
filebeat	10.150.33.123
kafka & zookeeper	10.150.33.126	zookeeper集群，单机kafka	9092、2181
elk	10.150.33.126	需与kafka处于同一network	9200,5601,9300,5000,9600

#Nginx
/var/log/nginx下有文件，Nginx中的access和error日志格式是不同的，需要通过logstash进行处理

• www.test.com.access.log
• www.test.com.error.log
• api.test.com.access.log
• api.test.com.error.log
• openapi.test.com.access.log
• openapi.test.com.error.log

#filebeat部署
先看filebeat的目录结构如图

#####第一步：编辑Dockerfile

FROM docker.elastic.co/beats/filebeat:6.6.2
##enable Nginx modules，注意这里需要开启filebeat的Nginx模块
RUN /usr/share/filebeat/filebeat modules enable nginx
COPY filebeat.yml /usr/share/filebeat/filebeat.yml
USER root
RUN chown root:filebeat /usr/share/filebeat/filebeat.yml
USER filebeat

具体参考官方文档
#####第二步：编辑docker-compose.yml

version: '2.3'
services:
  beat:
    build:
      context: ${PWD}/.
    user: root
    environment:
      - BEAT_STRICT_PERMS=false
    restart: always
    volumes:
       #filebeat.yml作为配置文件，ro表示只读
      - ${PWD}/filebeat.yml:/usr/share/filebeat/filebeat.yml:ro
      #为了filebeat的module.d配置nginx.yml
      - ${PWD}/modules.d:/usr/share/filebeat/modules.d
      - /var/lib/docker/containers:/var/lib/docker/containers:ro
      # We launch docker containers to test docker autodiscover:
      - /var/run/docker.sock:/var/run/docker.sock
      #把logs和data共享出来
      - ${PWD}/logs:/usr/share/filebeat/logs
      - ${PWD}/data:/usr/share/filebeat/data

      ##为了读取外部的日志文件，开启共享，下面举例为读取外部Nginx的/var/logs/nginx里的日志
      - /var/log/nginx:/var/log/nginx
    extra_hosts:
     ## 这里是为了解决kafka的一个坑，需要在filebeat上作hosts的映射
      - "kafka:10.150.33.126"

#####第三步：编辑module.d的nginx.yml文件
可以通过下载filebeat的安装包然后把里面的module.d文件夹复制过来
然后把nginx.yml.disabled修改名为nginx.yml，然后编辑如下：

# Module: nginx
# Docs: https://www.elastic.co/guide/en/beats/filebeat/master/filebeat-module-nginx.html

- module: nginx
  # Access logs
  access:
    enabled: true
    # Set custom paths for the log files. If left empty,
    # Filebeat will choose the paths depending on your OS.
    #var.paths:
    var.paths: ["/var/log/nginx/*.test.com.access.log"]
    # Convert the timestamp to UTC. Requires Elasticsearch >= 6.1.
    var.convert_timezone: true
  # Error logs
  error:
    enabled: true
    # Set custom paths for the log files. If left empty,
    # Filebeat will choose the paths depending on your OS.
    var.paths: ["/var/log/nginx/*.test.com.error.log"]
    # Convert the timestamp to UTC. Requires Elasticsearch >= 6.1.
    var.convert_timezone: true

具体参考官方文档 Nginx Filebeat module
#####第四步：编辑filebeat.yml

###################### Filebeat Configuration Example #########################

# This file is an example configuration file highlighting only the most common
# options. The filebeat.reference.yml file from the same directory contains all the
# supported options with more comments. You can use it as a reference.
#
# You can find the full configuration reference here:
# https://www.elastic.co/guide/en/beats/filebeat/index.html

# For more available modules and options, please see the filebeat.reference.yml sample
# configuration file.

#=========================== Filebeat inputs =============================

filebeat.inputs:

# Each - is an input. Most options can be set at the input level, so
# you can use different inputs for various configurations.
# Below are the input specific configurations.

# - type: log

#   # Change to true to enable this input configuration.
#   enabled: false

#   # Paths that should be crawled and fetched. Glob based paths.
#   paths:
#     - /var/log/*.log
    #- c:\programdata\elasticsearch\logs\*

  # Exclude lines. A list of regular expressions to match. It drops the lines that are
  # matching any regular expression from the list.
  #exclude_lines: ['^DBG']

  # Include lines. A list of regular expressions to match. It exports the lines that are
  # matching any regular expression from the list.
  #include_lines: ['^ERR', '^WARN']

  # Exclude files. A list of regular expressions to match. Filebeat drops the files that
  # are matching any regular expression from the list. By default, no files are dropped.
  #exclude_files: ['.gz$']

  # Optional additional fields. These fields can be freely picked
  # to add additional information to the crawled log files for filtering
  #fields:
  #  level: debug
  #  review: 1

  ### Multiline options

  # Multiline can be used for log messages spanning multiple lines. This is common
  # for Java Stack Traces or C-Line Continuation

  # The regexp Pattern that has to be matched. The example pattern matches all lines starting with [
  #multiline.pattern: ^\[

  # Defines if the pattern set under pattern should be negated or not. Default is false.
  #multiline.negate: false

  # Match can be set to "after" or "before". It is used to define if lines should be append to a pattern
  # that was (not) matched before or after or as long as a pattern is not matched based on negate.
  # Note: After is the equivalent to previous and before is the equivalent to to next in Logstash
  #multiline.match: after


#============================= Filebeat modules ===============================

filebeat.config.modules:
  # Glob pattern for configuration loading
  ##加载modules的配置
  path: ${path.config}/modules.d/*.yml

  # Set to true to enable config reloading
  reload.enabled: true

  # Period on which files under path should be checked for changes
  #reload.period: 10s

#==================== Elasticsearch template setting ==========================

setup.template.settings:
  index.number_of_shards: 1
  #index.codec: best_compression
  #_source.enabled: false

#================================ General =====================================

# The name of the shipper that publishes the network data. It can be used to group
# all the transactions sent by a single shipper in the web interface.
##filebeat.name配不配都行
filebeat.name: "nginx"

# The tags of the shipper are included in their own field with each
# transaction published.
#tags: ["service-X", "web-tier"]
##filbeat.tags配不配都行
filebeat.tags: ["nginx", 'access', 'log', 'error']

# Optional fields that you can specify to add additional information to the
# output.
#fields:
#  env: staging


#============================== Dashboards =====================================
# These settings control loading the sample dashboards to the Kibana index. Loading
# the dashboards is disabled by default and can be enabled either by setting the
# options here, or by using the `-setup` CLI flag or the `setup` command.
#setup.dashboards.enabled: false

# The URL from where to download the dashboards archive. By default this URL
# has a value which is computed based on the Beat name and version. For released
# versions, this URL points to the dashboard archive on the artifacts.elastic.co
# website.
#setup.dashboards.url:

#============================== Kibana =====================================

# Starting with Beats version 6.0.0, the dashboards are loaded via the Kibana API.
# This requires a Kibana endpoint configuration.
#setup.kibana:

  # Kibana Host
  # Scheme and port can be left out and will be set to the default (http and 5601)
  # In case you specify and additional path, the scheme is required: http://localhost:5601/path
  # IPv6 addresses should always be defined as: https://[2001:db8::1]:5601
  #host: "localhost:5601"

  # Kibana Space ID
  # ID of the Kibana Space into which the dashboards should be loaded. By default,
  # the Default Space will be used.
  #space.id:

#============================= Elastic Cloud ==================================

# These settings simplify using filebeat with the Elastic Cloud (https://cloud.elastic.co/).

# The cloud.id setting overwrites the `output.elasticsearch.hosts` and
# `setup.kibana.host` options.
# You can find the `cloud.id` in the Elastic Cloud web UI.
#cloud.id:

# The cloud.auth setting overwrites the `output.elasticsearch.username` and
# `output.elasticsearch.password` settings. The format is `:`.
#cloud.auth:

#================================ Outputs =====================================

# Configure what output to use when sending the data collected by the beat.

#-------------------------- Elasticsearch output ------------------------------
# 这里我们不输出到es，果断注释掉
# output.elasticsearch:
#   # Array of hosts to connect to.
#   hosts: ["localhost:9200"]

  # Enabled ilm (beta) to use index lifecycle management instead daily indices.
  #ilm.enabled: false

  # Optional protocol and basic auth credentials.
  #protocol: "https"
  #username: "elastic"
  #password: "changeme"

#----------------------------- Logstash output --------------------------------
# 这里我们不输出到logstash，果断注释掉
# output.logstash:
#   # The Logstash hosts
#   hosts: ["0.0.0.0:5044"]

  # Optional SSL. By default is off.
  # List of root certificates for HTTPS server verifications
  #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"]

  # Certificate for SSL client authentication
  #ssl.certificate: "/etc/pki/client/cert.pem"

  # Client Certificate Key
  #ssl.key: "/etc/pki/client/cert.key"

#----------------------------- Redis output --------------------------------
# 这里我们不用redis作为中间件，所以注释掉，可以参考博主的配置，但最好看回官方文档了解每个参数的作用
# output.redis:
#   ## The redis hsots
#   hosts: ["10.150.33.126"]
#   ## redis password
#   ## password: "my_password"
#   datatype: "list"

#   key: "nginx_log"
#   # 存储的key
#   keys:
#     - key: "nginx_www_access_log"
#       when.equals:
#         source: "/var/log/nginx/logs/www.test.com.access.log"
#     - key: "nginx_openapi_access_log"
#       when.equals:
#         source: "/var/log/nginx/logs/openapi.test.com.access.log"
#     - key: "nginx_api_access_log"
#       when.equals:
#         source: "/var/log/nginx/logs/api.test.com.access.log"
#     - key: "nginx_www_error_log"
#       when.equals:
#         source: "/var/log/nginx/logs/www.test.com.error.log"
#     - key: "nginx_openapi_error_log"
#       when.equals:
#         source: "/var/log/nginx/logs/openapi.test.com.error.log"
#     - key: "nginx_api_error_log"
#       when.equals:
#         source: "/var/log/nginx/logs/api.test.com.error.log"


#   ##存储的db
#   db: 0
#   ##超时
#   timeout: 60


#----------------------------- Kafka output --------------------------------
output.kafka:

  ##kafka位于10.150.33.126上，这里由于在docker-compose.yml上做了映射，所以配置上kafka即可
  hosts: ["kafka:9092"]
  ##key: "nginx_log"
  #存储的key
  #为了针对不同的source文件分配不同的topic，这样后面可以在es上分配不同的index
  topics:
    - topic: "nginx-www-access-log"
      when.equals:
        source: "/var/log/nginx/www.test.com.access.log"
    - topic: "nginx-openapi-access-log"
      when.equals:
        source: "/var/log/nginx/openapi.test.com.access.log"
    - topic: "nginx-api-access-log"
      when.equals:
        source: "/var/log/nginx/api.test.com.access.log"
    - topic: "nginx-www-error-log"
      when.equals:
        source: "/var/log/nginx/www.test.com.error.log"
    - topic: "nginx-openapi-error-log"
      when.equals:
        source: "/var/log/nginx/openapi.test.com.error.log"
    - topic: "nginx-api-error-log"
      when.equals:
        source: "/var/log/nginx/api.test.com.error.log"
  ##超时
  timeout: 60

  ##partition策略必须为random、round_robin或者hash的其中一个

  ##在分区程序选择下一个分区之前，设置要发布到同一分区的事件数。默认值为1，表示每次事件后将选择下一个分区。
  partition.round_robin:
    reachable_only: false


  ##ACK可靠性级别要求，0：无响应，1：等待本地提交，-1：等待所有副本提交，默认值为1
  required_acks: 1

  ## none，snappy，lz4或gzip其中一个
  compression: gzip

  ##超过1000000字节的事件会被丢弃
  max_message_bytes: 100000000



#================================ Processors =====================================

# Configure processors to enhance or manipulate events generated by the beat.

processors:
  - add_host_metadata: ~
  - add_cloud_metadata: ~

#================================ Logging =====================================

# Sets log level. The default log level is info.
# Available log levels are: error, warning, info, debug
#logging.level: debug

# At debug level, you can selectively enable logging only for some components.
# To enable all selectors use ["*"]. Examples of other selectors are "beat",
# "publish", "service".
#logging.selectors: ["*"]

#============================== Xpack Monitoring ===============================
# filebeat can export internal metrics to a central Elasticsearch monitoring
# cluster.  This requires xpack monitoring to be enabled in Elasticsearch.  The
# reporting is disabled by default.

# Set to true to enable the monitoring reporter.
#xpack.monitoring.enabled: false

# Uncomment to send the metrics to Elasticsearch. Most settings from the
# Elasticsearch output are accepted here as well. Any setting that is not set is
# automatically inherited from the Elasticsearch output configuration, so if you
# have the Elasticsearch output configured, you can simply uncomment the
# following line.
#xpack.monitoring.elasticsearch:

具体参考官方文档如下：
filebeat.yml
filebeat.output for kafka

#####第五步：运行
在项目根目录中运行docker-compose up -d --build

#部署kafka2.1.1
kafka & zookeeper则采用 wurstmeister/kafka-docker
把代码拉下来
#####第一步：编辑docker-compose.yml

version: '2'
services:
  zookeeper:
    image: wurstmeister/zookeeper
    ports:
      - "2181:2181"
    restart: always

  kafka1:
    image: kafka_kafka1
    ports:
      ##防止容器被销毁后端口发生变化，而且部署的是kafka单机
      - "9092:9092"
    depends_on:
      ##确保在zookeeper后运行
      - zookeeper
    restart: always
    environment:
      ##固定broker_id为1，防止发生变化把以前的数据丢失了
      KAFKA_BROKER_ID: 1
      KAFKA_ADVERTISED_PORT: 9092
      ##保存数据的时间为168小时，配不配都行
      KAFKA_LOG_RETENTION_HOURS: "168"
      ##超过10000000字节的事件会被丢弃，配不配都行
      KAFKA_LOG_RETENTION_BYTES: "100000000"
      KAFKA_ADVERTISED_HOST_NAME: 172.19.0.3
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092
      KAFKA_LISTENERS: PLAINTEXT://kafka:9092
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      ##预先设好topic，1个leader和一个副本
      KAFKA_CREATE_TOPICS: "nginx-www-access-log:1:1,nginx-openapi-access-log:1:1,nginx-api-access-log:1:1,nginx-www-error-log:1:1,nginx-openapi-error-log:1:1,nginx-api-error-log:1:1"
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock
      - ./logs:/kafka
    extra_hosts:
      ##这里必须注意，要采用映射的方式，且172.19.0.3表示为kafka在docker网络里的ip，可以通过docker exec kafka1 bash ifconfig查看eth0中得到
      - "kafka:172.19.0.3"

#####第二步：运行
在项目根目录中运行docker-compose up -d --build

#部署elk6.6.1
采用的是 deviantony/docker-elk
把代码拉下来

#####第一步：编辑docker-compose.yml

version: '2.3'
services:
  elasticsearch:
    build:
      context: elasticsearch/
      args:
        ELK_VERSION: $ELK_VERSION
    container_name: elasticsearch
    volumes:
      - ./elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml:ro
    ports:
      - "9200:9200"
      - "9300:9300"
    restart: always
    environment:
      ##可用配置为docker的1/4，因为要和logstash平分docker的一半堆内存
      ##默认为docker的1/8，注意，设置太高会使得es的影响其他字段存储
      ##这里因为126机器为24g内存，所以设为3g
      ES_JAVA_OPTS: -Xms3g -Xmx3g
    networks:
      - elk

  logstash:
    build:
      context: logstash/
      args:
        ELK_VERSION: $ELK_VERSION
    container_name: logstash
    volumes:
      - ./logstash/config/logstash.yml:/usr/share/logstash/config/logstash.yml:ro
      - ./logstash/pipeline:/usr/share/logstash/pipeline:ro
      - ./logstash/template:/usr/share/logstash/template
    ports:
      - "5000:5000"
      - "9600:9600"
      - "5044:5044"  ##这是为了filebeat直接传入logstash，可以关闭该端口
    restart: always
    environment:
      ##可用配置为docker的1/4，因为要和es平分docker的一半堆内存
      ##默认为docker的1/8，注意，设置太高会使得es的影响其他字段存储
      ##这里因为126机器为24g内存，所以设为3g
      LS_JAVA_OPTS: "-Xmx3g -Xms3g"
    networks:
      - elk
    depends_on:
      - elasticsearch
    ##这里做host的映射
    extra_hosts:
      - "kafka:172.19.0.3"

  kibana:
    build:
      context: kibana/
      args:
        ELK_VERSION: $ELK_VERSION
    container_name: kibana
    volumes:
      - ./kibana/config/:/usr/share/kibana/config:ro
    ports:
      - "5601:5601"
    restart: always
    networks:
      - elk
    depends_on:
      - elasticsearch

##让elk能够和kafka处于同一网段，这样可以读取docker内部的kafka服务
networks:
  elk: 
    external:
      name: kafka_default  ##kafka_default是kakfa的默认网络

#####第二步：修改Dockerfile

ARG ELK_VERSION

# https://github.com/elastic/logstash-docker
FROM docker.elastic.co/logstash/logstash-oss:${ELK_VERSION}
##这是为了个让logstash支持kafka输入
##RUN logstash-plugin install logstash-input-beats
##RUN logstash-plugin install logstash-input-redis
RUN logstash-plugin install logstash-input-kafka

# Add your logstash plugins setup here
# Example: RUN logstash-plugin install logstash-filter-json

#####第三步：修改logstash/pipeline/logstash.conf

input {
	##这是支持filebeat input的配置
	##filebeat input
	# beats {
	# 	port => 5044
	# 	##codec => "json"
	# }

        ##支持Redis input的配置
	##Redis input
	# redis {
	# 	key => "nginx_www_access_log"
	# 	host => ["10.150.33.126"]
	# 	port => 6379
	# 	data_type => "list"
    #   db => 0
	# 	tags => ["nginx", "www", "access"]
	# }

        ##支持kafka input的配置
	##kafka input
	kafka {
		client_id => "beats"  ##由于filebeat默认为beats，必须要填写才能有数据进来
		bootstrap_servers => "kafka:9092"  ##填写对应的kafka所在机器的ip地址和端口，即对应在docker里的ip地址
		topics => ["nginx-www-access-log", "nginx-api-access-log", "nginx-openapi-access-log", "nginx-www-error-log", "nginx-api-error-log", "nginx-openapi-error-log"]  ##要订阅kafka的对应topic
		group_id => "beats"  ##设不设的问题都不大，最好设了，毕竟走通了
        consumer_threads => 3  
		codec => "json"  ##数据json化才能读取到message数据
		decorate_events => true  ##decorate_events开启后用mutate才可以拿到topic字段
	}
	
}

## Add your filters / logstash plugins configuration here

filter {

	mutate {

		##拿到@metadata嵌套里topic字段放到topic字段里
        copy => { "@metadata" => "meta" }
		add_field => { 
			"topic" => "%{[meta][topic]}" 
		 }
    }

    ##针对Nginx的access log进行解析
	if [fileset][name] == "access" {
		dissect {

			##匹配，dissect比grok更快更方便使用
			mapping => {
				"message" => '[%{logtime}] %{remote_addr} %{http_x_forwarded_for} %{remote_user} "%{request}" %{status_code} %{request_time} %{upstream_response_time} %{request_length} %{body_bytes_sent} "%{http_referer}" "%{http_user_agent}"'
				}

			##不在output中输出以下字段，节省空间
			remove_field => [
				"beat",
				"@version",
				"host",
				"meta",
				"message",
				"input",
				"offset",
				"source",
				"fileset",
				"event",
				"prospector",
				"log"
			]

			##字段类型转化，作为int可以在绘制图表的时候进行聚簇
			convert_datatype => {
				"request_length" => "int"
				"body_bytes_sent" => "int"
				"status_code" => "int"
			}
		}

		##日志生成的时间替换掉@timestamp（原本是入es的时间），这里替换掉进行日志按日切割
		date {
            ##这里的yyyy/MM/dd HH:mm:ss是因为error日志里的时间格式是这样，而不是你想要配置成这样的格式
			"match" => ["logtime", "dd/MMM/yyyy:HH:mm:ss Z"]
			"target" => "@timestamp"
  		}
		
	}
	
	##针对Nginx的error log进行解析
	if [fileset][name] == "error" {
		grok {

			##匹配error日志格式
            match => [ "message" , "(?%{YEAR}[./-]%{MONTHNUM}[./-]%{MONTHDAY}[- ]%{TIME}) \[%{LOGLEVEL:severity}\] %{POSINT:pid}#%{NUMBER}: %{GREEDYDATA:errormessage}(?:, client: (?%{IP}|%{HOSTNAME}))(?:, server: %{IPORHOST:server}?)(?:, request: %{QS:request})?(?:, upstream: (?\"%{URI}\"|%{QS}))?(?:, host: %{QS:request_host})?(?:, referrer: \"%{URI:referrer}\")?"]

            ##不在output中输出以下字段，节省空间
			remove_field => [
				"beat",
				"@version",
				"host",
				"meta",
				"message",
				"input",
				"offset",
				"source",
				"fileset",
				"event",
				"prospector",
				"log"
			]
		}

		##日志生成的时间替换掉@timestamp（原本是入es的时间），这里替换掉进行日志按日切割
		date {
            ##这里的yyyy/MM/dd HH:mm:ss是因为error日志里的时间格式是这样，而不是你想要配置成这样的格式
			"match" => ["logtime", "yyyy/MM/dd HH:mm:ss"]
			"target" => "@timestamp"
  		}
	}
}

output {

	##根据filebeat传过来的topic确定对应不同的access文件或者error文件，然后生成es的index
	if [topic] == "nginx-www-access-log" {
		elasticsearch {
				hosts => ["elasticsearch:9200"]
		    	index => "nginx_www_access_%{+YYYY.MM.dd}"  ##根据@timestamp进行index分割，即根据日志的生成时间进行分割
				manage_template => true
			    template => "/usr/share/logstash/template/nginx_mapping.json"
				template_name => "nginx-access-log"
		}
	}
	if [topic] == "nginx-api-access-log" {
		elasticsearch {
				hosts => ["elasticsearch:9200"]
		    	index => "nginx_api_access_%{+YYYY.MM.dd}"
				manage_template => true
			    template => "/usr/share/logstash/template/nginx_mapping.json"
				template_name => "nginx-access-log"
		}
	} 
	if [topic] == "nginx-openapi-access-log" {
		elasticsearch {
				hosts => ["elasticsearch:9200"]
		    	index => "nginx_openapi_access_%{+YYYY.MM.dd}"
				manage_template => true
			    template => "/usr/share/logstash/template/nginx_mapping.json"
				template_name => "nginx-access-log"
		}
	}
	if [topic] == "nginx-www-error-log" {
		elasticsearch {
				hosts => ["elasticsearch:9200"]
		    	index => "nginx_www_error_%{+YYYY.MM.dd}"
				manage_template => false
			
		}
	} 
	if [topic] == "nginx-api-error-log" {
		elasticsearch {
				hosts => ["elasticsearch:9200"]
		    	index => "nginx_api_error_%{+YYYY.MM.dd}"
				manage_template => false
		}
	} 
	if [topic] == "nginx-openapi-error-log" {
		elasticsearch {
				hosts => ["elasticsearch:9200"]
		    	index => "nginx_openapi_error_%{+YYYY.MM.dd}"
				manage_template => false
		}
	}  

	##输出到控制台
	##if [topic] == "nginx-www-error-log" {
	##	stdout {
	##  	  codec => rubydebug
	##	}
	##}
}

#####第四步：新增logstash/template/nginx_mapping.json模板（这里只是为了玩一下模板，如果不需要，则在logstash.conf去掉对应配置）

{
 "index_patterns": ["nginx-access-log"],
 "mappings": {
   "doc": {
     "properties": {
       "logtime" : { 
          "type" : "date",
          "format": "dd/MMM/yyyy:HH:mm:ss Z"
        },
       "http_x_forwarded_for": { 
         "type": "ip",
         "doc_values": true
        },
       "remote_addr": { 
         "type": "ip",
         "doc_values": true
        },
       "remote_user": { "type": "keyword" },
       "request": { "type": "text" },
       "status_code": { "type": "integer" },
       "request_time": { "type": "double" },
       "upstream_response_time": { "type": "keyword" },
       "request_length": { "type": "integer" },
       "body_bytes_sent": { "type": "integer" }
      }
    }
  }
}

#####第五步：运行
在项目根目录中运行docker-compose up -d --build

#结束
完美运行！
后面采用kibana绘制图标就不写了，意义不大

期间遇到的一些其他问题
1.由于在项目中运行拉取kafka的镜像失败，所以在其他机子上把kafka的镜像拉取下来，然后运行docker save -o images.tar openjdk kafka_kafka wurstmeister/zookeeper，把镜像导出来
然后在线上运行docker load images.tar

#参考资料
filebeat reference官方文档

logstash reference官方文档
logstash介绍
logstash解析Nginx error日志格式
logstash把message中日志时间替换到@timestamp
logstash实用介绍

kafka官方文档
学会kafka shell脚本测试kafka

kibana绘图教程1
kibana绘图教程2
kibana绘图教程3

es的索引模板学习参考文章

mac搭建kafka集群参考文章
elk+redis集群参考文章

让外网访问docker里的kafka服务参考文章1
让外网访问docker里的kafka服务参考文章2
让外网访问docker里的kafka服务参考文章3
让外网访问docker里的kafka服务参考文章4