filebeat + ELK 部署篇

ELK Stack

• Elasticsearch：分布式搜索和分析引擎，具有高可伸缩、高可靠和易管理等特点。基于 Apache Lucene 构建，能对大容量的数据进行接近实时的存储、搜索和分析操作。通常被用作某些应用的基础搜索引擎，使其具有复杂的搜索功能；
• Logstash：数据收集引擎。它支持动态的从各种数据源搜集数据，并对数据进行过滤、分析、丰富、统一格式等操作，然后存储到用户指定的位置；
• Kibana：数据分析和可视化平台。通常与 Elasticsearch 配合使用，对其中数据进行搜索、分析和以统计图表的方式展示；
• Filebeat：ELK 协议栈的新成员，一个轻量级开源日志文件数据搜集器，基于 Logstash-Forwarder 源代码开发，是对它的替代。在需要采集日志数据的 server 上安装 Filebeat，并指定日志目录或日志文件后，Filebeat 就能读取数据，迅速发送到 Logstash 进行解析，亦或直接发送到 Elasticsearch 进行集中式存储和分析。

目前成熟架构(亿级)：
Filebeat * n + redis + logstash + elasticsearch + kibana
中小型（本文部署）:
Filebeat*n +logstash + elasticsearch + kibana

Docker 部署Filebeat

docker-compose.yml

version: '3'

services:
  filebeat:
    build:
      context: .
      args:
        ELK_VERSION: 7.1.1
    user: root
    container_name: 'filebeat'
    volumes:
      - ./config/filebeat.yml:/usr/share/filebeat/filebeat.yml:ro # 配置文件，只读
      - /var/lib/docker/containers:/var/lib/docker/containers:ro # 采集docker日志数据
      - /var/run/docker.sock:/var/run/docker.sock:ro

Dockerfile

ARG ELK_VERSION

FROM docker.elastic.co/beats/filebeat:${ELK_VERSION}

config/filebeat.yml

filebeat.config:
  modules:
    path: ${path.config}/modules.d/*.yml
    reload.enabled: false

filebeat.autodiscover:
  providers:
    - type: docker
      hints.enabled: true

processors:
- add_cloud_metadata: ~

filebeat.inputs:
- type: json-file
  paths:
    - /var/lib/docker/containers/*/*.log

output.logstash:
  hosts: ["192.168.31.45:5000"] # 此处修改为logstash监听地址

但这里我们发现，日志文件的命名方式是使用containerId来命名的，因此无法区分日志的容器所对应的镜像，因此我们需要在各容器docker-compose文件添加labels信息.

version: "3"
services:
  nginx:
    image: nginx
    container_name: nginx
    labels:
      service: nginx
    ports:
      - 80:80
    logging:
      driver: json-file
      options:
        labels: "service"

日志输出如下，即可区分不同的容器创建不同的es库

{"log":"172.18.0.1 - - [05/Jul/2019:06:33:55 +0000] \"GET / HTTP/1.1\" 200 612 \"-\" \"curl/7.29.0\" \"-\"\n","stream":"stdout","attrs":{"service":"nginx"},"time":"2019-07-05T06:33:55.973727477Z"}

---

Docker部署ELK

说实话，贴代码配置其实看上去会挺繁琐的，也不可能每个配置项都讲解到，看不懂的配置项或者docker-compose知识点，需要自己去恶补。
让我们先来看一下文件目录结构

├── docker-compose.yml
├── elasticsearch
│   ├── config
│   │   └── elasticsearch.yml
│   └── Dockerfile
├── kibana
│   ├── config
│   │   └── kibana.yml
│   └── Dockerfile
└── logstash
    ├── config
    │   └── logstash.yml
    ├── Dockerfile
    └── pipeline
        └── logstash.conf

docker-compose.yml

version: '2'
services:
  elasticsearch:
    build:
      context: elasticsearch/
      args:
        ELK_VERSION: 7.1.1
    volumes:
      - esdata:/usr/share/elasticsearch/data
      - ./elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml:ro
    ports:
      - "9200:9200"
      - "9300:9300"
    environment:
      ES_JAVA_OPTS: "-Xmx512m -Xms512m"
    networks:
      - elk

  logstash:
    build:
      context: logstash/
      args:
        ELK_VERSION: 7.1.1
    volumes:
      - ./logstash/config/logstash.yml:/usr/share/logstash/config/logstash.yml:ro
      - ./logstash/pipeline:/usr/share/logstash/pipeline:ro
    ports:
      - "5000:5000"
      - "9600:9600"
    environment:
      LS_JAVA_OPTS: "-Xmx512m -Xms512m"
    networks:
      - elk
    depends_on:
      - elasticsearch

  kibana:
    build:
      context: kibana/
      args:
        ELK_VERSION: 7.1.1
    volumes:
      - ./kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml:ro
    ports:
      - "5601:5601"
    networks:
      - elk
    depends_on:
      - elasticsearch

networks:
  elk:
    driver: bridge
volumes:
  esdata:

---

elasticsearch

elasticsearch/config/elasticsearch.yml

cluster.name: docker-cluster

node.name: master
node.master: true
node.data: true
network.host: 0.0.0.0
network.publish_host: 192.168.31.45 # 这里是我内网ip
cluster.initial_master_nodes:
  - master

http.cors.enabled: true
http.cors.allow-origin: "*"

elasticsearch/Dockerfile

ARG ELK_VERSION

FROM docker.elastic.co/elasticsearch/elasticsearch:${ELK_VERSION}

kibana

kibana/config/kibana.yml

server.name: kibana
server.host: "0"
elasticsearch.hosts: [ "http://elasticsearch:9200" ]

kibana/Dockerfile

ARG ELK_VERSION

FROM docker.elastic.co/kibana/kibana:${ELK_VERSION}

logstash

logstash/config/logstash.yml

http.host: "0.0.0.0"
xpack.monitoring.elasticsearch.hosts: [ "http://elasticsearch:9200" ]

logstash/pipeline/logstash.conf

input {
	beats {
		port => 5000
	}
}

## Add your filters / logstash plugins configuration here

output {
	elasticsearch {
		hosts => "elasticsearch:9200"
	}
}

logstash/Dockerfile

ARG ELK_VERSION

FROM docker.elastic.co/logstash/logstash:${ELK_VERSION}

至此部署成功，需要修改的地方有elasticsearch.yml的内网ip，logstash.conf新增filter