kafka-elk-docker-compose

This repository deploys with docker-compose an ELK stack which has kafka cluster buffering the logs collection process. This repository tries to make your life easier while testing a similar architecture. It is highly discouraged to use this repository as a production ready solution of this stack.

Setup

1. Install Docker engine
2. Install Docker compose
3. Clone this repository:

   git clone [email protected]:sermilrod/kafka-elk-docker-compose.git
   

4. Configure File Descriptors and MMap To do so you have to type the following command:

   sysctl -w vm.max_map_count=262144
   

   Be aware that the previous sysctl setting vanishes when your machine restarts. If you want to make it permanent place vm.max_map_count setting in your /etc/sysctl.conf.
5. Create the elasticsearch volume:

   $ cd kafka-elk-docker-compose
   $ mkdir esdata
   

   By default the docker-compose.yml uses esdata as the host volumen path name. If you want to use another name you have to edit the docker-compose.yml file and create your own structure.
6. Create the apache-logs folder:

   $ cd kafka-elk-docker-compose
   $ mkdir apache-logs
   

   This repository uses a default apache container to generate logs and it is required for filebeat to be present. If you do not want to use this apache or you want to add new components to the system just use the docker-compose.yml as a base for your use case.

Usage

Deploy your Kafka+ELK Stack using docker-compose:

$ docker-compose up -d

By default the apache container generating logs is exposed through port 8888. You can perform some requests to generate a few log entries for later visualization in kibana:

$ curl http://localhost:8888/

The full stack takes around a minute to be fully functional as there are dependencies beteween services. After that you should be able to hit Kibana http://localhost:5601

Before you see the log entries generated before you have to configure an index pattern in kibana. Make sure you configure it with these two options:

• Index name or pattern: logstash-*
• Time-field name: @timestamp

Configuration

The docker-compose.yml deploys an ELK solution using kafka as a buffer for log collection. This repository is shipped with the minimal amount of configuration needed to make the stack work. The default config files are:

filebeat.yml:

filebeat.prospectors:
- paths:
    - /apache-logs/access.log
  tags:
    - testenv
    - apache_access
  input_type: log
  document_type: apache_access
  fields_under_root: true

- paths:
    - /apache-logs/error.log
  tags:
    - testenv
    - apache_error
  input_type: log
  document_type: apache_error
  fields_under_root: true

output.kafka:
  hosts: ["kafka1:9092", "kafka2:9092", "kafka3:9092"]
  topic: 'log'
  partition.round_robin:
    reachable_only: false
  required_acks: 1
  compression: gzip
  max_message_bytes: 1000000

As you can see it is configured to read the default apache logs and push them to kafka. Any addition or change to the filebeat agent should be perform in this config file.

logstash.conf:

input {
  kafka {
    bootstrap_servers => "kafka1:9092,kafka2:9092,kafka3:9092"
    client_id => "logstash"
    group_id => "logstash"
    consumer_threads => 3
    topics => ["log"]
    codec => "json"
    tags => ["log", "kafka_source"]
    type => "log"
  }
}

filter {
  if [type] == "apache_access" {
    grok {
      match => { "message" => "%{COMMONAPACHELOG}" }
    }
    date {
      match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
      remove_field => ["timestamp"]
    }
  }
  if [type] == "apache_error" {
    grok {
      match => { "message" => "%{COMMONAPACHELOG}" }
    }
    date {
      match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
      remove_field => ["timestamp"]
    }
  }
}

output {
  if [type] == "apache_access" {
    elasticsearch {
         hosts => ["elasticsearch:9200"]
         index => "logstash-apache-access-%{+YYYY.MM.dd}"
    }
  }
  if [type] == "apache_error" {
    elasticsearch {
         hosts => ["elasticsearch:9200"]
         index => "logstash-apache-error-%{+YYYY.MM.dd}"
    }
  }
}

As you can, logstash is configured as a kafka consumer to parse apache logs and to insert them into elasticsearch. Any addition or change to the logstash behaviour should be perform in this config file.

kibana.yml:

server.name: kibana
server.host: "0"
elasticsearch.url: http://elasticsearch:9200
xpack.monitoring.ui.container.elasticsearch.enabled: false

It is remarkable the fact that by default that both kibana and elasticsearch docker images enable by default the xpack plugin, which you will have to pay for it after the trial. This repository disables this paid feature by default. Any addition or change to the kibana behaviour should be perform in this config file.

Other configuration:

You can configure much more each of the components of the stack. It is up to you and your use case to extend the configuration files and change the docker-compose.yml to make it so.