Docker ELK stack

Run the latest version of the ELK (Elasticsearch, Logstash, Kibana) stack with Docker and Docker-compose.

It will give you the ability to analyze any data set by using the searching/aggregation capabilities of Elasticsearch and the visualization power of Kibana.

Based on the official images:

• elasticsearch
• logstash
• kibana

Note: Other branches in this project are available:

• ELK 5 with X-Pack support: https://github.com/deviantony/docker-elk/tree/x-pack
• ELK 5 in Vagrant: https://github.com/deviantony/docker-elk/tree/vagrant
• ELK 5 with Search Guard: https://github.com/deviantony/docker-elk/tree/searchguard

Requirements

Setup

1. Install Docker.
2. Install Docker-compose version >= 1.6.
3. Clone this repository

SELinux

On distributions which have SELinux enabled out-of-the-box you will need to either re-context the files or set SELinux into Permissive mode in order for docker-elk to start properly. For example on Redhat and CentOS, the following will apply the proper context:

$ chcon -R system_u:object_r:admin_home_t:s0 docker-elk/

Usage

Run ./up_stack to start the ELK stack, which increases vm.max_map_count on your host (mandatory to run elasticsearch Install Elasticsearch with Docker) then runs docker-compose up

Now that the stack is running, you'll want to inject logs in it. The shipped logstash configuration allows you to send content via tcp:

$ nc localhost 5000 < /path/to/logfile.log

And then access Kibana UI by hitting http://localhost:5601 with a web browser.

NOTE: You'll need to inject data into logstash before being able to configure a logstash index pattern in Kibana. Then all you should have to do is to hit the create button.

Refer to Connect Kibana with Elasticsearch for detailed instructions about the index pattern configuration.

By default, the stack exposes the following ports:

• 5000: Logstash TCP input.
• 9200: Elasticsearch HTTP
• 9300: Elasticsearch TCP transport
• 5601: Kibana

WARNING: If you're using boot2docker, you must access it via the boot2docker IP address instead of localhost.

WARNING: If you're using Docker Toolbox, you must access it via the docker-machine IP address instead of localhost.

Configuration

NOTE: Configuration is not dynamically reloaded, you will need to restart the stack after any change in the configuration of a component.

How can I tune Kibana configuration?

The Kibana default configuration is stored in kibana/config/kibana.yml.

How can I tune Logstash configuration?

The logstash configuration is stored in logstash/config/logstash.yml.

It is also possible to map the entire config directory inside the container in the docker-compose.yml. Update the logstash container declaration to:

logstash:
  build: logstash/
  volumes:
    - ./logstash/pipeline:/usr/share/logstash/pipeline
    - ./logstash/config:/usr/share/logstash/config
  ports:
    - "5000:5000"
  networks:
    - elk
  depends_on:
    - elasticsearch

In the above example the folder logstash/config is mapped onto the container /usr/share/logstash/config so you can create more than one file in that folder if you'd like to. However, you must be aware that config files will be read from the directory in alphabetical order, and that Logstash will be expecting a log4j2.properties file for its own logging.

How can I tune Elasticsearch configuration?

The Elasticsearch container is using the shipped configuration.

If you want to override the default configuration, create a file elasticsearch/config/elasticsearch.yml and add your configuration in it.

Then, you'll need to map your configuration file inside the container in the docker-compose.yml. Update the elasticsearch container declaration to:

elasticsearch:
  build: elasticsearch/
  ports:
    - "9200:9200"
    - "9300:9300"
  environment:
    ES_JAVA_OPTS: "-Xmx256m -Xms256m"
  networks:
    - elk
  volumes:
    - ./elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml

You can also specify the options you want to override directly via environment variables:

elasticsearch:
  build: elasticsearch/
  ports:
    - "9200:9200"
    - "9300:9300"
  environment:
    ES_JAVA_OPTS: "-Xmx256m -Xms256m"
    network.host: "_non_loopback_"
    cluster.name: "my-cluster"
  networks:
    - elk

How can I scale up the Elasticsearch cluster?

Follow the instructions from the Wiki: Scaling up Elasticsearch

Storage

How can I store Elasticsearch data?

The data stored in Elasticsearch will be persisted after container reboot but not after container removal.

In order to persist Elasticsearch data even after removing the Elasticsearch container, you'll have to mount a volume on your Docker host. Update the elasticsearch container declaration to:

elasticsearch:
  build: elasticsearch/
  ports:
    - "9200:9200"
    - "9300:9300"
  environment:
    ES_JAVA_OPTS: "-Xmx256m -Xms256m"
    network.host: "_non_loopback_"
    cluster.name: "my-cluster"
  networks:
    - elk
  volumes:
    - /path/to/storage:/usr/share/elasticsearch/data

This will store Elasticsearch data inside /path/to/storage.

Extensibility

How can I add plugins?

To add plugins to any ELK component you have to:

1. Add a RUN statement to the corresponding Dockerfile (eg. RUN logstash-plugin install logstash-filter-json)
2. Add the associated plugin code configuration to the service configuration (eg. Logstash input/output)

JVM tuning

How can I specify the amount of memory used by a service?

By default, both Elasticsearch and Logstash start with 1/4 of the total host memory allocated to the JVM Heap Size.

The startup scripts for Elasticsearch and Logstash can append extra JVM options from the value of an environment variable, allowing the user to adjust the amount of memory that can be used by each component:

Service	Environment variable
Elasticsearch	ES_JAVA_OPTS
Logstash	LS_JAVA_OPTS

To accomodate environments where memory is scarce (Docker for Mac has only 2 GB available by default), the Heap Size allocation is capped by default to 256MB per service within the docker-compose.yml file. If you want to override the default JVM configuration, edit the matching environment variable(s) in the docker-compose.yml file.

For example, to increase the maximum JVM Heap Size for Logstash:

logstash:
  build: logstash/
  volumes:
    - ./logstash/pipeline:/usr/share/logstash/pipeline
  ports:
    - "5000:5000"
  networks:
    - elk
  depends_on:
    - elasticsearch
  environment:
    LS_JAVA_OPTS: "-Xmx1g -Xms1g"

How can I enable a remote JMX connection to a service?

As for the Java Heap memory (see above), you can specify JVM options to enable JMX and map the JMX port on the docker host.

Update the {ES,LS}_JAVA_OPTS environment variable with the following content (I've mapped the JMX service on the port 18080, you can change that). Do not forget to update the -Djava.rmi.server.hostname option with the IP address of your Docker host (replace DOCKER_HOST_IP):

logstash:
  build: logstash/
  volumes:
    - ./logstash/pipeline:/usr/share/logstash/pipeline
  ports:
    - "5000:5000"
  networks:
    - elk
  depends_on:
    - elasticsearch
  environment:
    LS_JAVA_OPTS: "-Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.port=18080 -Dcom.sun.management.jmxremote.rmi.port=18080 -Djava.rmi.server.hostname=DOCKER_HOST_IP -Dcom.sun.management.jmxremote.local.only=false"