Install Elasticsearch with Dockeredit

Elasticsearch is also available as a Docker image. The image is built with X-Pack.

Security noteedit

X-Pack is preinstalled in this image. Please take a few minutes to familiarize yourself with X-Pack Security and how to change default passwords. The default password for the elastic user is changeme.

X-Pack includes a trial license for 30 days. After that, you can obtain one of the available subscriptions or disable Security. The Basic license is free and includes the Monitoring extension.

Obtaining Elasticsearch for Docker is as simple as issuing a docker pull command against the Elastic Docker registry.

The Docker image can be retrieved with the following command:

docker pull

Running Elasticsearch from the command lineedit

Development modeedit

Elasticsearch can be quickly started for development or testing use with the following command:

docker run -p 9200:9200 -e "" -e ""

Production modeedit

The vm_max_map_count kernel setting needs to be set to at least 262144 for production use. Depending on your platform:

  • Linux

    The vm_map_max_count setting should be set permanently in /etc/sysctl.conf:

    $ grep vm.max_map_count /etc/sysctl.conf

    To apply the setting on a live system type: sysctl -w vm.max_map_count=262144

  • OSX with Docker for Mac

    The vm_max_map_count setting must be set within the xhyve virtual machine:

    $ screen ~/Library/Containers/com.docker.docker/Data/com.docker.driver.amd64-linux/tty

    Log in with root and no password. Then configure the sysctl setting as you would for Linux:

    sysctl -w vm.max_map_count=262144
  • OSX with Docker Toolbox

    The vm_max_map_count setting must be set via docker-machine:

    docker-machine ssh
    sudo sysctl -w vm.max_map_count=262144

The following example brings up a cluster comprising two Elasticsearch nodes. To bring up the cluster, use the docker-compose.yml and just type:

docker-compose up

docker-compose is not pre-installed with Docker on Linux. Instructions for installing it can be found on the docker-compose webpage.

The node elasticsearch1 listens on localhost:9200 while elasticsearch2 talks to elasticsearch1 over a Docker network.

This example also uses Docker named volumes, called esdata1 and esdata2 which will be created if not already present.


version: '2'
    container_name: elasticsearch1
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
        soft: -1
        hard: -1
        soft: 65536
        hard: 65536
    mem_limit: 1g
      - IPC_LOCK
      - esdata1:/usr/share/elasticsearch/data
      - 9200:9200
      - esnet
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
      - ""
        soft: -1
        hard: -1
        soft: 65536
        hard: 65536
    mem_limit: 1g
      - IPC_LOCK
      - esdata2:/usr/share/elasticsearch/data
      - esnet

    driver: local
    driver: local

    driver: bridge

To stop the cluster, type docker-compose down. Data volumes will persist, so it’s possible to start the cluster again with the same data using docker-compose up. To destroy the cluster and the data volumes just type docker-compose down -v.

Inspect status of cluster:edit

curl -u elastic
Enter host password for user 'elastic':
1472225929 15:38:49 docker-cluster green 2 2 4 2 0 0 0 0 - 100.0%

Log messages go to the console and are handled by the configured Docker logging driver. By default you can access logs with docker logs.

Configuring Elasticsearch with Dockeredit

Elasticsearch loads its configuration from files under /usr/share/elasticsearch/config/. These configuration files are documented in Configuring Elasticsearch and Setting JVM options.

The image offers several methods for configuring Elasticsearch settings with the conventional approach being to provide customized files, i.e. elasticsearch.yml, but it’s also possible to use environment variables to set options:

A. Present the parameters via Docker environment variablesedit

For example, to define the cluster name with docker run you can pass -e "". Double quotes are required.

There is a difference between defining default settings and normal settings. The former are prefixed with default. and cannot override normal settings, if defined.

B. Bind-mounted configurationedit

Create your custom config file and mount this over the image’s corresponding file. For example, bind-mounting a custom_elasticsearch.yml with docker run can be accomplished with the parameter:

-v full_path_to/custom_elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml

The container runs Elasticsearch as user elasticsearch using uid:gid 1000:1000. Bind mounted host directories and files, such as custom_elasticsearch.yml above, need to be accessible by this user. For the data and log dirs, such as /usr/share/elasticsearch/data, write access is required as well.

C. Customized imageedit

In some environments, it may make more sense to prepare a custom image containing your configuration. A Dockerfile to achieve this may be as simple as:

ADD elasticsearch.yml /usr/share/elasticsearch/config/
USER root
RUN chown elasticsearch:elasticsearch config/elasticsearch.yml
USER elasticsearch

You could then build and try the image with something like:

docker build --tag=elasticsearch-custom .
docker run -ti -v /usr/share/elasticsearch/data elasticsearch-custom

D. Override the image’s default CMDedit

Options can be passed as command-line options to the Elasticsearch process by overriding the default command for the image. For example:

docker run <various parameters> bin/elasticsearch

Notes for production use and defaultsedit

We have collected a number of best practices for production use.

Any Docker parameters mentioned below assume the use of docker run.

  1. Elasticsearch inside the container runs as user elasticsearch using uid:gid 1000:1000. If you are bind mounting a local directory or file, ensure it is readable by this user while the data and log dirs additionally require write access.
  2. It is important to correctly set capabilities and ulimits via the Docker CLI. As seen earlier in the example docker-compose.yml, the following options are required:

    --cap-add=IPC_LOCK --ulimit memlock=-1:-1 --ulimit nofile=65536:65536
  3. Ensure bootstrap.memory_lock is set to true as explained in "Disable swapping".

    This can be achieved through any of the configuration methods, e.g. by setting the appropriate environments variable with -e "bootstrap.memory_lock=true".

  4. The image exposes TCP ports 9200 and 9300. For clusters it is recommended to randomize the published ports with --publish-all, unless you are pinning one container per host.
  5. Use the ES_JAVA_OPTS environment variable to set heap size, e.g. to use 16GB use -e ES_JAVA_OPTS="-Xms16g -Xmx16g" with docker run. It is also recommended to set a memory limit for the container.
  6. Pin your deployments to a specific version of the Elasticsearch Docker image, e.g.
  7. Always use a volume bound on /usr/share/elasticsearch/data, as shown in the production example, for the following reasons:

    1. The data of your elasticsearch node won’t be lost if the container is killed
    2. Elasticsearch is I/O sensitive and the Docker storage driver is not ideal for fast I/O
    3. It allows the use of advanced Docker volume plugins
  8. If you are using the devicemapper storage driver (default on at least RedHat (rpm) based distributions) make sure you are not using the default loop-lvm mode. Configure docker-engine to use direct-lvm instead.
  9. Consider centralizing your logs by using a different logging driver. Also note that the default json-file logging driver is not ideally suited for production use.

Next stepsedit

You now have a test Elasticsearch environment set up. Before you start serious development or go into production with Elasticsearch, you will need to do some additional setup: