Run the latest version of the Elastic stack with Docker and Docker Compose.

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

ℹ️ The Docker images backing this stack include X-Pack with paid features enabled by default (see How to disable paid features to disable them). The trial license is valid for 30 days. After this license expires, you can continue using the free features seamlessly, without losing any data.

Based on the official Docker images from Elastic:

• Elasticsearch
• Logstash
• Kibana

Other available stack variants:

• tls: TLS encryption enabled in Elasticsearch
• searchguard: Search Guard support

We aim at providing the simplest possible entry into the Elastic stack for anybody who feels like experimenting with this powerful combo of technologies. This project's default configuration is purposely minimal and unopinionated. It does not rely on any external dependency or custom automation to get things up and running.

Instead, we believe in good documentation so that you can use this repository as a template, tweak it, and make it your own. sherifabdlnaby/elastdocker is one example among others of project that builds upon this idea.

1. Requirements
   • Host setup
   • Docker Desktop
     • Windows
     • macOS
2. Usage
   • Initial setup
     • Setting up user authentication
     • Injecting data
   • Cleanup
   • Version selection
3. Configuration
   • How to configure Elasticsearch
   • How to configure Kibana
   • How to configure Logstash
   • How to disable paid features
   • How to scale out the Elasticsearch cluster
   • How to reset a password programmatically
4. Extensibility
   • How to add plugins
   • How to enable the provided extensions
5. JVM tuning
   • How to specify the amount of memory used by a service
   • How to enable a remote JMX connection to a service
6. Going further
   • Plugins and integrations
   • Swarm mode

• Docker Engine version 17.05 or newer
• Docker Compose version 1.20.0 or newer
• 1.5 GB of RAM

ℹ️ Especially on Linux, make sure your user has the required permissions to interact with the Docker daemon.

By default, the stack exposes the following ports:

• 5044: Logstash Beats input
• 5000: Logstash TCP input
• 9600: Logstash monitoring API
• 9200: Elasticsearch HTTP
• 9300: Elasticsearch TCP transport
• 5601: Kibana

⚠️ Elasticsearch's bootstrap checks were purposely disabled to facilitate the setup of the Elastic stack in development environments. For production setups, we recommend users to set up their host according to the instructions from the Elasticsearch documentation: Important System Configuration.

If you are using the legacy Hyper-V mode of Docker Desktop for Windows, ensure File Sharing is enabled for the C: drive.

The default configuration of Docker Desktop for Mac allows mounting files from /Users/, /Volume/, /private/, /tmp and /var/folders exclusively. Make sure the repository is cloned in one of those locations or follow the instructions from the documentation to add more locations.

⚠️ You must rebuild the stack images with docker-compose build whenever you switch branch or update the version of an already existing stack.

Clone this repository onto the Docker host that will run the stack, then start the Elasticsearch service locally using Docker Compose:

$ docker-compose up -d elasticsearch

We will start the rest of the Elastic components after completing the initial setup described in this section. These steps only need to be performed once.

⚠️ Starting with Elastic v8.0.0, it is no longer possible to run Kibana using the bootstraped privileged elastic user. If you are starting the stack for the very first time, you MUST initialize a password for the built-in kibana_system user to be able to start and access Kibana. Please read the section below attentively.

ℹ️ Refer to Security settings in Elasticsearch to disable authentication.

The stack is pre-configured with the following privileged bootstrap user:

• user: elastic
• password: changeme

For increased security, we will reset this bootstrap password, and generate a set of passwords to be used by unprivileged built-in users within components of the Elastic stack.

1. Initialize passwords for built-in users

   The commands below generate random passwords for the elastic and kibana_system users. Take note of them.

   $ docker-compose exec -T elasticsearch bin/elasticsearch-reset-password --batch --user elastic

   $ docker-compose exec -T elasticsearch bin/elasticsearch-reset-password --batch --user kibana_system

   If the need for it arises (e.g. if you want to collect monitoring information through Beats and other components), feel free to repeat this operation at any time for the rest of the built-in users.

2. Replace usernames and passwords in configuration files

   Replace the password of the kibana_system user inside the Kibana configuration file (kibana/config/kibana.yml) with the password generated in the previous step.

   Replace the password of the elastic user inside the Logstash pipeline file (logstash/pipeline/logstash.conf) with the password generated in the previous step.

   ℹ️ Do not use the logstash_system user inside the Logstash pipeline file, it does not have sufficient permissions to create indices. Follow the instructions at Configuring Security in Logstash to create a user with suitable roles.

   See also the Configuration section below.

3. Unset the bootstrap password (optional)

   Remove the ELASTIC_PASSWORD environment variable from the elasticsearch service inside the Compose file (docker-compose.yml). It is only used to initialize the keystore during the initial startup of Elasticsearch, and is ignored on subsequent runs.

4. Start Kibana and Logstash

   $ docker-compose up -d

   The -d flag runs all services in the background (detached mode).

   On subsequent runs of the Elastic stack, it is sufficient to execute the above command in order to start all components.

   ℹ️ Learn more about the security of the Elastic stack at Secure the Elastic Stack.

Give Kibana about a minute to initialize, then access the Kibana web UI by opening http://localhost:5601 in a web browser and use the following credentials to log in:

• user: elastic
• password: <your generated elastic password>

Now that the stack is running, you can go ahead and inject some log entries. The shipped Logstash configuration allows you to send content via TCP:

# Using BSD netcat (Debian, Ubuntu, MacOS system, ...)
$ cat /path/to/logfile.log | nc -q0 localhost 5000

# Using GNU netcat (CentOS, Fedora, MacOS Homebrew, ...)
$ cat /path/to/logfile.log | nc -c localhost 5000

You can also load the sample data provided by your Kibana installation.

Elasticsearch data is persisted inside a volume by default.

In order to entirely shutdown the stack and remove all persisted data, use the following Docker Compose command:

$ docker-compose down -v

This repository stays aligned with the latest version of the Elastic stack. The main branch tracks the current major version (8.x).

To use a different version of the core Elastic components, simply change the version number inside the .env file. If you are upgrading an existing stack, please carefully read the note in the next section.

⚠️ Always pay attention to the official upgrade instructions for each individual component before performing a stack upgrade.

Older major versions are also supported on separate branches:

• release-7.x: 7.x series
• release-6.x: 6.x series (End-of-life)
• release-5.x: 5.x series (End-of-life)

ℹ️ Configuration is not dynamically reloaded, you will need to restart individual components after any configuration change.

The Elasticsearch configuration is stored in elasticsearch/config/elasticsearch.yml.

You can also specify the options you want to override by setting environment variables inside the Compose file:

elasticsearch:

  environment:
    network.host: _non_loopback_
    cluster.name: my-cluster

Please refer to the following documentation page for more details about how to configure Elasticsearch inside Docker containers: Install Elasticsearch with Docker.

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

You can also specify the options you want to override by setting environment variables inside the Compose file:

kibana:

  environment:
    SERVER_NAME: kibana.example.org

Please refer to the following documentation page for more details about how to configure Kibana inside Docker containers: Install Kibana with Docker.

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

You can also specify the options you want to override by setting environment variables inside the Compose file:

logstash:

  environment:
    LOG_LEVEL: debug

Please refer to the following documentation page for more details about how to configure Logstash inside Docker containers: Configuring Logstash for Docker.

Switch the value of Elasticsearch's xpack.license.self_generated.type setting from trial to basic (see License settings).

You can also cancel an ongoing trial before its expiry date — and thus revert to a basic license — either from the License Management panel of Kibana, or using Elasticsearch's Licensing APIs.

Follow the instructions from the Wiki: Scaling out Elasticsearch

If for any reason your are unable to use Kibana to change the password of your users (including built-in users), you can use the Elasticsearch API instead and achieve the same result.

In the example below, we reset the password of the elastic user (notice "/user/elastic" in the URL):

$ curl -XPOST -D- 'http://localhost:9200/_security/user/elastic/_password' \
    -H 'Content-Type: application/json' \
    -u elastic:<your current elastic password> \
    -d '{"password" : "<your new password>"}'

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)
3. Rebuild the images using the docker-compose build command

A few extensions are available inside the extensions directory. These extensions provide features which are not part of the standard Elastic stack, but can be used to enrich it with extra integrations.

The documentation for these extensions is provided inside each individual subdirectory, on a per-extension basis. Some of them require manual changes to the default ELK configuration.

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:

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 in 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:

  environment:
    LS_JAVA_OPTS: -Xmx1g -Xms1g

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:

  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

See the following Wiki pages:

• External applications
• Popular integrations

Experimental support for Docker Swarm mode is provided in the form of a docker-stack.yml file, which can be deployed in an existing Swarm cluster using the following command:

$ docker stack deploy -c docker-stack.yml elk

If all components get deployed without any error, the following command will show 3 running services:

$ docker stack services elk

ℹ️ To scale Elasticsearch in Swarm mode, configure seed hosts with the DNS name tasks.elasticsearch instead of elasticsearch.