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

This variant includes Search Guard.

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 and have Search Guard Enterprise features enabled by default (see How to disable paid features to disable them). The trial license is valid for 60 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

The Default Search Guard configuration in this repo is:

• Basic authentication required to access Elasticsearch/Kibana
• HTTPS disabled
• Hostname verification disabled
• Self-signed SSL certificate for transport protocol (do not use in production)

Check the Demo users and roles documentation page for a list and description of the built-in Search Guard users.

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
   • Version selection
   • Bringing up the stack
   • Cleanup
   • Initial setup
     • Setting up user authentication
     • Injecting data
     • Default Kibana index pattern creation
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
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.

This repository tries to stay aligned with the latest versions of the Elastic stack and Search Guard.

To use different versions of those components, simply change the version numbers 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.

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

$ docker-compose up

You can also run all services in the background (detached mode) by adding the -d flag to the above command.

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

If you are starting the stack for the very first time, please read the section below attentively.

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

ℹ️ Refer to How to disable paid features to disable authentication.

Search Guard must be initialized after Elasticsearch is started:

$ docker-compose exec -T elasticsearch bin/init_sg.sh

This executes sgadmin and loads the configuration from elasticsearch/config/sg/sg\*.yml.

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: admin
• password: admin

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.

When Kibana launches for the first time, it is not configured with any index pattern.

ℹ️ You need to inject data into Logstash before being able to configure a Logstash index pattern via the Kibana web UI.

Navigate to the Discover view of Kibana from the left sidebar. You will be prompted to create an index pattern. Enter logstash-* to match Logstash indices then, on the next page, select @timestamp as the time filter field. Finally, click Create index pattern and return to the Discover view to inspect your log entries.

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

Create an index pattern via the Kibana API:

$ curl -XPOST -D- 'http://localhost:5601/api/saved_objects/index-pattern' \
    -H 'Content-Type: application/json' \
    -H 'kbn-version: 7.17.4' \
    -u kibanaserver:kibanaserver \
    -d '{"attributes":{"title":"logstash-*","timeFieldName":"@timestamp"}}'

The created pattern will automatically be marked as the default index pattern as soon as the Kibana UI is opened for the first time.

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.

It is also possible to map the entire config directory instead of a single file.

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.

It is also possible to map the entire config directory instead of a single file, however you must be aware that Logstash will be expecting a log4j2.properties file for its own logging.

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 searchguard.enterprise_modules_enabled setting to false (see License settings).

Follow the instructions from the Wiki: Scaling out Elasticsearch

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.