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:
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.
- 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
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/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 version of the Elastic stack. The main branch tracks the current
major version (7.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.
Older major versions are also supported on separate branches:
release-6.x: 6.x seriesrelease-5.x: 5.x series (End-Of-Life)
Clone this repository onto the Docker host that will run the stack, then start services locally using Docker Compose:
$ docker-compose upYou can also run all services in the background (detached mode) by adding the -d flag to the above command.
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 -vℹ️ Refer to How to disable paid features to disable authentication.
The stack is pre-configured with the following privileged bootstrap user:
- user: elastic
- password: changeme
Although all stack components work out-of-the-box with this user, we strongly recommend using the unprivileged built-in users instead for increased security.
-
Initialize passwords for built-in users
$ docker-compose exec -T elasticsearch bin/elasticsearch-setup-passwords auto --batchPasswords for all 6 built-in users will be randomly generated. Take note of them.
-
Unset the bootstrap password (optional)
Remove the
ELASTIC_PASSWORDenvironment variable from theelasticsearchservice inside the Compose file (docker-compose.yml). It is only used to initialize the keystore during the initial startup of Elasticsearch. -
Replace usernames and passwords in configuration files
Use the
kibana_systemuser (kibanafor releases <7.8.0) inside the Kibana configuration file (kibana/config/kibana.yml) and thelogstash_systemuser inside the Logstash configuration file (logstash/config/logstash.yml) in place of the existingelasticuser.Replace the password for the
elasticuser inside the Logstash pipeline file (logstash/pipeline/logstash.conf).ℹ️ Do not use the
logstash_systemuser 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.
-
Restart Kibana and Logstash to apply changes
$ docker-compose restart kibana logstashℹ️ 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 5000You 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: 7.15.2' \
-u elastic:<your generated elastic password> \
-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-clusterPlease 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 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:
- Add a
RUNstatement to the correspondingDockerfile(eg.RUN logstash-plugin install logstash-filter-json) - Add the associated plugin code configuration to the service configuration (eg. Logstash input/output)
- Rebuild the images using the
docker-compose buildcommand
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:
| 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 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 -Xms1gAs 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=falseSee the following Wiki pages:
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 elkIf all components get deployed without any error, the following command will show 3 running services:
$ docker stack services elkℹ️ To scale Elasticsearch in Swarm mode, configure seed hosts with the DNS name tasks.elasticsearch
instead of elasticsearch.