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:
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
- Install Docker.
- Install Docker-compose version >= 1.6.
- Clone this repository
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/
Start the ELK stack using docker-compose:
$ docker-compose up
You can also choose to run it in background (detached mode):
$ docker-compose up -d
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.
Example of reloading logstash:
docker restart dockerelk_logstash_1
- Install filebeat.
- Edit the respective .sh file in
./filebeat
, filling in information such as server names. - Run any respective .sh files in ./filebeat.
Example of running on an ongoing basis:
watch -n 20 ./cognos_filebeat.sh
NOTE: Configuration is not dynamically reloaded, you will need to restart the stack after any change in the configuration of a component.
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.
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.
The Elasticsearch configuration is stored in 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
Follow the instructions from the Wiki: Scaling up Elasticsearch
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 service 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
.
To add plugins to any ELK component you have to:
- Add a
RUN
statement 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)
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:
build: logstash/
volumes:
- ./logstash/pipeline:/usr/share/logstash/pipeline
ports:
- "5000:5000"
networks:
- elk
depends_on:
- elasticsearch
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:
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"