Docker BELK stack

This fork is meant to be used with KIPP, having the filebeat running on KIPP machine and the ELK stack on Docker or otherwise running on a different machine/cluster.

TODO: Need to clean up the rest of this README below.

To run filebeat on kipp-vagrant:

sudo filebeat -e --strict.perms=false -c /apps/kipp/kipp/beats/config/filebeat.yml

Project forked from docker-elk.

Run the latest version of the BELK (Elasticsearch, Logstash, Kibana, Beats) 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 Docker images:

• elasticsearch
• logstash
• kibana
• filebeat

Contents

1. Requirements
   • Host setup
   • SELinux
2. Getting started
   • Bringing up the stack
   • Initial setup
3. Configuration
   • How can I tune the Kibana configuration?
   • How can I tune the Logstash configuration?
   • How can I tune the Elasticsearch configuration?
   • How can I scale out the Elasticsearch cluster?
   • How can I tune the Beats configuration?
4. Storage
   • How can I persist Elasticsearch data?
5. Extensibility
   • How can I add plugins?
6. JVM tuning
   • How can I specify the amount of memory used by a service?
   • How can I enable a remote JMX connection to a service?
7. E2E debugging

Requirements

Host setup

1. Install Docker version 1.10.0+
2. Install Docker Compose version 1.6.0+
3. Clone this repository

SELinux

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-belk 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-belk/

Usage

Bringing up the stack

Start the BELK stack using docker-compose:

$ docker-compose up

You can also choose to run it in background (detached mode):

$ docker-compose up -d

Give Kibana about 2 minutes to initialize, then access the Kibana web UI by hitting http://localhost:5601 with a web browser.

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.

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

$ nc localhost 5000 < /path/to/logfile.log

Initial setup

Default Kibana index pattern creation

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

Via the Kibana web UI

NOTE: You need to inject data into Logstash before being able to configure a Logstash index pattern via the Kibana web UI. Then all you have to do is hit the Create button.

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

On the command line

Run this command to create a Logstash index pattern:

$ curl -XPUT -D- 'http://localhost:9200/.kibana/index-pattern/logstash-*' \
    -H 'Content-Type: application/json' \
    -d '{"title" : "logstash-*", "timeFieldName": "@timestamp", "notExpandable": true}'

This command will mark the Logstash index pattern as the default index pattern:

$ curl -XPUT -D- 'http://localhost:9200/.kibana/config/5.5.0' \
    -H 'Content-Type: application/json' \
    -d '{"defaultIndex": "logstash-*"}'

Configuration

NOTE: Configuration is not dynamically reloaded, you will need to restart the stack after any change in the configuration of a component.

How can I tune the Kibana configuration?

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.

How can I tune the Logstash configuration?

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.

How can I tune the Elasticsearch configuration?

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:

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

How can I tune the Beats configuration?

TODO

How can I scale out the Elasticsearch cluster?

Follow the instructions from the Wiki: Scaling out Elasticsearch

Storage

How can I persist Elasticsearch data?

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:

  volumes:
    - /path/to/storage:/usr/share/elasticsearch/data

This will store Elasticsearch data inside /path/to/storage.

NOTE: beware of these OS-specific considerations:

• Linux: the unprivileged elasticsearch user is used within the Elasticsearch image, therefore the mounted data directory must be owned by the uid 1000.
• macOS: the default Docker for Mac configuration allows mounting files from /Users/, /Volumes/, /private/, and /tmp exclusively. Follow the instructions from the documentation to add more locations.

Extensibility

How can I add plugins?

To add plugins to any BELK 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

JVM tuning

How can I specify the amount of memory used by a service?

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 -Xms1g"

How can I enable a remote JMX connection to a service?

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"

E2E debugging

Once we have all the containers up and running we can use the following commands to do various checks:

Creates logs on the filebeat container:

docker exec -it dockerbelk_filebeat_1 bash -c "echo 'some logs..' >> /var/log/testing_belk.log"

Checks logstash is processing data:

docker logs -ft dockerbelk_logstash_1 2>&1 message

Finally, we should check Kibana on http://0.0.0.0:5601/