Docker ELGKGC stack

Original configs are from https://github.com/deviantony/docker-elk but this has collectD and Grafana also enabled.

Run the latest version of the ELK (Elasticsearch, Logstash, Kibana, Grafana, Graphite, CollectD) 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 or Grafana.

Based on the official Docker images:

• elasticsearch
• logstash
• kibana
• grafana
• graphite
• collectD(Not based on official image)

Contents

1. Requirements
   • Host setup
   • SELinux
   • DockerForWindows
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?
4. Storage
   • How can I persist Elasticsearch data?
5. Extensibility
   • How can I add plugins?
   • How can I enable the provided extensions?
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?

Requirements

Host setup

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

Usage

Bringing up the stack

Note: In case you switched branch or updated a base image - you may need to run docker-compose build first

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

Give Kibana a few seconds 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
• 3000: Grafana
• 25826: Logstash collectD input

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

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: 6.2.4' \
    -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.

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 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.

Extensibility

How can I add plugins?

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

How can I enable the provided extensions?

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.