Run the latest version of the ELK (Elasticseach, 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 Elasticseach and the visualization power of Kibana.

Uses Docker images which support Raspberry Pi based on the official images:

• rpi-elasticsearch
• rpi-logstash
• rpi-kibana

1. Install Docker on Raspberry Pi.
2. Install Docker-compose on Raspberry Pi.
3. Clone this repository on Raspberry Pi.

NOTE: Give a try to HypriotOS if you want to easily install Docker on your Raspberry Pi.

Start the ELK stack using docker-compose in your Raspberry Pi:

$ 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://raspberry-pi-ip:5601 with a web browser.

NOTE: You'll need to inject data into logstash before being able to create a logstash index in Kibana. Then all you should have to do is to hit the create button.

See: https://www.elastic.co/guide/en/kibana/current/setup.html#connect

You can also access:

• Sense: http://raspberry-pi-ip:5601/app/sense

By default, the stack exposes the following ports:

• 5000: Logstash TCP input.
• 9200: Elasticsearch HTTP
• 9300: Elasticsearch TCP transport
• 5601: Kibana

You can get more information about how to configure ELK stack in the original Docker ELK stack repository.

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

Tested on Raspberry Pi 2