This repository contains sample Kibana4 dashboards for visualizing the data gathered by the Elastic Beats.
To load the dashboards, execute the script pointing to the Elasticsearch HTTP URL:
# Unix ./load.sh -url "http://localhost:9200" # Windows .\load.ps1 -url "http://localhost:9200"
If you want to use HTTP authentication for Elasticsearch, you can specify the credentials as a second parameter:
# Unix ./load.sh -url "http://localhost:9200" -user "admin:secret" # Windows .\load.ps1 -url "http://localhost:9200" -user "admin:secret"
dashboards folder contains the JSON files as exported from Kibana, by
using the simple python tool from the
save directory. The loader is a simple
shell script so that you don't need python installed when loading the
Create a new dashboard
If you added support for a new protocol in Packetbeat or a module in
Metricbeat, it would be nice to create a dedicated Kibana dashboard to
visualize your data.
The Kibana dashboards are saved in a special index in Elasticsearch. By default
.kibana, but it can be configured to anything else.
The first step in creating your own Kibana dashboard is to get a fresh
installation of the Kibana dashboards/visualizations/searches/index patterns,
that you can use as a starting point for your own dashboard. You can use the
load.sh script on Unix and
load.ps1 on Windows for loading the sample
dashboards/visualizations/searches/index patterns in Kibana. The usage of this
script is described above.
Note: Make sure you are using the latest Kibana version to create and download the dashboards.
Then, you can create the dashboard together with the necessary
visualizations and searches in Kibana. After the dashboard is ready, you can download
all the dashboards using the
Before executing the save/kibana_dump.py script, make sure you have python and virtualenv installed:
# Prepare the environment virtualenv env . env/bin/activate pip install -r requirements.txt # go to save directory cd save # Download all Kibana dashboards to your host python kibana_dump.py --url 'http://localhost:9200' --dir output
url points to the Elasticsearch URL, and
dir is the directory where
you want to save the Kibana dashboards.
Finally, copy the related dashboards, visualizations, searches and
eventually index patterns to the
dashboards directory, and send us a pull request.