This example provides supporting files for the blog post Operational Analytics at ElasticON 2017 - Part 2. This blog post describes the steps for creating a custom tile map for rendering in Kibana e.g. A server room.

The files including in this folder include:

• elastic{ON}_simplified.svg - A simplified svg for the Elastic{ON} floor plan. This svg is used in the blog post.
• styles - A folder of styles for the sample layers created in the blog post.
• shape_files - A folder of shape files representing the layers created in the blog post. Allows the reader to skip step 1.
• generate_random_data.py - A script to generate random data for the floor plan. See below for further details.
• elastic{ON}_full_floor_plan.pdf - A full pdf of the Elastic{ON} floor plan. This can be used to reproduce the demo at Elastic{ON}. This includes a style tablet.

The script generate_random_data.py allows random data to be generated for the floor plan. By creating document clusters, with a random number of documents, the script aims to produce a range of data clusters for the tile map. Improvements welcome.

The example has been tested in the following versions (earlier versions may work but have not been tested):

• Elasticsearch 5.3.0 or greater
• Python 3.5.x

See requirements.txt. Install via pip e.g. pip install -r requirements.txt

This script accepts the following optional parameters:

• es_host - Elasticsearch host and port. Defaults to localhost:9200
• es_user - Elasticsearch user if X-Pack is installed with basic auth (https not supported). Defaults to elastic.
• es_password - Elasticsearch password if X-Pack is installed with basic auth (https not supported). Defaults to changeme.
• num_centroids - Number of clusters/centroids to generate on the floor plan i.e. sources of datapoints. Defaults to 10.
• min_per_centroid - Minimum docs per centroid. Defaults to 10.
• max_per_centroid - Maximum docs per centroid. Defaults to 5000.

python generate_random_data.py --es_host localhost:9200 --es_user elastic --es_password changeme --num_centroids 20 --min_per_centroid 10 --max_per_centroid 10000