A lot of data are available in realtime on Swiss public transportation. Vehicles positions, station board (with delays) etc.
We use these data to illustrate a common pattern and build a proof of concept project. The idea is to address the question: "Is it possible to build a simple scalable infrastructure, to dispatch, transform and visualize 'near real time' massive data and achieve a posteriori analysis?"
We will describe such an infrastructure, focusing on the different bricks:
* streaming events with Kafka and Logstash;
* flow transformation with Akka or Play Streaming;
* storage in Elasticsearch;
* real time visualization with ReactJS and d3.js;
* a posteriori analysis with Python and Jupyter;
* not to forget DevOps with Docker, GCE and AWS.
A conference given at softshake 2016 in Geneva - www.softshake.ch