by Alexandre Masselot (OCTO Technology Switzerland), Catherine Zwahlen (OCTO Technology Switzerland) and Jonathan Gianfreda.
The possibility of custom plugins is a strong Kibana promise. We propose an end to end tutorial to write such plugins. But this “end to end” approach also means “how to continuously deploy them?”, “how to share an environment with seeded data?” Those questions will bring us in a full fledged integration infrastructure, backed by Docker.
The Elasticsearch has grown from a Lucene evolution to a full fledged distributed document store, with powerful storage, search and aggregation capabilities. Kibana has definitely brought a strong component for interactive searching and visualization, transforming the data storage tier into an end user browser.
Customizable dashboards via a rich library of graphical components made its success, but soon, the need for real customization arose. If plugins were thought to be integrated from early on, the actual customization often lied into forking the master project and adapting to on particular purpose. Merging back fixes was soon to be a daunting effort to keep up with the high pace of the Github repository evolution .
So, that should be easy. Just google and you would craft wonderful shiny visualizations.
But not fast, young Kibana Padavan! Documentation lacks, resources are valuable but scarce. But the promise is still shiny and we want to reach it.
In this post, we propose to share our journey into the writing of Kibana plugins, the little pitfalls we fell in and the setup of continuous deployment into a Docker environment. There is no dramatic discovery or stunning breakthrough today, but a tentative to write a map to make your journey easier.