Evaluating Kibana for reporting and visualization

[raff (Rafal Korytkowski)]

I can’t recall us being ever able to get deidentified data from an implementation (yes, let’s make one more attempt!), but we may get them to try out what we accomplish here and have an incentive to collaborate further on that setup. It is why I think it is important to do it in Docker so it can be easily run by others on real data.

There are official docker images for the whole stack at elastic · GitHub with documentation so it shouldn’t be hard.

@darius

Also, I think that @jdick and AMPATH may already be putting OpenMRS data into ElasticSearch for analysis, and maybe we could use something they’ve done as a starting point. Also, @mogoodrich and @mseaton were recently experimenting with something along these lines, but I think they went another way.

I’m very excited to hear your stories!

@darius

Specifically, if you were to index all the observations into ES it’s going get huge, and require more resources than OpenMRS itself. That seems impractical for a typical implementation, so from the beginning I would avoid this

Has ever anyone evaluated how much it is in practice? I figure you can always limit to a year of observations and still find it useful.

@lluismf, how about @adamg will work on creating the docker setup and you take it from there… @adamg, would you be interested in creating docker-compose with RA 2.6 and ELK (full stack)?