Hi,
Just found the Disco Fmw few days ago. I have been on other options though.
I am very interested in Disco
Have you watched the movie The Martian?
Basically, I have studied the Hadoop stack but Java is not really my thing. The (formal) complexity of MapReduce is too high for the purposes I am implementing this pipeline (small-medium projects running on cloud providers, with very segmented data. Basically every microservices would handle few variables indexed by geopoints and its aggregates) and usually too resources-draining in terms of learning/working hours and compute costs. Something like the map and reduce command pipeline used by MongoDB CLI (former versions) would be already a quite powerful tool.
By now I am doing research and using the module for netCDF https://netcdf4-python.googlecode.com/svn/trunk/docs/netCDF4-module.html that is a network format for exchanging HDF5, the highly distributed file system by Unidata; and open source GIS solutions for geoquerying.
My focus now is to design and develop simple ad-hoc solutions to map HDF5 data to Web services with Python.
Soon I would like to add some new layers to this pipeline: map-reduce ( and I found the Disco Fmwk Python API) or a basic homebrewed library with some simple methods (as told before about early Mongo implementations), and a “compute unit” to ease data-scientists studying aggregates.
I thought to integrate this system with Kubernetes using multiple clusters of microservices. It’s a cool experiment I think.
I am considering Elixir because of I always wanted to learn functional, and concurrency can be the thing for making this possible.
Any idea or comment welcome 
PS. Doing something with Elixir would make everything not monolithic, easily scalable for any level of usage, lowering deploying barriers. Making Python and Elixir working together programmatically on HTTP would be great!
PPS. I am also on Slack as lorenzogotuned, I started a channel #web-and-data
