Using Julia Containers as logic processors inside the KBL

Previous work in this blog has focused on providing a framework for the orchestration of processing.  Yet, one piece was left for last.  The actual implementation of the computation logic.  

Kubernetes and Go Channels are good for orchestration  (uber and micro-level) But Julia is good for scientific computing.  What if you had a type of wide receiver on the team that the Go-based quarterback could throw the ball to?  This wide-receiver being a quarterback himself with his own team.  As it turns out.  Julia is well set up to live in such an environment and Julia is Fast! 

https://julialang.org/

Maybe this article is the path. ? 

https://cloud4scieng.org/2018/12/13/julia-distributed-computing-in-the-cloud/

It states:

In this and the next example, we simplify the task of deploying Julia on the remote host by deploying our Julia package as a docker container launched on that host.  To make the ssh connection work we have mapped the ssh port 22 on the docker container to port 3456 on the host.   (We describe the container construction and how it is launched in the next section.)

and this:

To create a worker instance on another host Julia uses secure shell (ssh) tunnels to talk to it.  Hence you need five things:  the IP address of the host, the port that secure shell uses, the identity of the “user” on that host and the private ssh key for that user.  The ssh key pair must be password-less.  The location of the Julia command on that host is also needed.

Another note as per <newsletter@juliacomputing.com> 

As of Jan 1, 2020, Julia has been downloaded more than 12.95 million times - an increase of 77% in just one year. Julia use and popularity grew by double digits last year on every one of the 30+ metrics we track, including those listed below.