My favorite way to deploy RShiny locally is to simply package it into a docker image and run it. Running any application in docker makes it easily transportable, and is a generally acceptable way of distributing applications in 2019.

This solution does not require rshiny-server or shinyapps.io, not because I have anything against either of those solutions. I just tend to stick to a few favorite deployment methods to keep my head from spinning straight off my body. ;-)

If you're not familiar with docker then I have a FREE course available. The first module is plenty to get you up and running and can be completed in an hour or two. For the most part, if you can use a command line you can use docker.

Package your R Shiny App in Docker

Now that we've covered some housekeeping let's get started building your docker image. Like any project, you want to have all your relevant code in a directory. This way it is accessible to the docker build process.

Project Directory Structure 

If your head is spinning over which deployment scenario to choose for your RShiny app look no further! I have a whole series planned out for you on various deployment options and why you should choose each one.

Why should you use AWS Lightsail for RShiny Deployment?

Deployment scenarios are like snowflakes. No two are exactly alike! ;-) You need different level of power and control for different deployment scenarios. Here we are going to talk about RShiny deployments, but it applies to just about everything.

Lightsail is a relatively recent addition to the whole AWS deployment ecosystem.  It makes it much simpler and more streamlined to deploy a web application than some of their other, more powerful solutions.

Lightsail would be a good choice for deployment for you if:

• You don't feel comfortable deploying web applications or configuring web servers (Apache, NGINX).
• You are just fine with configuring webservers but you need something quick and easy.
• You have a smallish...