Deploy RShiny on AWS

Overview

The Deploy RShiny on AWS Guide walks you through: 

• Getting started by packaging your RShiny Application with Docker by building a custom docker image with Miniconda. Using Miniconda is especially useful if you need to integrate with other scientific software!
• Alternately, the guide will walk you through packaging your RShiny application up with the default Rocker/Shiny image, with RShiny already installed and ready to go.

Once your application is packaged up and ready to go we'll get into deployment scenarios. For each deployment scenario, I'll discuss the pros and cons, and when it is better to use one over another.  

• Once you have your application packaged with Docker you can deploy to Lightsail, EC2, or Kubernetes.

As a bonus I've included how to deploy a Kubernetes cluster using Terraform, an infrastructure as code library. You do not need to know how to use Terraform to complete this exercise. The work is done for you up front. 

• Included in the guide is how to automatically deploy a Kubernetes Cluster with your data visualization app using Terraform and Helm.

All Open Source

All the code and examples included in the guide are completely open-source. Each deployment scenario includes all the code! Code examples include:

1. A sample RShiny app
2. Docker build files for custom builds with Miniconda and the default RShiny docker image
3. Terraform infrastructure as code recipes for autodeploying Kubernetes clusters
4. A chart recipe to deploy your RShiny App on any Kubernetes Cluster