Deploy RShiny on AWS EKS with Terraform

Today we will be deploying the rocker/shiny image on Kubernetes with AWS, or EKS.

If you're following along with the deploy RShiny on AWS Series, you'll know that I covered deploying RShiny with a helm chart . Today, I want to go deeper into deploying RShiny on EKS, along with some tips and tricks that I use for my everyday deployments.

An Extremely Brief Introduction to Kubernetes

Kubernetes is kind of a beast to get started with, and people constantly complain that its extremely complicated to get started with. They would be correct, but I'm here to give the 2 minute rundown of what you need to know to deploy your RShiny (or Dash, Flask, Django, Ruby on Rails, etc) application on Kubernetes. This is because Kubernetes is not magical, and it's not even that new. It's a very nice abstraction layer on top of infrastructure concepts that already exist.

Disclaimer! I know I am oversimplifying things here, and I am totally...

If you are deploying RShiny with docker you can roll your own image , or you can use the rocker Dockerhub image .

Which solution you go for will depend upon your own needs. Normally, I am using a lot of bioinformatics and/or data science packages and nothing really beats the conda ecosystem for that in my opinion. On the other hand having an image with RShiny already installed is really nice! I also quite like the way that the rocker/shiny image is configured. You drop your files into a directory and as long as you have the packages you need your shiny app will start up directly!

Deploy a simple shiny app using the rocker/shiny image

Here is our usual shiny app mostly stolen from the R shiny docs . ;-)

#!/usr/bin/env Rscript # This example comes from the r-shiny examples github repo. # https://github.com/rstudio/shiny-examples/blob/master/001-hello/app.R library(shiny) # Define UI for app that draws a histogram ---- ui <- fluidPage( # App title ---- titlePanel("Hello Shiny!"), #...

If you want a very robust solution to deploy your RShiny applications a managed Kubernetes service on AWS, or EKS, is a great choice! Kubernetes has, for now, fully dominated the DevOps and deployment space in terms of deploying containerized services.

Should I Use Kubernetes to Deploy my RShiny App?

As with all things, there are pros and cons to using Kubernetes.

Cons

• Kubernetes is a beast to get started with.
• You need to have your RShiny App packaged with docker.

Pros

• Kubernetes is incredibly well supported across a range of providers, including AWS, GCP, Azure, Digital Ocean, etc.
• Kubernetes is complicated, but with complicated comes armies of engineers who want to abstract away the complicated into configuration files. So you if you stick with the growing pains it's likely you will get a lot of benefit and things will get less painful over time.
• Kubernetes has been embraced by the "people who deploy stuff" community, which means that there are a lot of resources out for it.
• ...

If you're deploying applications on AWS one of the easier ways to get started is to simply deploy everything on EC2. If you're not familiar with AWS EC2, EC2 instances are compute instances. They are like your (linux) desktop, except that yous spin them up and kill them on demand with AWS console (or CLI or some other infrastructure automation tool).

Should I use EC2 to Deploy my RShiny App?

If you're looking for a solution that has some built in scale and ability to throw a Load Balancer at it EC2 is fine. It's also nice because it's just a computer. You don't have to find a work around to get you a computer the way you do with Docker (docker run) or Kubernetes (kube exec). You deal with an EC2 instance the way you would any remote server, but its on AWS so you get some additional niceness such as the backups, Elastic IPs, and Load Balancers.

This is slightly more difficult than using LightSail. If you are completely new to AWS and on a tight deadline you may want to start there....

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...