A quick template for booting up a fresh EC2 instance with RStudio Server running

RStudio_EC2.md

Provision EC2 instance

• Use AMI Ubuntu Server 18.04 LTS (HVM), SSD Volume Type - ami-005bdb005fb00e791 (64-bit x86)
• At least a t2.medium
• At least 30 GB Root volume
• Set up TCP port 22 and port 8787 (RStudio server) access for my IP
• Tag with Name = turbo-rstudio
• Use the turbo-rstudio keypair
  • You already have this .pem file in your ~/Downloads/ dir, already did chmod 0400

Connect (from your Chromebook in this example)

• Open a shell, run ssh -i /home/chronos/user/Downloads/turbo-rstudio.pem ubuntu@ec2-34-213-182-15.us-west-2.compute.amazonaws.com
  • Obvi, switch the URL for this instance's URL
• When connected, run this block:

sudo apt-get update
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9 
sudo apt-add-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/'
sudo apt-get -y install r-base r-base-dev gdebi-core wget libxml2-dev libcurl4-openssl-dev libssl-dev default-jre default-jdk
wget https://download2.rstudio.org/server/bionic/amd64/rstudio-server-1.2.1335-amd64.deb
sudo gdebi rstudio-server-1.2.1335-amd64.deb
sudo R CMD javareconf
sudo passwd ubuntu # make it 'ubuntu'

• Open in a web browser: http://ec2-34-213-182-15.us-west-2.compute.amazonaws.com:8787
• Run install.packages(c("tidyverse", "ggsci")) cause it takes forever

Other stuff you'll likely want to do

• install.packages("doParallel")

• install.packages(c("bayesAB", "lmerTest", "BayesFactor"))

• install.packages("caret")

• install.packages("bartMachine")

• This whole thing will take up about 4GB of space on the root partition