Current AMI Quick Reference (17th October 2017)
Amazon instance type reference
Click to launch through AWS web interface:
Region64-bit HVM AMI
EU West, Ireland ami-93805fea
EU West, London ami-bf6b76db
EU Central, Frankfurt ami-a80db3c7
Canada, Central ami-75c17911
US East, Virginia ami-fd2ffe87
US East, Ohio ami-3b0c205e
US West, N. California ami-7291a312
US West, Oregon ami-bca063c4
South America, São Paulo ami-c9344da5
Asia Pacific, Singapore ami-5b9bde38
Asia Pacific, Tokyo ami-9cbe65fa
Asia Pacific, Seoul ami-1280257c
Asia Pacific, Sydney ami-6735d805
Asia Pacific, Mumbai ami-63cb880c

RStudio1.1.383  20GB SSD EBS store
R3.4.2  RStudio on port 80 (HTTP)
Julia0.6.0  Shiny at /shiny/rstudio
CUDA8  Jupyter at /julia
Ubuntu16.04 LTS  Username: rstudioPassword: rstudio

What's new recently?
  • Updated R, RStudio and Julia versions.
  • CUDA 8 and cuDNN 6 enabling easy use of GPU instances with Tensorflow/Keras
  • Magma 2.2.0 GPU linear algebra library

< Back to homepage

Amazon’s EC2 platform provides a convenient environment for rapidly procuring computational resources in the cloud. As a Statistician, my interest is specifically in statistical computation with R and the advent of RStudio Server has made it a hand-in-glove fit with the cloud.

To get started with the Amazon cloud, you must first signup for an AWS account if you don’t already have one. To use the AMIs described on this page, you simply click your chosen AMI ID which will take you through to the Amazon web interface and preselect the correct region and AMI. Simply ensure that your ‘security group’ settings allow incoming HTTP (port 80) traffic and then copy-and-paste the ‘Public DNS’ for your running instance to a web browser address bar to bring up the login page.

Click here for a simple video guide to using the AMIs listed here, or for more detailed information read on.

What is this?

If you want to run a server in the Amazon cloud, you have to select what system you are going to bootup. This is made easy by a vast array of system images (or AMIs) which pre-pacakge a system ready for you to boot on your own custom virtual server. Many of these are simply base operating system installs, such as Debian or Ubuntu, but others add on pre-configured extra software into the image to reduce time-to-getting-stuff-done! I have created an AMI specifically targeted at R and RStudio Server with the goal of making it a 1 minute job to get going for anyone with an AWS account.

In particular, many common tools and dependencies are built-in. Features include:


As of May 2016 there is experimental support for Julia (and Python). Julia is an exciting new technical computing language which is very high performance. A lot of R programmers may be interested in levereging both languages, so the AMIs now include a web interface (Jupyter) which enables using Julia immediately. In order to access this interface, simply go to the URL http://<instance IP address>/julia

Initially, updates in the AMI related to Julia will be pegged to R releases.

Why an RStudio AMI?

The RStudio team have done a phenomenal job with making it simplicity itself to install, but there are still several motivating factors which led to me creating this AMI:

AMI Release History

Check back for updates as I will be periodically removing old AMIs because I can’t afford indefinite storage for them. For historical purposes, the AMI release history is recorded here (scroll right to see all):

Release EU West
EU West
EU Central
US East
US East
US West
(N. Calif.)
US West
S. America
(São Paulo)
Asia Pacific
Asia Pacific
Asia Pacific
Asia Pacific
Asia Pacific
RStudio 1.1.383
R 3.4.2
Julia 0.6.0
CUDA 8/cuDNN 6
ami-93805fea ami-bf6b76db ami-a80db3c7 ami-75c17911 ami-fd2ffe87 ami-3b0c205e ami-7291a312 ami-bca063c4 ami-c9344da5 ami-5b9bde38 ami-9cbe65fa ami-1280257c ami-6735d805 ami-63cb880c
RStudio 1.0.153
R 3.4.1
Julia 0.6.0
ami-f0df2489 ami-dfdbcbbb ami-0e5cf661 ami-7245fb16 ami-69909f12 ami-12d1f277 ami-ee56628e ami-013dd679 ami-6307740f ami-a13b59c2 ami-2ea35b48 ami-3b5f8755 ami-75b0aa16 ami-2a3c7845
RStudio 1.0.143
R 3.4.0
Julia 0.5.2
ami-cbd3c6ad ami-57021533 ami-4421f92b ami-6b5ee20f ami-65206673 ami-fe98bf9b ami-fe42629e ami-82ccade2 ami-07bcd26b ami-c6db5da5 ami-849fa4e3 ami-f867ba96 ami-d45246b7 ami-5ed2af31
RStudio 0.99.903
R 3.3.1
Julia 0.4.6
ami-b1b0c3c2 N/A* ami-ca46b6a5 N/A* ami-8fe18f98 N/A* ami-c0b8f5a0 ami-6a52840a ami-55079639 ami-ce9c47ad ami-1f79b17e ami-41f4212f ami-b9093fda N/A*
RStudio 0.99.896
R 3.3.0
Julia 0.4.5
ami-ca149fb9 N/A* ami-6ec92401 N/A* ami-0acd2067 N/A* ami-ada2dbcd ami-c78875a7 ami-af26afc3 ami-3f9a4c5c ami-90dd39f1 ami-6e68a000 ami-72def211 N/A*
RStudio 0.99.491
R 3.2.3
ami-e95df59a N/A* ami-52edf33e N/A* ami-7f9dc615 N/A* ami-d1e792b1 ami-1d7f657c ami-50f1703c ami-b277bad1 ami-2549744b N/A* ami-a54a6fc6 N/A*
RStudio 0.99.484
R 3.2.2
ami-776d5a00 N/A* ami-88bab895 N/A* ami-753e7c10 N/A* ami-b733f5f3 ami-0ea84c3d ami-2b24b336 ami-22b6a070 ami-a449d2a4 N/A* ami-1170382b N/A*
RStudio 0.99.447
R 3.2.1
ami-0c13557b N/A* ami-4c360d51 N/A* ami-47a6622c N/A* ami-a7cc3ae3 ami-55353265 ami-99c34e84 ami-f4dbdda6 ami-bca606bc N/A* ami-d57336ef N/A*
RStudio 0.98.1103
R 3.2.0
ami-a76705d0 N/A* ami-f8a995e5 N/A* ami-628c8a0a N/A* ami-45c72a01 ami-a9596d99 ami-cb1b9ed6 ami-a4cef3f6 ami-84539484 N/A* ami-2581fc1f N/A*
RStudio 0.98.1103
R 3.1.3
ami-a544dad2 N/A* ami-bc0538a1 N/A* ami-bc5877d4 N/A* ami-e7a140a3 ami-73ad8143 ami-6907bf74 ami-2897a67a ami-47f90f47 N/A* ami-65ec9c5f N/A*
RStudio 0.98.1091
R 3.1.2
ami-368c3241 N/A* ami-5275454f N/A* ami-a0c7a6c8 N/A* ami-01dcce44 ami-418fde71 ami-6314a47e ami-2978577b ami-58636c59 N/A* ami-3f84ec05 N/A*
RStudio 0.98.1060
R 3.1.1
64-bit ami-ae05a1d9 N/A* N/A* N/A* ami-4e4ce226 N/A* ami-47f3fa02 ami-614b0b51 ami-fb9832e6 ami-46012514 ami-658da164 N/A* ami-ef6a09d5 N/A*
RStudio 0.98.501
R 3.1.0
64-bit ami-2f7d8658 N/A* N/A* N/A* ami-7376691a N/A* ami-a6b68fe3 ami-b00c6680 ami-ed2785f0 ami-4a356618 ami-b3b5ccb2 N/A* ami-0b41d931 N/A*
RStudio 0.98.501
R 3.0.3
64-bit ami-470ff130 N/A* N/A* N/A* ami-930f18fa N/A* ami-76e9d733 ami-04c7ae34 ami-abdc7eb6 ami-f06131a2 ami-4599e444 N/A* ami-d9cb53e3 N/A*
RStudio 0.97.551
R 3.0.1
64-bit ami-6bfeed1f N/A* N/A* N/A* ami-69fa8d00 N/A* ami-2387a966 ami-1ffd6d2f ami-1c832601 ami-7cc28c2e ami-b747ccb6 N/A* ami-05b7243f N/A*
RStudio 0.97.320
R 2.15.3
64-bit ami-4ab7bf3e N/A* N/A* N/A* ami-0ed24c67 N/A* ami-90705dd5 ami-6868fd58 ami-9b33e886 ami-4cfab71e ami-5151d050 N/A* ami-2848d912 N/A*
RStudio 0.97.245
R 2.15.2
64 bit ami-e6b5b892 N/A* N/A* N/A* ami-f129ab98 N/A* ami-4686a703 ami-d677ffe6 ami-f3fc24ee ami-9d0745cf ami-d0fd46d1 N/A* ami-1f48df25 N/A*
RStudio 0.95.256
R 2.14.1
32 bit ami-4b3c023f N/A* N/A* N/A* ami-13f1207a N/A* ami-61174e24 ami-5852df68 ami-504b944d ami-e02460b2 ami-50863051 N/A* N/A* N/A*
64 bit ami-0b3c027f N/A* N/A* N/A* ami-a5f120cc N/A* ami-6b174e2e ami-5c52df6c ami-524b944f ami-e82460ba ami-58863059 N/A* N/A* N/A*
RStudio 0.94.110
R 2.14.0
32 bit ami-438cb137 N/A* N/A* N/A* ami-83a961ea N/A* ami-47530c02 ami-848c01b4 N/A* ami-b4dda7e6 ami-30e65131 N/A* N/A* N/A*
64 bit ami-1184b965 N/A* N/A* N/A* ami-53be763a N/A* ami-f74e11b2 ami-9c8f02ac N/A* ami-28d1ab7a ami-7ee3547f N/A* N/A* N/A*
RStudio 0.92.94
R 2.13.1
32 bit ami-a06e5dd4 N/A* N/A* N/A* ami-2b77b642 N/A* ami-1d411c58 N/A* N/A* ami-08770c5a ami-ee893cef N/A* N/A* N/A*
64 bit ami-b86e5dcc N/A* N/A* N/A* ami-2d77b644 N/A* ami-1f411c5a N/A* N/A* ami-0a770c58 ami-ec893ced N/A* N/A* N/A*
* N/A since these data centres were not yet open when the images were built.

Regions, 32-bit, 64-bit, HVM???

There are a lot of AMIs to maintain because Amazon have a relatively complicated set of options for running virtual servers. Recently that has simplified so that the only major choice to make is what region you would like to run in, because all instance types now support 64-bit and HVM (the highest performance).

Choosing a region close to you should help reducing latency. More advanced users may choose the cheapest region for a spot instance.

Once you have chosen, simply click on the link above to be taken straight to the AWS launch page and login to your account.


Simply launch an instance using the appropriate AMI ID (above) for your region and ensure that the security group you setup allows (as a minimum) inbound HTTP (port 80) traffic. Once your instance moves from the “pending” to “running” state, then copy and paste the public DNS address or IP address from the instance properties to your browser and you should receive an RStudio login page. The default login details are:


You will then be in and able to use R straight away. It is highly recommended you change the password immediately and an easy means of doing this is explained upon login in the script that is loaded there. However, users who are comfortable with Linux can follow the usual procedure for changing system user passwords via SSH if they prefer.

In order to access Julia or Python via Jupyter, simply add /julia to the end of the URL. Likewise, publicly visible Shiny apps can be accessed at /shiny/username (e.g. /shiny/rstudio for the default user). To make shiny apps visible, they should be placed in a folder named ShinyApps in the user’s home directory.

The AMI now ships with a package called RStudioAMI preloaded. Currently this contains two main areas of functionality:





comments powered by Disqus