In 4 Steps your Application (including R) is running on a Cloud Computing Cluster

[This article was first published on » R-project, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Today, cloud computing is used in many application areas from academic research to industry. Commercial cloud providers as Amazon Web Services (AWS) advertise the simple and fast access to cloud computing resources. Posts in different blogs proof that you can get your application running in the cloud, but it will cost you more than 15 clicks. Nice and self-explanatory examples are provided in the Travis Nelson blog about getting the statistical software R ( running on AWS:

All these posts only describe how to get one instance running in the cloud. If you have computer intensive analyses you will need a small or big computer cluster with several instances and all the configuration and installation gets more complex. Already watching the simple AWS HPC introduction video takes your more than 18 minutes. provides you with the resources to perform high performance calculations in the cloud. Check our latest video presentation how to save costs with

Within 5 minutes you get access to a powerful cluster with more than 1000 cores or a simple high memory machine in the cloud:

  1. Go to http:///, click on “Register for free now” and create your account.
  2. Go to and login with your e-mail and password. You are now logged in to the’s dashboard.

    Feel free and explore all the different areas. Many explanations and tutorial you can find in our customer service area.
  3. Start your first workspace by using the default Sample Workspace. The workspace is not to be mistaken with an R Workspace. Your workspace is a fully featured online file system which is encrypted with AES 256 Bit. You can up- and download data with FTPS or a browser HTTPS upload including Drag & Drop (check our latest workspace video).
  4. “Start a Session” with the corresponding button. Now there are 5 additional clicks to configure your cloud computing cluster.
    • Select a workspace and a database (optional): You have to choose one of your workspaces in order to mount it with the session. Please note: your workspaces can only be mounted to one session at a time. As needed you can select a dataset that you want to make available on your cluster.
    • Choose an application: currently provides different applications in the cloud: e.g. R, Python. Soon we will expand our portfolio to many other open source HPC applications. If you have any suggestions please contact us: [email protected]
    • Customize the application: Many applications offer a variety of packages that can be installed on top. For the statistical software R the CRAN and Bioconductor packages are available. If you need any other package please contact us: [email protected]
    • Choose the instance type and cluster size: Depending on your rate plan you can start clusters with up to 128 instances and 68 GB of memory. This step allows you to specify your needs. Please note that you have to adopt your script in order to be able to process your calculations parallel on more than one instance. You can find many tips and tricks in our blog and in our customer service area.
    • Confirm: Please check your session details again and start the session. This can take some minutes depending on your configuration and cluster size. You will get an email as soon as the session is up and running.

Now you are all set and ready to go. Simply choose whether you would like to run your application in our webinterface (click on “open console”) or if you would like to use the SSH console on your computer. In order to do so click on “SSH Key + Show details” after the cluster is ready.

In this example your default R command line interface is running in your web browser using on computing instance in the cloud:

This is only a selection of features available at We provide you with many more features. For example, our workspace browser supports Drag & Drop of files from a folder on your desktop directly onto the browser and the upload of a bunch of files at once. Or go to the tab “Console” and start a desktop environment in the cloud.
Furthermore, you can use for serial computing, too. There is no need to use a computer cluster. For example, if you need a lot of main memory for your application we can provide you a big memory machine. Just choose your favorite instance type.

Keep on following our blog to get more information about running R or any other application in parallel and in a high efficient way in the cloud. If you have any questions, problems or feedback concerning please send us an email and we will help you immediately: [email protected]

Register and test at for free now!

To leave a comment for the author, please follow the link and comment on their blog: » R-project. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)