How To: Deploy RStudio Server (sys-admin nomination required)

Author:Alessandro Costantini
Version:1
Copyright:This document has been placed in the public domain.

1. The RStudio Server

The following procedure will guide you into the deployment of the self-consistent RStudio server. RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.

2. Prerequisites

The user has to be registered in the INFN Cloud Identity and Access management (IAM) system, https://iam.cloud.infn.it/ in order to access the INFN-CLOUD dashboard, https://my.cloud.infn.it/.

Warning

The solution presented in this guide is available only to the beta-testers group. You need to be member of this IAM group to use it.

3. User responsabilities

Important

The solution described in this guide consists on instantiation of a Virtual Machine instantiated on INFN-CLOUD infrastructure. The instantiation of a VM comes with the responsibility of maintaining it and all the services it hosts.

Please read the INFN Cloud AUP in order to understand the responsabilities you have in managing this service.

4. Notes for the reader

The current deployment does not support the GPU implementation. Only CPU implementation is avaialble. Selecting providers with GPU resources (see Step 2 - Select and Configure the RStudio deployment) does not enable the use of GPU in the deployed RStudio application.

5. How to deploy and access RStudio Server

RStudio is an integrated development environment (IDE) for R that includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.

Step 1 - Connecting and authenticating to the INFN-CLOUD dashboard

In order to access to the INFN-CLOUD dashboard (https://my.cloud.infn.it/), the user needs to authenticate using the its INFN AAI credentials.

Figure 1: INFN-CLOUD dashboard login

Figure 1: INFN-CLOUD dashboard login

Figure 2: INFN-CLOUD IAM login

Figure 2: INFN-CLOUD IAM login

Step 2 - Select and Configure the RStudio deployment

Note

If you belong to multiple projects, aka multiple IAM-groups, after login into the dashboard, from the upper right corner, select the one to be used for the deployment you intend to perform. Not all solutions are available for all projects. The resources used for the deployment will be accounted to the respective project, and impact on their available quota. See figure below.

../_images/howto1_01.png

After selecting RStudio from the list of applications (see Fig. 3) and the related project he or she belong to, the user is redirected to the deployment setting window (see Fig. 4 and Fig. 5).

Figure 3: INFN-CLOUD Dashboard applications

Figure 3: INFN-CLOUD Dashboard applications

Figure 4: Rstudio deployment settings – Configuration

Figure 4: Rstudio deployment settings – Configuration

Figure 5: Rstudio deployment settings - Advanced

Figure 5: Rstudio deployment settings - Advanced

Note

Before to continue you have to upload your public (asimmetric) SSH key into the dashboard. The pair public_key and IAM_username will be used to login into the VM. Alternatively, you can generate your own public-private key pair. For more detail visit the section Getting started.

The user has to fill these required mandatory fileds:

  • Deployment description: a brief description of the deployment
  • Configuration TAB
    • Cpus: number of CPU to be used for the deployment
    • Mem: RAM memory to be used for the deployment
    • rstudio_password: password to access the application (by default “rstudio” is used as account name)
  • Advanced TAB
    • Scheduling: set automatic (recommended) or manual (perform a direct submission towards one of the providers available) scheduling
    • Creation timeout (minutes): amount of time to wait until the deployment should be considered failed
    • Failure policy: delete, or not, the deployment in case of failure
    • E-mail: send, or not, a confirmation email when deployment is complete

Note1: Selecting providers with GPU resources does not enable the use of GPU in the deployed RStudio application. See section 2 “Notes for the reader”.

Step 3 - Submitting the RStudio Deployment

After submitting the deployment (green button in Fig. 5), the user is redirected to the deployment list (see Fig. 6) where he or she can follow the evolution of the deployment.

Once successful deployment completion (“CREATE_COMPLETE” flag in Fig. 6), the user can reach the deployed RStudio Server by using the link available by clicking:

  • to the link of Deployment identifier (see Fig. 6)
  • to the Details button at the end of the row (see Fig. 6)
Figure 6: User deployment list

Figure 6: User deployment list

Step 4 - Operate with the deployed RStudio Server

Following the link under ENDPOINT (see Fig. 7), the user is redirected to the RStudio Server that can be accessed by using the credentials (username and password) defined during the deployment configuration phase in Step 2. At this phase, the user can enjoy RStudio (see Fig. 8).

Figure 7: User deployment details

Figure 7: User deployment details

Figure 8: User deployment details

Figure 8: User deployment details