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Scaling R Shiny Apps to Multiple Concurrent Users in a Secured HPC Environment Using Open OnDemand

Published: 28 July 2019 Publication History

Abstract

Open OnDemand is an open source project to provide web based access to HPC resources (https://openondemand.org). OnDemand's "Interactive Apps" support launching web applications like Jupyter and RStudio on cluster compute nodes, proxying HTTP requests to those apps, and secure user separation of both app and data access enforced at the OS level [5]. This paper describes leveraging OnDemand to enable the deployment of R Shiny applications that can be launched in OnDemand's interactive HPC environment by multiple analysts at the same time to visualize different datasets. Dataset and app authorization is managed using network file system (NFS) file access lists (ACLs). A custom OnDemand app was built to enable admins to manage who has access to specific apps and what datasets can be loaded by those apps. By using OnDemand to facilitate the use of an HPC batch scheduler as the process manager and OnDemand as the proxy we can support multiple analysts launching Shiny apps to access their data in a scalable and secure manner without the need for managing a separate dedicated installation of RStudio or Shiny Server.

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Cited By

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  • (2021)Open OnDemand as a Platformfor Virtual Learning in Higher EducationProceedings of Sixth International Congress on Information and Communication Technology10.1007/978-981-16-1781-2_30(323-331)Online publication date: 10-Sep-2021

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cover image ACM Other conferences
PEARC '19: Practice and Experience in Advanced Research Computing 2019: Rise of the Machines (learning)
July 2019
775 pages
ISBN:9781450372275
DOI:10.1145/3332186
  • General Chair:
  • Tom Furlani
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2019

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Author Tags

  1. High Performance Computing
  2. Interactive
  3. OSC
  4. Open OnDemand
  5. R
  6. Shiny
  7. Web platform

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  • Refereed limited

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PEARC '19

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Overall Acceptance Rate 133 of 202 submissions, 66%

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Cited By

View all
  • (2021)Open OnDemand as a Platformfor Virtual Learning in Higher EducationProceedings of Sixth International Congress on Information and Communication Technology10.1007/978-981-16-1781-2_30(323-331)Online publication date: 10-Sep-2021

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