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Deploying Jupyter Notebooks at scale on XSEDE resources for Science Gateways and workshops

Authors:

Andrea Zonca,

Robert S. SinkovitsAuthors Info & Claims

PEARC '18: Proceedings of the Practice and Experience on Advanced Research Computing: Seamless Creativity

Article No.: 8, Pages 1 - 7

https://doi.org/10.1145/3219104.3219122

Published: 22 July 2018 Publication History

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Abstract

Jupyter Notebooks have become a mainstream tool for interactive computing in every field of science. Jupyter Notebooks are suitable as companion applications for Science Gateways, providing more flexibility and post-processing capability to the users. Moreover they are often used in training events and workshops to provide immediate access to a pre-configured interactive computing environment. The Jupyter team released the JupyterHub web application to provide a platform where multiple users can login and access a Jupyter Notebook environment. When the number of users and memory requirements are low, it is easy to setup JupyterHub on a single server. However, setup becomes more complicated when we need to serve Jupyter Notebooks at scale to tens or hundreds of users. In this paper we will present three strategies for deploying JupyterHub at scale on XSEDE resources. All options share the deployment of JupyterHub on a Virtual Machine on XSEDE Jetstream. In the first scenario, JupyterHub connects to a supercomputer and launches a single node job on behalf of each user and proxies back the Notebook from the computing node back to the user's browser. In the second scenario, implemented in the context of a XSEDE consultation for the IRIS consortium for Seismology, we deploy Docker in Swarm mode to coordinate many XSEDE Jetstream virtual machines to provide Notebooks with persistent storage and quota. In the last scenario we install the Kubernetes containers orchestration framework on Jetstream to provide a fault-tolerant JupyterHub deployment with a distributed filesystem and capability to scale to thousands of users. In the conclusion section we provide a link to step-by-step tutorials complete with all the necessary commands and configuration files to replicate these deployments.

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Cited By

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Michels APadmanabhan ALi ZWang S(2023)EasyScienceGateway: A new framework for providing reproducible user environments on science gatewaysConcurrency and Computation: Practice and Experience10.1002/cpe.792936:4Online publication date: 13-Oct-2023
https://doi.org/10.1002/cpe.7929
Elhayany MNair RStaubitz TMeinel CKizilcec RDavis KOchoa X(2022)A Study about Future Prospects of JupyterHub in MOOCsProceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3529537(275-279)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1145/3491140.3529537
Hancock DFischer JLowe JSnapp-Childs WPierce MMarru SCoulter JVaughn MBeck BMerchant NSkidmore EJacobs G(2021)Jetstream2: Accelerating cloud computing via JetstreamPractice and Experience in Advanced Research Computing 2021: Evolution Across All Dimensions10.1145/3437359.3465565(1-8)Online publication date: 17-Jul-2021
https://dl.acm.org/doi/10.1145/3437359.3465565
Show More Cited By

Index Terms

Deploying Jupyter Notebooks at scale on XSEDE resources for Science Gateways and workshops
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Web-based interaction
2. Theory of computation
  1. Models of computation
    1. Interactive computation

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PEARC '18: Proceedings of the Practice and Experience on Advanced Research Computing: Seamless Creativity

July 2018

652 pages

ISBN:9781450364461

DOI:10.1145/3219104

General Chair:
Sergiu Sanielevici
Pittsburgh Supercomputing Center

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 the author(s) 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: 22 July 2018

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PEARC '18

PEARC '18: Practice and Experience in Advanced Research Computing

July 22 - 26, 2018

PA, Pittsburgh, USA

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PEARC '18 Paper Acceptance Rate 79 of 123 submissions, 64%;

Overall Acceptance Rate 133 of 202 submissions, 66%

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Michels APadmanabhan ALi ZWang S(2023)EasyScienceGateway: A new framework for providing reproducible user environments on science gatewaysConcurrency and Computation: Practice and Experience10.1002/cpe.792936:4Online publication date: 13-Oct-2023
https://doi.org/10.1002/cpe.7929
Elhayany MNair RStaubitz TMeinel CKizilcec RDavis KOchoa X(2022)A Study about Future Prospects of JupyterHub in MOOCsProceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3529537(275-279)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1145/3491140.3529537
Hancock DFischer JLowe JSnapp-Childs WPierce MMarru SCoulter JVaughn MBeck BMerchant NSkidmore EJacobs G(2021)Jetstream2: Accelerating cloud computing via JetstreamPractice and Experience in Advanced Research Computing 2021: Evolution Across All Dimensions10.1145/3437359.3465565(1-8)Online publication date: 17-Jul-2021
https://dl.acm.org/doi/10.1145/3437359.3465565
Cunha RVilla Real LSouza RSilva BNetto M(2021)Context-aware Execution Migration Tool for Data Science Jupyter Notebooks on Hybrid Clouds2021 IEEE 17th International Conference on eScience (eScience)10.1109/eScience51609.2021.00013(30-39)Online publication date: Sep-2021
https://doi.org/10.1109/eScience51609.2021.00013
Kim BHenke G(2021)Easy-to-Use Cloud Computing for Teaching Data ScienceJournal of Statistics and Data Science Education10.1080/10691898.2020.186072629:sup1(S103-S111)Online publication date: 22-Mar-2021
https://doi.org/10.1080/10691898.2020.1860726
Arms SChastang JGrover MThielen JWilson MDirks D(2020)Introducing Students to Scientific Python for Atmospheric ScienceBulletin of the American Meteorological Society10.1175/BAMS-D-20-0069.1101:9(E1492-E1496)Online publication date: 1-Sep-2020
https://doi.org/10.1175/BAMS-D-20-0069.1
Mehringer SBarker B(2020)Using Containers to Create More Interactive Online Training and Education MaterialsPractice and Experience in Advanced Research Computing 2020: Catch the Wave10.1145/3311790.3396641(246-251)Online publication date: 26-Jul-2020
https://dl.acm.org/doi/10.1145/3311790.3396641
Chandrashekara ATalluri RSivarathri SMitra RCalyam PKee KNair S(2018)Fuzzy-Based Conversational Recommender for Data-intensive Science Gateway Applications2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8622046(4870-4875)Online publication date: Dec-2018
https://doi.org/10.1109/BigData.2018.8622046

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Recommendations

Interactive HPC Gateways with Jupyter and Jupyterhub

UNICORE in XSEDE: Through Development, Integration, Deployment and beyond

Homogenizing OSG and XSEDE: Providing Access to XSEDE Allocations through OSG Infrastructure

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