Navigating New Frontiers: Mapping NeSI's progress with the new Open OnDemand Training Environment
Year: 2024
Type: article
Abstract: New Zealand eScience Infrastructure (NeSI) has launched a transformative cloud-based Training Environment using Open OnDemand, marking a significant step in enhancing user experience and accessibility for the research community. By leveraging community feedback and sector best practices, NeSI designed and deployed this training environment through close collaboration between technical experts, product designers, and stakeholders. Key strategies included integrating user-friendly interfaces, streamlining workflows, and enhancing support resources to ensure seamless navigation and engagement. Workshops such as Introduction to R, Machine Learning and Image Analysis, and RNA Sequencing were piloted on the new training environment to assess and enhance its functionality. The overall user experience has been incredibly positive, prompting us to explore ways to enhance it further. The team aimed for a training environment that could be quickly deployed at any time, easing the setup of trainee accounts (previously hindered by the need for NeSI HPC accounts). We wanted our partnering trainers, starting with trainers from Genomics Aotearoa, to provision a training environment with minimal assistance from NeSI, with the potential for additional long-term goals. We leveraged Open OnDemand and OpenStack cloud infrastructure, utilising Terraform and Ansible for a code-based deployment approach, which helps with reproducibility, interoperability, and portability. Currently, the OpenOnDemand training environment is at a pivotal juncture, with significant progress in development and testing. Preliminary user trials and feedback have provided valuable insights for further refinement. To support NeSI s commitment to innovation and improvement, this presentation maps progress and invites feedback on refinement tactics.
Author: Ghatak, Nisha
Institution: New Zealand eScience Infrastructure
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6930708452
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