Cb-WoFS: Migrating the Warn-on-Forecast System to the Cloud

Abstract This article provides a brief, technical narrative of the WoFS journey to a cloud-based high-performance computing (HPC) system, including some of the technological challenges encountered and solutions found. Also, discussed are a few new components that are in development for cloud-based Warn-on-Forecast System (cb-WoFS), such as the cloud infrastructure project for managing resources, as well as a new web application that manages cb-WoFS runs. An important initial step in our cloud journey is containerizing all of the compiled applications, such as WRF, GSI, and EnKF and their dependencies like netCDF and MPI. With these applications compiled within an Apptainer container, WoFS can run on any local or cloud-based HPC cluster that supports MPI. Furthermore, an additional software layer was developed that creates and manages cloud vendor resources. This layer, which is referred to as the WoFS framework, contains the workflow required to run cb-WoFS, as well as management for other aspects of cb-WoFS (including but not limited to creation of HPC pools in the end-to-end workflow, runtime notifications, and database management). This additional layer was developed to separate the WoFS business logic from vendor-specific API calls. The WoFS framework exposes features through its service library, which is then referenced by the newly developed cb-WoFS web application and other cloud applications. This makes WoFS a complete end-to-end cloud-based application, where an administrator can launch a model run, manage resources, and view output all within a single web app.

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Publication Details

Journal
Bulletin of the American Meteorological Society
Published
2024-09-27
DOI
https://doi.org/10.1175/bams-d-23-0296.1
Citations
1
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.78
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Cb-WoFS: Migrating the Warn-on-Forecast System to the Cloud

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1 citations
Bulletin of the American Meteorological Society
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article

Cb-WoFS: Migrating the Warn-on-Forecast System to the Cloud

Joshua Martin, Kent H. Knopfmeier, Louis J. Wicker, Nusrat Yussouf, Pamela L. Heinselman, Brian C. Matilla, Patrick C. Burke, Salar Adili, Adam J. Clark
article en
1 citations

Abstract

Abstract This article provides a brief, technical narrative of the WoFS journey to a cloud-based high-performance computing (HPC) system, including some of the technological challenges encountered and solutions found. Also, discussed are a few new components that are in development for cloud-based Warn-on-Forecast System (cb-WoFS), such as the cloud infrastructure project for managing resources, as well as a new web application that manages cb-WoFS runs. An important initial step in our cloud journey is containerizing all of the compiled applications, such as WRF, GSI, and EnKF and their dependencies like netCDF and MPI. With these applications compiled within an Apptainer container, WoFS can run on any local or cloud-based HPC cluster that supports MPI. Furthermore, an additional software layer was developed that creates and manages cloud vendor resources. This layer, which is referred to as the WoFS framework, contains the workflow required to run cb-WoFS, as well as management for other aspects of cb-WoFS (including but not limited to creation of HPC pools in the end-to-end workflow, runtime notifications, and database management). This additional layer was developed to separate the WoFS business logic from vendor-specific API calls. The WoFS framework exposes features through its service library, which is then referenced by the newly developed cb-WoFS web application and other cloud applications. This makes WoFS a complete end-to-end cloud-based application, where an administrator can launch a model run, manage resources, and view output all within a single web app.

Bulletin of the American Meteorological SocietyVol. 105(10)
Microsoft (United States) (US), Cooperative Institute for Mesoscale Meteorological Studies (US), NOAA National Severe Storms Laboratory (US), University of Oklahoma (US)
Openalex Percentile: Top 21%
Cloud Computing and Resource Management
0.78
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