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CMCC Data Delivery System: Overview, Recent Advances and Future Perspectives

داریوش
داریوش

CMCC Webinar

Speaker
Marco Mancini, CMCC – ASC Division

Moderator
Monia Santini, CMCC – IAFES Division

Abstract
The CMCC Data Delivery System (DDS) has been operational since December 2020 for publishing and disseminating scientific dataset produced by CMCC Research Divisions. Since its first deployment, the system has evolved to ensure better robustness and performance. Current version relies on a cloud-native microservices-based architecture that has been deployed — using Kubernetes — to the production environment in March 2023. In this webinar, we will describe in detail the new DDS architecture and the different frameworks, tools, libraries and technologies that have been adopted for the DDS architectural components. The core of the DDS is geokube; it is a Python library we have been developing with the aim to improve the user experience (UX) as well as for the analysis and visualisation of climate and earth science data. It provides high-level abstractions in terms of both Data Model (inspired by Climate Forecast and Unidata Common Data Models) and Application Programming Interface (inspired by xarray package).

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CMCC Data Delivery System: Overview, Recent Advances and Future Perspectives

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CMCC Webinar

Speaker
Marco Mancini, CMCC – ASC Division

Moderator
Monia Santini, CMCC – IAFES Division

Abstract
The CMCC Data Delivery System (DDS) has been operational since December 2020 for publishing and disseminating scientific dataset produced by CMCC Research Divisions. Since its first deployment, the system has evolved to ensure better robustness and performance. Current version relies on a cloud-native microservices-based architecture that has been deployed — using Kubernetes — to the production environment in March 2023. In this webinar, we will describe in detail the new DDS architecture and the different frameworks, tools, libraries and technologies that have been adopted for the DDS architectural components. The core of the DDS is geokube; it is a Python library we have been developing with the aim to improve the user experience (UX) as well as for the analysis and visualisation of climate and earth science data. It provides high-level abstractions in terms of both Data Model (inspired by Climate Forecast and Unidata Common Data Models) and Application Programming Interface (inspired by xarray package).

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