Serverless databases: Architectural evolution, implementation strategies, and future directions in cloud-native data management

The evolution of modern data centers demands innovative approaches to fabric provisioning, particularly when integrating new switches, hosts, and storage into existing infrastructures. This article introduces a Smart Fabric Provisioning solution powered by Agentic AI that transforms traditional manual processes into automated, intelligent workflows. By creating dynamic full-mesh fabrics with simulated environments, the solution addresses critical challenges in solution qualification and resource utilization during proof-of-concept phases. The AI-driven approach enables logical link manipulation to test various conditions without physical reconfiguration, significantly streamlining deployment workflows while reducing human error. This dual-purpose technology serves both as an internal efficiency tool for engineering teams across multiple geographies and as a valuable automated offering for end customers, representing a paradigm shift in how network fabrics are provisioned, tested, and deployed.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-31
DOI
https://doi.org/10.5281/zenodo.17293642
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
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article

Serverless databases: Architectural evolution, implementation strategies, and future directions in cloud-native data management

Zenodo (CERN European Organization for Nuclear Research)
Cloud Computing and Resource Management
article

Serverless databases: Architectural evolution, implementation strategies, and future directions in cloud-native data management

article en

Abstract

The evolution of modern data centers demands innovative approaches to fabric provisioning, particularly when integrating new switches, hosts, and storage into existing infrastructures. This article introduces a Smart Fabric Provisioning solution powered by Agentic AI that transforms traditional manual processes into automated, intelligent workflows. By creating dynamic full-mesh fabrics with simulated environments, the solution addresses critical challenges in solution qualification and resource utilization during proof-of-concept phases. The AI-driven approach enables logical link manipulation to test various conditions without physical reconfiguration, significantly streamlining deployment workflows while reducing human error. This dual-purpose technology serves both as an internal efficiency tool for engineering teams across multiple geographies and as a valuable automated offering for end customers, representing a paradigm shift in how network fabrics are provisioned, tested, and deployed.

Zenodo (CERN European Organization for Nuclear Research)
University of Madras (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Cloud Computing and Resource Management
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Serverless databases: Architectural evolution, implementation strategies, and future directions in cloud-native data management · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS