Hybrid Cloud Architectures for Research Computing: Applications and Use Cases

Fuente: arXiv
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Autori principali: Stiensmeier, Xaver, Kanitz, Alexander, Krüger, Jan, Insua, Santiago, Rošinec, Adrián, Spišáková, Viktória, Hejtmánek, Lukáš, Yuan, David, Farrell, Gavin, Tedds, Jonathan, Törnroos, Juha, Wagener, Harald, Sczyrba, Alex, Hoffmann, Nils, Antol, Matej
Natura: Preprint
Pubblicazione: 2026
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author Stiensmeier, Xaver
Kanitz, Alexander
Krüger, Jan
Insua, Santiago
Rošinec, Adrián
Spišáková, Viktória
Hejtmánek, Lukáš
Yuan, David
Farrell, Gavin
Tedds, Jonathan
Törnroos, Juha
Wagener, Harald
Sczyrba, Alex
Hoffmann, Nils
Antol, Matej
author_facet Stiensmeier, Xaver
Kanitz, Alexander
Krüger, Jan
Insua, Santiago
Rošinec, Adrián
Spišáková, Viktória
Hejtmánek, Lukáš
Yuan, David
Farrell, Gavin
Tedds, Jonathan
Törnroos, Juha
Wagener, Harald
Sczyrba, Alex
Hoffmann, Nils
Antol, Matej
contents Scientific research increasingly depends on robust and scalable IT infrastructures to support complex computational workflows. With the proliferation of services provided by research infrastructures, NRENs, and commercial cloud providers, researchers must navigate a fragmented ecosystem of computing environments, balancing performance, cost, scalability, and accessibility. Hybrid cloud architectures offer a compelling solution by integrating multiple computing environments to enhance flexibility, resource efficiency, and access to specialised hardware. This paper provides a comprehensive overview of hybrid cloud deployment models, focusing on grid and cloud platforms (OpenPBS, SLURM, OpenStack, Kubernetes) and workflow management tools (Nextflow, Snakemake, CWL). We explore strategies for federated computing, multi-cloud orchestration, and workload scheduling, addressing key challenges such as interoperability, data security, reproducibility, and network performance. Drawing on implementations from life sciences, as coordinated by the ELIXIR Compute Platform and their integration into a wider EOSC context, we propose a roadmap for accelerating hybrid cloud adoption in research computing, emphasising governance frameworks and technical solutions that can drive sustainable and scalable infrastructure development.
format Preprint
id arxiv_https___arxiv_org_abs_2601_04349
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Hybrid Cloud Architectures for Research Computing: Applications and Use Cases
Stiensmeier, Xaver
Kanitz, Alexander
Krüger, Jan
Insua, Santiago
Rošinec, Adrián
Spišáková, Viktória
Hejtmánek, Lukáš
Yuan, David
Farrell, Gavin
Tedds, Jonathan
Törnroos, Juha
Wagener, Harald
Sczyrba, Alex
Hoffmann, Nils
Antol, Matej
Distributed, Parallel, and Cluster Computing
Scientific research increasingly depends on robust and scalable IT infrastructures to support complex computational workflows. With the proliferation of services provided by research infrastructures, NRENs, and commercial cloud providers, researchers must navigate a fragmented ecosystem of computing environments, balancing performance, cost, scalability, and accessibility. Hybrid cloud architectures offer a compelling solution by integrating multiple computing environments to enhance flexibility, resource efficiency, and access to specialised hardware. This paper provides a comprehensive overview of hybrid cloud deployment models, focusing on grid and cloud platforms (OpenPBS, SLURM, OpenStack, Kubernetes) and workflow management tools (Nextflow, Snakemake, CWL). We explore strategies for federated computing, multi-cloud orchestration, and workload scheduling, addressing key challenges such as interoperability, data security, reproducibility, and network performance. Drawing on implementations from life sciences, as coordinated by the ELIXIR Compute Platform and their integration into a wider EOSC context, we propose a roadmap for accelerating hybrid cloud adoption in research computing, emphasising governance frameworks and technical solutions that can drive sustainable and scalable infrastructure development.
title Hybrid Cloud Architectures for Research Computing: Applications and Use Cases
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2601.04349