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.
@article{arxiv.2601.04349,
title = {Hybrid Cloud Architectures for Research Computing: Applications and Use Cases},
author = {Xaver Stiensmeier and Alexander Kanitz and Jan Krüger and Santiago Insua and Adrián Rošinec and Viktória Spišáková and Lukáš Hejtmánek and David Yuan and Gavin Farrell and Jonathan Tedds and Juha Törnroos and Harald Wagener and Alex Sczyrba and Nils Hoffmann and Matej Antol},
journal= {arXiv preprint arXiv:2601.04349},
year = {2026}
}