Rucio is a software framework that provides scientific collaborations with the ability to organise, manage and access large volumes of data using customisable policies. The data can be spread across globally distributed locations and across heterogeneous data centres, uniting different storage and network technologies as a single federated entity. Rucio offers advanced features such as distributed data recovery or adaptive replication, and is highly scalable, modular, and extensible. Rucio has been originally developed to meet the requirements of the high-energy physics experiment ATLAS, and is being continuously extended to support LHC experiments and other diverse scientific communities. In recent years several R&D projects in these communities have started to evaluate the integration of both private and commercially-provided cloud storage systems. As they are using Rucio, new functionality has been developed to make the integration as seamless as possible. In addition the underlying systems, FTS and GFAL/Davix, have been extended for these use cases. In this contribution we detail the technical aspects of this work. In particular the challenges when building a generic interface to self-hosted cloud storage such as MinIO or CEPH S3 Gateway, to established providers such as Google Cloud Storage and Amazon Simple Storage Service, as well as upcoming decentralised clouds such as SEAL. We will highlight aspects such as authentication and authorisation, direct and remote access, throughput and cost estimation, and give experiences on daily operations.
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