ALISE - The Account LInking SErvice
Modern research computing environments increasingly rely on federated identity management to provide seamless access to distributed resources. However, many computer centres face a significant challenge: they need to support federated users while maintaining compatibility with traditional Unix-based systems that require local account mappings. ALISE (Account LInking SErvice) addresses this gap by providing a robust solution that enables users to link their federated identities with local computer centre accounts. ALISE is a comprehensive web application designed to serve three distinct user communities. End users can easily manage their account linkages through an intuitive web interface. Application developers can integrate federated identity mapping into their services via a well-defined REST API. System administrators can deploy and configure ALISE to implement institution-specific policies while maintaining operational simplicity. Within the AARC Blueprint Architecture framework, ALISE operates at the "End-Services" layer, implementing account linking at the service level rather than at higher authentication layers. This design choice enables direct integration with existing infrastructure while maintaining security and governance requirements. The service workflow begins when users authenticate with their existing computer centre accounts. Subsequently, they can link multiple federated identities to their local accounts, creating a comprehensive mapping database. Authorised services can then query this database through the ALISE REST API to resolve federated identities to their corresponding local Unix accounts, enabling seamless integration with traditional authorisation systems. ALISE has been successfully deployed to support storage systems such as dCache and general-purpose services like teapot. The system is available as open source software under the MIT License, encouraging community adoption and contribution.
Authors
- Marcus Hardt (ORCID: https://orcid.org/0000-0001-9149-244X)
- Paul Millar (ORCID: https://orcid.org/0000-0002-3957-1279)
- Diana Gudu (ORCID: https://orcid.org/0000-0002-6931-2710)
Publication Details
- Published
- 2025-10-20
- DOI
- https://doi.org/10.22323/1.488.0012
- Primary Topic
- Modeling, Simulation, and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00