Operational experience with the Hyperloop train system is presented. This framework facilitates organized grid data analysis in ALICE at the Large Hadron Collider (LHC). Operational since LHC Run 3, the system enables efficient management of distributed computing resources via a web-based interface, optimizing workflow execution and resource utilization. Hyperloop structures analyses as modular trains composed of interconnected wagons – configurable workflows handling both user-defined tasks and expert-level services. Key features encompass automated resource estimation, testing, submission, alongside tools for version control and dataset comparison.
Based on multiple years of work as a Hyperloop operator, the role of such framework in running the organized grid-based analysis for large collaborations is highlighted, and its adaptability to other mega-science projects is discussed. Solutions for stability, validation, and user accessibility are highlighted. Furthermore, the application of this operational experience to the development of analysis train systems for the MPD experiment at the NICA collider is discussed.
The author acknowledge Saint-Petersburg State University for a research project 103821868