47 Rapp, Vitaliy Kerssemakers, Jules Klimczyk, Krzysztof Salabura, Piotr ACO 20th Int. Conf. Accel. Large Exp. Phys. Control Syst. JACoW Publishing Geneva, Switzerland Chicago, IL, USA 978-3-95450-255-4 10.18429/JACOW-ICALEPCS2025-TUPD109 English 747-751 With the recent rise of AI and various machine learning models, the importance of storing and managing data generated by control systems is greater than ever before. In 2016, GSI began developing an archiving system to collect, store, and retrieve data from the diverse accelerator devices managed by the GSI control infrastructure. The system was successfully deployed in production in 2021. To evaluate its capabilities and suitability for operational needs, the system was initially launched with a limited storage capacity of 50 TB and reduced computing power. With a current data volume of over 100 GB per day, the archiving system quickly exceeded its initial limits. However, the experience gained in day-to-day operations thus far has allowed us to better understand our use-cases and identify areas for further improvement. In preparation for the anticipated start of FAIR operations in 2027, the system will require significant scaling to meet future demands. Therefore, this is an opportune moment to review and refine the system’s architecture based on the experience gained so far. This paper outlines the challenges encountered with the current implementation and presents the solutions that will be incorporated into the system for FAIR operations. Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 license. ; 33, ; PUB:(DE-HGF)8, ; PUB:(DE-HGF)7, ; Accelerator Physics MC16 - MC16: Data Management and Analytics Contribution to a conference proceedings 2025 2026-09-20 - 2026-09-26 GSI-2026-00371 2026-09-20 - 2026-09-26 2025 https://repository.gsi.de/record/365277 https://doi.org/10.18429/JACOW-ICALEPCS2025-TUPD109