Space logistics has always been a complex and resource-intensive challenge, with the high costs of launches and the very limited volume available in space vehicles and modules posing significant constraints. Given the increasing frequency of space missions, the opening to commercial space activities and the growing interest in exploration missions, even beyond Low Earth Orbit (LEO), optimizing the packing of cargo in space containers, thereby preserving habitable volume and crew time for scientific operations, has become a critical task. Manual planning of cargo stowage is often inefficient and time-consuming, leading to suboptimal use of available space and increased operational costs. This thesis presents the development of Space Container Assignment & Tracking for on-Orbit Logistics Automation (S.C.A.T.O.L.A.), a microservice designed to automate the 3D packing process via algorithmic optimization.