Developed a configurable memory management feature for the zauberzeug/rosys repository, focusing on system optimization and configuration management. The work introduced a memory-based garbage collection threshold, allowing deployments to specify a megabyte limit that triggers garbage collection dynamically. This approach enables more precise control over memory usage and performance tuning across different environments. Implemented in Python, the solution leverages configuration management principles to make garbage collection behavior adaptable to varying resource constraints. No bug fixes were addressed during this period, with efforts concentrated on enhancing configurability and system efficiency through targeted feature development and thoughtful integration into the existing codebase.