A computational tool employing a two-fold Lehman frequency scaling approach allows for the analysis and prediction of system behavior under varying workloads. For example, this method can be applied to determine the necessary infrastructure capacity to maintain performance at twice the anticipated user base or data volume.
This methodology offers a robust framework for capacity planning and performance optimization. By understanding how a system responds to doubled demands, organizations can proactively address potential bottlenecks and ensure service reliability. This approach provides a significant advantage over traditional single-factor scaling, especially in complex systems where resource utilization is non-linear. Its historical roots lie in the work of Manny Lehman on software evolution dynamics, where understanding the increasing complexity of systems over time became crucial.
