👉 Square computing, also referred to as square-cubic computing or cubic scaling, is a method of scaling computational resources that aims to balance efficiency and cost-effectiveness. It involves distributing workloads across a network of servers that are arranged in a square grid, with each layer adding one more dimension (typically a third) to the existing two-dimensional grid. This approach ensures that as the workload increases, the number of servers scales proportionally, maintaining a consistent ratio between the total number of servers and the available computational capacity. This results in predictable scaling costs, as the number of servers needed grows cubically with the workload, making it particularly suitable for applications requiring consistent performance and predictable resource allocation. By optimizing resource usage and minimizing waste, square computing enables organizations to efficiently handle varying workloads without incurring unnecessary expenses.
