When designing a distributed system like SingleStore, predictability is key to optimizing performance and resource utilization. A shared-nothing architecture allows for easy scalability, low network congestion, and efficient I/O management. By understanding how reads and writes are handled across the cluster, developers can optimize the mix of aggregators and leaves to meet specific workload requirements. Capacity planning involves measuring and testing workloads to determine the optimal number of servers needed, making it straightforward to scale up performance testing. However, certain operations like DDL commands and large data transfers require special consideration to avoid bottlenecks.