Redpanda, a data streaming platform optimized for modern hardware, requires careful cluster sizing for effective production-level performance. While its default settings suffice for basic use, production environments benefit from fine-tuning to avoid bottlenecks or underutilization. Key considerations for sizing include I/O performance, with a recommended 2:1 core-to-disk ratio using NVMe SSDs for optimal throughput; memory allocation of at least 2GB per core to enhance processing efficiency via its thread-per-core model; network bandwidth management, crucial in cloud deployments for predictable performance; and strategic storage solutions, like Redpanda's Tiered Storage, to balance high throughput with extensive data retention capabilities. These factors ensure Redpanda efficiently scales within infrastructure limits, minimizing operational costs.