In big databases, IOPS (Input/Output Operations Per Second) and throughput can become performance bottlenecks. Sharding is a technique that helps scale out IOPS and throughput beyond the limitations of a single server by distributing data across multiple servers. This reduces costs for large-scale workloads as it allows each instance to use more affordable EBS volumes. For example, in a sharded database, IO and throughput requirements are distributed across many primaries, enabling efficient handling of I/O intensive workloads like databases without needing to pay an EBS premium.