Sharding is a key consideration for achieving performance at scale in MongoDB, allowing databases to automatically scale out across multiple nodes and regions to handle growing data sizes and write-intensive workloads. This enables seamless scaling of the database as applications grow beyond hardware limits without adding complexity to the application. Sharding offers different strategies, including ranged sharding for range-based queries, hashed sharding for uniform distribution of writes, and zoned sharding for custom data placement rules, with MongoDB Atlas providing a visual UI or API for implementing these policies. To get the full benefit of sharding, it's essential to ensure a uniform distribution of shard keys, avoid scatter-gather queries for operational workloads, use hashed-based sharding when appropriate, and pre-split and distribute chunks before loading data into new collections.