MongoDB Sharding Decision Guide: Understand Data Distribution Before Scaling Horizontally
MongoDB sharding can distribute data and workload across multiple nodes, but it also introduces complexity in routing, metadata, balancing, redundancy, and cross-shard queries. Starting with evidence from capacity and query behavior, this article explains how to evaluate shard keys, choose between range-based and hashed strategies, design high availability for core components, and plan testing and rollback. It helps enterprises adopt a governable architecture when horizontal scaling is genuinely required instead of assigning indexing or data-model problems to more machines, while also establishing clear responsibilities for monitoring and recovery.