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Horizontal partitioning of data across multiple nodes to enable scaling and load distribution.
Sharding is an architectural pattern for horizontal partitioning of data across multiple database nodes. It improves scalability and availability by distributing load, but requires routing logic, consistency considerations and additional operational effort. Design decisions include shard keys, rebalancing strategies, cross-shard transactions and monitoring.
Number of successfully processed transactions per second across the sharded system.
Latency at high percentiles to detect hotspots and outliers.
Ratio of data size and request load between shards to assess balance.
Product data partitioned by category to distribute search and update load.
Tenants distributed across shards to ensure isolation and scalable resource allocation.
Regional shards reduce latency and satisfy data residency requirements.
analyze query patterns and choose candidate shard keys
prototype implementation with routing logic and tests
incremental migration, automate monitoring and rebalancing