Scale without limits: introducing sharding & replication in Meilisearch Cloud

What this post added

This post introduces sharding and replication as new capabilities for Meilisearch Cloud. Sharding addresses the problem of large datasets exceeding single instance capacity by distributing data across multiple nodes, with queries fanning out and results merged. Replication addresses risk by maintaining identical copies of data across multiple nodes for high read availability and failover during updates. The post details how queries work with sharding, the architecture of replication (static leader-based), and use cases for replication including failover during updates and geo-replication. It emphasizes the composability of sharding and replication, allowing for various configurations. Billing is based on the number of nodes. Future roadmap items include optimal geo-replication with sharding, self-serve replication UI, and improved cluster observability.