Introducing Scale: SurrealDB Cloud, built for high availability and scale

Author: Tobie Morgan Hitchcock Today we're launching Scale, a new tier of SurrealDB Cloud built for the workloads you can't afford to have go down. Our first tier, Start, was designed for building and shipping fast. Scale is designed for what happens next: production traffic, uptime commitments, and the kind of resilience your users never notice because there are always available nodes. It's the tier for teams running SurrealDB as the scalable context layer behind real applications and AI agents in production. What you get with Scale Scale is about one thing: keeping your database available and consistent under real-world conditions. Highly-available, fault-tolerant clusters. Scale runs your database as a multi-node cluster designed to survive node and infrastructure failures without dropping writes or losing consistency. A single point of failure is no longer a single point of downtime. Multiple availability-zone deployment. Your cluster is distributed across multiple availability zones, so even the loss of an entire zone doesn't take your database with it. Traffic keeps flowing while the cluster recovers in the background. Horizontal scale. As demand grows, Scale grows with it. Add capacity by scaling out across nodes rather than being capped by the size of a single machine. Start with three nodes, and keep adding to scale your application or agent's needs. See more information about SurrealDB Cloud Scale architecture here . Built on SurrealDS Scale is powered by SurrealDS , SurrealDB's distributed storage engine and the foundation that makes all of this possible. SurrealDS is a new generation distributed storage architecture, rethought from first principles. Instead of coupling storage to compute on a single box or to a proprietary cloud tier, SurrealDS embeds consensus directly in SurrealDB nodes and separates the two layers cleanly. Here's what that architecture gives you. Architecture overview Compute and storage separation. Scale compute for QPS and storage f