The Production Leap: Scaling Agent Workflows Globally on thingd.cloud (Part 4)

Short summary

The fourth post in a series about thingd.cloud describes the architectural challenges of scaling a local-first agent data engine to support thousands of concurrent autonomous agents. It covers tenant isolation and high-concurrency orchestration, noting that AI agents have zero patience for latency unlike human SaaS users. The control plane uses NestJS and React while the core engine remains in Rust.

• •Scaling agent infrastructure from local to cloud requires solving tenant isolation and high-concurrency orchestration
• •AI agents are intolerant of latency spikes, making cold starts and connection pool issues critical
• •Control plane built with NestJS/React; core execution engine stays in Rust with SQLite primitives

Generated with AI, which can make mistakes.