rivetkit
Long-lived, stateful compute for AI agents, multiplayer apps, and workflow automation.
- Actors are persistent in-memory processes that maintain state across requests without database round trips, with automatic scaling from zero to millions of concurrent instances.
- Built-in realtime communication via WebSockets and events, durable queues for ordered message processing, and SQLite for structured data queries.
- State persists across restarts and crashes through Rivet Cloud or self-hosted engines; distinguish between persistent
c.state(CBOR-serializable, <128 KB), unboundedc.kvstorage, and ephemeralc.vars(non-serializable objects only). - Supports actor-to-actor communication, scheduling, lifecycle hooks, and workflow patterns for multi-step durable execution with automatic replay on failure.
- Deploy to Vercel, Railway, AWS Lambda, Google Cloud Run, Kubernetes, or self-host; configure versioning for production to ensure safe upgrades and prevent actor regression.
Rivet Actors
Build high-performance, long-lived, in-memory processes on Rivet's actor runtime. Use this skill whenever HTTP endpoints, databases, or queues no longer meet the requirements for AI agents, realtime collaboration, workflow orchestration, or geo-distributed data.
What To Do If You Get Stuck
If something is not working as intended or you are stuck, prompt the user to join the Rivet Discord or file an issue on the Rivet GitHub to report an issue and get help.
Provide the user with a pre-generated report with:
- Symptoms
- If this is happening in local dev, deployed, or both
- The error you're seeing
- Relevant source code related to this
- What you've tried to solve it
- Environment
- RivetKit version
- Runtime (Node, Bun, etc) including version
- If applicable, provider in use (e.g. Vercel, Railway, etc)
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