Is Rivet Right for Your Project, and How Do You Get Started?

Updated

Rivet (rivet.dev) is an orchestrator for agentic workloads that runs agents, workflows, and sandboxes as durable Actors. It fits projects that need long-lived agent processes, multi-step operations that survive restarts, sandboxed execution of untrusted code, or a per-user backend deployed on demand. It is open-source and self-hostable, so teams that must keep data inside their own VPC have a path. If you only need a simple request/response API with no durable state, Rivet is likely more machinery than you need.

What Rivet actually is

Rivet describes itself as "a fast, high-density and scalable orchestrator for every workload an agent needs," running workloads as durable Actors. The site groups the workloads into a few shapes:

Workload What it gives you
Actors A durable process for each agent to live in
Workflows Multi-step operations that replay instead of starting over
Sandboxes A filesystem, shell, and network for code you did not write
Dynamic Apps A backend per user, deployed the moment it is generated

The recurring idea is the Actor: a durable unit that keeps its state and resumes after restarts. The site's example shows a coding agent fixing a flaky test, hitting a failure, and then "resumed after 2 restarts" before opening a PR — the point being that the process survives interruptions rather than starting over.

Who it is for

Rivet is a reasonable fit when your project matches one or more of these:

  • Coding agents and agent OS-style tools — you need a durable process per agent that can be interrupted and resumed.
  • Agent app builders — you generate a schema, API, and deployment per user (the site's CRM example generates 4 tables, 11 routes, and a live release).
  • Company-specific agents inside your own cloud — the enterprise example runs in "Your VPC · no data leaves your cloud," connecting systems like Postgres, an Orders API, and a helpdesk.
  • Personal agents with memory and schedules — the example tracks 1,204 memories and runs a weekday 07:00 briefing.
  • Realtime collaborative apps — the example shows multiple editors syncing, with "synced · 12 ms" called out.

If your workload is stateless and short-lived, or you don't need durability, replay, or sandboxing, the Actor model adds concepts you won't use.

The density and cold-start claims

Rivet's headline performance claims are worth understanding because they drive the cost argument:

  • 12 ms cold starts — "Start in milliseconds, not minutes."
  • 72 KB per Actor — the page states 72.4 KB per running Actor RSS increase.
  • 2,829× more workloads per server — the mechanism given is that "an Actor lives inside a worker process you already run, not in its own container or VM. A server that held hundreds of pods holds hundreds of thousands of Actors."

The takeaway: Rivet's density comes from not giving each workload its own container or VM. That is the same design choice that makes cold starts fast. If your current setup spins up a container per agent or per user, this is the dimension to compare against.

Deployment and data residency

Two facts from the site matter for selection:

  • Open-source and self-hostable. You can run it yourself.
  • Data can stay in your VPC. The enterprise example explicitly runs inside your own cloud with no data leaving it.

There is a Pricing page at rivet.dev/pricing, so a hosted or paid option exists to check. The site does not state prices, tiers, or whether any hosted tier is free — verify those on the Pricing page before assuming cost.

How to get started

The site's stated entry point is to hand setup to your coding agent:

npx skills add rivet-dev/skills

The page frames this as "Give this to your coding agent." The expected result is that your coding agent picks up Rivet's skills and can start building Actors, Workflows, Sandboxes, or Dynamic Apps for you. From there, the site offers "Start Building" and "Explore" links for each workload type (Actors, agentOS, Dynamic Apps, Enterprise, Realtime apps) so you can follow the pattern closest to your use case.

What to check before committing

  • Deployment model — self-hosted vs. hosted, and where your data lives.
  • Data residency — confirm the VPC/no-data-egress behavior matches your compliance needs.
  • Scale and ops cost — the density claim (thousands of Actors per server) is the lever; validate it against your own workload rather than the headline number.
  • Pricing — read rivet.dev/pricing for current terms; the site does not publish them in the material here.
  • Fit — if you need durable, resumable, sandboxed, or per-user workloads, Rivet targets exactly that; if not, a simpler runtime may serve you better.