Cloud and Community
ControlBird Cloud (hosted for you) and Community Edition (self-hosted Docker) are the same product, free for personal use.
ControlBird is one product with two ways to run it. ControlBird Cloud is the same ControlBird, hosted for you. Community Edition (CE) is the same ControlBird, self-hosted on your own infrastructure. Both are free for personal use, and both include the same Store, visual builders, integrations, protocols, historian, alarms, ControlBird AI, and white labeling.
- Cloud: hosted for you, with no server to maintain, remote access without port forwarding, and up to 3 nodes per account.
- Community Edition (CE): a Docker Compose stack that runs a node on your own infrastructure.
Same product, different place to run it
The concepts, builders, and workflows you learn carry across either one. The only difference is where ControlBird runs and who looks after the server.
At a Glance
| Capability | Cloud | Community Edition |
|---|---|---|
| Where it runs | Hosted for you | Your own Docker Compose stack |
| Price | Free for personal use; commercial license via sales@controlbird.io | Free for personal use; commercial license via sales@controlbird.io |
| Container images | Managed (no images to run) | A Compose file from controlbird.io, which pulls public images |
| Signing in | Your ControlBird account | Local credentials |
| Core builders & integrations | Yes | Yes |
| Protocols, including BACnet, DNP3, and EtherNet/IP | Yes | Yes |
| Historian | Yes | Yes |
| ControlBird AI | Yes (bring your own provider key) | Yes (bring your own provider key) |
| White labeling | Yes | Yes |
Running Each One
Cloud
Cloud users sign in to their account and work through the cloud control plane to manage nodes and users. From there you can deploy nodes and enable secure tunnel access for nodes that live on a local network. See the configure walkthrough and the certificates guide for setup details.
Community Edition
Community Edition runs as a Docker Compose stack, one container for each part of ControlBird. Download the Compose file from controlbird.io and start it. The stack publishes the web ports, HTTP on 3000 and HTTPS on 3443, and keeps your data in Docker volumes:
curl -fsSLO https://controlbird.io/compose.yaml
docker compose up -d The kernel port (9100) is deliberately not published. The containers reach the kernel over the stack's private network, so a single node needs nothing else. Publish 9100 only if you are running several nodes that peer with each other. Even then, only do it on a network you trust, because that port has no authentication of its own.
Once the stack is running, open the web UI and claim the node in the setup wizard. The node serves HTTPS with a self-signed certificate it creates on first start; you can download that certificate to trust it on your devices, or replace it with your own in the Certificate Manager. The dedicated CE walkthrough covers this in three steps: install Docker, run the stack, and access the UI.
A Community Edition node keeps its entity and field data in memory for sub-millisecond reads. Every change is recorded in a write-ahead log and captured in snapshots in the data volume, so your data survives a restart. Memory use grows with the size of your data, which matters most on memory-constrained hosts like a Raspberry Pi.
Two ways to get started
The getting-started walkthrough follows the way you run ControlBird. The Cloud path has three setup steps (sign up, deploy a node, access it); the CE path has three (install Docker, run the stack, access the UI). After setup, both share the same steps: architecture, exploring the platform, adding devices, building schematics, and creating automations.
Choosing Where to Run It
Pick Cloud when you would rather not run a server: hosting, SSL, and remote access are handled for you. Pick Community Edition when you want ControlBird on your own hardware, with your data on your own network. Because the product is the same, you can move between the two without relearning anything.
For a deeper look at the entity tree ControlBird configures, see Data Model, and for how the Store and services fit together, see Architecture Overview.