Cages
A cage is an isolated Fargate container where your AI agent runs. Each cage has its own filesystem, network namespace, and persistent storage — no inbound ports, configurable egress.
What you get
- Full Linux environment — Ubuntu-based container with root access
- Persistent storage — EFS volume mounted at
/workspace, survives restarts and hibernation - No inbound ports — Nothing can connect to your cage directly (webhooks go through the gateway proxy)
- Configurable egress — Outbound internet access for API calls, package installs, etc.
- Environment variables — KMS envelope-encrypted, injected at boot
Cage sizes
| Size | vCPU | Memory | Credits/hr |
|---|---|---|---|
| Starter | 1 | 4 GB | 60 |
| Standard | 2 | 8 GB | 120 |
| Power | 4 | 16 GB | 240 |
| Extreme | 8 | 32 GB | 480 |
Naming
Cage names must be unique per account. They’re used as identifiers in the CLI and API:
lobster deploy my-agent # create cage named "my-agent"
lobster ssh my-agent # connect to it
lobster status my-agent # check its stateLifecycle states
| State | Description |
|---|---|
starting | Container is provisioning |
running | Active and accepting connections |
stopping | Shutting down |
stopped | Compute stopped, data preserved |
hibernating | Transitioning to hibernation |
hibernated | No compute, storage persisted, wakes on demand |
Unique per account
Each cage name is unique within your account. You can have multiple cages running simultaneously, up to your plan’s limit.
| Plan | Max cages |
|---|---|
| Free | 1 |
| Starter | 15 |
| Enterprise | Custom |