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309b968 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | # Connecting machines with Tailscale (recommended)
DaisyChain needs every node reachable by a **stable IP on one interface**.
Tailscale gives you exactly that: a private mesh where each machine gets a
`100.x.y.z` address on the `tailscale0` interface, reachable P2P across NATs and
different networks — no port-forwarding.
## 1. Install on every machine
- Linux: `curl -fsSL https://tailscale.com/install.sh | sh`
- Windows / macOS: <https://tailscale.com/download>
Bring each up (same tailnet / account) and note its IP:
```bash
sudo tailscale up
tailscale ip -4 # e.g. 100.101.102.10
tailscale status # see every machine + IP
```
## 2. Configure the cluster
Pick one machine as **rank 0** and use its Tailscale IP as `MASTER_ADDR`. On
every machine:
```bash
export MASTER_ADDR=100.101.102.10
export MASTER_PORT=29560
export WORLD_SIZE=3
export GLOO_SOCKET_IFNAME=tailscale0 # pin gloo to the mesh NIC
export RANK=0 # 1, 2, ... on the others
daisychain-train
```
`GLOO_SOCKET_IFNAME=tailscale0` is the important line — it stops gloo from
wandering onto a LAN/VPN/Docker interface.
## 3. Verify
Run `daisychain-dashboard` (point `config/nodes.example.json` at the Tailscale
IPs). Green banner = every node reachable and ports open → launch training.
> On Windows the Tailscale interface name differs and gloo tensor collectives are
> unstable anyway — prefer Linux nodes or Docker for the actual training.
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