Compute Pools

beam machine list
beam pool list
beam pool offers --gpu H100 --nodes 1 --ttl 1h --max-spend 10

beam pool create training
beam pool scale training --gpu H100 --nodes 1 --ttl 1h --max-spend 10
beam pool machines training

beam machine reserve --gpu H100 --ttl 6h --name training --yes

from beam import function


@function(gpu="H100", pool="training")
def handler():
    return {"ok": True}

beam deploy --name trainer --dockerfile Dockerfile --pool training --gpu H100 --no-ports

{
  "private_pools": [
    {
      "name": "training",
      "status": "active",
      "reservations": [
        {
          "status": "active",
          "gpu_count": 1,
          "hourly_cost_micros": "2090000",
          "created_at": "2026-10-10T16:38:06Z",
          "expires_at": "2026-10-10T18:38:06Z",
          "billing_renewal_at": "2026-10-10T17:38:06Z",
          "terminating_reason": ""
        }
      ]
    }
  ]
}

# Keep the pool's nodes for another 12 hours from now
beam pool extend training --ttl 12h

# Raise the spend cap on a long-lived pool
beam pool extend training --max-spend 50

beam pool join my-hardware

beam pool join-command my-hardware --ttl 30m