Resource Configuration

Configure CPU and memory limits for machines.

TIP

There's no limit on how many machines you can create — machine count is never capped. Usage is measured by total vCPU and memory, not the number of machines.

Basic Configuration

const machine = await Machine.create({
  name: 'high-performance',
  resources: {
    cpus: 4,
    memoryMb: 2048
  }
});

from smolvm import MachineConfig, ResourceSpec

config = MachineConfig(
    name="high-performance",
    resources=ResourceSpec(
        cpus=4,
        memory_mb=2048
    )
)

Resource Options

Option	Type	Default	Description
`cpus`	number	4	Number of vCPUs
`memoryMb` / `memory_mb`	number	8192	Memory in megabytes (elastic via virtio balloon)
`gpu`	boolean	false	Enable GPU acceleration (details)
`network`	boolean	default applied by the server if omitted	Enable networking
`overlayGb`	number	default applied by the server if omitted	Overlay (writable layer) size in gigabytes
`storageGb`	number	default applied by the server if omitted	Persistent storage size in gigabytes

Default Resources

If not specified, machines use:

1 vCPU
512 MB memory

Resource Examples

Minimal (CI tasks)

resources: {
  cpus: 1,
  memoryMb: 256
}

Standard (most workloads)

resources: {
  cpus: 2,
  memoryMb: 1024
}

High Performance (ML, compilation)

resources: {
  cpus: 4,
  memoryMb: 4096
}

Best Practices

Match Workload Needs

Don’t over-allocate resources. More vCPUs doesn’t always mean faster:

// For I/O bound tasks, 1-2 CPUs is usually sufficient
const ioMachine = await Machine.create({
  name: 'io-task',
  resources: { cpus: 1, memoryMb: 512 }
});

// For CPU-intensive tasks, allocate more
const cpuMachine = await Machine.create({
  name: 'cpu-task',
  resources: { cpus: 4, memoryMb: 2048 }
});

Memory for Large Data

Python data processing often needs more memory:

# Processing large datasets
config = MachineConfig(
    name="data-processing",
    resources=ResourceSpec(
        cpus=2,
        memory_mb=4096  # 4GB for pandas/numpy
    )
)

Compilation Tasks

Compilation benefits from multiple cores:

const machine = await Machine.create({
  name: 'builder',
  resources: {
    cpus: 4,      // Parallel compilation
    memoryMb: 2048 // Linking needs memory
  }
});

await machine.run('rust:alpine', ['cargo', 'build', '--release', '-j4']);