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Kubernetes: set NVIDIA_VISIBLE_DEVICES=void for CPU-only pods #4011

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Merged
un-def merged 1 commit into from
Jul 8, 2026
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Kubernetes: set NVIDIA_VISIBLE_DEVICES=void for CPU-only pods #4011

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32 changes: 18 additions & 14 deletions src/dstack/_internal/core/backends/kubernetes/compute.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1131,28 +1131,31 @@ def _create_job_pod(
tolerations: list[client.V1Toleration] = []
volumes_: list[client.V1Volume] = []
volume_mounts: list[client.V1VolumeMount] = []
env_vars: list[client.V1EnvVar] = []

resources_spec = job_spec.requirements.resources
assert isinstance(resources_spec.cpu, CPUSpec)
if (cpu_min := resources_spec.cpu.count.min) is not None:
resources_requests["cpu"] = str(cpu_min)
if (cpu_max := resources_spec.cpu.count.max) is not None:
resources_limits["cpu"] = str(cpu_max)
if (gpu_spec := resources_spec.gpu) is not None:
if (gpu_request := get_gpu_request_from_gpu_spec(gpu_spec)) > 0:
gpu_resource, node_affinity, node_taint = _get_pod_spec_parameters_for_gpu(
api, gpu_spec
gpu_spec = resources_spec.gpu
if gpu_spec is not None and (gpu_request := get_gpu_request_from_gpu_spec(gpu_spec)) > 0:
gpu_resource, node_affinity, node_taint = _get_pod_spec_parameters_for_gpu(api, gpu_spec)
logger.debug("Requesting GPU resource: %s=%d", gpu_resource, gpu_request)
resources_requests[gpu_resource] = str(gpu_request)
# Limit must be set (GPU resources cannot be overcommitted) and must be equal to request.
resources_limits[gpu_resource] = str(gpu_request)
# It should be NoSchedule, but we also add NoExecute toleration just in case.
for effect in [TaintEffect.NO_SCHEDULE, TaintEffect.NO_EXECUTE]:
tolerations.append(
client.V1Toleration(key=node_taint, operator=Operator.EXISTS, effect=effect)
)
logger.debug("Requesting GPU resource: %s=%d", gpu_resource, gpu_request)
resources_requests[gpu_resource] = str(gpu_request)
# Limit must be set (GPU resources cannot be overcommitted)
# and must be equal to request.
resources_limits[gpu_resource] = str(gpu_request)
# It should be NoSchedule, but we also add NoExecute toleration just in case.
for effect in [TaintEffect.NO_SCHEDULE, TaintEffect.NO_EXECUTE]:
tolerations.append(
client.V1Toleration(key=node_taint, operator=Operator.EXISTS, effect=effect)
)
else:
# Prevents GPU allocation if NVIDIA_VISIBLE_DEVICES with a value such as "all" is baked
# into the image (NVIDIA images and images based on them including dstackai/base)
# See https://github.com/NVIDIA/k8s-device-plugin/issues/61
env_vars.append(client.V1EnvVar(name="NVIDIA_VISIBLE_DEVICES", value="void"))
if (memory_min := resources_spec.memory.min) is not None:
resources_requests["memory"] = format_memory(memory_min)
if (memory_max := resources_spec.memory.max) is not None:
Expand Down Expand Up @@ -1272,6 +1275,7 @@ def _create_job_pod(
limits=resources_limits,
),
volume_mounts=volume_mounts,
env=env_vars,
)
],
image_pull_secrets=(
Expand Down
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