GatherAllocatedState and ListAllAllocatedDevices need to collect information
from different sources (allocated devices, in-flight claims), potentially even
multiple times (GatherAllocatedState first gets allocated devices, then the
capacities).
The underlying assumption that nothing bad happens in parallel is not always
true. The following log snippet shows how an update of the assume
cache (feeding the allocated devices tracker) and in-flight claims lands such
that GatherAllocatedState doesn't see the device in that claim as allocated:
dra_manager.go:263: I0115 15:11:04.407714 18778] scheduler: Starting GatherAllocatedState
...
allocateddevices.go:189: I0115 15:11:04.407945 18066] scheduler: Observed device allocation device="testdra-all-usesallresources-hvs5d.driver/worker-5/worker-5-device-094" claim="testdra-all-usesallresources-hvs5d/claim-0553"
dynamicresources.go:1150: I0115 15:11:04.407981 89109] scheduler: Claim stored in assume cache pod="testdra-all-usesallresources-hvs5d/my-pod-0553" claim="testdra-all-usesallresources-hvs5d/claim-0553" uid=<types.UID>: a84d3c4d-f752-4cfd-8993-f4ce58643685 resourceVersion="5680"
dra_manager.go:201: I0115 15:11:04.408008 89109] scheduler: Removed in-flight claim claim="testdra-all-usesallresources-hvs5d/claim-0553" uid=<types.UID>: a84d3c4d-f752-4cfd-8993-f4ce58643685 version="1211"
dynamicresources.go:1157: I0115 15:11:04.408044 89109] scheduler: Removed claim from in-flight claims pod="testdra-all-usesallresources-hvs5d/my-pod-0553" claim="testdra-all-usesallresources-hvs5d/claim-0553" uid=<types.UID>: a84d3c4d-f752-4cfd-8993-f4ce58643685 resourceVersion="5680" allocation=<
{
"devices": {
"results": [
{
"request": "req-1",
"driver": "testdra-all-usesallresources-hvs5d.driver",
"pool": "worker-5",
"device": "worker-5-device-094"
}
]
},
"nodeSelector": {
"nodeSelectorTerms": [
{
"matchFields": [
{
"key": "metadata.name",
"operator": "In",
"values": [
"worker-5"
]
}
]
}
]
},
"allocationTimestamp": "2026-01-15T14:11:04Z"
}
>
dra_manager.go:280: I0115 15:11:04.408085 18778] scheduler: Device is in flight for allocation device="testdra-all-usesallresources-hvs5d.driver/worker-5/worker-5-device-095" claim="testdra-all-usesallresources-hvs5d/claim-0086"
dra_manager.go:280: I0115 15:11:04.408137 18778] scheduler: Device is in flight for allocation device="testdra-all-usesallresources-hvs5d.driver/worker-5/worker-5-device-096" claim="testdra-all-usesallresources-hvs5d/claim-0165"
default_binder.go:69: I0115 15:11:04.408175 89109] scheduler: Attempting to bind pod to node pod="testdra-all-usesallresources-hvs5d/my-pod-0553" node="worker-5"
dra_manager.go:265: I0115 15:11:04.408264 18778] scheduler: Finished GatherAllocatedState allocatedDevices=<map[string]interface {} | len:2>: {
Initial state: "worker-5-device-094" is in-flight, not in cache
- goroutine #1: starts GatherAllocatedState, copies cache
- goroutine #2: adds to assume cache, removes from in-flight
- goroutine #1: checks in-flight
=> device never seen as allocated
This is the second reason for double allocation of the same device in two
different claims. The other was timing in the assume cache. Both were
tracked down with an integration test (separate commit). It did not fail
all the time, but enough that regressions should show up as flakes.
Thanks to the tracker, the plugin sees all taints directly in the device
definition and can compare it against the tolerations of a request while
trying to find a device for the request.
When the feature is turnedd off, taints are ignored during scheduling.
The controller is derived from the node taint eviction controller.
In contrast to that controller it tracks the UID of pods to prevent
deleting the wrong pod when it got replaced.
If there was an unexpected status, the code extracting the expected error
message crashed with a panic. Happened once so far, for unknown reasons
because the unexpected status then didn't get logged.
The tests and comments have also been updated because while
VolumeCapacityPriority preferred a node with the least allocatable,
StorageCapacityScoring preferred a node with the maximum allocatable.
This was previously caught during Filter by the allocator check. Doing it
sooner avoids wasting resources on a pod which ultimately cannot get scheduled.
While at it, be a bit more clear about which feature is disabled. The user
might not know that.
- Refactored `PreScore` method in `balanced_allocation.go` to skip
best-effort pods.
- Updated unit tests in `balanced_allocation_test.go` to check for
the new status codes.
