6.4.2. Monitoring AllocationClaims

流程

1. 运行以下命令检查活跃的 AllocationClaim 资源：

   $ oc get allocationclaims -n das-operator

   输出示例

   NAME                                                                                           AGE
   13950288-57df-4ab5-82bc-6138f646633e-harpatil000034jma-qh5fm-worker-f-57md9-cuda-vectoradd-0   5m
   ce997b60-a0b8-4ea4-9107-cf59b425d049-harpatil000034jma-qh5fm-worker-f-fl4wg-cuda-vectoradd-0   5m

2. 运行以下命令，查看有关特定 AllocationClaim 的详细信息：

   $ oc get allocationclaims -n das-operator -o yaml

   输出示例（截断）

   apiVersion: inference.redhat.com/v1alpha1
   kind: AllocationClaim
   metadata:
     name: 13950288-57df-4ab5-82bc-6138f646633e-harpatil000034jma-qh5fm-worker-f-57md9-cuda-vectoradd-0
     namespace: das-operator
   spec:
     gpuUUID: GPU-9003fd9c-1ad1-c935-d8cd-d1ae69ef17c0
     migPlacement:
       size: 1
       start: 0
     nodename: harpatil000034jma-qh5fm-worker-f-57md9
     podRef:
       kind: Pod
       name: cuda-vectoradd-f4b84b678-l2m69
       namespace: default
       uid: 13950288-57df-4ab5-82bc-6138f646633e
     profile: 1g.5gb
   status:
     conditions:
     - lastTransitionTime: "2025-08-06T19:28:48Z"
       message: Allocation is inUse
       reason: inUse
       status: "True"
       type: State
     state: inUse

3. 运行以下命令，检查不同状态中的声明：

   $ oc get allocationclaims -n das-operator -o jsonpath='{range .items[*]}{.metadata.name}{"\t"}{.status.state}{"\n"}{end}'

   输出示例

   13950288-57df-4ab5-82bc-6138f646633e-harpatil000034jma-qh5fm-worker-f-57md9-cuda-vectoradd-0	inUse
   ce997b60-a0b8-4ea4-9107-cf59b425d049-harpatil000034jma-qh5fm-worker-f-fl4wg-cuda-vectoradd-0	inUse

4. 运行以下命令，查看与 AllocationClaim 资源相关的事件：

   $ oc get events -n das-operator --field-selector involvedObject.kind=AllocationClaim

5. 运行以下命令，检查 NodeAccelerator 资源以验证 GPU 硬件检测：

   $ oc get nodeaccelerator -n das-operator

   输出示例

   NAME                                     AGE
   harpatil000034jma-qh5fm-worker-f-57md9   96m
   harpatil000034jma-qh5fm-worker-f-fl4wg   96m

   NodeAccelerator 资源代表 DAS Operator 检测到的 GPU 功能的节点。