深入分析kubelet（8）——|深入分析kubelet（8）—— 删除extender resource 深入分析kubelet（8）——删除

上一篇分析了kubelet如何选取挂载哪些gpu，那么对应的就会有删除gpu使用记录的操作。
每次分配的时候都是比较已分配和所有健康的设备

devicesInUse := m.allocatedDevices[resource] available := m.healthyDevices[resource].Difference(devicesInUse)

删除已分配设备，需要先删除Pod，而Pod和Dev的关系是通过podDevices维护的，所以删除已分配设备不需要管allocatedDevices，而是关注podDevices

// ManagerImpl is the structure in charge of managing Device Plugins. type ManagerImpl struct { // healthyDevices contains all of the registered healthy resourceNames and their exported device IDs. healthyDevices map[string]sets.String// allocatedDevices contains allocated deviceIds, keyed by resourceName. allocatedDevices map[string]sets.String// podDevices contains pod to allocated device mapping. podDevicespodDevices }

func (pdev podDevices) delete(pods []string) { for _, uid := range pods { delete(pdev, uid) } }// updateAllocatedDevices gets a list of active pods and then frees any Devices that are bound to // terminated pods. Returns error on failure. func (m *ManagerImpl) updateAllocatedDevices(activePods []*v1.Pod) { activePodUids := sets.NewString() for _, pod := range activePods { activePodUids.Insert(string(pod.UID)) } allocatedPodUids := m.podDevices.pods() podsToBeRemoved := allocatedPodUids.Difference(activePodUids)klog.V(3).Infof("pods to be removed: %v", podsToBeRemoved.List()) m.podDevices.delete(podsToBeRemoved.List()) // Regenerated allocatedDevices after we update pod allocation information. m.allocatedDevices = m.podDevices.devices() }

【深入分析kubelet（8）——|深入分析kubelet（8）—— 删除extender resource】以podDevices为切入点，找到对应delete方法，再找到updateAllocatedDevices，这里一切就明了了。