本篇内容介绍了“Kubernetes Endpoints Controller的源码解析”的有关知识,在实际案例的操作过程中,不少人都会遇到这样的困境,接下来就让小编带领大家学习一下如何处理这些情况吧!希望大家仔细阅读,能够学有所成!
--concurrent-endpoint-syncs
int32 Default: 5 The number of endpoint syncing operations that will be done concurrently. Larger number = faster endpoint updating, but more CPU (and network) load.
--leader-elect-resource-lock
endpoints Default: "endpoints" The type of resource object that is used for locking during leader election. Supported options are endpoints (default) and configmaps
.
Core/V1/Pods
Core/V1/Services
Core/V1/Endpoints
Add Service Event --> enqueueService
Update Service Event --> enqueueService(new)
Delete Service Event --> enqueueService
Add Pod Event --> addPod
Update Pod Event --> updatePod
Delete Pod Event --> deletePod
Add/Update/Delete Endpoints Event --> nil
启动两类go协程:
一类协程数为--concurrent-endpoint-syncs配置值(default 5),每个worker负责从service queue中pop service进行syncService同步,完成一次sync后等待1s再从service queue中pop一个service进行sync,如此反复。
另一类协程只有一个协程,负责checkLeftoverEndpoints,只有启动时会执行一次。
// Run will not return until stopCh is closed. workers determines how many // endpoints will be handled in parallel. func (e *EndpointController) Run(workers int, stopCh <-chan struct{}) { defer utilruntime.HandleCrash() defer e.queue.ShutDown() glog.Infof("Starting endpoint controller") defer glog.Infof("Shutting down endpoint controller") if !controller.WaitForCacheSync("endpoint", stopCh, e.podsSynced, e.servicesSynced, e.endpointsSynced) { return } // workers = --concurrent-endpoint-syncs's value (default 5) for i := 0; i < workers; i++ { // workerLoopPeriod = 1s go wait.Until(e.worker, e.workerLoopPeriod, stopCh) } go func() { defer utilruntime.HandleCrash() e.checkLeftoverEndpoints() }() <-stopCh }
checkLeftoverEndpoints负责List所有当前集群中的endpoints并将它们对应的services添加到queue中,由workers进行syncService同步。
这是为了防止在controller-manager发生重启时时,用户删除了某些Services或者某些Endpoints还没删除干净,Endpoints Controller没有处理的情况下,在Endpoints Controller再次启动时能通过checkLeftoverEndpoints检测到那些孤立的endpionts(没有对应services),将虚构的Services重新加入到队列进行syncService操作,从而完成这些孤立endpoint的清理工作。
上面提到的虚构Services其实是把Endpoints的Key(namespace/name)作为Services的Key,因此这就是为什么要求Endpiont和Service的名字要一致的原因之一。
func (e *EndpointController) checkLeftoverEndpoints() { list, err := e.endpointsLister.List(labels.Everything()) if err != nil { utilruntime.HandleError(fmt.Errorf("Unable to list endpoints (%v); orphaned endpoints will not be cleaned up. (They're pretty harmless, but you can restart this component if you want another attempt made.)", err)) return } for _, ep := range list { if _, ok := ep.Annotations[resourcelock.LeaderElectionRecordAnnotationKey]; ok { // when there are multiple controller-manager instances, // we observe that it will delete leader-election endpoints after 5min // and cause re-election // so skip the delete here // as leader-election only have endpoints without service continue } key, err := keyFunc(ep) if err != nil { utilruntime.HandleError(fmt.Errorf("Unable to get key for endpoint %#v", ep)) continue } e.queue.Add(key) } }
另外,还需要注意一点,对于kube-controller-manager多实例HA部署时,各个contorller-manager endpoints是没有对应service的,这种情况下,我们不能把虚构的Service加入到队列触发这些“理应孤立”的endpoints被清理,因此我们给这些“理应孤立”的endpoints加上Annotation "control-plane.alpha.kubernetes.io/leader"以做跳过处理。
Service的Add/Update/Delete Event Handler都是将Service Key加入到Queue中,等待worker进行syncService处理:
根据queue中得到的service key(namespace/name)去indexer中获取对应的Service Object,如果没获取到,则调api删除同Key(namespace/name)的Endpoints Object进行清理工作,这对应到checkLeftoverEndpoints中描述到的那些孤立endpoints清理工作。
因为Service是通过LabelSelector进行Pod匹配,将匹配的Pods构建对应的Endpoints Subsets加入到Endpoints中,因此这里会先过滤掉那些没有LabelSelector的Services。
然后用Service的LabelSelector获取同namespace下的所有Pods。
检查service.Spec.PublishNotReadyAddresses是否为true,或者Service Annotations "service.alpha.kubernetes.io/tolerate-unready-endpoints"是否为true(/t/T/True/TRUE/1),如果为true,则表示tolerate Unready Endpoints,即Unready的Pods信息也会被加入该Service对应的Endpoints中。
注意,Annotations "service.alpha.kubernetes.io/tolerate-unready-endpoints"在Kubernetes 1.13中将被弃用,后续只使用.Spec.PublishNotReadyAddresses Field。
接下来就是遍历前面获取到的Pods,用各个Pod的IP、ContainerPorts、HostName及Service的Port去构建Endpoints的Subsets,注意如下特殊处理:
4)当tolerate Unready Endpoints为true(即使Pod not Ready)或者Pod isReady时,Pod对应的EndpointAddress也会被加入到(Ready)Addresses中。
5)tolerate Unready Endpoints为false且Pod isNotReady情况下:
- 当pod.Spec.RestartPolicy为Never,Pod Status.Phase为非结束状态(非Failed/Successed)时,Pod对应的EndpointAddress也会被加入到NotReadyAddresses中。 - 当pod.Spec.RestartPolicy为OnFailure, Pod Status.Phase为非Successed时,Pod对应的EndpointAddress也会被加入到NotReadyAddresses中。 - 其他情况下,Pod对应的EndpointAddress也会被加入到NotReadyAddresses中。
跳过没有pod.Status.PodIP为空的pod;
当tolerate Unready Endpoints为false时,跳过那些被标记删除(DeletionTimestamp != nil)的Pods;
对于Headless Service,因为没有Service Port,因此构建EndpointSubset时对应的Ports内容为空;
从indexer中获取service对应的Endpoints Object(currentEndpoints),如果从indexer中没有返回对应的Endpoints Object,则构建一个与该Service同名、同Labels的Endpoints对象(newEndpoints)。
如果currentEndpoints的ResourceVersion不为空,则对比currentEndpoints.Subsets、Labels与前面构建的Subsets、Service.Labels是否DeepEqual,如果是则说明不需要update,流程结束。
否则,就像currentEndpoints DeepCopy给newEndpoints,并用前面构建的Subsets和Services.Labels替换newEndpoints中对应内容。
如果currentEndpoints的ResourceVersion为空,则调用Create API去创建上一步的newEndpoints Object。如果currentEndpoints的ResourceVersion不为空,表示已经存在对应的Endpoints,则调用Update API用newEndpoints去更新该Endpoints。
流程结束。
通过Services LabeleSelector与Pod Labels进行匹配的方法,将该Pod能匹配上的所有Services都找出来,然后将它们的Key(namespace/name)都加入到queue等待sync。
// When a pod is added, figure out what services it will be a member of and // enqueue them. obj must have *v1.Pod type. func (e *EndpointController) addPod(obj interface{}) { pod := obj.(*v1.Pod) services, err := e.getPodServiceMemberships(pod) if err != nil { utilruntime.HandleError(fmt.Errorf("Unable to get pod %s/%s's service memberships: %v", pod.Namespace, pod.Name, err)) return } for key := range services { e.queue.Add(key) } }
如果newPod.ResourceVersion等于oldPod.ResourceVersion,则跳过,不进行任何update。
检查新老Pod的DeletionTimestamp、Ready Condition以及由PodIP,Hostname等建构的EndpointAddress是否发生变更,只要其中之一发生变更,podChangedFlag就为true。
检查新老Pod Spec的Labels、HostName、Subdomain是否发生变更,只要其中之一发生变更,labelChangedFlag就为true。
如果podChangedFlag和labelChangedFlag都为false,则跳过,不做任何update。
通过Services LabeleSelector与Pod Labels进行匹配的方法,将newPod能匹配上的所有Services都找出来(services记录),如果labelChangedFlag为true,则根据LabelSelector匹配找出oldPod对应的oldServices:
互相差值进行union集合的含义:
services.Difference(oldServices).Union(oldServices.Difference(services))
如果podChangedFlag为true,则将services和oldServices进行union集合,将集合内的所有Services Key都加入到queue中等待sync;
如果podChangedFlag为false,则将services和oldServices的互相差值进行union集合,将集合内的所有Services Key都加入到queue中等待sync;
如果该pod还是个完整记录的pod,则跟addPod逻辑一样:通过Services LabeleSelector与Pod Labels进行匹配的方法,将该Pod能匹配上的所有Services都找出来,然后将它们的Key(namespace/name)都加入到queue等待sync。
如果该pod是tombstone object(final state is unrecorded),则将其转换成v1.pod后,再调用addPod。相比正常的Pod,就是多了一步:从tombstone到v1.pod的转换。
// When a pod is deleted, enqueue the services the pod used to be a member of. // obj could be an *v1.Pod, or a DeletionFinalStateUnknown marker item. func (e *EndpointController) deletePod(obj interface{}) { if _, ok := obj.(*v1.Pod); ok { // Enqueue all the services that the pod used to be a member // of. This happens to be exactly the same thing we do when a // pod is added. e.addPod(obj) return } // If we reached here it means the pod was deleted but its final state is unrecorded. tombstone, ok := obj.(cache.DeletedFinalStateUnknown) if !ok { utilruntime.HandleError(fmt.Errorf("Couldn't get object from tombstone %#v", obj)) return } pod, ok := tombstone.Obj.(*v1.Pod) if !ok { utilruntime.HandleError(fmt.Errorf("Tombstone contained object that is not a Pod: %#v", obj)) return } glog.V(4).Infof("Enqueuing services of deleted pod %s/%s having final state unrecorded", pod.Namespace, pod.Name) e.addPod(pod) }
里面有几个struct,挺容易混淆的,简单用图表示下,方便比对:
通过对Endpoints Controller的源码分析,我们了解了其中很多细节,比如对Service和Pod事件处理逻辑、对孤立Pod的处理方法、Pod Labels变更带来的影响等等,这对我们通过Watch Endpoints去写自己的Ingress组件对接公司内部的路由组件时是有帮助的。
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