diff --git a/.DS_Store b/.DS_Store index 9326b38..eb688fd 100644 Binary files a/.DS_Store and b/.DS_Store differ diff --git a/controller/Kubernetes源码学习-Controller-P4-ReplicaSet Controller.md b/controller/Kubernetes源码学习-Controller-P4-ReplicaSet Controller.md new file mode 100644 index 0000000..8878a66 --- /dev/null +++ b/controller/Kubernetes源码学习-Controller-P4-ReplicaSet Controller.md @@ -0,0 +1,495 @@ +# P4-ReplicaSet Controller + +## 前言 + +在上一篇文章中，对deployment controller的工作模式进行了详细地分析: + +[Controller-P3-Controller](https://github.com/yinwenqin/kubeSourceCodeNote/blob/master/controller/Kubernetes源码学习-Controller-P3-Controller分类与Deployment Controller.md) + +分析后得知，deployment controller更多的是对每个相应版本的replicaset副本数进行管理，而不涉及直接对pod的管理，因此，承接上节，本章来分析replicaSet Controller的源码. + + + +## ReplicaSet Controller + +### 初始化 + +参照上节一样，直接来到各类controller初始化的函数: + +`cmd/kube-controller-manager/app/controllermanager.go:343` + +```go +controllers["replicaset"] = startReplicaSetController +``` + +==> `cmd/kube-controller-manager/app/apps.go:69` + +```go + go replicaset.NewReplicaSetController( + // replicaSet controller只关注ReplicaSets和Pod这两种资源。 + ctx.InformerFactory.Apps().V1().ReplicaSets(), + ctx.InformerFactory.Core().V1().Pods(), + ctx.ClientBuilder.ClientOrDie("replicaset-controller"), + replicaset.BurstReplicas, + ).Run(int(ctx.ComponentConfig.ReplicaSetController.ConcurrentRSSyncs), ctx.Stop) +``` + + + +### 创建ReplicaSetController + +先来看看NewReplicaSetController创建的过程: + +==> `pkg/controller/replicaset/replica_set.go:109` + +```go +func NewReplicaSetController(rsInformer appsinformers.ReplicaSetInformer, podInformer coreinformers.PodInformer, kubeClient clientset.Interface, burstReplicas int) *ReplicaSetController { + eventBroadcaster := record.NewBroadcaster() + eventBroadcaster.StartLogging(klog.Infof) + eventBroadcaster.StartRecordingToSink(&v1core.EventSinkImpl{Interface: kubeClient.CoreV1().Events("")}) + // NewBaseController方法往下看 + return NewBaseController(rsInformer, podInformer, kubeClient, burstReplicas, + apps.SchemeGroupVersion.WithKind("ReplicaSet"), + "replicaset_controller", + "replicaset", + controller.RealPodControl{ + KubeClient: kubeClient, + Recorder: eventBroadcaster.NewRecorder(scheme.Scheme, v1.EventSource{Component: "replicaset-controller"}), + }, + ) +} + +// NewBaseController is the implementation of NewReplicaSetController with additional injected +// parameters so that it can also serve as the implementation of NewReplicationController. +func NewBaseController(rsInformer appsinformers.ReplicaSetInformer, podInformer coreinformers.PodInformer, kubeClient clientset.Interface, burstReplicas int, + gvk schema.GroupVersionKind, metricOwnerName, queueName string, podControl controller.PodControlInterface) *ReplicaSetController { + if kubeClient != nil && kubeClient.CoreV1().RESTClient().GetRateLimiter() != nil { + metrics.RegisterMetricAndTrackRateLimiterUsage(metricOwnerName, kubeClient.CoreV1().RESTClient().GetRateLimiter()) + } + + rsc := &ReplicaSetController{ + GroupVersionKind: gvk, + kubeClient: kubeClient, + podControl: podControl, + burstReplicas: burstReplicas, + expectations: controller.NewUIDTrackingControllerExpectations(controller.NewControllerExpectations()), + queue: workqueue.NewNamedRateLimitingQueue(workqueue.DefaultControllerRateLimiter(), queueName), + } + + rsInformer.Informer().AddEventHandler(cache.ResourceEventHandlerFuncs{ + AddFunc: rsc.enqueueReplicaSet, + UpdateFunc: rsc.updateRS, + DeleteFunc: rsc.enqueueReplicaSet, + }) + rsc.rsLister = rsInformer.Lister() + // informer会同步待操作的资源到本地的queue中，HasSynced方法就是用来判断判断queue是否已同步的 + rsc.rsListerSynced = rsInformer.Informer().HasSynced + + podInformer.Informer().AddEventHandler(cache.ResourceEventHandlerFuncs{ + AddFunc: rsc.addPod, + UpdateFunc: rsc.updatePod, + DeleteFunc: rsc.deletePod, + }) + rsc.podLister = podInformer.Lister() + // informer会同步待操作的资源到本地的queue中，HasSynced方法就是用来判断判断queue是否已同步的 + rsc.podListerSynced = podInformer.Informer().HasSynced + + rsc.syncHandler = rsc.syncReplicaSet + + return rsc +} +``` + +NewBaseController这里主要关注AddEventHandler为资源的informer增加的curd方法，例如pod相关的addPod、updatePod、deletePod方法。 + + + +### ReplicaSetController Run方法 + +接着往下，创建好ReplicaSetController对象后，看它的运行过程，即Run方法。 + +==> `pkg/controller/replicaset/replica_set.go:177` + +```go +// Run begins watching and syncing. +func (rsc *ReplicaSetController) Run(workers int, stopCh <-chan struct{}) { + defer utilruntime.HandleCrash() + defer rsc.queue.ShutDown() + + controllerName := strings.ToLower(rsc.Kind) + klog.Infof("Starting %v controller", controllerName) + defer klog.Infof("Shutting down %v controller", controllerName) + + // 判断各个informer的缓存是否已经同步完毕的函数 + if !controller.WaitForCacheSync(rsc.Kind, stopCh, rsc.podListerSynced, rsc.rsListerSynced) { + return + } + // worker的数量默认是5个，开启5个worker，每个worker间隔1s运行一次rsc.worker函数，来检查并收敛rs的状态 + for i := 0; i < workers; i++ { + go wait.Until(rsc.worker, time.Second, stopCh) + } + + <-stopCh +} +``` + +来到了这里，可发现ReplicaSetController.Run()函数和上一节的DeploymentController.Run()函数非常地相似。所以，从这里开始，各类controller之间代码相似的步骤可能会跳过，不再每个地方都重复详细说明。 + +往上溯源，可以找到，worker的数量配置默认为5个，参见这里: + +`pkg/controller/apis/config/v1alpha1/defaults.go:219` + +```go +func SetDefaults_ReplicaSetControllerConfiguration(obj *kubectrlmgrconfigv1alpha1.ReplicaSetControllerConfiguration) { + if obj.ConcurrentRSSyncs == 0 { + obj.ConcurrentRSSyncs = 5 + } +} +``` + +wait.Until()函数是很有意思的，上节也做过仔细分析，可以再回顾一下这里: + +[waituntil循环计时器函数](https://github.com/yinwenqin/kubeSourceCodeNote/blob/master/controller/Kubernetes源码学习-Controller-P3-Controller分类与Deployment Controller.md#waituntil循环计时器函数) + +好，直接进入主题，开始分析rsc.worker工作函数. + + + +### 工作逻辑 + +`pkg/controller/replicaset/replica_set.go:190` + +```go + for i := 0; i < workers; i++ { + go wait.Until(rsc.worker, time.Second, stopCh) + } +``` + +==> `pkg/controller/replicaset/replica_set.go:432` + +```go +// processNextWorkItem()函数的作用是把informer work queue工作队列里的对象取出，按照申明的要求来处理它们，标记它们。 +func (rsc *ReplicaSetController) worker() { + for rsc.processNextWorkItem() { + } +} +``` + +==> `pkg/controller/replicaset/replica_set.go:437` + +```go +func (rsc *ReplicaSetController) processNextWorkItem() bool { + // work queue中取出队首元素 + key, quit := rsc.queue.Get() + if quit { + return false + } + defer rsc.queue.Done(key) + // syncHandler每一个队列对象，强保证同一时间只会有一个go协程处理它(无并发竞争)。所谓sync，意思是将work queue中待操作的对象，同步实现到运行环境中。 + err := rsc.syncHandler(key.(string)) + if err == nil { + rsc.queue.Forget(key) + return true + } + + utilruntime.HandleError(fmt.Errorf("Sync %q failed with %v", key, err)) + rsc.queue.AddRateLimited(key) + + return true +} +``` + +主要函数是这个**syncHandler**，接着追溯，可以在这里找到这个结构体属性函数的赋值： + +`pkg/controller/replicaset/replica_set.go:163` + +```go +// NewBaseController is the implementation of NewReplicaSetController with additional injected +// parameters so that it can also serve as the implementation of NewReplicationController. +func NewBaseController(rsInformer appsinformers.ReplicaSetInformer, podInformer coreinformers.PodInformer, kubeClient clientset.Interface, burstReplicas int, + gvk schema.GroupVersionKind, metricOwnerName, queueName string, podControl controller.PodControlInterface) *ReplicaSetController { + // ... 省略 + rsc.syncHandler = rsc.syncReplicaSet + + return rsc +} +``` + +接着便可以找到**ReplicaSetController.syncReplicaSet**函数： + +`pkg/controller/replicaset/replica_set.go:562` + +```go + +// syncReplicaSet will sync the ReplicaSet with the given key if it has had its expectations fulfilled, +// meaning it did not expect to see any more of its pods created or deleted. This function is not meant to be +// invoked concurrently with the same key. +func (rsc *ReplicaSetController) syncReplicaSet(key string) error { + + startTime := time.Now() + defer func() { + klog.V(4).Infof("Finished syncing %v %q (%v)", rsc.Kind, key, time.Since(startTime)) + }() + // key的字符串格式是这样的: ${NAMESPACE}/${NAME} + namespace, name, err := cache.SplitMetaNamespaceKey(key) + if err != nil { + return err + } + // 获取到rs对象 + rs, err := rsc.rsLister.ReplicaSets(namespace).Get(name) + if errors.IsNotFound(err) { + klog.V(4).Infof("%v %v has been deleted", rsc.Kind, key) + rsc.expectations.DeleteExpectations(key) + return nil + } + if err != nil { + return err + } + + // 判断rs是否实现所声明的期望状态，这里SatisfiedExpectations是使用expectations机制来判断这个rs是否满足期望状态。 + rsNeedsSync := rsc.expectations.SatisfiedExpectations(key) + selector, err := metav1.LabelSelectorAsSelector(rs.Spec.Selector) + if err != nil { + utilruntime.HandleError(fmt.Errorf("Error converting pod selector to selector: %v", err)) + return nil + } + + // list all pods to include the pods that don't match the rs`s selector + // anymore but has the stale controller ref. + // TODO: Do the List and Filter in a single pass, or use an index. + // 取出所有的的pod，labels.Everything()取到的是空selector，即不使用label selector，取全部pod + allPods, err := rsc.podLister.Pods(rs.Namespace).List(labels.Everything()) + if err != nil { + return err + } + + // Ignore inactive pods. + // 去除 inactive状态的pod + filteredPods := controller.FilterActivePods(allPods) + + + // 根据rs和selector来选择受此rs版本管理的pod + filteredPods, err = rsc.claimPods(rs, selector, filteredPods) + if err != nil { + return err + } + + + var manageReplicasErr error + // 如果rs未达到期望状态，则对副本进行管理，以使rs满足声明的期望状态 + if rsNeedsSync && rs.DeletionTimestamp == nil { + // 最重要的函数manageReplicas，未达期望时，管理rs对应的pod(新增/删除) + manageReplicasErr = rsc.manageReplicas(filteredPods, rs) + } + + rs = rs.DeepCopy() + newStatus := calculateStatus(rs, filteredPods, manageReplicasErr) + + // 只要有对应pod的更新，则需要更新rs的status字段 + updatedRS, err := updateReplicaSetStatus(rsc.kubeClient.AppsV1().ReplicaSets(rs.Namespace), rs, newStatus) + if err != nil { + // Multiple things could lead to this update failing. Requeuing the replica set ensures + // Returning an error causes a requeue without forcing a hotloop + return err + } + + // 当指定了MinReadySeconds时，即使pod 已经是ready状态了，但也不会视为Available，需要等待MinReadySeconds后再来刷新rs的状态。因此，enqueueReplicaSetAfter方法，异步等待MinReadySeconds后，把该rs重新压入work queue队列中 + if manageReplicasErr == nil && updatedRS.Spec.MinReadySeconds > 0 && + updatedRS.Status.ReadyReplicas == *(updatedRS.Spec.Replicas) && + updatedRS.Status.AvailableReplicas != *(updatedRS.Spec.Replicas) { + rsc.enqueueReplicaSetAfter(updatedRS, time.Duration(updatedRS.Spec.MinReadySeconds)*time.Second) + } + return manageReplicasErr +} +``` + +划重点，两个重要的函数：**SatisfiedExpectations**(判断是否满足sync条件) / **manageReplicas**(sync后续的副本pod新增、删除操作)。分别来看看 + + + +#### SatisfiedExpectations函数 + +在此之前，必须先了解一下rs controller(后面简称rsc)的Expectations机制。rsc会将每一个rs的期望状态(比如期望新增3个副本)保存在本地缓存中，在sync执行之前，会对期望状态进行条件判断，满足条件才会真正进行sync操作。 + +来看看SatisfiedExpectations函数的逻辑： + +`pkg/controller/controller_utils.go:181` + +```go +func (r *ControllerExpectations) SatisfiedExpectations(controllerKey string) bool { + // 若此key存在Expectations期望状态 + if exp, exists, err := r.GetExpectations(controllerKey); exists { + // Expectations期望状态达成或者过期，则需要sync + if exp.Fulfilled() { + klog.V(4).Infof("Controller expectations fulfilled %#v", exp) + return true + } else if exp.isExpired() { + klog.V(4).Infof("Controller expectations expired %#v", exp) + return true + } else { + // 存在期望状态但未达成，则无需sync。因为后面的handler在处理资源增删的时候会来新建和修改Expectations，说明当前正在接近期望状态中，所以本次无需再sync + klog.V(4).Infof("Controller still waiting on expectations %#v", exp) + return false + } + } + // 不存在Expectations(新增的资源对象)，或者获取Expectations出错，则视为需要执行sync + else if err != nil { + klog.V(2).Infof("Error encountered while checking expectations %#v, forcing sync", err) + } else { + klog.V(4).Infof("Controller %v either never recorded expectations, or the ttl expired.", controllerKey) + } + + return true +} +``` + + + +#### manageReplicas函数 + +==> `pkg/controller/replicaset/replica_set.go:459` + +```go +func (rsc *ReplicaSetController) manageReplicas(filteredPods []*v1.Pod, rs *apps.ReplicaSet) error { + // rs当前管理的pod数量 与 rs声明指定pod的数量 的差量 + diff := len(filteredPods) - int(*(rs.Spec.Replicas)) + rsKey, err := controller.KeyFunc(rs) + if err != nil { + utilruntime.HandleError(fmt.Errorf("Couldn't get key for %v %#v: %v", rsc.Kind, rs, err)) + return nil + } + // 当 rs当前管理的pod数量 小于 rs声明指定pod的数量 时，说明应该继续增加pod + if diff < 0 { + diff *= -1 + // 每次新增数量以突发增加数量burstReplicas为上限 + if diff > rsc.burstReplicas { + diff = rsc.burstReplicas + } + // 创建ExpectCreations期望 + rsc.expectations.ExpectCreations(rsKey, diff) + klog.V(2).Infof("Too few replicas for %v %s/%s, need %d, creating %d", rsc.Kind, rs.Namespace, rs.Name, *(rs.Spec.Replicas), diff) + + // slowStartBatch用来以指数级批量启动pod, 其中controller.SlowStartInitialBatchSize默认值为1，作为底数。 + successfulCreations, err := slowStartBatch(diff, controller.SlowStartInitialBatchSize, func() error { + // 创建单个pod的函数 CreatePodsWithControllerRef + err := rsc.podControl.CreatePodsWithControllerRef(rs.Namespace, &rs.Spec.Template, rs, metav1.NewControllerRef(rs, rsc.GroupVersionKind)) + if err != nil && errors.IsTimeout(err) { + + return nil + } + return err + }) + + + if skippedPods := diff - successfulCreations; skippedPods > 0 { + klog.V(2).Infof("Slow-start failure. Skipping creation of %d pods, decrementing expectations for %v %v/%v", skippedPods, rsc.Kind, rs.Namespace, rs.Name) + for i := 0; i < skippedPods; i++ { + // Decrement the expected number of creates because the informer won't observe this pod + rsc.expectations.CreationObserved(rsKey) + } + } + return err + + // 当 rs当前管理的pod数量 大于 rs声明指定pod的数量 时，说明应该减少pod + } else if diff > 0 { + if diff > rsc.burstReplicas { + diff = rsc.burstReplicas + } + klog.V(2).Infof("Too many replicas for %v %s/%s, need %d, deleting %d", rsc.Kind, rs.Namespace, rs.Name, *(rs.Spec.Replicas), diff) + + // 获取需要删除的pod + podsToDelete := getPodsToDelete(filteredPods, diff) + // 修改rs的期望状态，在期望中剔除将要删除的pod + rsc.expectations.ExpectDeletions(rsKey, getPodKeys(podsToDelete)) + + errCh := make(chan error, diff) + var wg sync.WaitGroup + wg.Add(diff) + // 并发删除目标pod + for _, pod := range podsToDelete { + go func(targetPod *v1.Pod) { + defer wg.Done() + if err := rsc.podControl.DeletePod(rs.Namespace, targetPod.Name, rs); err != nil { + // Decrement the expected number of deletes because the informer won't observe this deletion + podKey := controller.PodKey(targetPod) + klog.V(2).Infof("Failed to delete %v, decrementing expectations for %v %s/%s", podKey, rsc.Kind, rs.Namespace, rs.Name) + rsc.expectations.DeletionObserved(rsKey, podKey) + errCh <- err + } + }(pod) + } + wg.Wait() + + select { + case err := <-errCh: + // all errors have been reported before and they're likely to be the same, so we'll only return the first one we hit. + if err != nil { + return err + } + default: + } + } + + return nil +} +``` + +这个函数即是实际操控管理pod副本数量的函数，其中的slowStartBatch批量启动pod的功能比较有意思，来看看。 + + + +#### 批量启动pod + +`pkg/controller/replicaset/replica_set.go:658` + +```go +func slowStartBatch(count int, initialBatchSize int, fn func() error) (int, error) { + // 剩余要执行的数量 + remaining := count + // 累计成功执行的数量 + successes := 0 + // batchSize是每次批量执行的数量，从initialBatchSize(1)和剩余数量中取最小值。每次循环执行成功后，batchSize乘以2，以指数级扩充。 + for batchSize := integer.IntMin(remaining, initialBatchSize); batchSize > 0; batchSize = integer.IntMin(2*batchSize, remaining) { + errCh := make(chan error, batchSize) + var wg sync.WaitGroup + wg.Add(batchSize) + for i := 0; i < batchSize; i++ { + go func() { + defer wg.Done() + if err := fn(); err != nil { + errCh <- err + } + }() + } + wg.Wait() + curSuccesses := batchSize - len(errCh) + successes += curSuccesses + // 某一轮循环出错时，跳出循环，后续的不再执行。 + if len(errCh) > 0 { + return successes, <-errCh + } + remaining -= batchSize + } + return successes, nil +} +``` + + + +### ReplicaSetController工作流程总结 + +总结一下，在出现新版本的rs后，rsc按照以下步骤进行工作： + +1.通过SatisfiedExpectations函数，发现expectations期望状态本地缓存中不存在此rs key，因此返回true，需要sync + +2.通过manageReplicas管理pod，新增或删除 + +3.判断pod副本数是多了还是少了，多则要删，少则要增 + +4.增删之前创建expectations对象并设置add / del值 + +5.slowStartBatch新增 / 并发删除 pod + +6.更新expection + +expections缓存机制，在运行的pod副本数在向声明指定的副本数收敛之时，很好地避免了频繁的informer数据查询，以及可能随之而来的数据更新不及时的问题，这个机制设计巧妙贯穿整个rsc工作过程，也是不太易于理解之处。 \ No newline at end of file diff --git a/controller/README.md b/controller/README.md index 3ddf6ef..c2227d9 100644 --- a/controller/README.md +++ b/controller/README.md @@ -3,6 +3,7 @@ - [多实例leader选举](https://github.com/yinwenqin/kubeSourceCodeNote/blob/master/controller/Kubernetes源码学习-Controller-P1-多实例leader选举.md) - [Controller与informer](https://github.com/yinwenqin/kubeSourceCodeNote/blob/master/controller/Kubernetes源码学习-Controller-P2-Controller与informer.md) - [Controller分类与Deployment Controller](https://github.com/yinwenqin/kubeSourceCodeNote/blob/master/controller/Kubernetes源码学习-Controller-P3-Controller分类与Deployment Controller.md) +- [ReplicaSet Controller](https://github.com/yinwenqin/kubeSourceCodeNote/blob/master/controller/Kubernetes源码学习-Controller-P4-ReplicaSet Controller.md) - [StafulSet Controller] - 待补充