kube-scheduler调度任务的执行过程分析与源码解读(二)

概述

摘要：上文我们对Kube-scheduler的启动流程进行了分析，本文继续探究kube-scheduler执行pod的调度任务的过程。

正文

说明：基于 kubernetes v1.12.0 源码分析

上文讲到kube-scheduler组件通过sched.Run() 启动调度器实例。在sched.Run() 中循环的执行sched.scheduleOne获取一个pod，并执行Pod的调度任务。

源码位置k8s.io/kubernetes/cmd/kube-scheduler/scheduler.go

// Run begins watching and scheduling. It waits for cache to be synced, then starts a goroutine and returns immediately.
func (sched *Scheduler) Run() {
	if !sched.config.WaitForCacheSync() {
		return
	}
	// 启动协程循环的执行调度任务
	go wait.Until(sched.scheduleOne, 0, sched.config.StopEverything)
}

(sched *Scheduler) scheduleOne

继续探究scheduleOne函数，scheduleOne函数非常关键。函数的第一步就是 getNextPod() 从调度队列podQueue中取出一个待调度 pod

// scheduleOne does the entire scheduling workflow for a single pod.  It is serialized on the scheduling algorithm's host fitting.
func (sched *Scheduler) scheduleOne() {
  // 从调度队列podQueue中取出一个待调度 pod
	pod := sched.config.NextPod()
	if pod.DeletionTimestamp != nil {
		sched.config.Recorder.Eventf(pod, v1.EventTypeWarning, "FailedScheduling", "skip schedule deleting pod: %v/%v", pod.Namespace, pod.Name)
		glog.V(3).Infof("Skip schedule deleting pod: %v/%v", pod.Namespace, pod.Name)
		return
	}

	glog.V(3).Infof("Attempting to schedule pod: %v/%v", pod.Namespace, pod.Name)

	// Synchronously attempt to find a fit for the pod.
	start := time.Now()
	suggestedHost, err := sched.schedule(pod)
	if err != nil {
		// schedule() may have failed because the pod would not fit on any host, so we try to
		// preempt, with the expectation that the next time the pod is tried for scheduling it
		// will fit due to the preemption. It is also possible that a different pod will schedule
		// into the resources that were preempted, but this is harmless.
		if fitError, ok := err.(*core.FitError); ok {
			preemptionStartTime := time.Now()
			sched.preempt(pod, fitError)
			metrics.PreemptionAttempts.Inc()
			metrics.SchedulingAlgorithmPremptionEvaluationDuration.Observe(metrics.SinceInMicroseconds(preemptionStartTime))
			metrics.SchedulingLatency.WithLabelValues(metrics.PreemptionEvaluation).Observe(metrics.SinceInSeconds(preemptionStartTime))
		}
		return
	}
	metrics.SchedulingAlgorithmLatency.Observe(metrics.SinceInMicroseconds(start))
	// Tell the cache to assume that a pod now is running on a given node, even though it hasn't been bound yet.
	// This allows us to keep scheduling without waiting on binding to occur.
	assumedPod := pod.DeepCopy()

	// Assume volumes first before assuming the pod.
	//
	// If all volumes are completely bound, then allBound is true and binding will be skipped.
	//
	// Otherwise, binding of volumes is started after the pod is assumed, but before pod binding.
	//
	// This function modifies 'assumedPod' if volume binding is required.
	allBound, err := sched.assumeVolumes(assumedPod, suggestedHost)
	if err != nil {
		return
	}

	// assume modifies `assumedPod` by setting NodeName=suggestedHost
	err = sched.assume(assumedPod, suggestedHost)
	if err != nil {
		return
	}
	// bind the pod to its host asynchronously (we can do this b/c of the assumption step above).
	go func() {
		// Bind volumes first before Pod
		if !allBound {
			err = sched.bindVolumes(assumedPod)
			if err != nil {
				return
			}
		}

		err := sched.bind(assumedPod, &v1.Binding{
			ObjectMeta: metav1.ObjectMeta{Namespace: assumedPod.Namespace, Name: assumedPod.Name, UID: assumedPod.UID},
			Target: v1.ObjectReference{
				Kind: "Node",
				Name: suggestedHost,
			},
		})
		metrics.E2eSchedulingLatency.Observe(metrics.SinceInMicroseconds(start))
		if err != nil {
			glog.Errorf("Internal error binding pod: (%v)", err)
		}
	}()
}

scheduleOne函数较长我们提炼出关键步骤:

sched.config.NextPod() 从调度队列podQueue中取出一个待调度 pod
sched.schedule(pod) 执行对pod的调度任务，调度完成会返回一个合适的host(suggestedHost)
sched.bind 执行 bind ，即将 pod 绑定到 node,并发送post请求给apiserver

// scheduleOne does the entire scheduling workflow for a single pod.  It is serialized on the scheduling algorithm's host fitting.
func (sched *Scheduler) scheduleOne() {
  // 从调度队列podQueue中取出一个待调度 pod
	pod := sched.config.NextPod()
	
  // 执行pod的调度任务，调度完成会返回一个合适的host
	suggestedHost, err := sched.schedule(pod)

	// bind the pod to its host asynchronously (we can do this b/c of the assumption step above).
	go func() {
		// 执行 bind ，将 pod 绑定到 node
		err := sched.bind(assumedPod, &v1.Binding{
	}()
}

接下来，我们分别对获取待调度pod、执行pod调度任务、pod的绑定详细探究

源码如何实现调度任务

(sched *Scheduler) schedule

(sched *Scheduler) schedule 的作用是给定一个待调度pod，利用调度算法，返回一个合适的Host。函数内部直接执行调度任务的是sched.config.Algorithm.Schedule.

// schedule implements the scheduling algorithm and returns the suggested host.
func (sched *Scheduler) schedule(pod *v1.Pod) (string, error) {
  // 给定一个pod 和 一个NodeLister，返回一个合适的host
	host, err := sched.config.Algorithm.Schedule(pod, sched.config.NodeLister)
	if err != nil {
		pod = pod.DeepCopy()
		sched.config.Error(pod, err)
		sched.config.Recorder.Eventf(pod, v1.EventTypeWarning, "FailedScheduling", "%v", err)
		sched.config.PodConditionUpdater.Update(pod, &v1.PodCondition{
			Type:          v1.PodScheduled,
			Status:        v1.ConditionFalse,
			LastProbeTime: metav1.Now(),
			Reason:        v1.PodReasonUnschedulable,
			Message:       err.Error(),
		})
		return "", err
	}
	return host, err
}

(g *genericScheduler) Schedule

sched.config.Algorithm.Schedule 是一个接口，具体实现是genericScheduler结构的Schedule()方法。

在这里插入图片描述

找到genericScheduler结构体的Schedule()方法的源码

// Schedule tries to schedule the given pod to one of the nodes in the node list.
// If it succeeds, it will return the name of the node.
// If it fails, it will return a FitError error with reasons.
func (g *genericScheduler) Schedule(pod *v1.Pod, nodeLister algorithm.NodeLister) (string, error) {
	trace := utiltrace.New(fmt.Sprintf("Scheduling %s/%s", pod.Namespace, pod.Name))
	defer trace.LogIfLong(100 * time.Millisecond)

  // 执行一些检查工作
	if err := podPassesBasicChecks(pod, g.pvcLister); err != nil {
		return "", err
	}
	// 获取 所有node信息
	nodes, err := nodeLister.List()
	if err != nil {
		return "", err
	}
	if len(nodes) == 0 {
		return "", ErrNoNodesAvailable
	}

	// Used for all fit and priority funcs.
  // 更新缓存中Node信息
	err = g.cache.UpdateNodeNameToInfoMap(g.cachedNodeInfoMap)
	if err != nil {
		return "", err
	}

	trace.Step("Computing predicates")
  // findNodesThatFit 执行预选算法，过滤出符合的node节点
	startPredicateEvalTime := time.Now()
	filteredNodes, failedPredicateMap, err := g.findNodesThatFit(pod, nodes)
	if err != nil {
		return "", err
	}

	if len(filteredNodes) == 0 {
		return "", &FitError{
			Pod:              pod,
			NumAllNodes:      len(nodes),
			FailedPredicates: failedPredicateMap,
		}
	}
  // 记录数据用于promethues监控采集
	metrics.SchedulingAlgorithmPredicateEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPredicateEvalTime))
	metrics.SchedulingLatency.WithLabelValues(metrics.PredicateEvaluation).Observe(metrics.SinceInSeconds(startPredicateEvalTime))

	trace.Step("Prioritizing")
  // 接下来将执行优选算法(打分)，选出最优node
	startPriorityEvalTime := time.Now()
	// When only one node after predicate, just use it.
  // 如果最优的节点只有一个，就直接返回该节点
	if len(filteredNodes) == 1 {
		metrics.SchedulingAlgorithmPriorityEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPriorityEvalTime))
		return filteredNodes[0].Name, nil
	}

	metaPrioritiesInterface := g.priorityMetaProducer(pod, g.cachedNodeInfoMap)
  // PrioritizeNodes 执行优选算法(打分)，选出最优的node
	priorityList, err := PrioritizeNodes(pod, g.cachedNodeInfoMap, metaPrioritiesInterface, g.prioritizers, filteredNodes, g.extenders)
	if err != nil {
		return "", err
	}
	metrics.SchedulingAlgorithmPriorityEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPriorityEvalTime))
	metrics.SchedulingLatency.WithLabelValues(metrics.PriorityEvaluation).Observe(metrics.SinceInSeconds(startPriorityEvalTime))

	trace.Step("Selecting host")
  // selectHost 从最优的node列表中选出，最优的一个node节点
	return g.selectHost(priorityList)
}

代码较长，老规矩我们提炼出精华。(g *genericScheduler) Schedule的工作主要有3点：

g.findNodesThatFit(pod, nodes) 从nodes列表中过滤出适合pod调度的node列表，即所谓的“预选”。
PrioritizeNodes 对node列表中的node执行"打分"，选出分数最高的node列表（因为可能出现一些node的分数最高且相同，所以返回的是多个node的列表），即所谓的"“优选”。
.selectHost(priorityList) 从最优列表中选出一个最最最合适的node节点。

// Schedule tries to schedule the given pod to one of the nodes in the node list.
// If it succeeds, it will return the name of the node.
// If it fails, it will return a FitError error with reasons.
func (g *genericScheduler) Schedule(pod *v1.Pod, nodeLister algorithm.NodeLister) (string, error) {
	
	// 1. 获取所有node信息
	nodes, err := nodeLister.List()

  // 2. findNodesThatFit 执行预选算法，过滤出符合的node节点
	filteredNodes, failedPredicateMap, err := g.findNodesThatFit(pod, nodes)

	// When only one node after predicate, just use it.
  // 2.1 如果最优的节点只有一个，就直接返回该节点
	if len(filteredNodes) == 1 { return filteredNodes[0].Name, nil}

  // 3. PrioritizeNodes 执行优选算法(打分)，选出最优的node
	priorityList, err := PrioritizeNodes(pod, g.cachedNodeInfoMap, metaPrioritiesInterface, g.prioritizers, filteredNodes, g.extenders)

  // 4. selectHost 从最优的node列表中选出，最优的一个node节点
	return g.selectHost(priorityList)
}

g.findNodesThatFit和PrioritizeNodes 内容较多后面写一个文章单独分析。

(g *genericScheduler) Schedule的执行流程如图所示

（图片来自网络，如有侵权，请联系作者删除）

(g *genericScheduler) selectHost

柿子挑软的捏。selectHost逻辑最简单，所以先分析它。 selectHost的任务是从优选列表中选出``一个最优node，注意如果有多个node最大且分数一样时，会通过索引累计方式，避免多次调度到同一个宿主`。


// selectHost takes a prioritized list of nodes and then picks one
// in a round-robin manner from the nodes that had the highest score.
func (g *genericScheduler) selectHost(priorityList schedulerapi.HostPriorityList) (string, error) {
	if len(priorityList) == 0 {
		return "", fmt.Errorf("empty priorityList")
	}
  // findMaxScores 从 priorityList 计算出最大分数的一个或多个 node 的索引
	maxScores := findMaxScores(priorityList)
  // 重要!!!通过索引累计方式，避免多次调度到同一个宿主
	ix := int(g.lastNodeIndex % uint64(len(maxScores)))
	g.lastNodeIndex++

	return priorityList[maxScores[ix]].Host, nil
}

findMaxScores

findMaxScores 对 priorityList 遍历，找出分数最大node的索引并放入一个列表，如果最大分数有相同的，就都会放入列表。


// findMaxScores returns the indexes of nodes in the "priorityList" that has the highest "Score".
func findMaxScores(priorityList schedulerapi.HostPriorityList) []int {
	maxScoreIndexes := make([]int, 0, len(priorityList)/2)
	maxScore := priorityList[0].Score
	for i, hp := range priorityList {
		if hp.Score > maxScore {
			maxScore = hp.Score
      // 如果 node 的 score大于 maxScore就把所有放入列表 maxScoreIndexes
			maxScoreIndexes = maxScoreIndexes[:0]
			maxScoreIndexes = append(maxScoreIndexes, i)
		} else if hp.Score == maxScore {
			maxScoreIndexes = append(maxScoreIndexes, i)
		}
	}
	return maxScoreIndexes
}

源码如何实现从调度队列中获取待调度pod

schduleOne函数执行的第一步sched.config.NextPod()，作用是从调度队列podQueue中取出一个待调度pod。那么问题来了，podQueue是如何初始化的呢？是如何将数据放到队列里面去的呢？

我们先将视线回到server.go中的run()函数，会执行NewSchedulerConfig(c) 获取调度配置。

Run

// Run runs the Scheduler.
func Run(c schedulerserverconfig.CompletedConfig, stopCh <-chan struct{}) error {
	// 代码省略

	// Build a scheduler config from the provided algorithm source.
	schedulerConfig, err := NewSchedulerConfig(c)
	if err != nil {
		return err
	}
	// 代码省略
}

NewSchedulerConfig

NewSchedulerConfig 调用了 CreateFromProvider 函数。进一步查找 CreateFromProvider 函数

// NewSchedulerConfig creates the scheduler configuration. This is exposed for use by tests.
func NewSchedulerConfig(s schedulerserverconfig.CompletedConfig) (*scheduler.Config, error) {
	// 代码省略

	source := s.ComponentConfig.AlgorithmSource
	var config *scheduler.Config
	switch {
	case source.Provider != nil:
		// Create the config from a named algorithm provider.
		sc, err := configurator.CreateFromProvider(*source.Provider)
		if err != nil {
			return nil, fmt.Errorf("couldn't create scheduler using provider %q: %v", *source.Provider, err)
		}
		config = sc
	// 代码省略
}

(c *configFactory) CreateFromProvider

CreateFromProvider 调用了 CreateFromKeys 函数

// Creates a scheduler from the name of a registered algorithm provider.
func (c *configFactory) CreateFromProvider(providerName string) (*scheduler.Config, error) {
	glog.V(2).Infof("Creating scheduler from algorithm provider '%v'", providerName)
	provider, err := GetAlgorithmProvider(providerName)
	if err != nil {
		return nil, err
	}
	// 注意
	return c.CreateFromKeys(provider.FitPredicateKeys, provider.PriorityFunctionKeys, []algorithm.SchedulerExtender{})
}

(c *configFactory) CreateFromKeys

源码位置kubernetes/pkg/scheduler/factory/factory.go

在CreateFromKeys函数中终于找到NextPod的定义，我们继续查找c.getNextPod()

// Creates a scheduler from a set of registered fit predicate keys and priority keys.
func (c *configFactory) CreateFromKeys(predicateKeys, priorityKeys sets.String, extenders []algorithm.SchedulerExtender) (*scheduler.Config, error) {
	glog.V(2).Infof("Creating scheduler with fit predicates '%v' and priority functions '%v'", predicateKeys, priorityKeys)

	if c.GetHardPodAffinitySymmetricWeight() < 1 || c.GetHardPodAffinitySymmetricWeight() > 100 {
		return nil, fmt.Errorf("invalid hardPodAffinitySymmetricWeight: %d, must be in the range 1-100", c.GetHardPodAffinitySymmetricWeight())
	}

	predicateFuncs, err := c.GetPredicates(predicateKeys)
	if err != nil {
		return nil, err
	}

	priorityConfigs, err := c.GetPriorityFunctionConfigs(priorityKeys)
	if err != nil {
		return nil, err
	}

	priorityMetaProducer, err := c.GetPriorityMetadataProducer()
	if err != nil {
		return nil, err
	}

	predicateMetaProducer, err := c.GetPredicateMetadataProducer()
	if err != nil {
		return nil, err
	}

	// Init equivalence class cache
	if c.enableEquivalenceClassCache {
		c.equivalencePodCache = equivalence.NewCache()
		glog.Info("Created equivalence class cache")
	}
	// 重要！！！ 创建通用调度器
	algo := core.NewGenericScheduler(
		c.schedulerCache,
		c.equivalencePodCache,
		c.podQueue,
		predicateFuncs,
		predicateMetaProducer,
		priorityConfigs,
		priorityMetaProducer,
		extenders,
		c.volumeBinder,
		c.pVCLister,
		c.alwaysCheckAllPredicates,
		c.disablePreemption,
		c.percentageOfNodesToScore,
	)

	podBackoff := util.CreateDefaultPodBackoff()
	return &scheduler.Config{
		SchedulerCache: c.schedulerCache,
		Ecache:         c.equivalencePodCache,
		// The scheduler only needs to consider schedulable nodes.
		NodeLister:          &nodeLister{c.nodeLister},
		Algorithm:           algo,
		GetBinder:           c.getBinderFunc(extenders),
		PodConditionUpdater: &podConditionUpdater{c.client},
		PodPreemptor:        &podPreemptor{c.client},
		WaitForCacheSync: func() bool {
			return cache.WaitForCacheSync(c.StopEverything, c.scheduledPodsHasSynced)
		},
    // 重要！！！从调度队列中取出一个 待调度 pod
		NextPod: func() *v1.Pod {
			return c.getNextPod()
		},
		Error:           c.MakeDefaultErrorFunc(podBackoff, c.podQueue),
		StopEverything:  c.StopEverything,
		VolumeBinder:    c.volumeBinder,
    // 定义调度队列
		SchedulingQueue: c.podQueue,
	}, nil
}

getNextPod() 的逻辑很简单，就是从调度队列podQueue中Pop()出一个待调度的pod。podQueue是一个优先级队列，如果待调度pod在spec中配置了优先级，pop()会弹出优先级高的pod执行调度任务。

func (c *configFactory) getNextPod() *v1.Pod {
  // 从调度队列从弹出一个待调度的pod
	pod, err := c.podQueue.Pop()
	if err == nil {
		glog.V(4).Infof("About to try and schedule pod %v/%v", pod.Namespace, pod.Name)
		return pod
	}
	glog.Errorf("Error while retrieving next pod from scheduling queue: %v", err)
	return nil
}

到此，我们明白了，shed.run()启动s时会启动informer，informer中定义了pod事件handler回调函数，handler会将待调度的pod放入调度队列podQueue。而消费调度队列里面的pod，则是sheduleOne方法通过c.podQueue.Pop()取出一个待调度pod。

源码如何实现bind操作

scheduleOne选出一个 node 之后，调度器会创建一个v1.Binding 对象， Pod 的 ObjectReference 字段的值就是选中的 suggestedHost 的名字。

下面代码片段是scheduleOne中关于bind操作的内容

// 构建一个 v1.Binding 对象
err := sched.bind(assumedPod, &v1.Binding{
			ObjectMeta: metav1.ObjectMeta{Namespace: assumedPod.Namespace, Name: assumedPod.Name, UID: assumedPod.UID},
			Target: v1.ObjectReference{
				Kind: "Node",
				Name: suggestedHost,
			},
		})

v1.Binding资源类型的介绍

v1.Binding 是 Kubernetes API 的一个对象类型，用于将一个或多个 Pod 绑定到一个特定的节点上。为了将 Pod 绑定到特定的节点上，可以使用 v1.Binding 对象。该对象需要指定 Pod 的名称和命名空间，以及要绑定到的节点名称。

(b *binder) Bind 代码很多，但核心的就一行：

err := sched.config.GetBinder(assumed).Bind(b)

调用Binder接口的Bind方法。进一可以看到，Bind方法是利用clientset向apiserver发起一个Bind的POST请求

// bind binds a pod to a given node defined in a binding object.  We expect this to run asynchronously, so we
// handle binding metrics internally.
func (sched *Scheduler) bind(assumed *v1.Pod, b *v1.Binding) error {
	bindingStart := time.Now()
	// If binding succeeded then PodScheduled condition will be updated in apiserver so that
	// it's atomic with setting host.
  // 调用Binder接口的Bind方法
	err := sched.config.GetBinder(assumed).Bind(b)
  // 检查cache中对应pod的状态，确认是否bind成功
	if err := sched.config.SchedulerCache.FinishBinding(assumed); err != nil {
		glog.Errorf("scheduler cache FinishBinding failed: %v", err)
	}
  // 如果没有bind绑定成功,则记录错误原因
	if err != nil {
		glog.V(1).Infof("Failed to bind pod: %v/%v", assumed.Namespace, assumed.Name)
		if err := sched.config.SchedulerCache.ForgetPod(assumed); err != nil {
			glog.Errorf("scheduler cache ForgetPod failed: %v", err)
		}
		sched.config.Error(assumed, err)
		sched.config.Recorder.Eventf(assumed, v1.EventTypeWarning, "FailedScheduling", "Binding rejected: %v", err)
		sched.config.PodConditionUpdater.Update(assumed, &v1.PodCondition{
			Type:          v1.PodScheduled,
			Status:        v1.ConditionFalse,
			LastProbeTime: metav1.Now(),
			Reason:        "BindingRejected",
		})
		return err
	}
	// 记录metrics监控数据
	metrics.BindingLatency.Observe(metrics.SinceInMicroseconds(bindingStart))
	metrics.SchedulingLatency.WithLabelValues(metrics.Binding).Observe(metrics.SinceInSeconds(bindingStart))
	sched.config.Recorder.Eventf(assumed, v1.EventTypeNormal, "Scheduled", "Successfully assigned %v/%v to %v", assumed.Namespace, assumed.Name, b.Target.Name)
	return nil
}

Bind 是调用了clientset向apiserver发起一个Bind的POST请求

// Bind just does a POST binding RPC.
func (b *binder) Bind(binding *v1.Binding) error {
	glog.V(3).Infof("Attempting to bind %v to %v", binding.Name, binding.Target.Name)
  // 通过clientset向apiserver发起一个Bind的POST请求
	return b.Client.CoreV1().Pods(binding.Namespace).Bind(binding)
}

补充内容: apiserver收到bind请求后

当apiserver 收到这个 Binding object 请求后，将会更新 Pod 对象的下列字段：

设置 pod.Spec.NodeName
添加 annotations
设置 PodScheduled status 为 True

// k8s.io/kubernetes/pkg/registry/core/pod/storage/storage.go

// assignPod assigns the given pod to the given machine.
// 处理 api 收到到binding RESTful 请求
func (r *BindingREST) assignPod(ctx context.Context, podID string, machine string, annotations map[string]string, dryRun bool) (err error) {
  // 设置pod的 host 和 Annotation 信息
	if _, err = r.setPodHostAndAnnotations(ctx, podID, "", machine, annotations, dryRun); err != nil {
		err = storeerr.InterpretGetError(err, api.Resource("pods"), podID)
		err = storeerr.InterpretUpdateError(err, api.Resource("pods"), podID)
		if _, ok := err.(*errors.StatusError); !ok {
			err = errors.NewConflict(api.Resource("pods/binding"), podID, err)
		}
	}
	return
}

// k8s.io/kubernetes/pkg/registry/core/pod/storage/storage.go

func (r *BindingREST) setPodHostAndAnnotations(ctx context.Context, podID, oldMachine, machine string,
    annotations map[string]string, dryRun bool) (finalPod *api.Pod, err error) {

    podKey := r.store.KeyFunc(ctx, podID)
    r.store.Storage.GuaranteedUpdate(ctx, podKey, &api.Pod{}, false, nil,
        storage.SimpleUpdate(func(obj runtime.Object) (runtime.Object, error) {

        pod, ok := obj.(*api.Pod)
        // 设置 pod.Spec.NodeName 
        pod.Spec.NodeName = machine
        if pod.Annotations == nil {
            pod.Annotations = make(map[string]string)
        }
        // 更新 pod 的 annotations
        for k, v := range annotations {
            pod.Annotations[k] = v
        }
        // 设置pod 的 pod.status.conditions中的status值为truez
        podutil.UpdatePodCondition(&pod.Status, &api.PodCondition{
            Type:   api.PodScheduled,
            Status: api.ConditionTrue,
        })

        return pod, nil
    }), dryRun, nil)
}

更新pod.spec.Nodename后，将数据写入到etcd，之后被指定调度的node节点上的 kubelet监听到这个事件，kubelet接下来会在该机器上创建pod.

总结

经过分析scheduleOne函数会循环的从调度队列sheduling_Queue`,取出pop()待调度的pod, 之后利用`sched.schedule()执行调度任务，选出最佳的sugestHost。最后sched.bind()通过clientset向apiserver发起绑定bind的POST请求。至此，完成了一个完成的pod调度过程，流程如图所示。

在这里插入图片描述