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kube-scheduler的调度上下文

来源:互联网 收集:自由互联 发布时间:2022-07-22
Scheduler结构 Scheduler 是整个 kube-scheduler 的一个 structure,提供了 kube-scheduler 运行所需的组件。 type Scheduler struct {// Cache是一个抽象,会缓存pod的信息,作为scheduler进行查找,操作是基于
Scheduler结构

Scheduler 是整个 kube-scheduler 的一个 structure,提供了 kube-scheduler 运行所需的组件。

type Scheduler struct {
	// Cache是一个抽象,会缓存pod的信息,作为scheduler进行查找,操作是基于Pod进行增加
	Cache internalcache.Cache
	// Extenders 算是调度框架中提供的调度插件,会影响kubernetes中的调度策略
	Extenders []framework.Extender

	// NextPod 作为一个函数提供,会阻塞获取下一个ke'diao'du
	NextPod func() *framework.QueuedPodInfo

	// Error is called if there is an error. It is passed the pod in
	// question, and the error
	Error func(*framework.QueuedPodInfo, error)

	// SchedulePod 尝试将给出的pod调度到Node。
	SchedulePod func(ctx context.Context, fwk framework.Framework, state *framework.CycleState, pod *v1.Pod) (ScheduleResult, error)

	// 关闭scheduler的信号
	StopEverything <-chan struct{}

	// SchedulingQueue保存要调度的Pod
	SchedulingQueue internalqueue.SchedulingQueue

	// Profiles中是多个调度框架
	Profiles profile.Map
	client clientset.Interface
	nodeInfoSnapshot *internalcache.Snapshot
	percentageOfNodesToScore int32
	nextStartNodeIndex int
}

作为实际执行的两个核心,SchedulingQueue ,与 scheduleOne 将会分析到这两个

SchedulingQueue

在知道 kube-scheduler 初始化过程后,需要对 kube-scheduler 的整个 structureworkflow 进行分析

在 Run 中,运行的是 一个 SchedulingQueue 与 一个 scheduleOne ,从结构上看是属于 Scheduler

func (sched *Scheduler) Run(ctx context.Context) {
	sched.SchedulingQueue.Run()

	// We need to start scheduleOne loop in a dedicated goroutine,
	// because scheduleOne function hangs on getting the next item
	// from the SchedulingQueue.
	// If there are no new pods to schedule, it will be hanging there
	// and if done in this goroutine it will be blocking closing
	// SchedulingQueue, in effect causing a deadlock on shutdown.
	go wait.UntilWithContext(ctx, sched.scheduleOne, 0)

	<-ctx.Done()
	sched.SchedulingQueue.Close()
}

SchedulingQueue 是一个队列的抽象,用于存储等待调度的Pod。该接口遵循类似于 cache.FIFO 和 cache.Heap 的模式。

type SchedulingQueue interface {
	framework.PodNominator
	Add(pod *v1.Pod) error
	// Activate moves the given pods to activeQ iff they're in unschedulablePods or backoffQ.
	// The passed-in pods are originally compiled from plugins that want to activate Pods,
	// by injecting the pods through a reserved CycleState struct (PodsToActivate).
	Activate(pods map[string]*v1.Pod)
	// 将不可调度的Pod重入到队列中
	AddUnschedulableIfNotPresent(pod *framework.QueuedPodInfo, podSchedulingCycle int64) error
	// SchedulingCycle returns the current number of scheduling cycle which is
	// cached by scheduling queue. Normally, incrementing this number whenever
	// a pod is popped (e.g. called Pop()) is enough.
	SchedulingCycle() int64
	// Pop会弹出一个pod,并从head优先级队列中删除
	Pop() (*framework.QueuedPodInfo, error)
	Update(oldPod, newPod *v1.Pod) error
	Delete(pod *v1.Pod) error
	MoveAllToActiveOrBackoffQueue(event framework.ClusterEvent, preCheck PreEnqueueCheck)
	AssignedPodAdded(pod *v1.Pod)
	AssignedPodUpdated(pod *v1.Pod)
	PendingPods() []*v1.Pod
	// Close closes the SchedulingQueue so that the goroutine which is
	// waiting to pop items can exit gracefully.
	Close()
	// Run starts the goroutines managing the queue.
	Run()
}

而 PriorityQueue 是 SchedulingQueue 的实现,该部分的核心构成是两个子队列与一个数据结构,即 activeQbackoffQunschedulablePods

  • activeQ:是一个 heap 类型的优先级队列,是 sheduler 从中获得优先级最高的Pod进行调度
  • backoffQ:也是一个 heap 类型的优先级队列,存放的是不可调度的Pod
  • unschedulablePods :保存确定不可被调度的Pod
type SchedulingQueue interface {
	framework.PodNominator
	Add(pod *v1.Pod) error
	// Activate moves the given pods to activeQ iff they're in unschedulablePods or backoffQ.
	// The passed-in pods are originally compiled from plugins that want to activate Pods,
	// by injecting the pods through a reserved CycleState struct (PodsToActivate).
	Activate(pods map[string]*v1.Pod)
	// AddUnschedulableIfNotPresent adds an unschedulable pod back to scheduling queue.
	// The podSchedulingCycle represents the current scheduling cycle number which can be
	// returned by calling SchedulingCycle().
	AddUnschedulableIfNotPresent(pod *framework.QueuedPodInfo, podSchedulingCycle int64) error
	// SchedulingCycle returns the current number of scheduling cycle which is
	// cached by scheduling queue. Normally, incrementing this number whenever
	// a pod is popped (e.g. called Pop()) is enough.
	SchedulingCycle() int64
	// Pop removes the head of the queue and returns it. It blocks if the
	// queue is empty and waits until a new item is added to the queue.
	Pop() (*framework.QueuedPodInfo, error)
	Update(oldPod, newPod *v1.Pod) error
	Delete(pod *v1.Pod) error
	MoveAllToActiveOrBackoffQueue(event framework.ClusterEvent, preCheck PreEnqueueCheck)
	AssignedPodAdded(pod *v1.Pod)
	AssignedPodUpdated(pod *v1.Pod)
	PendingPods() []*v1.Pod
	// Close closes the SchedulingQueue so that the goroutine which is
	// waiting to pop items can exit gracefully.
	Close()
	// Run starts the goroutines managing the queue.
	Run()
}

在New scheduler 时可以看到会初始化这个queue

podQueue := internalqueue.NewSchedulingQueue(
    // 实现pod对比的一个函数即less
    profiles[options.profiles[0].SchedulerName].QueueSortFunc(),
    informerFactory,
    internalqueue.WithPodInitialBackoffDuration(time.Duration(options.podInitialBackoffSeconds)*time.Second),
    internalqueue.WithPodMaxBackoffDuration(time.Duration(options.podMaxBackoffSeconds)*time.Second),
    internalqueue.WithPodNominator(nominator),
    internalqueue.WithClusterEventMap(clusterEventMap),
    internalqueue.WithPodMaxInUnschedulablePodsDuration(options.podMaxInUnschedulablePodsDuration),
)

而 NewSchedulingQueue 则是初始化这个 PriorityQueue

// NewSchedulingQueue initializes a priority queue as a new scheduling queue.
func NewSchedulingQueue(
	lessFn framework.LessFunc,
	informerFactory informers.SharedInformerFactory,
	opts ...Option) SchedulingQueue {
	return NewPriorityQueue(lessFn, informerFactory, opts...)
}

// NewPriorityQueue creates a PriorityQueue object.
func NewPriorityQueue(
	lessFn framework.LessFunc,
	informerFactory informers.SharedInformerFactory,
	opts ...Option,
) *PriorityQueue {
	options := defaultPriorityQueueOptions
	for _, opt := range opts {
		opt(&options)
	}
	// 这个就是 less函数,作为打分的一部分
	comp := func(podInfo1, podInfo2 interface{}) bool {
		pInfo1 := podInfo1.(*framework.QueuedPodInfo)
		pInfo2 := podInfo2.(*framework.QueuedPodInfo)
		return lessFn(pInfo1, pInfo2)
	}

	if options.podNominator == nil {
		options.podNominator = NewPodNominator(informerFactory.Core().V1().Pods().Lister())
	}

	pq := &PriorityQueue{
		PodNominator:                      options.podNominator,
		clock:                             options.clock,
		stop:                              make(chan struct{}),
		podInitialBackoffDuration:         options.podInitialBackoffDuration,
		podMaxBackoffDuration:             options.podMaxBackoffDuration,
		podMaxInUnschedulablePodsDuration: options.podMaxInUnschedulablePodsDuration,
		activeQ:                           heap.NewWithRecorder(podInfoKeyFunc, comp, metrics.NewActivePodsRecorder()),
		unschedulablePods:                 newUnschedulablePods(metrics.NewUnschedulablePodsRecorder()),
		moveRequestCycle:                  -1,
		clusterEventMap:                   options.clusterEventMap,
	}
	pq.cond.L = &pq.lock
	pq.podBackoffQ = heap.NewWithRecorder(podInfoKeyFunc, pq.podsCompareBackoffCompleted, metrics.NewBackoffPodsRecorder())
	pq.nsLister = informerFactory.Core().V1().Namespaces().Lister()

	return pq
}

了解了Queue的结构,就需要知道 入队列与出队列是在哪里操作的。在初始化时,需要注册一个 addEventHandlerFuncs 这个时候,会注入三个动作函数,也就是controller中的概念;而在AddFunc中可以看到会入队列。

注入是对 Pod 的informer注入的,注入的函数 addPodToSchedulingQueue 就是入栈

Handler: cache.ResourceEventHandlerFuncs{
    AddFunc:    sched.addPodToSchedulingQueue,
    UpdateFunc: sched.updatePodInSchedulingQueue,
    DeleteFunc: sched.deletePodFromSchedulingQueue,
},

func (sched *Scheduler) addPodToSchedulingQueue(obj interface{}) {
	pod := obj.(*v1.Pod)
	klog.V(3).InfoS("Add event for unscheduled pod", "pod", klog.KObj(pod))
	if err := sched.SchedulingQueue.Add(pod); err != nil {
		utilruntime.HandleError(fmt.Errorf("unable to queue %T: %v", obj, err))
	}
}

而这个 SchedulingQueue 的实现就是 PriorityQueue ,而Add中则对 activeQ进行的操作

func (p *PriorityQueue) Add(pod *v1.Pod) error {
	p.lock.Lock()
	defer p.lock.Unlock()
    // 格式化入栈数据,包含podinfo,里会包含v1.Pod
    // 初始化的时间,创建的时间,以及不能被调度时的记录其plugin的名称
	pInfo := p.newQueuedPodInfo(pod)
    // 入栈
	if err := p.activeQ.Add(pInfo); err != nil {
		klog.ErrorS(err, "Error adding pod to the active queue", "pod", klog.KObj(pod))
		return err
	}
	if p.unschedulablePods.get(pod) != nil {
		klog.ErrorS(nil, "Error: pod is already in the unschedulable queue", "pod", klog.KObj(pod))
		p.unschedulablePods.delete(pod)
	}
	// Delete pod from backoffQ if it is backing off
	if err := p.podBackoffQ.Delete(pInfo); err == nil {
		klog.ErrorS(nil, "Error: pod is already in the podBackoff queue", "pod", klog.KObj(pod))
	}
	metrics.SchedulerQueueIncomingPods.WithLabelValues("active", PodAdd).Inc()
	p.PodNominator.AddNominatedPod(pInfo.PodInfo, nil)
	p.cond.Broadcast()

	return nil
}

在上面看 scheduler 结构时,可以看到有一个 nextPod的,nextPod就是从队列中弹出一个pod,这个在scheduler 时会传入 MakeNextPodFunc 就是这个 nextpod

func MakeNextPodFunc(queue SchedulingQueue) func() *framework.QueuedPodInfo {
	return func() *framework.QueuedPodInfo {
		podInfo, err := queue.Pop()
		if err == nil {
			klog.V(4).InfoS("About to try and schedule pod", "pod", klog.KObj(podInfo.Pod))
			for plugin := range podInfo.UnschedulablePlugins {
				metrics.UnschedulableReason(plugin, podInfo.Pod.Spec.SchedulerName).Dec()
			}
			return podInfo
		}
		klog.ErrorS(err, "Error while retrieving next pod from scheduling queue")
		return nil
	}
}

而这个 queue.Pop() 对应的就是 PriorityQueue 的 Pop() ,在这里会将作为 activeQ 的消费端

func (p *PriorityQueue) Pop() (*framework.QueuedPodInfo, error) {
   p.lock.Lock()
   defer p.lock.Unlock()
   for p.activeQ.Len() == 0 {
      // When the queue is empty, invocation of Pop() is blocked until new item is enqueued.
      // When Close() is called, the p.closed is set and the condition is broadcast,
      // which causes this loop to continue and return from the Pop().
      if p.closed {
         return nil, fmt.Errorf(queueClosed)
      }
      p.cond.Wait()
   }
   obj, err := p.activeQ.Pop()
   if err != nil {
      return nil, err
   }
   pInfo := obj.(*framework.QueuedPodInfo)
   pInfo.Attempts++
   p.schedulingCycle++
   return pInfo, nil
}

在上面入口部分也看到了,scheduleOne 和 scheduler,scheduleOne 就是去消费一个Pod,他会调用 NextPod,NextPod就是在初始化传入的 MakeNextPodFunc ,至此回到对应的 Pop来做消费。

schedulerOne是为一个Pod做调度的流程。

func (sched *Scheduler) scheduleOne(ctx context.Context) {
	podInfo := sched.NextPod()
	// pod could be nil when schedulerQueue is closed
	if podInfo == nil || podInfo.Pod == nil {
		return
	}
	pod := podInfo.Pod
	fwk, err := sched.frameworkForPod(pod)
	if err != nil {
		// This shouldn't happen, because we only accept for scheduling the pods
		// which specify a scheduler name that matches one of the profiles.
		klog.ErrorS(err, "Error occurred")
		return
	}
	if sched.skipPodSchedule(fwk, pod) {
		return
	}
...
调度上下文

image

图1:Pod的调度上下文
Source:https://kubernetes.io/docs/concepts/scheduling-eviction/scheduling-framework

当了解了scheduler结构后,下面分析下调度上下文的过程。看看扩展点是怎么工作的。这个时候又需要提到官网的调度上下文的图。

调度框架 [2]

调度框架 (scheduling framework SF ) 是kubernetes为 scheduler设计的一个pluggable的架构。SF 将scheduler设计为 Plugin 式的 API,API将上一章中提到的一些列调度策略实现为 Plugin

SF 中,定义了一些扩展点 (extension points EP ),而被实现为Plugin的调度程序将被注册在一个或多个 EP 中,换句话来说,在这些 EP 的执行过程中如果注册在多个 EP 中,将会在多个 EP 被调用。

每次调度都分为两个阶段,调度周期(Scheduling Cycel)与绑定周期(Binding Cycle)。

  • SC 表示为,为Pod选择一个节点;SC 是串行运行的。
  • BC 表示为,将 SC 决策结果应用于集群中;BC 可以同时运行。

调度周期与绑定周期结合一起,被称为调度上下文Scheduling Context),下图则是调度上下文的工作流

注:如果决策结果为Pod的调度结果无可用节点,或存在内部错误,则中止 SCBC。Pod将重入队列重试

扩展点 [3]

扩展点(Extension points)是指在调度上下文中的每个可扩展API,通过图提现为[图1]。其中 Filter 相当于 PredicateScoring 相当于 Priority

对于调度阶段会通过以下扩展点:

  • Sort:该插件提供了排序功能,用于对在调度队列中待处理 Pod 进行排序。一次只能启用一个队列排序。

  • preFilter:该插件用于在过滤之前预处理或检查 Pod 或集群的相关信息。这里会终止调度

  • filter:该插件相当于调度上下文中的 Predicates,用于排除不能运行 Pod 的节点。Filter 会按配置的顺序进行调用。如果有一个filter将节点标记位不可用,则将 Pod 标记为不可调度(即不会向下执行)。

  • postFilter:当没有为 pod 找到FN时,该插件会按照配置的顺序进行调用。如果任何postFilter插件将 Pod 标记为schedulable,则不会调用其余插件。即 filter 成功后不会进行这步骤

  • preScore:可用于进行预Score工作(通知性的扩展点)。

  • score:该插件为每个通过 filter 阶段的Node提供打分服务。然后Scheduler将选择具有最高加权分数总和的Node。

  • reserve:因为绑定事件时异步发生的,该插件是为了避免Pod在绑定到节点前时,调度到新的Pod,使节点使用资源超过可用资源情况。如果后续阶段发生错误或失败,将触发 UnReserve 回滚(通知性扩展点)。这也是作为调度周期中最后一个状态,要么成功到 postBind ,要么失败触发 UnReserve

  • permit:该插件可以阻止或延迟 Pod 的绑定,一般情况下这步骤会做三件事:

    • appove :调度器继续绑定过程
    • Deny:如果任何一个Premit拒绝了Pod与节点的绑定,那么将触发 UnReserve ,并重入队列
    • Wait: 如果 Permit 插件返回 Wait,该 Pod 将保留在内部 Wait Pod 列表中,直到被 Appove。如果发生超时,wait 变为 deny ,将Pod放回至调度队列中,并触发 Unreserve 回滚 。
  • preBind:该插件用于在 bind Pod 之前执行所需的前置工作。如,preBind 可能会提供一个网络卷并将其挂载到目标节点上。如果在该步骤中的任意插件返回错误,则Pod 将被 deny 并放置到调度队列中。

  • bind:在所有的 preBind 完成后,该插件将用于将Pod绑定到Node,并按顺序调用绑定该步骤的插件。如果有一个插件处理了这个事件,那么则忽略其余所有插件。

  • postBind:该插件在绑定 Pod 后调用,可用于清理相关资源(通知性的扩展点)。

  • multiPoint:这是一个仅配置字段,允许同时为所有适用的扩展点启用或禁用插件。

scheduler 对于调度上下文在代码中的实现就是 scheduleOne ,下面就是看这个调度上下文

Sort

Sort 插件提供了排序功能,用于对在调度队列中待处理 Pod 进行排序。一次只能启用一个队列排序。

在进入 scheduleOne 后,NextPodactiveQ 中队列中得到一个Pod,然后的 frameworkForPod 会做打分的动作就是调度上下文的第一个扩展点 sort

func (sched *Scheduler) scheduleOne(ctx context.Context) {
	podInfo := sched.NextPod()
	// pod could be nil when schedulerQueue is closed
	if podInfo == nil || podInfo.Pod == nil {
		return
	}
	pod := podInfo.Pod
	fwk, err := sched.frameworkForPod(pod)
...
    
func (sched *Scheduler) frameworkForPod(pod *v1.Pod) (framework.Framework, error) {
    // 获取指定的profile
	fwk, ok := sched.Profiles[pod.Spec.SchedulerName]
	if !ok {
		return nil, fmt.Errorf("profile not found for scheduler name %q", pod.Spec.SchedulerName)
	}
	return fwk, nil
}

回顾,因为在New scheduler时会初始化这个 sort 函数

podQueue := internalqueue.NewSchedulingQueue(
    profiles[options.profiles[0].SchedulerName].QueueSortFunc(),
    informerFactory,
    internalqueue.WithPodInitialBackoffDuration(time.Duration(options.podInitialBackoffSeconds)*time.Second),
    internalqueue.WithPodMaxBackoffDuration(time.Duration(options.podMaxBackoffSeconds)*time.Second),
    internalqueue.WithPodNominator(nominator),
    internalqueue.WithClusterEventMap(clusterEventMap),
    internalqueue.WithPodMaxInUnschedulablePodsDuration(options.podMaxInUnschedulablePodsDuration),
)
preFilter

preFilter作为第一个扩展点,是用于在过滤之前预处理或检查 Pod 或集群的相关信息。这里会终止调度

func (sched *Scheduler) scheduleOne(ctx context.Context) {
	podInfo := sched.NextPod()
	// pod could be nil when schedulerQueue is closed
	if podInfo == nil || podInfo.Pod == nil {
		return
	}
	pod := podInfo.Pod
	fwk, err := sched.frameworkForPod(pod)
	if err != nil {
		// This shouldn't happen, because we only accept for scheduling the pods
		// which specify a scheduler name that matches one of the profiles.
		klog.ErrorS(err, "Error occurred")
		return
	}
	if sched.skipPodSchedule(fwk, pod) {
		return
	}

	klog.V(3).InfoS("Attempting to schedule pod", "pod", klog.KObj(pod))

	// Synchronously attempt to find a fit for the pod.
	start := time.Now()
	state := framework.NewCycleState()
	state.SetRecordPluginMetrics(rand.Intn(100) < pluginMetricsSamplePercent)
	// Initialize an empty podsToActivate struct, which will be filled up by plugins or stay empty.
	podsToActivate := framework.NewPodsToActivate()
	state.Write(framework.PodsToActivateKey, podsToActivate)

	schedulingCycleCtx, cancel := context.WithCancel(ctx)
	defer cancel()
    // 这里将进入prefilter
	scheduleResult, err := sched.SchedulePod(schedulingCycleCtx, fwk, state, pod)

schedulePod 尝试将给定的 pod 调度到节点列表中的节点之一。如果成功,它将返回节点的名称。

func (sched *Scheduler) schedulePod(ctx context.Context, fwk framework.Framework, state *framework.CycleState, pod *v1.Pod) (result ScheduleResult, err error) {
	trace := utiltrace.New("Scheduling", utiltrace.Field{Key: "namespace", Value: pod.Namespace}, utiltrace.Field{Key: "name", Value: pod.Name})
	defer trace.LogIfLong(100 * time.Millisecond)
	// 用于将cache更新为当前内容
	if err := sched.Cache.UpdateSnapshot(sched.nodeInfoSnapshot); err != nil {
		return result, err
	}
	trace.Step("Snapshotting scheduler cache and node infos done")

	if sched.nodeInfoSnapshot.NumNodes() == 0 {
		return result, ErrNoNodesAvailable
	}
	// 找到一个合适的pod时,会执行扩展点
	feasibleNodes, diagnosis, err := sched.findNodesThatFitPod(ctx, fwk, state, pod)
	
    ...

findNodesThatFitPod 会执行对应的过滤插件来找到最适合的Node,包括备注,以及方法名都可以看到,这里运行的插件

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