[源码分析] kube-scheduler源码分析(三)之 scheduleOne

Posted by 胡伟煌 on 2018-10-03

kube-scheduler源码分析(三)之 scheduleOne

以下代码分析基于 kubernetes v1.12.0 版本。

本文主要分析/pkg/scheduler/中调度的基本流程。具体的预选调度逻辑优选调度逻辑节点抢占逻辑待后续再独立分析。

scheduler的pkg代码目录结构如下:

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scheduler
├── algorithm # 主要包含调度的算法
│   ├── predicates # 预选的策略
│   ├── priorities # 优选的策略
│   ├── scheduler_interface.go # ScheduleAlgorithm、SchedulerExtender接口定义
│   ├── types.go # 使用到的type的定义
├── algorithmprovider
│   ├── defaults
│   │   ├── defaults.go # 默认算法的初始化操作,包括预选和优选策略
├── cache # scheduler调度使用到的cache
│   ├── cache.go # schedulerCache
│   ├── interface.go
│   ├── node_info.go
│   ├── node_tree.go
├── core # 调度逻辑的核心代码
│   ├── equivalence
│   │   ├── eqivalence.go # 存储相同pod的调度结果缓存,主要给预选策略使用
│   ├── extender.go
│   ├── generic_scheduler.go # genericScheduler,主要包含默认调度器的调度逻辑
│   ├── scheduling_queue.go # 调度使用到的队列,主要用来存储需要被调度的pod
├── factory
│   ├── factory.go # 主要包括NewConfigFactory、NewPodInformer,监听pod事件来更新调度队列
├── metrics
│   └── metrics.go # 主要给prometheus使用
├── scheduler.go # pkg部分的Run入口(核心代码),主要包含Run、scheduleOne、schedule、preempt等函数
└── volumebinder
└── volume_binder.go # volume bind

1. Scheduler.Run

此部分代码位于pkg/scheduler/scheduler.go

此处为具体调度逻辑的入口。

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// 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
}

go wait.Until(sched.scheduleOne, 0, sched.config.StopEverything)
}

2. Scheduler.scheduleOne

此部分代码位于pkg/scheduler/scheduler.go

scheduleOne主要为单个pod选择一个适合的节点,为调度逻辑的核心函数。

对单个pod进行调度的基本流程如下:

  1. 通过podQueue的待调度队列中弹出需要调度的pod。
  2. 通过具体的调度算法为该pod选出合适的节点,其中调度算法就包括预选和优选两步策略。
  3. 如果上述调度失败,则会尝试抢占机制,将优先级低的pod剔除,让优先级高的pod调度成功。
  4. 将该pod和选定的节点进行假性绑定,存入scheduler cache中,方便具体绑定操作可以异步进行。
  5. 实际执行绑定操作,将node的名字添加到pod的节点相关属性中。

完整代码如下:

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// scheduleOne does the entire scheduling workflow for a single pod.  It is serialized on the scheduling algorithm's host fitting.
func (sched *Scheduler) scheduleOne() {
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)
}
}()
}

以下对重要代码分别进行分析。

3. config.NextPod

通过podQueue的方式存储待调度的pod队列,NextPod拿出下一个需要被调度的pod。

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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)

NextPod的具体函数在factory.go的CreateFromKey函数中定义,如下:

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func (c *configFactory) CreateFromKeys(predicateKeys, priorityKeys sets.String, extenders []algorithm.SchedulerExtender) (*scheduler.Config, error) {
...
return &scheduler.Config{
...
NextPod: func() *v1.Pod {
return c.getNextPod()
}
...
}

3.1. getNextPod

通过一个podQueue来存储需要调度的pod的队列,通过队列Pop的方式弹出需要被调度的pod。

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func (c *configFactory) getNextPod() *v1.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
}

4. Scheduler.schedule

此部分代码位于pkg/scheduler/scheduler.go

此部分为调度逻辑的核心,通过不同的算法为具体的pod选择一个最合适的节点。

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// 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
}

schedule通过调度算法返回一个最优的节点。

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// schedule implements the scheduling algorithm and returns the suggested host.
func (sched *Scheduler) schedule(pod *v1.Pod) (string, error) {
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,
Reason: v1.PodReasonUnschedulable,
Message: err.Error(),
})
return "", err
}
return host, err
}

4.1. ScheduleAlgorithm

ScheduleAlgorithm是一个调度算法的接口,主要的实现体是genericScheduler,后续分析genericScheduler.Schedule

ScheduleAlgorithm接口定义如下:

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// ScheduleAlgorithm is an interface implemented by things that know how to schedule pods
// onto machines.
type ScheduleAlgorithm interface {
Schedule(*v1.Pod, NodeLister) (selectedMachine string, err error)
// Preempt receives scheduling errors for a pod and tries to create room for
// the pod by preempting lower priority pods if possible.
// It returns the node where preemption happened, a list of preempted pods, a
// list of pods whose nominated node name should be removed, and error if any.
Preempt(*v1.Pod, NodeLister, error) (selectedNode *v1.Node, preemptedPods []*v1.Pod, cleanupNominatedPods []*v1.Pod, err error)
// Predicates() returns a pointer to a map of predicate functions. This is
// exposed for testing.
Predicates() map[string]FitPredicate
// Prioritizers returns a slice of priority config. This is exposed for
// testing.
Prioritizers() []PriorityConfig
}

5. genericScheduler.Schedule

此部分代码位于/pkg/scheduler/core/generic_scheduler.go

genericScheduler.Schedule实现了基本的调度逻辑,基于给定需要调度的pod和node列表,如果执行成功返回调度的节点的名字,如果执行失败,则返回错误和原因。主要通过预选和优选两步操作完成调度的逻辑。

基本流程如下:

  1. 对pod做基本性检查,目前主要是对pvc的检查。
  2. 通过findNodesThatFit预选策略选出满足调度条件的node列表。
  3. 通过PrioritizeNodes优选策略给预选的node列表中的node进行打分。
  4. 在打分的node列表中选择一个分数最高的node作为调度的节点。

完整代码如下:

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// 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)

if err := podPassesBasicChecks(pod, g.pvcLister); err != nil {
return "", err
}

nodes, err := nodeLister.List()
if err != nil {
return "", err
}
if len(nodes) == 0 {
return "", ErrNoNodesAvailable
}

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

trace.Step("Computing predicates")
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,
}
}
metrics.SchedulingAlgorithmPredicateEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPredicateEvalTime))
metrics.SchedulingLatency.WithLabelValues(metrics.PredicateEvaluation).Observe(metrics.SinceInSeconds(startPredicateEvalTime))

trace.Step("Prioritizing")
startPriorityEvalTime := time.Now()
// When only one node after predicate, just use it.
if len(filteredNodes) == 1 {
metrics.SchedulingAlgorithmPriorityEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPriorityEvalTime))
return filteredNodes[0].Name, nil
}

metaPrioritiesInterface := g.priorityMetaProducer(pod, g.cachedNodeInfoMap)
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")
return g.selectHost(priorityList)
}

5.1. podPassesBasicChecks

podPassesBasicChecks主要做一下基本性检查,目前主要是对pvc的检查。

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if err := podPassesBasicChecks(pod, g.pvcLister); err != nil {
return "", err
}

podPassesBasicChecks具体实现如下:

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// podPassesBasicChecks makes sanity checks on the pod if it can be scheduled.
func podPassesBasicChecks(pod *v1.Pod, pvcLister corelisters.PersistentVolumeClaimLister) error {
// Check PVCs used by the pod
namespace := pod.Namespace
manifest := &(pod.Spec)
for i := range manifest.Volumes {
volume := &manifest.Volumes[i]
if volume.PersistentVolumeClaim == nil {
// Volume is not a PVC, ignore
continue
}
pvcName := volume.PersistentVolumeClaim.ClaimName
pvc, err := pvcLister.PersistentVolumeClaims(namespace).Get(pvcName)
if err != nil {
// The error has already enough context ("persistentvolumeclaim "myclaim" not found")
return err
}

if pvc.DeletionTimestamp != nil {
return fmt.Errorf("persistentvolumeclaim %q is being deleted", pvc.Name)
}
}

return nil
}

5.2. findNodesThatFit

预选,通过预选函数来判断每个节点是否适合被该Pod调度。

具体的findNodesThatFit代码实现细节待后续文章独立分析。

genericScheduler.Schedule中对findNodesThatFit的调用过程如下:

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trace.Step("Computing predicates")
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,
}
}
metrics.SchedulingAlgorithmPredicateEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPredicateEvalTime))
metrics.SchedulingLatency.WithLabelValues(metrics.PredicateEvaluation).Observe(metrics.SinceInSeconds(startPredicateEvalTime))

5.3. PrioritizeNodes

优选,从满足的节点中选择出最优的节点。

具体操作如下:

  • PrioritizeNodes通过并行运行各个优先级函数来对节点进行优先级排序。
  • 每个优先级函数会给节点打分,打分范围为0-10分。
  • 0 表示优先级最低的节点,10表示优先级最高的节点。
  • 每个优先级函数也有各自的权重。
  • 优先级函数返回的节点分数乘以权重以获得加权分数。
  • 最后组合(添加)所有分数以获得所有节点的总加权分数。

具体PrioritizeNodes的实现逻辑待后续文章独立分析。

genericScheduler.Schedule中对PrioritizeNodes的调用过程如下:

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trace.Step("Prioritizing")
startPriorityEvalTime := time.Now()
// When only one node after predicate, just use it.
if len(filteredNodes) == 1 {
metrics.SchedulingAlgorithmPriorityEvaluationDuration.Observe(metrics.SinceInMicroseconds(startPriorityEvalTime))
return filteredNodes[0].Name, nil
}
metaPrioritiesInterface := g.priorityMetaProducer(pod, g.cachedNodeInfoMap)
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))

5.4. selectHost

scheduler在最后会从priorityList中选择分数最高的一个节点。

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trace.Step("Selecting host")
return g.selectHost(priorityList)

selectHost获取优先级的节点列表,然后从分数最高的节点以循环方式选择一个节点。

具体代码如下:

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// 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")
}

maxScores := findMaxScores(priorityList)
ix := int(g.lastNodeIndex % uint64(len(maxScores)))
g.lastNodeIndex++

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

5.4.1. findMaxScores

findMaxScores返回priorityList中具有最高Score的节点的索引。

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// 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
maxScoreIndexes = maxScoreIndexes[:0]
maxScoreIndexes = append(maxScoreIndexes, i)
} else if hp.Score == maxScore {
maxScoreIndexes = append(maxScoreIndexes, i)
}
}
return maxScoreIndexes
}

6. Scheduler.preempt

如果pod在预选和优选调度中失败,则执行抢占操作。抢占主要是将低优先级的pod的资源空间腾出给待调度的高优先级的pod。

具体Scheduler.preempt的实现逻辑待后续文章独立分析。

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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
}

7. Scheduler.assume

将该pod和选定的节点进行假性绑定,存入scheduler cache中,方便可以继续执行调度逻辑,而不需要等待绑定操作的发生,具体绑定操作可以异步进行。

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// 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
}

如果假性绑定成功则发送请求给apiserver,如果失败则scheduler会立即释放已分配给假性绑定的pod的资源。

assume方法的具体实现:

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// assume signals to the cache that a pod is already in the cache, so that binding can be asynchronous.
// assume modifies `assumed`.
func (sched *Scheduler) assume(assumed *v1.Pod, host string) error {
// Optimistically assume that the binding will succeed and send it to apiserver
// in the background.
// If the binding fails, scheduler will release resources allocated to assumed pod
// immediately.
assumed.Spec.NodeName = host
// NOTE: Because the scheduler uses snapshots of SchedulerCache and the live
// version of Ecache, updates must be written to SchedulerCache before
// invalidating Ecache.
if err := sched.config.SchedulerCache.AssumePod(assumed); err != nil {
glog.Errorf("scheduler cache AssumePod failed: %v", err)

// This is most probably result of a BUG in retrying logic.
// We report an error here so that pod scheduling can be retried.
// This relies on the fact that Error will check if the pod has been bound
// to a node and if so will not add it back to the unscheduled pods queue
// (otherwise this would cause an infinite loop).
sched.config.Error(assumed, err)
sched.config.Recorder.Eventf(assumed, v1.EventTypeWarning, "FailedScheduling", "AssumePod failed: %v", err)
sched.config.PodConditionUpdater.Update(assumed, &v1.PodCondition{
Type: v1.PodScheduled,
Status: v1.ConditionFalse,
Reason: "SchedulerError",
Message: err.Error(),
})
return err
}

// Optimistically assume that the binding will succeed, so we need to invalidate affected
// predicates in equivalence cache.
// If the binding fails, these invalidated item will not break anything.
if sched.config.Ecache != nil {
sched.config.Ecache.InvalidateCachedPredicateItemForPodAdd(assumed, host)
}
return nil
}

8. Scheduler.bind

异步的方式给pod绑定到具体的调度节点上。

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// 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)
}
}()

bind具体实现如下:

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// 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.
err := sched.config.GetBinder(assumed).Bind(b)
if err := sched.config.SchedulerCache.FinishBinding(assumed); err != nil {
glog.Errorf("scheduler cache FinishBinding failed: %v", err)
}
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,
Reason: "BindingRejected",
})
return err
}

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
}

9. 总结

本文主要分析了单个pod的调度过程。具体流程如下:

  1. 通过podQueue的待调度队列中弹出需要调度的pod。
  2. 通过具体的调度算法为该pod选出合适的节点,其中调度算法就包括预选和优选两步策略。
  3. 如果上述调度失败,则会尝试抢占机制,将优先级低的pod剔除,让优先级高的pod调度成功。
  4. 将该pod和选定的节点进行假性绑定,存入scheduler cache中,方便具体绑定操作可以异步进行。
  5. 实际执行绑定操作,将node的名字添加到pod的节点相关属性中。

其中核心的部分为通过具体的调度算法选出调度节点的过程,即genericScheduler.Schedule的实现部分。该部分包括预选和优选两个部分。

genericScheduler.Schedule调度的基本流程如下:

  1. 对pod做基本性检查,目前主要是对pvc的检查。
  2. 通过findNodesThatFit预选策略选出满足调度条件的node列表。
  3. 通过PrioritizeNodes优选策略给预选的node列表中的node进行打分。
  4. 在打分的node列表中选择一个分数最高的node作为调度的节点。

参考:



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