Kubernetes Job Controller源码分析

摘要: 对于一般用户，学习和使用Job，官方文档就足够了，但如果你是个变态，那你总会去想，Job Controller和Deployment Controller在管理Pod上，除了RestartPolicy等不同外，还有哪些不同呢？其实是因为最近在搞TensorFlow on Kubernetes项目，想通过Job映射分布式TensorFlow中的worker task，达到训练完数据，自动回收资源资源等目的。本博文通过Job Controller代码分析其内部主要流程。

Author: xidianwangtao@gmail.com

实现流程图

废话不多说，先把完整流程贴出来。

New JobController

type JobController struct {
kubeClient clientset.Interface
podControl controller.PodControlInterface

// To allow injection of updateJobStatus for testing.
updateHandler func(job *batch.Job) error
syncHandler   func(jobKey string) (bool, error)
// podStoreSynced returns true if the pod store has been synced at least once.
// Added as a member to the struct to allow injection for testing.
podStoreSynced cache.InformerSynced
// jobStoreSynced returns true if the job store has been synced at least once.
// Added as a member to the struct to allow injection for testing.
jobStoreSynced cache.InformerSynced

// A TTLCache of pod creates/deletes each rc expects to see
expectations controller.ControllerExpectationsInterface

// A store of jobs
jobLister batchv1listers.JobLister

// A store of pods, populated by the podController
podStore corelisters.PodLister

// Jobs that need to be updated
queue workqueue.RateLimitingInterface

recorder record.EventRecorder
}

func NewJobController(podInformer coreinformers.PodInformer, jobInformer batchinformers.JobInformer, kubeClient clientset.Interface) *JobController {
eventBroadcaster := record.NewBroadcaster()
eventBroadcaster.StartLogging(glog.Infof)
// TODO: remove the wrapper when every clients have moved to use the clientset.
eventBroadcaster.StartRecordingToSink(&v1core.EventSinkImpl{Interface: v1core.New(kubeClient.CoreV1().RESTClient()).Events("")})

if kubeClient != nil && kubeClient.CoreV1().RESTClient().GetRateLimiter() != nil {
metrics.RegisterMetricAndTrackRateLimiterUsage("job_controller", kubeClient.CoreV1().RESTClient().GetRateLimiter())
}

jm := &JobController{
kubeClient: kubeClient,
podControl: controller.RealPodControl{
KubeClient: kubeClient,
Recorder:   eventBroadcaster.NewRecorder(scheme.Scheme, v1.EventSource{Component: "job-controller"}),
},
expectations: controller.NewControllerExpectations(),
queue:        workqueue.NewNamedRateLimitingQueue(workqueue.NewItemExponentialFailureRateLimiter(DefaultJobBackOff, MaxJobBackOff), "job"),
recorder:     eventBroadcaster.NewRecorder(scheme.Scheme, v1.EventSource{Component: "job-controller"}),
}

jobInformer.Informer().AddEventHandler(cache.ResourceEventHandlerFuncs{
AddFunc:    jm.enqueueController,
UpdateFunc: jm.updateJob,
DeleteFunc: jm.enqueueController,
})
jm.jobLister = jobInformer.Lister()
jm.jobStoreSynced = jobInformer.Informer().HasSynced

podInformer.Informer().AddEventHandler(cache.ResourceEventHandlerFuncs{
AddFunc:    jm.addPod,
UpdateFunc: jm.updatePod,
DeleteFunc: jm.deletePod,
})
jm.podStore = podInformer.Lister()
jm.podStoreSynced = podInformer.Informer().HasSynced

jm.updateHandler = jm.updateJobStatus
jm.syncHandler = jm.syncJob

return jm
}

构造JobController，并初始化相关数据，比如rate limiter queue;

watch pod and job object;

注册podInformer的add/del/update EventHandler；

注册jobInformer的add/del/update EventHandler;

注册updataHandler为updateJobStatus，用来更新Job状态；

注册syncHandler为syncJob，用来进行处理queue中的Job；

JobController Run

// Run the main goroutine responsible for watching and syncing jobs.
func (jm *JobController) Run(workers int, stopCh <-chan struct{}) {
defer utilruntime.HandleCrash()
defer jm.queue.ShutDown()

glog.Infof("Starting job controller")
defer glog.Infof("Shutting down job controller")

if !controller.WaitForCacheSync("job", stopCh, jm.podStoreSynced, jm.jobStoreSynced) {
return
}

for i := 0; i < workers; i++ {
go wait.Until(jm.worker, time.Second, stopCh)
}

<-stopCh
}

// worker runs a worker thread that just dequeues items, processes them, and marks them done.
// It enforces that the syncHandler is never invoked concurrently with the same key.
func (jm *JobController) worker() {
for jm.processNextWorkItem() {
}
}

func (jm *JobController) processNextWorkItem() bool {
key, quit := jm.queue.Get()
if quit {
return false
}
defer jm.queue.Done(key)

forget, err := jm.syncHandler(key.(string))
if err == nil {
if forget {
jm.queue.Forget(key)
}
return true
}

utilruntime.HandleError(fmt.Errorf("Error syncing job: %v", err))
jm.queue.AddRateLimited(key)

return true
}

WaitForCacheSync等待jobController cache同步；

启动5个goruntine，每个协程分别执行worker，每个worker执行完后等待1s，继续执行，如此循环；

worker负责从从queue中get job key，对每个job，调用syncJob进行同步，如果syncJob成功，则forget the job（其实就是让rate limiter 停止tracking it），否则将该key再次加入到queue中，等待下次sync。

syncJob

// syncJob will sync the job 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 (jm *JobController) syncJob(key string) (bool, error) {
startTime := time.Now()
defer func() {
glog.V(4).Infof("Finished syncing job %q (%v)", key, time.Now().Sub(startTime))
}()

ns, name, err := cache.SplitMetaNamespaceKey(key)
if err != nil {
return false, err
}
if len(ns) == 0 || len(name) == 0 {
return false, fmt.Errorf("invalid job key %q: either namespace or name is missing", key)
}
sharedJob, err := jm.jobLister.Jobs(ns).Get(name)
if err != nil {
if errors.IsNotFound(err) {
glog.V(4).Infof("Job has been deleted: %v", key)
jm.expectations.DeleteExpectations(key)
return true, nil
}
return false, err
}
job := *sharedJob

// if job was finished previously, we don't want to redo the termination
if IsJobFinished(&job) {
return true, nil
}

// retrieve the previous number of retry
previousRetry := jm.queue.NumRequeues(key)

// Check the expectations of the job before counting active pods, otherwise a new pod can sneak in
// and update the expectations after we've retrieved active pods from the store. If a new pod enters
// the store after we've checked the expectation, the job sync is just deferred till the next relist.
jobNeedsSync := jm.expectations.SatisfiedExpectations(key)

pods, err := jm.getPodsForJob(&job)
if err != nil {
return false, err
}

activePods := controller.FilterActivePods(pods)
active := int32(len(activePods))
succeeded, failed := getStatus(pods)
conditions := len(job.Status.Conditions)
// job first start
if job.Status.StartTime == nil {
now := metav1.Now()
job.Status.StartTime = &now
// enqueue a sync to check if job past ActiveDeadlineSeconds
if job.Spec.ActiveDeadlineSeconds != nil {
glog.V(4).Infof("Job %s have ActiveDeadlineSeconds will sync after %d seconds",
key, *job.Spec.ActiveDeadlineSeconds)
jm.queue.AddAfter(key, time.Duration(*job.Spec.ActiveDeadlineSeconds)*time.Second)
}
}

var manageJobErr error
jobFailed := false
var failureReason string
var failureMessage string

jobHaveNewFailure := failed > job.Status.Failed

// check if the number of failed jobs increased since the last syncJob
if jobHaveNewFailure && (int32(previousRetry)+1 > *job.Spec.BackoffLimit) {
jobFailed = true
failureReason = "BackoffLimitExceeded"
failureMessage = "Job has reach the specified backoff limit"
} else if pastActiveDeadline(&job) {
jobFailed = true
failureReason = "DeadlineExceeded"
failureMessage = "Job was active longer than specified deadline"
}

if jobFailed {
errCh := make(chan error, active)
jm.deleteJobPods(&job, activePods, errCh)
select {
case manageJobErr = <-errCh:
if manageJobErr != nil {
break
}
default:
}

// update status values accordingly
failed += active
active = 0
job.Status.Conditions = append(job.Status.Conditions, newCondition(batch.JobFailed, failureReason, failureMessage))
jm.recorder.Event(&job, v1.EventTypeWarning, failureReason, failureMessage)
} else {
if jobNeedsSync && job.DeletionTimestamp == nil {
active, manageJobErr = jm.manageJob(activePods, succeeded, &job)
}
completions := succeeded
complete := false
if job.Spec.Completions == nil {
// This type of job is complete when any pod exits with success.
// Each pod is capable of
// determining whether or not the entire Job is done.  Subsequent pods are
// not expected to fail, but if they do, the failure is ignored.  Once any
// pod succeeds, the controller waits for remaining pods to finish, and
// then the job is complete.
if succeeded > 0 && active == 0 {
complete = true
}
} else {
// Job specifies a number of completions.  This type of job signals
// success by having that number of successes.  Since we do not
// start more pods than there are remaining completions, there should
// not be any remaining active pods once this count is reached.
if completions >= *job.Spec.Completions {
complete = true
if active > 0 {
jm.recorder.Event(&job, v1.EventTypeWarning, "TooManyActivePods", "Too many active pods running after completion count reached")
}
if completions > *job.Spec.Completions {
jm.recorder.Event(&job, v1.EventTypeWarning, "TooManySucceededPods", "Too many succeeded pods running after completion count reached")
}
}
}
if complete {
job.Status.Conditions = append(job.Status.Conditions, newCondition(batch.JobComplete, "", ""))
now := metav1.Now()
job.Status.CompletionTime = &now
}
}

forget := false
// no need to update the job if the status hasn't changed since last time
if job.Status.Active != active || job.Status.Succeeded != succeeded || job.Status.Failed != failed || len(job.Status.Conditions) != conditions {
job.Status.Active = active
job.Status.Succeeded = succeeded
job.Status.Failed = failed

if err := jm.updateHandler(&job); err != nil {
return false, err
}

if jobHaveNewFailure && !IsJobFinished(&job) {
// returning an error will re-enqueue Job after the backoff period
return false, fmt.Errorf("failed pod(s) detected for job key %q", key)
}

forget = true
}

return forget, manageJobErr
}

从Indexer中查找指定的Job是否存在，如果不存在，则从expectations中删除该job，流程结束返回true。否则继续下面流程。

根据JobCondition Complete or Failed判断Job是否Finished，如果Finished，则流程结束返回true，否则继续下面流程。

调用SatisfiedExpectations，如果ControlleeExpectations中待add和del都<=0，或者expectations已经超过5分钟没更新过了，则返回jobNeedsSync=true，表示需要进行一次manageJob了。

对于那些第一次启动的jobs (StartTime==nil), 需要把设置StartTime，并且如果ActiveDeadlineSeconds不为空，则经过ActiveDeadlineSeconds后再次把该job加入到queue中进行sync。

获取该job管理的所有pods，过滤出activePods，计算出actived,successed,failed pods的数量。如果failed > job.Status.Failed，说明该job又有新failed Pods了，则jobHaveNewFailure为true。

如果jobHaveNewFailure，并且queue记录的该job retry次数加1，比job.Spec.BackoffLimit(默认为6)，则表示该job BackoffLimitExceeded，jobFailed。如果job StartTime到现在为止的历时>=ActiveDeadlineSeconds，则表示该job DeadlineExceeded，jobFailed。

如果jobFailed，则用sync.WaitGroup并发等待删除所有的前面过滤出来的activePods，删除成功，则failed += acitve, active = 0, 并设置Condition Failed为true。

如果job not failed, jobNeedSync为true，并且job的DeletionTimestamp为空（没有标记为删除），则调用manageJob对Job管理的pods根据复杂的策略进行add or del。

如果job not failed且job.Spec.Completions为nil，表示This type of job is complete when any pod exits with success。因此如果succeeded > 0 && active == 0，则表示job completed。

如果如果job not failed且job.Spec.Completions不为nil，表示This type of job signals success by having that number of successes。因此如果succeeded >= job.Spec.Completions，则表示job completed。

如果job completed，则更新其Conditions Complete为true，并设置CompletionTime。

接下来invoke updateJobStatus更新etcd中job状态，如果更新失败，则返回false，该job将再次加入queue。如果jobHaveNewFailure为true，并且Job Condition显示该Job not Finished，则返回false，该job将再次加入queue。

manageJob

// manageJob is the core method responsible for managing the number of running
// pods according to what is specified in the job.Spec.
// Does NOT modify <activePods>.
func (jm *JobController) manageJob(activePods []*v1.Pod, succeeded int32, job *batch.Job) (int32, error) {
var activeLock sync.Mutex
active := int32(len(activePods))
parallelism := *job.Spec.Parallelism
jobKey, err := controller.KeyFunc(job)
if err != nil {
utilruntime.HandleError(fmt.Errorf("Couldn't get key for job %#v: %v", job, err))
return 0, nil
}

var errCh chan error
if active > parallelism {
diff := active - parallelism
errCh = make(chan error, diff)
jm.expectations.ExpectDeletions(jobKey, int(diff))
glog.V(4).Infof("Too many pods running job %q, need %d, deleting %d", jobKey, parallelism, diff)
// Sort the pods in the order such that not-ready < ready, unscheduled
// < scheduled, and pending < running. This ensures that we delete pods
// in the earlier stages whenever possible.
sort.Sort(controller.ActivePods(activePods))

active -= diff
wait := sync.WaitGroup{}
wait.Add(int(diff))
for i := int32(0); i < diff; i++ {
go func(ix int32) {
defer wait.Done()
if err := jm.podControl.DeletePod(job.Namespace, activePods[ix].Name, job); err != nil {
defer utilruntime.HandleError(err)
// Decrement the expected number of deletes because the informer won't observe this deletion
glog.V(2).Infof("Failed to delete %v, decrementing expectations for job %q/%q", activePods[ix].Name, job.Namespace, job.Name)
jm.expectations.DeletionObserved(jobKey)
activeLock.Lock()
active++
activeLock.Unlock()
errCh <- err
}
}(i)
}
wait.Wait()

} else if active < parallelism {
wantActive := int32(0)
if job.Spec.Completions == nil {
// Job does not specify a number of completions.  Therefore, number active
// should be equal to parallelism, unless the job has seen at least
// once success, in which leave whatever is running, running.
if succeeded > 0 {
wantActive = active
} else {
wantActive = parallelism
}
} else {
// Job specifies a specific number of completions.  Therefore, number
// active should not ever exceed number of remaining completions.
wantActive = *job.Spec.Completions - succeeded
if wantActive > parallelism {
wantActive = parallelism
}
}
diff := wantActive - active
if diff < 0 {
utilruntime.HandleError(fmt.Errorf("More active than wanted: job %q, want %d, have %d", jobKey, wantActive, active))
diff = 0
}
jm.expectations.ExpectCreations(jobKey, int(diff))
errCh = make(chan error, diff)
glog.V(4).Infof("Too few pods running job %q, need %d, creating %d", jobKey, wantActive, diff)

active += diff
wait := sync.WaitGroup{}

// Batch the pod creates. Batch sizes start at SlowStartInitialBatchSize
// and double with each successful iteration in a kind of "slow start".
// This handles attempts to start large numbers of pods that would
// likely all fail with the same error. For example a project with a
// low quota that attempts to create a large number of pods will be
// prevented from spamming the API service with the pod create requests
// after one of its pods fails.  Conveniently, this also prevents the
// event spam that those failures would generate.
for batchSize := int32(integer.IntMin(int(diff), controller.SlowStartInitialBatchSize)); diff > 0; batchSize = integer.Int32Min(2*batchSize, diff) {
errorCount := len(errCh)
wait.Add(int(batchSize))
for i := int32(0); i < batchSize; i++ {
go func() {
defer wait.Done()
err := jm.podControl.CreatePodsWithControllerRef(job.Namespace, &job.Spec.Template, job, metav1.NewControllerRef(job, controllerKind))
if err != nil && errors.IsTimeout(err) {
// Pod is created but its initialization has timed out.
// If the initialization is successful eventually, the
// controller will observe the creation via the informer.
// If the initialization fails, or if the pod keeps
// uninitialized for a long time, the informer will not
// receive any update, and the controller will create a new
// pod when the expectation expires.
return
}
if err != nil {
defer utilruntime.HandleError(err)
// Decrement the expected number of creates because the informer won't observe this pod
glog.V(2).Infof("Failed creation, decrementing expectations for job %q/%q", job.Namespace, job.Name)
jm.expectations.CreationObserved(jobKey)
activeLock.Lock()
active--
activeLock.Unlock()
errCh <- err
}
}()
}
wait.Wait()
// any skipped pods that we never attempted to start shouldn't be expected.
skippedPods := diff - batchSize
if errorCount < len(errCh) && skippedPods > 0 {
glog.V(2).Infof("Slow-start failure. Skipping creation of %d pods, decrementing expectations for job %q/%q", skippedPods, job.Namespace, job.Name)
active -= skippedPods
for i := int32(0); i < skippedPods; i++ {
// Decrement the expected number of creates because the informer won't observe this pod
jm.expectations.CreationObserved(jobKey)
}
// The skipped pods will be retried later. The next controller resync will
// retry the slow start process.
break
}
diff -= batchSize
}
}

select {
case err := <-errCh:
// all errors have been reported before, we only need to inform the controller that there was an error and it should re-try this job once more next time.
if err != nil {
return active, err
}
default:
}

return active, nil
}

如果active > job.Spec.Parallelism, 表示要scale down：

计算active与parallelism的差值diff，修改ControllerExpectations中该job的dels为diff，表示要删除diff这么多的pod。

计算active与parallelism的差值diff，修改ControllerExpectations中该job的dels为diff，表示要删除diff这么多的pod。

将activePods中的Pods按照not-ready < ready, unscheduled < scheduled, pending < running进行排序，确保先删除stage越早的pods。

更新active (active减去diff），用sync.WaitGroup并发等待删除etcd中那些Pods。如果删除某个Pod失败，active要加1，expectations中dels要减1.

返回active

如果active < job.Spec.Parallelism，
表示要scale up：

如果job.Spec.Completions为nil，且succeeded大于0，则diff设为0；如果job.Spec.Completions为nil，但successed = 0，则diff为 parallelism-active；如果job.Spec.Completions不为nil，则diff为max(job.Spec.Completions - succeeded，parallelim) - active；

修改ControllerExpectations中该job的adds为diff，表示要新增diff这么多的pod。

更新active (active加上diff），用sync.WaitGroup分批的创建Pods，第一批创建1个(代码写死SlowStartInitialBatchSize = 1)，第二批创建2，然后4,8,16...这样下去，但是每次不能超过diff的值。每一批创建pod后，注意更新diff的值（减去batchsize）。如果某一批创建过程Pods中存在失败情况，则更新active和expectations中adds，且不进行后续未启动的批量创建pods行为。

如果active == job.Spec.Parallelism，返回active。

总结

关于Job工作原理及配置，请直接阅读官方文档 jobs run to completion,那里有关于job配置

.spec.completions

,

.spec.parallelism

,

spec.activeDeadlineSeconds

的使用说明，但是并没有把真正内部怎么工作的讲清楚，本博文就是希望能把这些东西讲清楚。