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# 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)
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podlabels.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。