浅析kubernetes中client

之前了解了client-go中的架构设计，也就是 tools/cache 下面的一些概念，那么下面将对informer进行分析

Controller

在client-go informer架构中存在一个 controller ，这个不是 Kubernetes 中的Controller组件；而是在 tools/cache 中的一个概念，controller 位于 informer 之下，Reflector 之上。code

Config

从严格意义上来讲，controller 是作为一个 sharedInformer 使用，通过接受一个 Config ，而 Reflector 则作为 controller 的 slot。Config 则包含了这个 controller 里所有的设置。

type Config struct {  Queue // DeltaFIFO  ListerWatcher // 用于list watch的  Process ProcessFunc // 定义如何从DeltaFIFO中弹出数据后处理的操作  ObjectType runtime.Object // Controller处理的对象数据，实际上就是kubernetes中的资源  FullResyncPeriod time.Duration // 全量同步的周期  ShouldResync ShouldResyncFunc // Reflector通过该标记来确定是否应该重新同步  RetryOnError bool } 

controller

然后 controller 又为 reflertor 的上层

type controller struct {  config         Config  reflector      *Reflector   reflectorMutex sync.RWMutex  clock          clock.Clock }  type Controller interface {  // controller 主要做两件事，     // 1. 构建并运行 Reflector,将listerwacther中的泵压到queue（Delta fifo）中     // 2. Queue用Pop()弹出数据，具体的操作是Process     // 直到 stopCh 不阻塞，这两个协程将退出  Run(stopCh <-chan struct{})  HasSynced() bool // 这个实际上是从store中继承的，标记这个controller已经  LastSyncResourceVersion() string } 

controller 中的方法，仅有一个 Run() 和 New()；这意味着，controller 只是一个抽象的概念，作为 Reflector, Delta FIFO 整合的工作流

而 controller 则是 SharedInformer 了。

Queue

这里的 queue 可以理解为是一个具有 Pop() 功能的 Indexer ;而 Pop() 的功能则是 controller 中的一部分；也就是说 queue 是一个扩展的 Store ， Store 是不具备弹出功能的。

type Queue interface {  Store  // Pop会阻塞等待，直到有内容弹出，删除对应的值并处理计数器  Pop(PopProcessFunc) (interface{}, error)   // AddIfNotPresent puts the given accumulator into the Queue (in  // association with the accumulator's key) if and only if that key  // is not already associated with a non-empty accumulator.  AddIfNotPresent(interface{}) error   // HasSynced returns true if the first batch of keys have all been  // popped.  The first batch of keys are those of the first Replace  // operation if that happened before any Add, Update, or Delete;  // otherwise the first batch is empty.  HasSynced() bool  Close() // 关闭queue } 

而弹出的操作是通过 controller 中的 processLoop() 进行的，最终走到Delta FIFO中进行处理。

通过忙等待去读取要弹出的数据，然后在弹出前 通过PopProcessFunc 进行处理

func (c *controller) processLoop() {  for {   obj, err := c.config.Queue.Pop(PopProcessFunc(c.config.Process))   if err != nil {    if err == ErrFIFOClosed {     return    }    if c.config.RetryOnError {     // This is the safe way to re-enqueue.     c.config.Queue.AddIfNotPresent(obj)    }   }  } } 

DeltaFIFO.Pop()

func (f *DeltaFIFO) Pop(process PopProcessFunc) (interface{}, error) {  f.lock.Lock()  defer f.lock.Unlock()  for {   for len(f.queue) == 0 {    // When the queue is empty, invocation of Pop() is blocked until new item is enqueued.    // When Close() is called, the f.closed is set and the condition is broadcasted.    // Which causes this loop to continue and return from the Pop().    if f.IsClosed() {     return nil, ErrFIFOClosed    }     f.cond.Wait()   }   id := f.queue[0]   f.queue = f.queue[1:]   if f.initialPopulationCount > 0 {    f.initialPopulationCount--   }   item, ok := f.items[id]   if !ok {    // Item may have been deleted subsequently.    continue   }   delete(f.items, id)   err := process(item) // 进行处理   if e, ok := err.(ErrRequeue); ok {    f.addIfNotPresent(id, item) // 如果失败，再重新加入到队列中    err = e.Err    }   // Don't need to copyDeltas here, because we're transferring   // ownership to the caller.   return item, err  } } 

Informer

通过对 Reflector, Store, Queue, ListerWatcher、ProcessFunc, 等的概念，发现由 controller 所包装的起的功能并不能完成通过对API的动作监听，并通过动作来处理本地缓存的一个能力；这个情况下诞生了 informer 严格意义上来讲是 sharedInformer

func newInformer(  lw ListerWatcher,  objType runtime.Object,  resyncPeriod time.Duration,  h ResourceEventHandler,  clientState Store, ) Controller {  // This will hold incoming changes. Note how we pass clientState in as a  // KeyLister, that way resync operations will result in the correct set  // of update/delete deltas.  fifo := NewDeltaFIFOWithOptions(DeltaFIFOOptions{   KnownObjects:          clientState,   EmitDeltaTypeReplaced: true,  })   cfg := &Config{   Queue:            fifo,   ListerWatcher:    lw,   ObjectType:       objType,   FullResyncPeriod: resyncPeriod,   RetryOnError:     false,    Process: func(obj interface{}) error {    // from oldest to newest    for _, d := range obj.(Deltas) {     switch d.Type {     case Sync, Replaced, Added, Updated:      if old, exists, err := clientState.Get(d.Object); err == nil && exists {       if err := clientState.Update(d.Object); err != nil {        return err       }       h.OnUpdate(old, d.Object)      } else {       if err := clientState.Add(d.Object); err != nil {        return err       }       h.OnAdd(d.Object)      }     case Deleted:      if err := clientState.Delete(d.Object); err != nil {       return err      }      h.OnDelete(d.Object)     }    }    return nil   },  }  return New(cfg) } 

newInformer是位于 tools/cache/controller.go 下，可以看出，这里面并没有informer的概念，这里通过注释可以看到，newInformer实际上是一个提供了存储和事件通知的informer。他关联的 queue 则是 Delta FIFO，并包含了 ProcessFunc, Store 等 controller的概念。最终对外的方法为 NewInformer()

func NewInformer(  lw ListerWatcher,  objType runtime.Object,  resyncPeriod time.Duration,  h ResourceEventHandler, ) (Store, Controller) {  // This will hold the client state, as we know it.  clientState := NewStore(DeletionHandlingMetaNamespaceKeyFunc)   return clientState, newInformer(lw, objType, resyncPeriod, h, clientState) }  type ResourceEventHandler interface {  OnAdd(obj interface{})  OnUpdate(oldObj, newObj interface{})  OnDelete(obj interface{}) } 

可以看到 NewInformer() 就是一个带有 Store功能的controller，通过这些可以假定出，Informer 就是controller ，将queue中相关操作分发给不同事件处理的功能

SharedIndexInformer

shareInformer 为客户端提供了与apiserver一致的数据对象本地缓存，并支持多事件处理程序的informer，而 shareIndexInformer 则是对shareInformer 的扩展

type SharedInformer interface {  // AddEventHandler adds an event handler to the shared informer using the shared informer's resync  // period.  Events to a single handler are delivered sequentially, but there is no coordination  // between different handlers.  AddEventHandler(handler ResourceEventHandler)  // AddEventHandlerWithResyncPeriod adds an event handler to the  // shared informer with the requested resync period; zero means  // this handler does not care about resyncs.  The resync operation  // consists of delivering to the handler an update notification  // for every object in the informer's local cache; it does not add  // any interactions with the authoritative storage.  Some  // informers do no resyncs at all, not even for handlers added  // with a non-zero resyncPeriod.  For an informer that does  // resyncs, and for each handler that requests resyncs, that  // informer develops a nominal resync period that is no shorter  // than the requested period but may be longer.  The actual time  // between any two resyncs may be longer than the nominal period  // because the implementation takes time to do work and there may  // be competing load and scheduling noise.  AddEventHandlerWithResyncPeriod(handler ResourceEventHandler, resyncPeriod time.Duration)  // GetStore returns the informer's local cache as a Store.  GetStore() Store  // GetController is deprecated, it does nothing useful  GetController() Controller  // Run starts and runs the shared informer, returning after it stops.  // The informer will be stopped when stopCh is closed.  Run(stopCh <-chan struct{})  // HasSynced returns true if the shared informer's store has been  // informed by at least one full LIST of the authoritative state  // of the informer's object collection.  This is unrelated to "resync".  HasSynced() bool  // LastSyncResourceVersion is the resource version observed when last synced with the underlying  // store. The value returned is not synchronized with access to the underlying store and is not  // thread-safe.  LastSyncResourceVersion() string } 

SharedIndexInformer 是对SharedInformer的实现，可以从结构中看出，SharedIndexInformer 大致具有如下功能：

• 索引本地缓存
• controller，通过list watch拉取API并推入 Deltal FIFO
• 事件的处理

type sharedIndexInformer struct {  indexer    Indexer // 具有索引的本地缓存  controller Controller // controller   processor             *sharedProcessor // 事件处理函数集合  cacheMutationDetector MutationDetector   listerWatcher ListerWatcher  objectType runtime.Object  resyncCheckPeriod time.Duration  defaultEventHandlerResyncPeriod time.Duration  clock clock.Clock  started, stopped bool  startedLock      sync.Mutex  blockDeltas sync.Mutex } 

而在 tools/cache/share_informer.go 可以看到 shareIndexInformer 的运行过程

func (s *sharedIndexInformer) Run(stopCh <-chan struct{}) {  defer utilruntime.HandleCrash()   fifo := NewDeltaFIFOWithOptions(DeltaFIFOOptions{   KnownObjects:          s.indexer,   EmitDeltaTypeReplaced: true,  })   cfg := &Config{   Queue:            fifo,   ListerWatcher:    s.listerWatcher,   ObjectType:       s.objectType,   FullResyncPeriod: s.resyncCheckPeriod,   RetryOnError:     false,   ShouldResync:     s.processor.shouldResync,    Process: s.HandleDeltas, // process 弹出时操作的流程  }   func() {   s.startedLock.Lock()   defer s.startedLock.Unlock()    s.controller = New(cfg)   s.controller.(*controller).clock = s.clock   s.started = true  }()   // Separate stop channel because Processor should be stopped strictly after controller  processorStopCh := make(chan struct{})  var wg wait.Group  defer wg.Wait()              // Wait for Processor to stop  defer close(processorStopCh) // Tell Processor to stop  wg.StartWithChannel(processorStopCh, s.cacheMutationDetector.Run)  wg.StartWithChannel(processorStopCh, s.processor.run) // 启动事件处理函数   defer func() {   s.startedLock.Lock()   defer s.startedLock.Unlock()   s.stopped = true // Don't want any new listeners  }()     s.controller.Run(stopCh) // 启动controller，controller会启动Reflector和fifo的Pop() } 

而在操作Delta FIFO中可以看到，做具体操作时，会将动作分发至对应的事件处理函数中，这个是informer初始化时对事件操作的函数

func (s *sharedIndexInformer) HandleDeltas(obj interface{}) error {  s.blockDeltas.Lock()  defer s.blockDeltas.Unlock()    for _, d := range obj.(Deltas) {   switch d.Type {   case Sync, Replaced, Added, Updated:    s.cacheMutationDetector.AddObject(d.Object)    if old, exists, err := s.indexer.Get(d.Object); err == nil && exists {     if err := s.indexer.Update(d.Object); err != nil {      return err     }      isSync := false     switch {     case d.Type == Sync:      isSync = true     case d.Type == Replaced:      if accessor, err := meta.Accessor(d.Object); err == nil {       if oldAccessor, err := meta.Accessor(old); err == nil {        isSync = accessor.GetResourceVersion() == oldAccessor.GetResourceVersion()       }      }     }                 // 事件的分发     s.processor.distribute(updateNotification{oldObj: old, newObj: d.Object}, isSync)    } else {     if err := s.indexer.Add(d.Object); err != nil {      return err     }                 // 事件的分发     s.processor.distribute(addNotification{newObj: d.Object}, false)    }   case Deleted:    if err := s.indexer.Delete(d.Object); err != nil {     return err    }    s.processor.distribute(deleteNotification{oldObj: d.Object}, false)   }  }  return nil } 

事件处理函数 processor

启动informer时也会启动注册进来的事件处理函数；processor 就是这个事件处理函数。

run() 函数会启动两个 listener，j监听事件处理业务函数 listener.run 和 事件的处理

wg.StartWithChannel(processorStopCh, s.processor.run)  func (p *sharedProcessor) run(stopCh <-chan struct{}) {  func() {   p.listenersLock.RLock()   defer p.listenersLock.RUnlock()   for _, listener := range p.listeners {    p.wg.Start(listener.run)     p.wg.Start(listener.pop)   }   p.listenersStarted = true  }()  <-stopCh  p.listenersLock.RLock()  defer p.listenersLock.RUnlock()  for _, listener := range p.listeners {   close(listener.addCh) // Tell .pop() to stop. .pop() will tell .run() to stop  }  p.wg.Wait() // Wait for all .pop() and .run() to stop } 

可以看出，就是拿到的事件，根据注册的到informer的事件函数进行处理

func (p *processorListener) run() {  stopCh := make(chan struct{})  wait.Until(func() {   for next := range p.nextCh { // 消费事件    switch notification := next.(type) {    case updateNotification:     p.handler.OnUpdate(notification.oldObj, notification.newObj)    case addNotification:     p.handler.OnAdd(notification.newObj)    case deleteNotification:     p.handler.OnDelete(notification.oldObj)    default:     utilruntime.HandleError(fmt.Errorf("unrecognized notification: %T", next))    }   }   // the only way to get here is if the p.nextCh is empty and closed   close(stopCh)  }, 1*time.Second, stopCh) } 

informer中的事件的设计

了解了informer如何处理事件，就需要学习下，informer的事件系统设计 prossorListener

事件的添加

当在handleDelta时，会分发具体的事件

// 事件的分发 s.processor.distribute(updateNotification{oldObj: old, newObj: d.Object}, isSync) 

此时，事件泵 Pop() 会根据接收到的事件进行处理

// run() 时会启动一个事件泵 p.wg.Start(listener.pop)  func (p *processorListener) pop() {  defer utilruntime.HandleCrash()  defer close(p.nextCh)    var nextCh chan<- interface{}  var notification interface{}  for {   select {         case nextCh <- notification: // 这里实际上是一个阻塞的等待             // 单向channel 可能不会走到这步骤    var ok bool             // deltahandle 中 distribute 会将事件添加到addCh待处理事件中             // 处理完事件会再次拿到一个事件    notification, ok = p.pendingNotifications.ReadOne()    if !ok { // Nothing to pop     nextCh = nil // Disable this select case    }         // 处理 分发过来的事件 addCh   case notificationToAdd, ok := <-p.addCh: // distribute分发的事件    if !ok {     return    }             // 这里代表第一次，没有任何事件时，或者上面步骤完成读取    if notification == nil { // 就会走这里     notification = notificationToAdd      nextCh = p.nextCh     } else {                  // notification否则代表没有处理完，将数据再次添加到待处理中     p.pendingNotifications.WriteOne(notificationToAdd)    }   }  } } 

该消息事件的流程图为

通过一个简单实例来学习client-go中的消息通知机制

package main  import (  "fmt"  "time"   "k8s.io/utils/buffer" )  var nextCh1 = make(chan interface{}) var addCh = make(chan interface{}) var stopper = make(chan struct{}) var notification interface{} var pendding = *buffer.NewRingGrowing(2)  func main() {  // pop  go func() {   var nextCh chan<- interface{}   var notification interface{}   //var n int   for {    fmt.Println("busy wait")    fmt.Println("entry select", notification)    select {    // 初始时，一个未初始化的channel，nil，形成一个阻塞（单channel下是死锁）    case nextCh <- notification:     fmt.Println("entry nextCh", notification)     var ok bool     // 读不到数据代表已处理完，置空锁     notification, ok = pendding.ReadOne()     if !ok {      fmt.Println("unactive nextch")      nextCh = nil     }    // 事件的分发，监听，初始时也是一个阻塞    case notificationToAdd, ok := <-addCh:     fmt.Println(notificationToAdd, notification)     if !ok {      return     }     // 线程安全     // 当消息为空时，没有被处理     // 锁为空，就分发数据     if notification == nil {      fmt.Println("frist notification nil")      notification = notificationToAdd      nextCh = nextCh1 // 这步骤等于初始化了局部的nextCh，会触发上面的流程     } else {      // 在第三次时，会走到这里，数据进入环      fmt.Println("into ring", notificationToAdd)      pendding.WriteOne(notificationToAdd)     }    }   }  }()  // producer  go func() {   i := 0   for {    i++    if i%5 == 0 {     addCh <- fmt.Sprintf("thread 2 inner -- %d", i)     time.Sleep(time.Millisecond * 9000)    } else {     addCh <- fmt.Sprintf("thread 2 outer -- %d", i)     time.Sleep(time.Millisecond * 500)    }   }  }()  // subsriber  go func() {   for {    for next := range nextCh1 {     time.Sleep(time.Millisecond * 300)     fmt.Println("consumer", next)    }   }  }()  <-stopper } 

总结，这里的机制类似于线程安全，进入临界区的一些算法，临界区就是 nextCh，notification 就是保证了至少有一个进程可以进入临界区（要么分发事件，要么生产事件）；nextCh 和 nextCh1 一个是局部管道一个是全局的，管道未初始化代表了死锁（阻塞）；当有消息要处理时，会将局部管道 nextCh 赋值给 全局 nextCh1 此时相当于解除了分发的步骤（对管道赋值，触发分发操作）；ringbuffer 实际上是提供了一个对 notification 加锁的操作，在没有处理的消息时，需要保障 notification 为空，同时也关闭了流程 nextCh 的写入。这里主要是考虑对golang中channel的用法