这张时序图描述了kube-proxy的整体逻辑结构,由于kub-proxy组件和其它的kube-* 组件一样都是使用pflag和cobra库去构建命令行应用程序。所以先简单介绍下该包的基本使用方式:
func main() {
command := &cobra.Command{
Use: "echo [string to echo]",
Short: "Echo anything to the screen",
Long: `echo is for echoing anything back.Echo works a lot like print, except it has a child command.`,
Args: cobra.MinimumNArgs(1),
Run: func(cmd *cobra.Command, args []string) {
fmt.Println("Print: " + strings.Join(args, " "))
},
}
command.Execute()
}
上面这段代码就是使用cobra包的一个最简单的例子,首先初始化Command结构,其中该结构中的Run就是最终要执行的真正逻辑。当初始化完成Command之后,通过commnad.Execute去启动应用程序。
现在看上面的图就能比较直观的理解程序的启动机制了,这张图的整体过程就是对Commnad结构中的Run进行核心逻辑实现。也就是说kube-proxy核心逻辑入口就是从这里开始(Command.Run)。
在Command.Run中主要做了如下几件事,看下面的代码:
// Run runs the specified ProxyServer.
func (o *Options) Run() error {
defer close(o.errCh)
//....
proxyServer, err := NewProxyServer(o)
if err != nil {
return err
}
if o.CleanupAndExit {
return proxyServer.CleanupAndExit()
}
o.proxyServer = proxyServer
return o.runLoop()
}
1.对ProxyServer实例进行初始化。 2.如果在启动kube-proxy服务时,CleanupAndExit参数设置为true,则会将userspace, iptables, ipvs三种模式之前设置的所有规则清除掉,然后直接退出。 3.如果在启动kube-proxy服务时,CleanupAndExit参数设置为flase,则会调用runLoop来启动ProxyServer服务。
首先先来看看ProxyServer的结构定义:
type ProxyServer struct {
Client clientset.Interface
EventClient v1core.EventsGetter
IptInterface utiliptables.Interface
IpvsInterface utilipvs.Interface
IpsetInterface utilipset.Interface
execer exec.Interface
Proxier proxy.ProxyProvider
Broadcaster record.EventBroadcaster
Recorder record.EventRecorder
ConntrackConfiguration kubeproxyconfig.KubeProxyConntrackConfiguration
Conntracker Conntracker // if nil, ignored
ProxyMode string
NodeRef *v1.ObjectReference
CleanupIPVS bool
MetricsBindAddress string
EnableProfiling bool
OOMScoreAdj *int32
ConfigSyncPeriod time.Duration
HealthzServer *healthcheck.HealthzServer
}
在ProxyServer结构中包含了与kube-apiserver通信的Client、操作Iptables的IptInterface、操作IPVS的IpvsInterface、操作IpSet的IpsetInterface,以及通过ProxyMode参数获取基于userspace, iptables, ipvs三种方式中的哪种使用的Proxier。
接下来重点介绍基于ipvs模式实现的Proxier, 在ipvs模式下Proxier结构的定义:
type Proxier struct {
endpointsChanges *proxy.EndpointChangeTracker
serviceChanges *proxy.ServiceChangeTracker
//...
serviceMap proxy.ServiceMap
endpointsMap proxy.EndpointsMap
portsMap map[utilproxy.LocalPort]utilproxy.Closeable
//...
syncRunner *async.BoundedFrequencyRunner // governs calls to syncProxyRules
//...
iptables utiliptables.Interface
ipvs utilipvs.Interface
ipset utilipset.Interface
exec utilexec.Interface
//...
ipvsScheduler string
}
在Proxier结构中,先介绍下async.BoundedFrequencyRunner,其它的在介绍ProxyServer.Run的时候介绍。
BoundedFrequencyRunner的定义结构如下:
type BoundedFrequencyRunner struct {
name string // the name of this instance
minInterval time.Duration // the min time between runs, modulo bursts
maxInterval time.Duration // the max time between runs
run chan struct{} // try an async run
mu sync.Mutex // guards runs of fn and all mutations
fn func() // function to run
lastRun time.Time // time of last run
timer timer // timer for deferred runs
limiter rateLimiter // rate limiter for on-demand runs
}
BoundedFrequencyRunner结构中的run会异步的去定期的执行任务fn,比如定期的执行proxier.syncProxyRules去创建或者更新VirtuaServer和RealServer并将VirtualServer的VIP绑定到dummy interface(kube-ipvs0)。
下面是在NewProxier方法中初始化BoundedFrequencyRunner对象的示例:
proxier.syncRunner = async.NewBoundedFrequencyRunner(
"sync-runner", proxier.syncProxyRules, minSyncPeriod, syncPeriod, burstSyncs)
其中:
minSyncPeriod: 规则最小的更新时间
syncPeriod: 规则最大更新时间
proxier.syncProxyRules: 同步规则的实现函数(也是kube-proxy基于ipvs同步规则的核心实现)
这部分介绍下ProxyServer.Run的逻辑实现,ProxyServer启动流程如下图所示:
在启动过程中,主要做了下面这几件事情:
接下来详细的介绍下[4-7]这几步的流程。
ServiceConfig的结构定义如下:
type ServiceConfig struct {
listerSynced cache.InformerSynced
eventHandlers []ServiceHandler
}
ServiceHandler的结构定义如下:
type ServiceHandler interface {
// OnServiceAdd is called whenever creation of new service object
// is observed.
OnServiceAdd(service *v1.Service)
// OnServiceUpdate is called whenever modification of an existing
// service object is observed.
OnServiceUpdate(oldService, service *v1.Service)
// OnServiceDelete is called whenever deletion of an existing service
// object is observed.
OnServiceDelete(service *v1.Service)
// OnServiceSynced is called once all the initial even handlers were
// called and the state is fully propagated to local cache.
OnServiceSynced()
}
创建ServiceConfig实例对象的具体实现如下:
func NewServiceConfig(serviceInformer coreinformers.ServiceInformer, resyncPeriod time.Duration) *ServiceConfig {
result := &ServiceConfig{
listerSynced: serviceInformer.Informer().HasSynced,
}
serviceInformer.Informer().AddEventHandlerWithResyncPeriod(
cache.ResourceEventHandlerFuncs{
AddFunc: result.handleAddService,
UpdateFunc: result.handleUpdateService,
DeleteFunc: result.handleDeleteService,
},
resyncPeriod,
)
return result
}
我们看看handleAddService触发函数的实现逻辑,具体代码如下:
func (c *ServiceConfig) handleAddService(obj interface{}) {
service, ok := obj.(*v1.Service)
if !ok {
utilruntime.HandleError(fmt.Errorf("unexpected object type: %v", obj))
return
}
for i := range c.eventHandlers {
klog.V(4).Info("Calling handler.OnServiceAdd")
c.eventHandlers[i].OnServiceAdd(service)
}
}
当watch到kubernetes集群中有新的Service被创建之后,会触发handleAddService函数,并在该函数中遍历eventHandlers分别去调用OnServiceAdd来对proxier结构中的serviceChanages进行更新并去同步相应的规则。
OnServiceAdd的具体实现逻辑如下:
// OnServiceAdd is called whenever creation of new service object is observed.
func (proxier *Proxier) OnServiceAdd(service *v1.Service) {
proxier.OnServiceUpdate(nil, service)
}
// OnServiceUpdate is called whenever modification of an existing service object is observed.
func (proxier *Proxier) OnServiceUpdate(oldService, service *v1.Service) {
if proxier.serviceChanges.Update(oldService, service) && proxier.isInitialized() {
proxier.syncRunner.Run()
}
}
ServiceChangeTracker的结构定义如下:
// ServiceChangeTracker carries state about uncommitted changes to an arbitrary number of
// Services, keyed by their namespace and name.
type ServiceChangeTracker struct {
// lock protects items.
lock sync.Mutex
// items maps a service to its serviceChange.
items map[types.NamespacedName]*serviceChange
// makeServiceInfo allows proxier to inject customized information when processing service.
makeServiceInfo makeServicePortFunc
// isIPv6Mode indicates if change tracker is under IPv6/IPv4 mode. Nil means not applicable.
isIPv6Mode *bool
recorder record.EventRecorder
}
serviceChanage的结构定义如下:
// serviceChange contains all changes to services that happened since proxy rules were synced. For a single object,
// changes are accumulated, i.e. previous is state from before applying the changes,
// current is state after applying all of the changes.
type serviceChange struct {
previous ServiceMap
current ServiceMap
}
到这里在回过头来看上面的基于IPVS实现的Proxier的整体流程就完全通了,ProxyServer.Run函数在启动时,通过kubernetes LIST/WATCH机制去实时的感知kubernetes集群Service资源的变化,然后不断的在更新Proxier结构中的ServiceChanges,然后将变化的Service保存在ServiceChanges结构中的ServiceMap中,给后续的async.BoundedFrequencyRunner去执行同步规则函数syncProxyRules来使用。
8. endpointConfig的实现机制和serviceConfig的机制完全一样,这里就不在详细的介绍了。
9.上面做的所有预处理工作,会在informerFactory.Start这步生效。
10. birthCry的作用就是通过event的方式通知kubernetes, kube-proxy这边的所有准备工作都处理好了,我要启动了。
s.Recorder.Eventf(s.NodeRef, api.EventTypeNormal, "Starting", "Starting kube-proxy.")
}
11. 最终通过SyncLoop启动kube-proxy服务,并立刻执行syncProxyRules先来一遍同步再说.之后便会通过异步的方式定期的去同步IPVS, Iptables, Ipset的规则。
而syncProxyRules函数是kube-proxy实现的核心。主体逻辑是遍历ServiceMap并遍历ServiceMap下的endpointsMap及创建的Service类型(如: CLusterIP, Loadbalancer, NodePort)去分别创建相应的IPVS规则。
syncProxyRules的函数实现定义如下:
func (proxier *Proxier) syncProxyRules() {
//.....
// Build IPVS rules for each service.
for svcName, svc := range proxier.serviceMap {
//......
// Handle traffic that loops back to the originator with SNAT.
for _, e := range proxier.endpointsMap[svcName] {
//....
}
// Capture the clusterIP.
// ipset call
entry := &utilipset.Entry{
IP: svcInfo.ClusterIP().String(),
Port: svcInfo.Port(),
Protocol: protocol,
SetType: utilipset.HashIPPort,
}
// add service Cluster IP:Port to kubeServiceAccess ip set for the purpose of solving hairpin.
// proxier.kubeServiceAccessSet.activeEntries.Insert(entry.String())
if valid := proxier.ipsetList[kubeClusterIPSet].validateEntry(entry); !valid {
klog.Errorf("%s", fmt.Sprintf(EntryInvalidErr, entry, proxier.ipsetList[kubeClusterIPSet].Name))
continue
}
proxier.ipsetList[kubeClusterIPSet].activeEntries.Insert(entry.String())
// ipvs call
serv := &utilipvs.VirtualServer{
Address: svcInfo.ClusterIP(),
Port: uint16(svcInfo.Port()),
Protocol: string(svcInfo.Protocol()),
Scheduler: proxier.ipvsScheduler,
}
// Set session affinity flag and timeout for IPVS service
if svcInfo.SessionAffinityType() == v1.ServiceAffinityClientIP {
serv.Flags |= utilipvs.FlagPersistent
serv.Timeout = uint32(svcInfo.StickyMaxAgeSeconds())
}
// We need to bind ClusterIP to dummy interface, so set `bindAddr` parameter to `true` in syncService()
if err := proxier.syncService(svcNameString, serv, true); err == nil {
activeIPVSServices[serv.String()] = true
activeBindAddrs[serv.Address.String()] = true
// ExternalTrafficPolicy only works for NodePort and external LB traffic, does not affect ClusterIP
// So we still need clusterIP rules in onlyNodeLocalEndpoints mode.
if err := proxier.syncEndpoint(svcName, false, serv); err != nil {
klog.Errorf("Failed to sync endpoint for service: %v, err: %v", serv, err)
}
} else {
klog.Errorf("Failed to sync service: %v, err: %v", serv, err)
}
// Capture externalIPs.
for _, externalIP := range svcInfo.ExternalIPStrings() {
//....
}
// Capture load-balancer ingress.
for _, ingress := range svcInfo.LoadBalancerIPStrings() {
//.....
}
if svcInfo.NodePort() != 0 {
//....
}
}
// sync ipset entries
for _, set := range proxier.ipsetList {
set.syncIPSetEntries()
}
// Tail call iptables rules for ipset, make sure only call iptables once
// in a single loop per ip set.
proxier.writeIptablesRules()
// Sync iptables rules.
// NOTE: NoFlushTables is used so we don't flush non-kubernetes chains in the table.
proxier.iptablesData.Reset()
proxier.iptablesData.Write(proxier.natChains.Bytes())
proxier.iptablesData.Write(proxier.natRules.Bytes())
proxier.iptablesData.Write(proxier.filterChains.Bytes())
proxier.iptablesData.Write(proxier.filterRules.Bytes())
}
kube-proxy的代码逻辑还是比较简洁的,整体的思想就是kube-proxy服务去watch kubernetes集群的Service和Endpoint对象,当这两个资源对象有状态变化时,会把它们保存在ServiceMap和EndPonintMap中,然后会通过async.BoundedFrequencyRunner去异步的执行syncProxyRules去下发规则。
本文转载自公众号360云计算(ID:hulktalk)。
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