Kubernetes源码分析之kube-controller-manager

本节所有的代码基于1.13.4版本。

启动分析

Controller-manager的启动主要包括各种controller的配置与初始化。初始化方法在NewControllerManagerCommand下，该方法通过创建一个cobra.Command对象，完成初始化的配置工作。
进入NewControllerManagerCommand方法，该方法主要对controller-manager管理的所有controller进行初始化参数的配置，代码如下

// NewKubeControllerManagerOptions creates a new KubeControllerManagerOptions with a default config.
func NewKubeControllerManagerOptions() (*KubeControllerManagerOptions, error) {
	componentConfig, err := NewDefaultComponentConfig(ports.InsecureKubeControllerManagerPort)
	if err != nil {
		return nil, err
	}

	// 包含各种Controller的初始化配置
	s := KubeControllerManagerOptions{
		Generic:         cmoptions.NewGenericControllerManagerConfigurationOptions(componentConfig.Generic),
		KubeCloudShared: cmoptions.NewKubeCloudSharedOptions(componentConfig.KubeCloudShared),
		AttachDetachController: &AttachDetachControllerOptions{
			ReconcilerSyncLoopPeriod: componentConfig.AttachDetachController.ReconcilerSyncLoopPeriod,
		},
		CSRSigningController: &CSRSigningControllerOptions{
			ClusterSigningCertFile: componentConfig.CSRSigningController.ClusterSigningCertFile,
			ClusterSigningKeyFile:  componentConfig.CSRSigningController.ClusterSigningKeyFile,
			ClusterSigningDuration: componentConfig.CSRSigningController.ClusterSigningDuration,
		},
		DaemonSetController: &DaemonSetControllerOptions{
			ConcurrentDaemonSetSyncs: componentConfig.DaemonSetController.ConcurrentDaemonSetSyncs,
		},
		DeploymentController: &DeploymentControllerOptions{
			ConcurrentDeploymentSyncs:      componentConfig.DeploymentController.ConcurrentDeploymentSyncs,
			DeploymentControllerSyncPeriod: componentConfig.DeploymentController.DeploymentControllerSyncPeriod,
		},
		DeprecatedFlags: &DeprecatedControllerOptions{
			RegisterRetryCount: componentConfig.DeprecatedController.RegisterRetryCount,
		},
		EndpointController: &EndpointControllerOptions{
			ConcurrentEndpointSyncs: componentConfig.EndpointController.ConcurrentEndpointSyncs,
		},
		GarbageCollectorController: &GarbageCollectorControllerOptions{
			ConcurrentGCSyncs:      componentConfig.GarbageCollectorController.ConcurrentGCSyncs,
			EnableGarbageCollector: componentConfig.GarbageCollectorController.EnableGarbageCollector,
		},
		HPAController: &HPAControllerOptions{
			HorizontalPodAutoscalerSyncPeriod:                   componentConfig.HPAController.HorizontalPodAutoscalerSyncPeriod,
			HorizontalPodAutoscalerUpscaleForbiddenWindow:       componentConfig.HPAController.HorizontalPodAutoscalerUpscaleForbiddenWindow,
			HorizontalPodAutoscalerDownscaleForbiddenWindow:     componentConfig.HPAController.HorizontalPodAutoscalerDownscaleForbiddenWindow,
			HorizontalPodAutoscalerDownscaleStabilizationWindow: componentConfig.HPAController.HorizontalPodAutoscalerDownscaleStabilizationWindow,
			HorizontalPodAutoscalerCPUInitializationPeriod:      componentConfig.HPAController.HorizontalPodAutoscalerCPUInitializationPeriod,
			HorizontalPodAutoscalerInitialReadinessDelay:        componentConfig.HPAController.HorizontalPodAutoscalerInitialReadinessDelay,
			HorizontalPodAutoscalerTolerance:                    componentConfig.HPAController.HorizontalPodAutoscalerTolerance,
			HorizontalPodAutoscalerUseRESTClients:               componentConfig.HPAController.HorizontalPodAutoscalerUseRESTClients,
		},
		JobController: &JobControllerOptions{
			ConcurrentJobSyncs: componentConfig.JobController.ConcurrentJobSyncs,
		},
		NamespaceController: &NamespaceControllerOptions{
			NamespaceSyncPeriod:      componentConfig.NamespaceController.NamespaceSyncPeriod,
			ConcurrentNamespaceSyncs: componentConfig.NamespaceController.ConcurrentNamespaceSyncs,
		},
		NodeIPAMController: &NodeIPAMControllerOptions{
			NodeCIDRMaskSize: componentConfig.NodeIPAMController.NodeCIDRMaskSize,
		},
		NodeLifecycleController: &NodeLifecycleControllerOptions{
			EnableTaintManager:     componentConfig.NodeLifecycleController.EnableTaintManager,
			NodeMonitorGracePeriod: componentConfig.NodeLifecycleController.NodeMonitorGracePeriod,
			NodeStartupGracePeriod: componentConfig.NodeLifecycleController.NodeStartupGracePeriod,
			PodEvictionTimeout:     componentConfig.NodeLifecycleController.PodEvictionTimeout,
		},
		PersistentVolumeBinderController: &PersistentVolumeBinderControllerOptions{
			PVClaimBinderSyncPeriod: componentConfig.PersistentVolumeBinderController.PVClaimBinderSyncPeriod,
			VolumeConfiguration:     componentConfig.PersistentVolumeBinderController.VolumeConfiguration,
		},
		PodGCController: &PodGCControllerOptions{
			TerminatedPodGCThreshold: componentConfig.PodGCController.TerminatedPodGCThreshold,
		},
		ReplicaSetController: &ReplicaSetControllerOptions{
			ConcurrentRSSyncs: componentConfig.ReplicaSetController.ConcurrentRSSyncs,
		},
		ReplicationController: &ReplicationControllerOptions{
			ConcurrentRCSyncs: componentConfig.ReplicationController.ConcurrentRCSyncs,
		},
		ResourceQuotaController: &ResourceQuotaControllerOptions{
			ResourceQuotaSyncPeriod:      componentConfig.ResourceQuotaController.ResourceQuotaSyncPeriod,
			ConcurrentResourceQuotaSyncs: componentConfig.ResourceQuotaController.ConcurrentResourceQuotaSyncs,
		},
		SAController: &SAControllerOptions{
			ConcurrentSATokenSyncs: componentConfig.SAController.ConcurrentSATokenSyncs,
		},
		ServiceController: &cmoptions.ServiceControllerOptions{
			ConcurrentServiceSyncs: componentConfig.ServiceController.ConcurrentServiceSyncs,
		},
		TTLAfterFinishedController: &TTLAfterFinishedControllerOptions{
			ConcurrentTTLSyncs: componentConfig.TTLAfterFinishedController.ConcurrentTTLSyncs,
		},
		SecureServing: apiserveroptions.NewSecureServingOptions().WithLoopback(),
		InsecureServing: (&apiserveroptions.DeprecatedInsecureServingOptions{
			BindAddress: net.ParseIP(componentConfig.Generic.Address),
			BindPort:    int(componentConfig.Generic.Port),
			BindNetwork: "tcp",
		}).WithLoopback(),
		Authentication: apiserveroptions.NewDelegatingAuthenticationOptions(),
		Authorization:  apiserveroptions.NewDelegatingAuthorizationOptions(),
	}

	s.Authentication.RemoteKubeConfigFileOptional = true
	s.Authorization.RemoteKubeConfigFileOptional = true
	s.Authorization.AlwaysAllowPaths = []string{"/healthz"}

	// Set the PairName but leave certificate directory blank to generate in-memory by default
	s.SecureServing.ServerCert.CertDirectory = ""
	s.SecureServing.ServerCert.PairName = "kube-controller-manager"
	s.SecureServing.BindPort = ports.KubeControllerManagerPort

	gcIgnoredResources := make([]kubectrlmgrconfig.GroupResource, 0, len(garbagecollector.DefaultIgnoredResources()))
	for r := range garbagecollector.DefaultIgnoredResources() {
		gcIgnoredResources = append(gcIgnoredResources, kubectrlmgrconfig.GroupResource{Group: r.Group, Resource: r.Resource})
	}

	s.GarbageCollectorController.GCIgnoredResources = gcIgnoredResources

	return &s, nil
}
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可以看到，我们熟悉的相应的controller都在配置内。
返回到NewControllerManagerCommand方法，在执行最终的Run方法之前，需要对初始化参数进行校验，并且需要对每个controller配置启动方法，相应的代码如下

进入到KnownControllers方法，该方法就是用来配置各种controller的启动方法，以map类型保存，最终的代码如下

func NewControllerInitializers(loopMode ControllerLoopMode) map[string]InitFunc {
	controllers := map[string]InitFunc{}
	controllers["endpoint"] = startEndpointController
	controllers["replicationcontroller"] = startReplicationController
	controllers["podgc"] = startPodGCController
	controllers["resourcequota"] = startResourceQuotaController
	controllers["namespace"] = startNamespaceController
	controllers["serviceaccount"] = startServiceAccountController
	controllers["garbagecollector"] = startGarbageCollectorController
	controllers["daemonset"] = startDaemonSetController
	controllers["job"] = startJobController
	controllers["deployment"] = startDeploymentController
	controllers["replicaset"] = startReplicaSetController
	controllers["horizontalpodautoscaling"] = startHPAController
	controllers["disruption"] = startDisruptionController
	controllers["statefulset"] = startStatefulSetController
	controllers["cronjob"] = startCronJobController
	controllers["csrsigning"] = startCSRSigningController
	controllers["csrapproving"] = startCSRApprovingController
	controllers["csrcleaner"] = startCSRCleanerController
	controllers["ttl"] = startTTLController
	controllers["bootstrapsigner"] = startBootstrapSignerController
	controllers["tokencleaner"] = startTokenCleanerController
	controllers["nodeipam"] = startNodeIpamController
	if loopMode == IncludeCloudLoops {
		controllers["service"] = startServiceController
		controllers["route"] = startRouteController
		// TODO: volume controller into the IncludeCloudLoops only set.
		// TODO: Separate cluster in cloud check from node lifecycle controller.
	}
	controllers["nodelifecycle"] = startNodeLifecycleController
	controllers["persistentvolume-binder"] = startPersistentVolumeBinderController
	controllers["attachdetach"] = startAttachDetachController
	controllers["persistentvolume-expander"] = startVolumeExpandController
	controllers["clusterrole-aggregation"] = startClusterRoleAggregrationController
	controllers["pvc-protection"] = startPVCProtectionController
	controllers["pv-protection"] = startPVProtectionController
	controllers["ttl-after-finished"] = startTTLAfterFinishedController
	controllers["root-ca-cert-publisher"] = startRootCACertPublisher

	return controllers
}
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其中各种以start前缀开头的均为相对应的controller的启动方法，后续分析。
进入最核心的Run方法，主要过程包括一些server的配置、各种健康检查以及是否需要配置Leader的选举（controller-manager的选举同scheduler一致），最终依次启动所有的start开头的controller，完成启动过程。
启动过程比较简洁，主要就是参数的配置、参数的校验以及最终的启动工作，和之前介绍的组件原理基本差不多，对controller-manager的分析主要还是要对应到每个具体的controller上。这里以最常用的Deployment为例。

Deployment的启动流程

熟悉CRD的应该都熟悉，kubernetes controller使用的是informer和workqueue的机制，即通过informer监控通知资源的变化，通过workqueue入队处理资源。Deployment也不例外。
之前说过，controller所有的入口都是以start开头，则Deployment Controller的入口方法为startDeploymentController。方法比较简单，如下

func startDeploymentController(ctx ControllerContext) (http.Handler, bool, error) {
	if !ctx.AvailableResources[schema.GroupVersionResource{Group: "apps", Version: "v1", Resource: "deployments"}] {
		return nil, false, nil
	}
	dc, err := deployment.NewDeploymentController(
		ctx.InformerFactory.Apps().V1().Deployments(),
		ctx.InformerFactory.Apps().V1().ReplicaSets(),
		ctx.InformerFactory.Core().V1().Pods(),
		ctx.ClientBuilder.ClientOrDie("deployment-controller"),
	)
	if err != nil {
		return nil, true, fmt.Errorf("error creating Deployment controller: %v", err)
	}
	go dc.Run(int(ctx.ComponentConfig.DeploymentController.ConcurrentDeploymentSyncs), ctx.Stop)
	return nil, true, nil
}
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主要分成三个步骤：
1、判断资源版本是否可用，即deployment应该为apps/v1；
2、通过NewDeploymentController创建一个DeploymentController对象；
3、启动，循环检测资源的变化，完成最终处理任务。
进入NewDeploymentController方法，对informer的操作主要有Deployment、ReplicaSet以及Pod，与我们对Deployment了解的资源基本符合，通过各种处理方法处理资源的CRUD等操作。
。

通过syncDeployment处理Deployment的检测，保证Deployment资源一直能够被处理，enqueue方法保证资源的及时入队。
创建完成之后，接下来就是启动操作。通过Run方法进入到最终的dc.worker方法，最终调用的为dc.syncHandler方法，也就是配置中的syncDeployment方法，通过不停循环检测执行syncDeployment方法，保证资源的及时处理。方法如下：

// syncDeployment will sync the deployment with the given key.
// This function is not meant to be invoked concurrently with the same key.
func (dc *DeploymentController) syncDeployment(key string) error {
	startTime := time.Now()
	klog.V(4).Infof("Started syncing deployment %q (%v)", key, startTime)
	defer func() {
		klog.V(4).Infof("Finished syncing deployment %q (%v)", key, time.Since(startTime))
	}()

	// 通过key获取资源的namespace和name
	namespace, name, err := cache.SplitMetaNamespaceKey(key)
	if err != nil {
		return err
	}
	// 通过namespace和name获取deployment信息
	deployment, err := dc.dLister.Deployments(namespace).Get(name)
	if errors.IsNotFound(err) {
		klog.V(2).Infof("Deployment %v has been deleted", key)
		return nil
	}
	if err != nil {
		return err
	}

	// Deep-copy otherwise we are mutating our cache.
	// TODO: Deep-copy only when needed.
	d := deployment.DeepCopy()

	everything := metav1.LabelSelector{}
	if reflect.DeepEqual(d.Spec.Selector, &everything) {
		dc.eventRecorder.Eventf(d, v1.EventTypeWarning, "SelectingAll", "This deployment is selecting all pods. A non-empty selector is required.")
		if d.Status.ObservedGeneration < d.Generation {
			d.Status.ObservedGeneration = d.Generation
			dc.client.AppsV1().Deployments(d.Namespace).UpdateStatus(d)
		}
		return nil
	}

	// List ReplicaSets owned by this Deployment, while reconciling ControllerRef
	// through adoption/orphaning.
	// 通过deployment获取其对应的ReplicaSet
	rsList, err := dc.getReplicaSetsForDeployment(d)
	if err != nil {
		return err
	}
	// List all Pods owned by this Deployment, grouped by their ReplicaSet.
	// Current uses of the podMap are:
	//
	// * check if a Pod is labeled correctly with the pod-template-hash label.
	// * check that no old Pods are running in the middle of Recreate Deployments.
	// 通过Deployment和ReplicaSet获取相应的pod信息
	podMap, err := dc.getPodMapForDeployment(d, rsList)
	if err != nil {
		return err
	}

	// 判断需要进行什么操作
	if d.DeletionTimestamp != nil {
		return dc.syncStatusOnly(d, rsList)
	}

	// Update deployment conditions with an Unknown condition when pausing/resuming
	// a deployment. In this way, we can be sure that we won't timeout when a user
	// resumes a Deployment with a set progressDeadlineSeconds.
	if err = dc.checkPausedConditions(d); err != nil {
		return err
	}

	if d.Spec.Paused {
		return dc.sync(d, rsList)
	}

	// rollback is not re-entrant in case the underlying replica sets are updated with a new
	// revision so we should ensure that we won't proceed to update replica sets until we
	// make sure that the deployment has cleaned up its rollback spec in subsequent enqueues.
	if getRollbackTo(d) != nil {
		return dc.rollback(d, rsList)
	}

	scalingEvent, err := dc.isScalingEvent(d, rsList)
	if err != nil {
		return err
	}
	if scalingEvent {
		return dc.sync(d, rsList)
	}

	switch d.Spec.Strategy.Type {
	case apps.RecreateDeploymentStrategyType:
		return dc.rolloutRecreate(d, rsList, podMap)
	case apps.RollingUpdateDeploymentStrategyType:
		return dc.rolloutRolling(d, rsList)
	}
	return fmt.Errorf("unexpected deployment strategy type: %s", d.Spec.Strategy.Type)
}
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步骤如下：
1、通过参数key获取资源的namespace和name；
2、通过namespace和name获取deployment信息；
3、通过Deployment获取其对应的ReplicaSet信息；
4、通过Deployment和ReplicaSet获取相对应的pod信息；
5、根据配置的参数，判断需要进行什么操作，包括sync、rollback、rolloutRecreate以及rolloutRolling操作。
至此，DeploymentController的任务基本完成。我们自定义实现CRD与Controller的步骤基本与此一致，都是通过监听需要的资源，通过对资源列表和资源操作进行比对，判断对资源最终的操作，完成controller任务。

转载于:https://juejin.im/post/5caab97de51d452b3e52bec8