Kubernetes 滚动升级

Kubernetes Rolling Upgrade

背景

Kubernetes 是一个很好的容器应用集群管理工具，尤其是采用ReplicaSet这种自动维护应用生命周期事件的对象后，将容器应用管理的技巧发挥得淋漓尽致。在容器应用管理的诸多特性中，有一个特性是最能体现Kubernetes强大的集群应用管理能力的，那就是滚动升级。

滚动升级的精髓在于升级过程中依然能够保持服务的连续性，使外界对于升级的过程是无感知的。整个过程中会有三个状态，全部旧实例，新旧实例皆有，全部新实例。旧实例个数逐渐减少，新实例个数逐渐增加，最终达到旧实例个数为0，新实例个数达到理想的目标值。

kubernetes 滚动升级

Kubernetes 中采用ReplicaSet（简称RS）来管理Pod实例。如果当前集群中的Pod实例数少于目标值，RS 会拉起新的Pod，反之，则根据策略删除多余的Pod。Deployment正是利用了这样的特性，通过控制两个RS里面的Pod，从而实现升级。
滚动升级是一种平滑过渡式的升级，在升级过程中，服务仍然可用。这是kubernetes作为应用服务化管理的关键一步。服务无处不在，并且按需使用。这是云计算的初衷，对于PaaS平台来说，应用抽象成服务，遍布整个集群，为应用提供随时随地可用的服务是PaaS的终极使命。
1.ReplicaSet
关于RS的概念大家都很清楚了，我们来看看在k8s源码中的RS。

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

    // internalPodInformer is used to hold a personal informer.  If we're using
    // a normal shared informer, then the informer will be started for us.  If
    // we have a personal informer, we must start it ourselves.   If you start
    // the controller using NewReplicationManager(passing SharedInformer), this
    // will be null
    internalPodInformer framework.SharedIndexInformer

    // A ReplicaSet is temporarily suspended after creating/deleting these many replicas.
    // It resumes normal action after observing the watch events for them.
    burstReplicas int
    // To allow injection of syncReplicaSet for testing.
    syncHandler func(rsKey string) error

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

    // A store of ReplicaSets, populated by the rsController
    rsStore cache.StoreToReplicaSetLister
    // Watches changes to all ReplicaSets
    rsController *framework.Controller
    // A store of pods, populated by the podController
    podStore cache.StoreToPodLister
    // Watches changes to all pods
    podController framework.ControllerInterface
    // 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 func() bool

    lookupCache *controller.MatchingCache

    // Controllers that need to be synced
    queue *workqueue.Type

    // garbageCollectorEnabled denotes if the garbage collector is enabled. RC
    // manager behaves differently if GC is enabled.
    garbageCollectorEnabled bool
}

这个结构体位于pkg/controllers/replicaset,这里我们可以看出，RS最主要的几个对象，一个是针对Pod的操作对象-podControl.看到这个名字就知道，这个对象是控制RS下面的Pod的生命周期的，我们看看这个PodControl所包含的方法。

// PodControlInterface is an interface that knows how to add or delete pods
// created as an interface to allow testing.
type PodControlInterface interface {
    // CreatePods creates new pods according to the spec.
    CreatePods(namespace string, template *api.PodTemplateSpec, object runtime.Object) error
    // CreatePodsOnNode creates a new pod accorting to the spec on the specified node.
    CreatePodsOnNode(nodeName, namespace string, template *api.PodTemplateSpec, object runtime.Object) error
    // CreatePodsWithControllerRef creates new pods according to the spec, and sets object as the pod's controller.
    CreatePodsWithControllerRef(namespace string, template *api.PodTemplateSpec, object runtime.Object, controllerRef *api.OwnerReference) error
    // DeletePod deletes the pod identified by podID.
    DeletePod(namespace string, podID string, object runtime.Object) error
    // PatchPod patches the pod.
    PatchPod(namespace, name string, data []byte) error
}

这里我们可以看到，RS可以完全控制Pod.这里有两个watch，rsController和podController，他们分别负责watch ETCD中RS和Pod的变化。这里一个重要的对象不得不提，那就是syncHandler，这个是所有Controller都有的对象。每一个控制器通过Watch来监视ETCD中的变化，使用sync的方式来同步这些对象的状态，注意这个Handler只是一个委托，实际真正的Handler在创建控制器的时候指定。这种模式不仅仅适用于RS，其他控制器亦如此。
下面的逻辑更加清晰地说明了watch的逻辑。

rsc.rsStore.Store, rsc.rsController = framework.NewInformer(
        &cache.ListWatch{
            ListFunc: func(options api.ListOptions) (runtime.Object, error) {
                return rsc.kubeClient.Extensions().ReplicaSets(api.NamespaceAll).List(options)
            },
            WatchFunc: func(options api.ListOptions) (watch.Interface, error) {
                return rsc.kubeClient.Extensions().ReplicaSets(api.NamespaceAll).Watch(options)
            },
        },
        &extensions.ReplicaSet{},
        // TODO: Can we have much longer period here?
        FullControllerResyncPeriod,
        framework.ResourceEventHandlerFuncs{
            AddFunc:    rsc.enqueueReplicaSet,
            UpdateFunc: rsc.updateRS,
            // This will enter the sync loop and no-op, because the replica set has been deleted from the store.
            // Note that deleting a replica set immediately after scaling it to 0 will not work. The recommended
            // way of achieving this is by performing a `stop` operation on the replica set.
            DeleteFunc: rsc.enqueueReplicaSet,
        },
    )

每次Watch到ETCD中的对象的变化，采取相应的措施，具体来说就是放入队列，更新或者取出队列。对于Pod来说，也有相应的处理。

podInformer.AddEventHandler(framework.ResourceEventHandlerFuncs{
        AddFunc: rsc.addPod,
        // This invokes the ReplicaSet for every pod change, eg: host assignment. Though this might seem like
        // overkill the most frequent pod update is status, and the associated ReplicaSet will only list from
        // local storage, so it should be ok.
        UpdateFunc: rsc.updatePod,
        DeleteFunc: rsc.deletePod,
    })

RS基本的内容就这些，在RS的上层是Deployment，这个对象也是一个控制器。

// DeploymentController is responsible for synchronizing Deployment objects stored
// in the system with actual running replica sets and pods.
type DeploymentController struct {
    client        clientset.Interface
    eventRecorder record.EventRecorder

    // To allow injection of syncDeployment for testing.
    syncHandler func(dKey string) error

    // A store of deployments, populated by the dController
    dStore cache.StoreToDeploymentLister
    // Watches changes to all deployments
    dController *framework.Controller
    // A store of ReplicaSets, populated by the rsController
    rsStore cache.StoreToReplicaSetLister
    // Watches changes to all ReplicaSets
    rsController *framework.Controller
    // A store of pods, populated by the podController
    podStore cache.StoreToPodLister
    // Watches changes to all pods
    podController *framework.Controller

    // dStoreSynced returns true if the Deployment store has been synced at least once.
    // Added as a member to the struct to allow injection for testing.
    dStoreSynced func() bool
    // rsStoreSynced returns true if the ReplicaSet store has been synced at least once.
    // Added as a member to the struct to allow injection for testing.
    rsStoreSynced func() bool
    // 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 func() bool

    // Deployments that need to be synced
    queue workqueue.RateLimitingInterface
}

对于DeploymentController来说，需要监听Deployment,RS和Pod。从Controller的创建过程中可以看出来。

dc.dStore.Store, dc.dController = framework.NewInformer(
        &cache.ListWatch{
            ListFunc: func(options api.ListOptions) (runtime.Object, error) {
                return dc.client.Extensions().Deployments(api.NamespaceAll).List(options)
            },
            WatchFunc: func(options api.ListOptions) (watch.Interface, error) {
                return dc.client.Extensions().Deployments(api.NamespaceAll).Watch(options)
            },
        },
        &extensions.Deployment{},
        FullDeploymentResyncPeriod,
        framework.ResourceEventHandlerFuncs{
            AddFunc:    dc.addDeploymentNotification,
            UpdateFunc: dc.updateDeploymentNotification,
            // This will enter the sync loop and no-op, because the deployment has been deleted from the store.
            DeleteFunc: dc.deleteDeploymentNotification,
        },
    )

    dc.rsStore.Store, dc.rsController = framework.NewInformer(
        &cache.ListWatch{
            ListFunc: func(options api.ListOptions) (runtime.Object, error) {
                return dc.client.Extensions().ReplicaSets(api.NamespaceAll).List(options)
            },
            WatchFunc: func(options api.ListOptions) (watch.Interface, error) {
                return dc.client.Extensions().ReplicaSets(api.NamespaceAll).Watch(options)
            },
        },
        &extensions.ReplicaSet{},
        resyncPeriod(),
        framework.ResourceEventHandlerFuncs{
            AddFunc:    dc.addReplicaSet,
            UpdateFunc: dc.updateReplicaSet,
            DeleteFunc: dc.deleteReplicaSet,
        },
    )

    dc.podStore.Indexer, dc.podController = framework.NewIndexerInformer(
        &cache.ListWatch{
            ListFunc: func(options api.ListOptions) (runtime.Object, error) {
                return dc.client.Core().Pods(api.NamespaceAll).List(options)
            },
            WatchFunc: func(options api.ListOptions) (watch.Interface, error) {
                return dc.client.Core().Pods(api.NamespaceAll).Watch(options)
            },
        },
        &api.Pod{},
        resyncPeriod(),
        framework.ResourceEventHandlerFuncs{
            AddFunc:    dc.addPod,
            UpdateFunc: dc.updatePod,
            DeleteFunc: dc.deletePod,
        },
        cache.Indexers{cache.NamespaceIndex: cache.MetaNamespaceIndexFunc},
    )

    dc.syncHandler = dc.syncDeployment
    dc.dStoreSynced = dc.dController.HasSynced
    dc.rsStoreSynced = dc.rsController.HasSynced
    dc.podStoreSynced = dc.podController.HasSynced

这里最核心的就是syncDeployment，因为这里面有rollingUpdate和rollback的实现。在这里如果watch到某个Deployment对象的RollbackTo.Revision部位nil,则执行rollingbach。这个Revision是版本号，注意虽然是回滚，但k8s内部记录的版本号永远是增长的。
有人会好奇,rollback是怎么做到的，其实原理很简单，k8s记录了各个版本的PodTemplate,把旧的PodTemplate覆盖新的Template即可。
对于K8S来说，升级有两种方式，一种是重新构建，一种是滚动升级。

switch d.Spec.Strategy.Type {
    case extensions.RecreateDeploymentStrategyType:
        return dc.rolloutRecreate(d)
    case extensions.RollingUpdateDeploymentStrategyType:
        return dc.rolloutRolling(d)
}

这个rolloutRolling里面包含了所有的秘密，这里我们可以看到。

func (dc *DeploymentController) rolloutRolling(deployment *extensions.Deployment) error {
    newRS, oldRSs, err := dc.getAllReplicaSetsAndSyncRevision(deployment, true)
    if err != nil {
        return err
    }
    allRSs := append(oldRSs, newRS)

    // Scale up, if we can.
    scaledUp, err := dc.reconcileNewReplicaSet(allRSs, newRS, deployment)
    if err != nil {
        return err
    }
    if scaledUp {
        // Update DeploymentStatus
        return dc.updateDeploymentStatus(allRSs, newRS, deployment)
    }

    // Scale down, if we can.
    scaledDown, err := dc.reconcileOldReplicaSets(allRSs, controller.FilterActiveReplicaSets(oldRSs), newRS, deployment)
    if err != nil {
        return err
    }
    if scaledDown {
        // Update DeploymentStatus
        return dc.updateDeploymentStatus(allRSs, newRS, deployment)
    }

    dc.cleanupDeployment(oldRSs, deployment)

    // Sync deployment status
    return dc.syncDeploymentStatus(allRSs, newRS, deployment)
}

这里做了如下几件事：
1. 查找新的RS和旧的RS，并计算出新的Revision（这是Revision的最大值）；
2. 对新的RS进行扩容操作；
3. 对旧的RS进行缩容操作；
4. 完成之后，删掉旧的RS；
5. 通过Deployment状态到etcd;

至此，我们知道了滚动升级在kubernetes中的原理。其实在传统的负载均衡应用中，滚动升��的做法很类似，但是在容器环境中，我们有RS，通过这种方法更为便捷。

Kubernetes 的详细介绍：请点这里
Kubernetes 的下载地址：请点这里