sync minor differences in /concepts
zhuzhenghao
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68750e724b
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@ -308,45 +308,46 @@ rules:
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## {{% heading "whatsnext" %}}
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<!--
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[Cloud Controller Manager Administration](/docs/tasks/administer-cluster/running-cloud-controller/#cloud-controller-manager)
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has instructions on running and managing the cloud controller manager.
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* [Cloud Controller Manager Administration](/docs/tasks/administer-cluster/running-cloud-controller/#cloud-controller-manager)
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has instructions on running and managing the cloud controller manager.
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To upgrade a HA control plane to use the cloud controller manager, see
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[Migrate Replicated Control Plane To Use Cloud Controller Manager](/docs/tasks/administer-cluster/controller-manager-leader-migration/).
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* To upgrade a HA control plane to use the cloud controller manager, see
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[Migrate Replicated Control Plane To Use Cloud Controller Manager](/docs/tasks/administer-cluster/controller-manager-leader-migration/).
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Want to know how to implement your own cloud controller manager, or extend an existing project?
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* Want to know how to implement your own cloud controller manager, or extend an existing project?
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-->
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[云控制器管理器的管理](/zh-cn/docs/tasks/administer-cluster/running-cloud-controller/#cloud-controller-manager)
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* [云控制器管理器的管理](/zh-cn/docs/tasks/administer-cluster/running-cloud-controller/#cloud-controller-manager)
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给出了运行和管理云控制器管理器的指南。
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要升级 HA 控制平面以使用云控制器管理器，
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* 要升级 HA 控制平面以使用云控制器管理器，
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请参见[将复制的控制平面迁移以使用云控制器管理器](/zh-cn/docs/tasks/administer-cluster/controller-manager-leader-migration/)。
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想要了解如何实现自己的云控制器管理器，或者对现有项目进行扩展么？
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* 想要了解如何实现自己的云控制器管理器，或者对现有项目进行扩展么？
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<!--
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The cloud controller manager uses Go interfaces to allow implementations from any cloud to be plugged in.
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Specifically, it uses the `CloudProvider` interface defined in
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[`cloud.go`](https://github.com/kubernetes/cloud-provider/blob/release-1.26/cloud.go#L43-L69) from
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[kubernetes/cloud-provider](https://github.com/kubernetes/cloud-provider).
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-->
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云控制器管理器使用 Go 语言的接口，从而使得针对各种云平台的具体实现都可以接入。
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其中使用了在 [kubernetes/cloud-provider](https://github.com/kubernetes/cloud-provider)
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项目中 [`cloud.go`](https://github.com/kubernetes/cloud-provider/blob/release-1.26/cloud.go#L43-L69)
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文件所定义的 `CloudProvider` 接口。
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<!--
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- The cloud controller manager uses Go interfaces, specifically, `CloudProvider` interface defined in
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[`cloud.go`](https://github.com/kubernetes/cloud-provider/blob/release-1.21/cloud.go#L42-L69)
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from [kubernetes/cloud-provider](https://github.com/kubernetes/cloud-provider) to allow
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implementations from any cloud to be plugged in.
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-->
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- 云控制器管理器使用 Go 语言的接口（具体指在
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[kubernetes/cloud-provider](https://github.com/kubernetes/cloud-provider)
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项目中 [`cloud.go`](https://github.com/kubernetes/cloud-provider/blob/release-1.26/cloud.go#L43-L69)
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文件中所定义的 `CloudProvider` 接口），从而使得针对各种云平台的具体实现都可以接入。
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<!--
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The implementation of the shared controllers highlighted in this document (Node, Route, and Service),
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and some scaffolding along with the shared cloudprovider interface, is part of the Kubernetes core.
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Implementations specific to cloud providers are outside the core of Kubernetes and implement the
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`CloudProvider` interface.
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<!--
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- The implementation of the shared controllers highlighted in this document (Node, Route, and Service),
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and some scaffolding along with the shared cloudprovider interface, is part of the Kubernetes core.
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Implementations specific to cloud providers are outside the core of Kubernetes and implement
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the `CloudProvider` interface.
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-->
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- 本文中列举的共享控制器（节点控制器、路由控制器和服务控制器等）的实现以及其他一些生成具有
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CloudProvider 接口的框架的代码，都是 Kubernetes 的核心代码。
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特定于云驱动的实现虽不是 Kubernetes 核心成分，仍要实现 `CloudProvider` 接口。
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For more information about developing plugins, see
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[Developing Cloud Controller Manager](/docs/tasks/administer-cluster/developing-cloud-controller-manager/).
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-->
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本文中列举的共享控制器（节点控制器、路由控制器和服务控制器等）的实现以及其他一些生成具有
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CloudProvider 接口的框架的代码，都是 Kubernetes 的核心代码。
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特定于云驱动的实现虽不是 Kubernetes 核心成分，仍要实现 `CloudProvider` 接口。
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关于如何开发插件的详细信息，
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可参考[开发云控制器管理器](/zh-cn/docs/tasks/administer-cluster/developing-cloud-controller-manager/)文档。
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<!--
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- For more information about developing plugins,
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see [Developing Cloud Controller Manager](/docs/tasks/administer-cluster/developing-cloud-controller-manager/).
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-->
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- 关于如何开发插件的详细信息，
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可参考[开发云控制器管理器](/zh-cn/docs/tasks/administer-cluster/developing-cloud-controller-manager/)文档。
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@ -810,7 +810,7 @@ For example, XFS and ext4fs offer project quotas.
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项目配额（Project Quota）是一个操作系统层的功能特性，用来管理文件系统中的存储用量。
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在 Kubernetes 中，你可以启用项目配额以监视存储用量。
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你需要确保节点上为 `emptyDir` 提供存储的文件系统支持项目配额。
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例如，XFS 和 ext4fs 文件系统都支持项目配额。
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例如，XFS 和 ext4fs 文件系统都支持项目配额。
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{{< note >}}
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<!--
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@ -1038,7 +1038,7 @@ extender.
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"apiVersion": "v1",
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"extenders": [
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{
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"urlPrefix":"<extender-endpoint>",
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"urlPrefix": "<extender-endpoint>",
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"bindVerb": "bind",
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"managedResources": [
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{
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@ -1289,10 +1289,10 @@ resource, including a configured ResourceQuota.
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包括所配置的 ResourceQuota。
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<!--
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### My Container is terminated
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### My container is terminated
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Your container might get terminated because it is resource-starved. To check
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whether a Container is being killed because it is hitting a resource limit, call
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whether a container is being killed because it is hitting a resource limit, call
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`kubectl describe pod` on the Pod of interest:
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-->
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@ -1384,4 +1384,3 @@ memory limit (and possibly request) for that container.
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* 阅读 XFS 中[配额](https://xfs.org/index.php/XFS_FAQ#Q:_Quota:_Do_quotas_work_on_XFS.3F)的文档
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* 进一步阅读 [kube-scheduler 配置参考 (v1beta3)](/zh-cn/docs/reference/config-api/kube-scheduler-config.v1beta3/)
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* 进一步阅读 [Pod 的服务质量等级](/zh-cn/docs/concepts/workloads/pods/pod-qos/)
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@ -1,7 +1,7 @@
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---
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title: EndpointSlice
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content_type: concept
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weight: 45
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weight: 60
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description: >-
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EndpointSlice API 是 Kubernetes 用于扩缩 Service
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以处理大量后端的机制，还允许集群高效更新其健康后端的列表。
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@ -12,7 +12,7 @@ reviewers:
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- freehan
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title: EndpointSlices
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content_type: concept
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weight: 45
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weight: 60
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description: >-
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The EndpointSlice API is the mechanism that Kubernetes uses to let your Service
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scale to handle large numbers of backends, and allows the cluster to update its
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@ -161,18 +161,18 @@ Services will always have the `ready` condition set to `true`.
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<!--
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#### Serving
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{{< feature-state for_k8s_version="v1.22" state="beta" >}}
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{{< feature-state for_k8s_version="v1.26" state="stable" >}}
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`serving` is identical to the `ready` condition, except it does not account for terminating states.
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Consumers of the EndpointSlice API should check this condition if they care about pod readiness while
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The `serving` condition is almost identical to the `ready` condition. The difference is that
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consumers of the EndpointSlice API should check the `serving` condition if they care about pod readiness while
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the pod is also terminating.
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-->
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#### Serving（服务中）
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{{< feature-state for_k8s_version="v1.22" state="beta" >}}
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{{< feature-state for_k8s_version="v1.26" state="stable" >}}
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`serving` 状况与 `ready` 状况相同，不同之处在于它不考虑终止状态。
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如果 EndpointSlice API 的使用者关心 Pod 终止时的就绪情况，就应检查此状况。
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`serving` 状况几乎与 `ready` 状况相同，不同之处在于它不考虑终止状态。
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如果 EndpointSlice API 的使用者关心 Pod 终止时的就绪情况，就应检查 `serving` 状况。
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{{< note >}}
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<!--
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@ -191,7 +191,7 @@ for terminating pods independent of the existing semantics for `ready`.
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的现有语义来跟踪处于终止中的 Pod 的就绪情况。
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{{< /note >}}
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<!--
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<!--
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#### Terminating
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{{< feature-state for_k8s_version="v1.22" state="beta" >}}
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@ -470,7 +470,6 @@ less noticeable; even then, some use cases of Kubernetes weren't well served.
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对象可能变得非常巨大。对于保持稳定的服务（长时间使用同一组端点），影响不太明显；
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即便如此，Kubernetes 的一些使用场景也没有得到很好的服务。
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<!--
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When a Service had a lot of backend endpoints and the workload was either
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scaling frequently, or rolling out new changes frequently, each update to
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@ -507,5 +506,3 @@ EndpointSlices 还支持围绕双栈网络和拓扑感知路由等新功能的
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* 遵循[使用 Service 连接到应用](/zh-cn/docs/tutorials/services/connect-applications-service/)教程
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* 阅读 EndpointSlice API 的 [API 参考](/zh-cn/docs/reference/kubernetes-api/service-resources/endpoint-slice-v1/)
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* 阅读 Endpoints API 的 [API 参考](/zh-cn/docs/reference/kubernetes-api/service-resources/endpoints-v1/)
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