From 404b218418a52b741eb930a3091e3d13170c9c14 Mon Sep 17 00:00:00 2001
From: AdamDang <adam.dang@daocloud.io>
Date: Sat, 5 Jan 2019 12:51:27 +0800
Subject: [PATCH] 
 zh-trans:/docs/tasks/debug-application-cluster/events-stackdriver.md (#11996)

zh-trans:/docs/tasks/debug-application-cluster/events-stackdriver.md
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+---
+reviewers:
+- piosz
+- x13n
+content_template: templates/concept
+title: StackDriver 中的事件
+---
+
+<!--
+---
+reviewers:
+- piosz
+- x13n
+content_template: templates/concept
+title: Events in Stackdriver
+---
+-->
+
+{{% capture overview %}}
+
+<!--
+Kubernetes events are objects that provide insight into what is happening
+inside a cluster, such as what decisions were made by scheduler or why some
+pods were evicted from the node. You can read more about using events
+for debugging your application in the [Application Introspection and Debugging
+](/docs/tasks/debug-application-cluster/debug-application-introspection/)
+section.
+-->
+
+Kubernetes 事件是一种对象，它为用户提供了洞察集群内发生的事情的能力，例如调度程序做出了什么决定，或者为什么某些 Pod 被逐出节点。
+您可以在[应用程序自检和调试](/docs/tasks/debug-application-cluster/debug-application-introspection/)中阅读有关使用事件调试应用程序的更多信息。
+
+<!--
+Since events are API objects, they are stored in the apiserver on master. To
+avoid filling up master's disk, a retention policy is enforced: events are
+removed one hour after the last occurrence. To provide longer history
+and aggregation capabilities, a third party solution should be installed
+to capture events.
+-->
+
+由于事件是 API 对象，因此它们存储在主节点上的 apiserver 中。
+为了避免主节点磁盘空间被填满，将强制执行保留策略：在最后一次事件发生一小时后删除事件。
+为了提供更长的历史记录和聚合能力，应该安装第三方解决方案来捕获事件。
+
+<!--
+This article describes a solution that exports Kubernetes events to
+Stackdriver Logging, where they can be processed and analyzed.
+-->
+
+本文描述了一个将 Kubernetes 事件导出为 Stackdriver Logging 的解决方案，在这里可以对它们进行处理和分析。
+
+{{< note >}}
+<!--
+It is not guaranteed that all events happening in a cluster will be
+exported to Stackdriver. One possible scenario when events will not be
+exported is when event exporter is not running (e.g. during restart or
+upgrade). In most cases it's fine to use events for purposes like setting up
+[metrics][sdLogMetrics] and [alerts][sdAlerts], but you should be aware
+of the potential inaccuracy.
+-->
+不能保证集群中发生的所有事件都将导出到 Stackdriver。
+事件不能导出的一种可能情况是事件导出器没有运行（例如，在重新启动或升级期间）。
+在大多数情况下，可以将事件用于设置 [metrics][sdLogMetrics] 和 [alerts][sdAlerts] 等目的，但您应该注意潜在的不准确性。
+{{< /note >}}
+
+[sdLogMetrics]: https://cloud.google.com/logging/docs/view/logs_based_metrics
+[sdAlerts]: https://cloud.google.com/logging/docs/view/logs_based_metrics#creating_an_alerting_policy
+
+{{% /capture %}}
+
+
+{{% capture body %}}
+
+<!--
+## Deployment
+-->
+
+## 部署
+
+### Google Kubernetes Engine
+
+<!--
+In Google Kubernetes Engine, if cloud logging is enabled, event exporter
+is deployed by default to the clusters with master running version 1.7 and
+higher. To prevent disturbing your workloads, event exporter does not have
+resources set and is in the best effort QOS class, which means that it will
+be the first to be killed in the case of resource starvation. If you want
+your events to be exported, make sure you have enough resources to facilitate
+the event exporter pod. This may vary depending on the workload, but on
+average, approximately 100Mb RAM and 100m CPU is needed.
+-->
+
+在 Google Kubernetes Engine 中，如果启用了云日志，那么事件导出器默认部署在主节点运行版本为 1.7 及更高版本的集群中。
+为了防止干扰您的工作负载，事件导出器没有设置资源，并且处于尽力而为的 QoS 类型中，这意味着它将在资源匮乏的情况下第一个被杀死。
+如果要导出事件，请确保有足够的资源给事件导出器 Pod 使用。
+这可能会因为工作负载的不同而有所不同，但平均而言，需要大约 100MB 的内存和 100m 的 CPU。
+
+<!--
+### Deploying to the Existing Cluster
+-->
+
+### 部署到现有集群
+
+<!--
+Deploy event exporter to your cluster using the following command:
+-->
+
+使用下面的命令将事件导出器部署到您的集群：
+
+```shell
+kubectl create -f https://k8s.io/examples/debug/event-exporter.yaml
+```
+
+<!--
+Since event exporter accesses the Kubernetes API, it requires permissions to
+do so. The following deployment is configured to work with RBAC
+authorization. It sets up a service account and a cluster role binding
+to allow event exporter to read events. To make sure that event exporter
+pod will not be evicted from the node, you can additionally set up resource
+requests. As mentioned earlier, 100Mb RAM and 100m CPU should be enough.
+-->
+
+由于事件导出器访问 Kubernetes API，因此它需要权限才能访问。
+以下的部署配置为使用 RBAC 授权。
+它设置服务帐户和集群角色绑定，以允许事件导出器读取事件。
+为了确保事件导出器 Pod 不会从节点中退出，您可以另外设置资源请求。
+如前所述，100MB 内存和 100m CPU 应该就足够了。
+
+{{< codenew file="debug/event-exporter.yaml" >}}
+
+<!--
+## User Guide
+-->
+
+## 用户指南
+
+<!--
+Events are exported to the `GKE Cluster` resource in Stackdriver Logging.
+You can find them by selecting an appropriate option from a drop-down menu
+of available resources:
+-->
+
+事件在 Stackdriver Logging 中被导出到 `GKE Cluster` 资源。
+您可以通过从可用资源的下拉菜单中选择适当的选项来找到它们：
+
+<img src="/images/docs/stackdriver-event-exporter-resource.png" alt="Events location in the Stackdriver Logging interface" width="500">
+
+<!--
+You can filter based on the event object fields using Stackdriver Logging
+[filtering mechanism](https://cloud.google.com/logging/docs/view/advanced_filters).
+For example, the following query will show events from the scheduler
+about pods from deployment `nginx-deployment`:
+-->
+
+您可以使用 Stackdriver Logging 的[过滤机制](https://cloud.google.com/logging/docs/view/advanced_filters)基于事件对象字段进行过滤。
+例如，下面的查询将显示调度程序中有关 Deployment `nginx-deployment` 中的 Pod 的事件：
+
+```
+resource.type="gke_cluster"
+jsonPayload.kind="Event"
+jsonPayload.source.component="default-scheduler"
+jsonPayload.involvedObject.name:"nginx-deployment"
+```
+
+{{< figure src="/images/docs/stackdriver-event-exporter-filter.png" alt="Filtered events in the Stackdriver Logging interface" width="500" >}}
+
+{{% /capture %}}