[zh] Fix links in zh localization (3)
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@@ -23,9 +23,9 @@ This page shows how to debug Pods and ReplicationControllers.
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<!--
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* You should be familiar with the basics of
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[Pods](/docs/concepts/workloads/pods/pod/) and [Pod Lifecycle](/docs/concepts/workloads/pods/pod-lifecycle/).
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[Pods](/docs/concepts/workloads/pods/) and [Pod Lifecycle](/docs/concepts/workloads/pods/pod-lifecycle/).
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-->
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* 你应该先熟悉 [Pods](/zh/docs/concepts/workloads/pods/pod/) 和
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* 你应该先熟悉 [Pods](/zh/docs/concepts/workloads/pods/) 和
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[Pod 生命周期](/zh/docs/concepts/workloads/pods/pod-lifecycle/) 的基础概念。
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<!-- steps -->
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@@ -20,7 +20,8 @@ This page explains how to debug Pods running (or crashing) on a Node.
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need that access to run the standard debug steps that use `kubectl`.
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-->
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* 你的 {{< glossary_tooltip text="Pod" term_id="pod" >}} 应该已经被调度并正在运行中,
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如果你的 Pod 还没有运行,请参阅[应用问题排查](/docs/tasks/debug-application-cluster/debug-application/)。
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如果你的 Pod 还没有运行,请参阅
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[应用问题排查](/zh/docs/tasks/debug-application-cluster/debug-application/)。
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* 对于一些高级调试步骤,你应该知道 Pod 具体运行在哪个节点上,在该节点上有权限去运行一些命令。
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你不需要任何访问权限就可以使用 `kubectl` 去运行一些标准调试步骤。
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@@ -147,7 +148,8 @@ images.
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## 使用临时容器来调试的例子 {#ephemeral-container-example}
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{{< note >}}
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本示例需要你的集群已经开启 `EphemeralContainers` [特性门控](/zh/docs/reference/command-line-tools-reference/feature-gates/),
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本示例需要你的集群已经开启 `EphemeralContainers`
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[特性门控](/zh/docs/reference/command-line-tools-reference/feature-gates/),
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`kubectl` 版本为 v1.18 或者更高。
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{{< /note >}}
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@@ -20,7 +20,7 @@ in the [Logging With Stackdriver Logging](/docs/user-guide/logging/stackdriver).
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-->
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在 Google Compute Engine (GCE) 平台上,默认的日志管理支持目标是
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[Stackdriver Logging](https://cloud.google.com/logging/),
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在[使用 Stackdriver Logging 管理日志](/docs/tasks/debug-application-cluster/logging-stackdriver/)
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在[使用 Stackdriver Logging 管理日志](/zh/docs/tasks/debug-application-cluster/logging-stackdriver/)
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中详细描述了这一点。
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<!--
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@@ -49,7 +49,8 @@ To use Elasticsearch and Kibana for cluster logging, you should set the
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following environment variable as shown below when creating your cluster with
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kube-up.sh:
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-->
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要使用 Elasticsearch 和 Kibana 处理集群日志,你应该在使用 kube-up.sh 脚本创建集群时设置下面所示的环境变量:
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要使用 Elasticsearch 和 Kibana 处理集群日志,你应该在使用 kube-up.sh
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脚本创建集群时设置下面所示的环境变量:
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```shell
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KUBE_LOGGING_DESTINATION=elasticsearch
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@@ -96,7 +97,7 @@ all be running in the kube-system namespace soon after the cluster comes to
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life.
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-->
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每个节点的 Fluentd Pod、Elasticsearch Pod 和 Kibana Pod 都应该在集群启动后不久运行在
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kube-system 命名空间中。
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kube-system 名字空间中。
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```shell
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kubectl get pods --namespace=kube-system
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@@ -137,8 +138,8 @@ and are not directly exposed via a publicly reachable IP address. To reach them,
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follow the instructions for [Accessing services running in a cluster](/docs/concepts/cluster-administration/access-cluster/#accessing-services-running-on-the-cluster).
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-->
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Elasticsearch 和 Kibana 服务都位于 `kube-system` 命名空间中,并且没有通过可公开访问的 IP 地址直接暴露。
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要访问它们,请参照
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Elasticsearch 和 Kibana 服务都位于 `kube-system` 名字空间中,并且没有通过
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可公开访问的 IP 地址直接暴露。要访问它们,请参照
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[访问集群中运行的服务](/zh/docs/tasks/access-application-cluster/access-cluster/#accessing-services-running-on-the-cluster)
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的说明进行操作。
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@@ -156,7 +157,8 @@ like. See [Elasticsearch's documentation](https://www.elastic.co/guide/en/elasti
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for more details on how to do so.
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-->
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现在你可以直接在浏览器中输入 Elasticsearch 查询,如果你愿意的话。
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请参考 [Elasticsearch 的文档](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-uri-request.html) 以了解这样做的更多细节。
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请参考 [Elasticsearch 的文档](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-uri-request.html)
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以了解这样做的更多细节。
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<!--
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Alternatively, you can view your cluster's logs using Kibana (again using the
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@@ -192,3 +194,4 @@ ideas on how to dig into it, check out [Kibana's documentation](https://www.elas
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-->
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Kibana 为浏览你的日志提供了各种强大的选项!有关如何深入研究它的一些想法,
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请查看 [Kibana 的文档](https://www.elastic.co/guide/en/kibana/current/discover.html)。
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@@ -367,7 +367,8 @@ log names:
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<!--
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You can learn more about viewing logs on [the dedicated Stackdriver page](https://cloud.google.com/logging/docs/view/logs_viewer).
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-->
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你可以在[专用 Stackdriver 页面](https://cloud.google.com/logging/docs/view/overview)上了解有关查看日志的更多信息。
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你可以在[Stackdriver 专用页面](https://cloud.google.com/logging/docs/view/overview)
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上了解有关查看日志的更多信息。
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<!--
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One of the possible ways to view logs is using the
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@@ -376,8 +377,11 @@ command line interface from the [Google Cloud SDK].
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It uses Stackdriver Logging [filtering syntax](https://cloud.google.com/logging/docs/view/advanced_filters)
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to query specific logs. For example, you can run the following command:
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-->
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查看日志的一种可能方法是使用 [Google Cloud SDK]((https://cloud.google.com/sdk/)) 中的 [`gcloud logging`](https://cloud.google.com/logging/docs/reference/tools/gcloud-logging) 命令行接口。
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它使用 Stackdriver 日志机制的[过滤语法](https://cloud.google.com/logging/docs/view/advanced_filters)查询特定日志。
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查看日志的一种可能方法是使用 [Google Cloud SDK](https://cloud.google.com/sdk/)
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中的 [`gcloud logging`](https://cloud.google.com/logging/docs/reference/tools/gcloud-logging)
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命令行接口。
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它使用 Stackdriver 日志机制的
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[过滤语法](https://cloud.google.com/logging/docs/view/advanced_filters)查询特定日志。
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例如,你可以运行以下命令:
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```none
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@@ -399,7 +403,8 @@ As you can see, it outputs messages for the count container from both
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the first and second runs, despite the fact that the kubelet already deleted
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the logs for the first container.
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-->
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如你所见,尽管 kubelet 已经删除了第一个容器的日志,日志中仍会包含 counter 容器第一次和第二次运行时输出的消息。
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如你所见,尽管 kubelet 已经删除了第一个容器的日志,日志中仍会包含 counter
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容器第一次和第二次运行时输出的消息。
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<!--
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### Exporting logs
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@@ -416,7 +421,8 @@ the Stackdriver [Exporting Logs page](https://cloud.google.com/logging/docs/expo
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你可以将日志导出到 [Google Cloud Storage](https://cloud.google.com/storage/) 或
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[BigQuery](https://cloud.google.com/bigquery/) 进行进一步的分析。
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Stackdriver 日志机制提供了接收器(Sink)的概念,你可以在其中指定日志项的存放地。
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可在 Stackdriver [导出日志页面](https://cloud.google.com/logging/docs/export/configure_export_v2)上获得更多信息。
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可在 Stackdriver [导出日志页面](https://cloud.google.com/logging/docs/export/configure_export_v2)
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上获得更多信息。
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<!--
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## Configuring Stackdriver Logging Agents
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@@ -453,14 +459,14 @@ If you're using GKE and Stackdriver Logging is enabled in your cluster, you
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cannot change its configuration, because it's managed and supported by GKE.
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However, you can disable the default integration and deploy your own.
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-->
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如果使用的是 GKE,并且集群中启用了 Stackdriver 日志机制,则无法更改其配置,因为它是由 GKE 管理和支持的。
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如果使用的是 GKE,并且集群中启用了 Stackdriver 日志机制,则无法更改其配置,
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因为它是由 GKE 管理和支持的。
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但是,你可以禁用默认集成的日志机制并部署自己的。
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<!--
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You will have to support and maintain a newly deployed configuration
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yourself: update the image and configuration, adjust the resources and so on.
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-->
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{{< note >}}
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你将需要自己支持和维护新部署的配置了:更新映像和配置、调整资源等等。
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{{< /note >}}
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@@ -478,7 +484,8 @@ gcloud beta container clusters update --logging-service=none CLUSTER
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You can find notes on how to then install Stackdriver Logging agents into
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a running cluster in the [Deploying section](#deploying).
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-->
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你可以在[部署部分](#deploying)中找到有关如何将 Stackdriver 日志代理安装到正在运行的集群中的说明。
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你可以在[部署部分](#deploying)中找到有关如何将 Stackdriver 日志代理安装到
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正在运行的集群中的说明。
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<!--
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### Changing `DaemonSet` parameters
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@@ -491,7 +498,8 @@ When you have the Stackdriver Logging `DaemonSet` in your cluster, you can just
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let's assume you've just installed the Stackdriver Logging as described above. Now you want to
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change the memory limit to give fluentd more memory to safely process more logs.
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-->
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当集群中有 Stackdriver 日志机制的 `DaemonSet` 时,你只需修改其 spec 中的 `template` 字段,daemonset 控制器将为你更新 pod。
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当集群中有 Stackdriver 日志机制的 `DaemonSet` 时,你只需修改其 spec 中的
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`template` 字段,daemonset 控制器将为你更新 Pod。
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例如,假设你按照上面的描述已经安装了 Stackdriver 日志机制。
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现在,你想更改内存限制,来给 fluentd 提供的更多内存,从而安全地处理更多日志。
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@@ -616,4 +624,6 @@ Fluentd 用 Ruby 编写,并允许使用 [plugins](https://www.fluentd.org/plug
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Then run `make build push` from this directory. After updating `DaemonSet` to pick up the
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new image, you can use the plugin you installed in the fluentd configuration.
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-->
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然后在该目录运行 `make build push`。在更新 `DaemonSet` 以使用新镜像后,你就可以使用在 fluentd 配置中安装的插件了。
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然后在该目录运行 `make build push`。
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在更新 `DaemonSet` 以使用新镜像后,你就可以使用在 fluentd 配置中安装的插件了。
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