sync resource-usage-monitoring.md

sync resource-usage-monitoring.md

content/zh-cn/docs/tasks/debug/debug-cluster/resource-usage-monitoring.md

@@ -108,6 +108,40 @@ Kubernetes 还可以根据集群的当前状态，使用 Pod 水平自动扩缩
 监控管道从 kubelet 获取度量值，然后通过适配器将它们公开给 Kubernetes，
 方法是实现 `custom.metrics.k8s.io` 或 `external.metrics.k8s.io` API。
 
+<!--
+Kubernetes is designed to work with [OpenMetrics](https://openmetrics.io/), 
+which is one of the
+[CNCF Observability and Analysis - Monitoring Projects](https://landscape.cncf.io/card-mode?category=monitoring&project=graduated,incubating,member,no&grouping=category&sort=stars),
+built upon and carefully extending [Prometheus exposition format](https://prometheus.io/docs/instrumenting/exposition_formats/)
+in almost 100% backwards-compatible ways.
+-->
+Kubernetes 在设计上保证能够与 [OpenMetrics](https://openmetrics.io/) 一同使用，
+OpenMetrics 是 
+[CNCF 可观测性和分析 - 监控项目](https://landscape.cncf.io/card-mode?category=monitoring&project=graduated,incubating,member,no&grouping=category&sort=stars)之一，
+它构建于 [Prometheus 暴露格式](https://prometheus.io/docs/instrumenting/exposition_formats/)之上，
+并对其进行了扩展，这些扩展几乎 100% 向后兼容。
+
+<!--
+If you glance over at the
+[CNCF Landscape](https://landscape.cncf.io/card-mode?category=monitoring&project=graduated,incubating,member,no&grouping=category&sort=stars), 
+you can see a number of monitoring projects that can work with Kubernetes by _scraping_
+metric data and using that to help you observe your cluster. It is up to you to select the tool
+or tools that suit your needs. The CNCF landscape for observability and analytics includes a
+mix of open-source software, paid-for software-as-a-service, and other commercial products.
+-->
+如果你浏览 [CNCF Landscape](https://landscape.cncf.io/card-mode?category=monitoring&project=graduated,incubating,member,no&grouping=category&sort=stars)，
+你可以看到许多监控项目，它们可以用在 Kubernetes 上，**抓取**指标数据并利用这些数据来观测你的集群，
+选择哪种工具或哪些工具可以满足你的需求，这完全取决于你自己。 
+CNCF 的可观测性和分析景观包括了各种开源软件、付费的软件即服务（SaaS）以及其他混合商业产品。
+
+<!--
+When you design and implement a full metrics pipeline you can make that monitoring data
+available back to Kubernetes. For example, a HorizontalPodAutoscaler can use the processed
+metrics to work out how many Pods to run for a component of your workload.
+-->
+当你设计和实现一个完整的指标监控数据管道时，你可以将监控数据反馈给 Kubernetes。
+例如，HorizontalPodAutoscaler 可以使用处理过的指标数据来计算出你的工作负载组件运行了多少个 Pod。
+
 <!--
 Integration of a full metrics pipeline into your Kubernetes implementation is outside
 the scope of Kubernetes documentation because of the very wide scope of possible