[zh] Sync tasks/debug-application-cluster/resource-metrics-pipeline.md
This commit is contained in:
Qiming Teng
@@ -14,28 +14,29 @@ content_type: concept
|
||||
|
||||
<!--
|
||||
Resource usage metrics, such as container CPU and memory usage,
|
||||
are available in Kubernetes through the Metrics API. These metrics can be either accessed directly
|
||||
by user, for example by using `kubectl top` command, or used by a controller in the cluster, e.g.
|
||||
are available in Kubernetes through the Metrics API. These metrics can be accessed either directly
|
||||
by the user with the `kubectl top` command, or by a controller in the cluster, for example
|
||||
Horizontal Pod Autoscaler, to make decisions.
|
||||
-->
|
||||
资源使用指标，例如容器 CPU 和内存使用率，可通过 Metrics API 在 Kubernetes 中获得。
|
||||
这些指标可以直接被用户访问，比如使用 `kubectl top` 命令行，或者这些指标由集群中的控制器使用，
|
||||
例如，Horizontal Pod Autoscaler，使用这些指标来做决策。
|
||||
这些指标可以直接被用户访问，比如使用 `kubectl top` 命令行，或者被集群中的控制器
|
||||
（例如 Horizontal Pod Autoscalers) 使用来做决策。
|
||||
|
||||
<!-- body -->
|
||||
|
||||
<!--
|
||||
## The Metrics API
|
||||
|
||||
Through the Metrics API you can get the amount of resource currently used
|
||||
Through the Metrics API, you can get the amount of resource currently used
|
||||
by a given node or a given pod. This API doesn't store the metric values,
|
||||
so it's not possible for example to get the amount of resources used by a
|
||||
so it's not possible, for example, to get the amount of resources used by a
|
||||
given node 10 minutes ago.
|
||||
-->
|
||||
## Metrics API {#the-metrics-api}
|
||||
|
||||
通过 Metrics API，你可以获得指定节点或 Pod 当前使用的资源量。
|
||||
此 API 不存储指标值，因此想要获取某个指定节点 10 分钟前的资源使用量是不可能的。
|
||||
此 API 不存储指标值，因此想要获取某个指定节点 10 分钟前的
|
||||
资源使用量是不可能的。
|
||||
|
||||
<!--
|
||||
The API is no different from any other API:
|
||||
@@ -43,12 +44,12 @@ The API is no different from any other API:
|
||||
此 API 与其他 API 没有区别：
|
||||
|
||||
<!--
|
||||
- it is discoverable through the same endpoint as the other Kubernetes APIs under `/apis/metrics.k8s.io/` path
|
||||
- it offers the same security, scalability and reliability guarantees
|
||||
- it is discoverable through the same endpoint as the other Kubernetes APIs under the path: `/apis/metrics.k8s.io/`
|
||||
- it offers the same security, scalability, and reliability guarantees
|
||||
-->
|
||||
- 此 API 和其它 Kubernetes API 一起位于同一端点（endpoint）之下，是可发现的，
|
||||
- 此 API 和其它 Kubernetes API 一起位于同一端点（endpoint）之下且可发现，
|
||||
路径为 `/apis/metrics.k8s.io/`
|
||||
- 它提供相同的安全性、可扩展性和可靠性保证
|
||||
- 它具有相同的安全性、可扩展性和可靠性保证
|
||||
|
||||
<!--
|
||||
The API is defined in [k8s.io/metrics](https://github.com/kubernetes/metrics/blob/master/pkg/apis/metrics/v1beta1/types.go)
|
||||
@@ -69,7 +70,11 @@ Metrics API 需要在集群中部署 Metrics Server。否则它将不可用。
|
||||
|
||||
### CPU
|
||||
|
||||
CPU is reported as the average usage, in [CPU cores](/docs/concepts/configuration/manage-compute-resources-container/#meaning-of-cpu), over a period of time. This value is derived by taking a rate over a cumulative CPU counter provided by the kernel (in both Linux and Windows kernels). The kubelet chooses the window for the rate calculation.
|
||||
CPU is reported as the average usage, in
|
||||
[CPU cores](/docs/concepts/configuration/manage-resources-containers/#meaning-of-cpu),
|
||||
over a period of time. This value is derived by taking a rate over a cumulative CPU counter
|
||||
provided by the kernel (in both Linux and Windows kernels).
|
||||
The kubelet chooses the window for the rate calculation.
|
||||
-->
|
||||
## 度量资源用量 {#measuring-resource-usage}
|
||||
|
||||
@@ -80,6 +85,15 @@ CPU 用量按其一段时间内的平均值统计，单位为
|
||||
此度量值通过在内核（包括 Linux 和 Windows）提供的累积 CPU 计数器乘以一个系数得到。
|
||||
`kubelet` 组件负责选择计算系数所使用的窗口大小。
|
||||
|
||||
<!--
|
||||
### Memory
|
||||
|
||||
Memory is reported as the working set, in bytes, at the instant the metric was collected.
|
||||
In an ideal world, the "working set" is the amount of memory in-use that cannot be freed under memory pressure.
|
||||
However, calculation of the working set varies by host OS, and generally makes heavy use of heuristics to produce an estimate.
|
||||
It includes all anonymous (non-file-backed) memory since Kubernetes does not support swap.
|
||||
The metric typically also includes some cached (file-backed) memory, because the host OS cannot always reclaim such pages.
|
||||
-->
|
||||
### 内存 {#memory}
|
||||
|
||||
内存用量按工作集（Working Set）的大小字节数统计，其数值为收集度量值的那一刻的内存用量。
|
||||
@@ -94,37 +108,35 @@ CPU 用量按其一段时间内的平均值统计，单位为
|
||||
<!--
|
||||
## Metrics Server
|
||||
|
||||
[Metrics Server](https://github.com/kubernetes-incubator/metrics-server) is a cluster-wide aggregator of resource usage data.
|
||||
Starting from Kubernetes 1.8 it's deployed by default in clusters created by `kube-up.sh` script
|
||||
[Metrics Server](https://github.com/kubernetes-sigs/metrics-server) is a cluster-wide aggregator of resource usage data.
|
||||
By default, it is deployed in clusters created by `kube-up.sh` script
|
||||
as a Deployment object. If you use a different Kubernetes setup mechanism you can deploy it using the provided
|
||||
[deployment yamls](https://github.com/kubernetes-incubator/metrics-server/tree/master/deploy).
|
||||
It's supported in Kubernetes 1.7+ (see details below).
|
||||
[deployment components.yaml](https://github.com/kubernetes-sigs/metrics-server/releases) file.
|
||||
-->
|
||||
## Metrics 服务器 {#metrics-server}
|
||||
|
||||
[Metrics 服务器](https://github.com/kubernetes-incubator/metrics-server)是集群范围资源使用数据的聚合器。
|
||||
在由 `kube-up.sh` 脚本创建的集群中默认会以 Deployment 的形式被部署。
|
||||
[Metrics 服务器](https://github.com/kubernetes-sings/metrics-server)
|
||||
是集群范围资源用量数据的聚合器。
|
||||
默认情况下，在由 `kube-up.sh` 脚本创建的集群中会以 Deployment 的形式被部署。
|
||||
如果你使用其他 Kubernetes 安装方法，则可以使用提供的
|
||||
[deployment yamls](https://github.com/kubernetes-incubator/metrics-server/tree/master/deploy)
|
||||
[部署组件 components.yaml](https://github.com/kubernetes-incubator/metrics-server/tree/master/deploy)
|
||||
来部署。
|
||||
|
||||
<!--
|
||||
Metric server collects metrics from the Summary API, exposed by [Kubelet](/docs/admin/kubelet/) on each node.
|
||||
Metric server collects metrics from the Summary API, exposed by
|
||||
[Kubelet](/docs/reference/command-line-tools-reference/kubelet/) on each node, and is registered with the main API server via
|
||||
[Kubernetes aggregator](/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/).
|
||||
-->
|
||||
Metric server 从每个节点上的 [Kubelet](/zh/docs/reference/command-line-tools-reference/kubelet/)
|
||||
Metric 服务器从每个节点上的 [kubelet](/zh/docs/reference/command-line-tools-reference/kubelet/)
|
||||
公开的 Summary API 中采集指标信息。
|
||||
该 API 通过
|
||||
[Kubernetes 聚合器](/zh/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/)
|
||||
注册到主 API 服务器上。
|
||||
|
||||
<!--
|
||||
Metrics Server registered in the main API server through
|
||||
[Kubernetes aggregator](/docs/concepts/api-extension/apiserver-aggregation/),
|
||||
which was introduced in Kubernetes 1.7.
|
||||
Learn more about the metrics server in
|
||||
[the design doc](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/metrics-server.md).
|
||||
-->
|
||||
Metrics 服务器通过
|
||||
[Kubernetes 聚合器](/zh/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/)
|
||||
注册到主 API 服务器。
|
||||
|
||||
<!--
|
||||
Learn more about the metrics server in [the design doc](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/metrics-server.md).
|
||||
-->
|
||||
在[设计文档](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/metrics-server.md)中可以了解到有关 Metrics 服务器的更多信息。
|
||||
在[设计文档](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/metrics-server.md)
|
||||
中可以了解到有关 Metrics 服务器的更多信息。
|
||||
|
||||
|
||||
Reference in New Issue
Block a user