Merge pull request #178 from helight/zh-translation-reference-metrics

zh-translation:/reference/metrics.md

docs/book/src/reference/metrics.md

@@ -1,68 +1,49 @@
-# Metrics
+# 指标
 
-By default, controller-runtime builds a global prometheus registry and
-publishes a collection of performance metrics for each controller.
+默认情况下，controller-runtime 会构建一个全局 prometheus 注册，并且会为每个控制器发布一系列性能指标。
 
-## Protecting the Metrics
+## 指标保护
 
-These metrics are protected by [kube-auth-proxy](https://github.com/brancz/kube-rbac-proxy)
-by default if using kubebuilder. Kubebuilder v2.2.0+ scaffold a clusterrole which
-can be found at `config/rbac/auth_proxy_client_clusterrole.yaml`.
+如果使用了 kubebuilder [kube-auth-proxy](https://github.com/brancz/kube-rbac-proxy) 默认会保护这些指标。Kubebuilder v2.2.0+ 会创建一个集群角色，它在 `config/rbac/auth_proxy_client_clusterrole.yaml` 文件中配置。
 
-You will need to grant permissions to your Prometheus server so that it can
-scrape the protected metrics. To achieve that, you can create a
-`clusterRoleBinding` to bind the `clusterRole` to the service account that your
-Prometheus server uses.
+你需要给你所有的 Prometheus 服务授权，以便它可以拿到这些被保护的指标。为实现授权，你可以创建一个 `clusterRoleBinding` 把 `clusterRole` 绑定到一个你的 Prometheus 服务使用的账户上。
 
-You can run the following kubectl command to create it. If using kubebuilder
-`<project-prefix>` is the `namePrefix` field in `config/default/kustomization.yaml`.
+可以运行下面的 kubectl 命令来创建它。如果你使用 kubebuilder，在`config/default/kustomization.yaml` 文件中 `namePrefix` 字段是 `<project-prefix>`。
 
 ```bash
 kubectl create clusterrolebinding metrics --clusterrole=<project-prefix>-metrics-reader --serviceaccount=<namespace>:<service-account-name>
 ```
 
-## Exporting Metrics for Prometheus
+## 给 Prometheus 导出指标
+按照下面的步骤来用 Prometheus Operator 导出指标：
 
-Follow the steps below to export the metrics using the Prometheus Operator:
-
-1. Install Prometheus and Prometheus Operator.
-We recommend using [kube-prometheus](https://github.com/coreos/kube-prometheus#installing) 
-in production if you don't have your own monitoring system.
-If you are just experimenting, you can only install Prometheus and Prometheus Operator.
-2. Uncomment the line `- ../prometheus` in the `config/default/kustomization.yaml`.
-It creates the `ServiceMonitor` resource which enables exporting the metrics.
+1. 安装 Prometheus 和 Prometheus Operator。如果没有自己的监控系统，在生产环境上我们推荐使用 [kube-prometheus](https://github.com/coreos/kube-prometheus#installing)。如果你只是做实验，那么可以只安装 Prometheus 和 Prometheus Operator。
+2. 在 `config/default/kustomization.yaml` 配置文件中取消 `- ../prometheus` 这一行的注释。它会创建可以导出指标的 `ServiceMonitor` 资源。
 
 ```yaml
-# [PROMETHEUS] To enable prometheus monitor, uncomment all sections with 'PROMETHEUS'.
+# [PROMETHEUS] 用于启用 prometheus 监控, 取消所有带 'PROMETHEUS' 部分的注释。
 - ../prometheus
 ```
 
-Note that, when you install your project in the cluster, it will create the
-`ServiceMonitor` to export the metrics. To check the ServiceMonitor, 
-run `kubectl get ServiceMonitor -n <project>-system`. See an example:
+注意，当你在集群中安装你的项目时，它会创建一个 `ServiceMonitor` 来导出指标。为了检查 ServiceMonitor，可以运行 `kubectl get ServiceMonitor -n <project>-system`。看下面的例子：
 
 ```
-$ kubectl get ServiceMonitor -n monitor-system 
+$ kubectl get ServiceMonitor -n monitor-system
 NAME                                         AGE
 monitor-controller-manager-metrics-monitor   2m8s
 ```
 
-Also, notice that the metrics are exported by default through port `8443`. In this way,
-you are able to check the Prometheus metrics in its dashboard. To verify it, search 
-for the metrics exported from the namespace where the project is running 
-`{namespace="<project>-system"}`. See an example: 
+同样，要注意默认情况下是通过 `8443` 端口导出指标的。这种情况下，你可以在自己的 dashboard 中检查 Prometheus metrics。要检查这些指标，在项目运行的 `{namespace="<project>-system"}` 命名空间下搜索导出的指标。看下面的例子：
 
-<img width="1680" alt="Screenshot 2019-10-02 at 13 07 13" src="https://user-images.githubusercontent.com/7708031/66042888-a497da80-e515-11e9-9d77-d8a9fc1159a5.png">  
+<img width="1680" alt="Screenshot 2019-10-02 at 13 07 13" src="https://user-images.githubusercontent.com/7708031/66042888-a497da80-e515-11e9-9d77-d8a9fc1159a5.png">
 
-## Publishing Additional Metrics
+## 发布额外的指标：
 
-If you wish to publish additional metrics from your controllers, this
-can be easily achieved by using the global registry from
-`controller-runtime/pkg/metrics`.
+如果你想从你的控制器发布额外的指标，可以通过在 `conoller-runtime/pkg/metrics` 中使用全局注册的方式来轻松做到。
 
-One way to achieve this is to declare your collectors as global variables and then register them using `init()`.
+实现发布额外指标的一种方式是把收集器声明为全局变量，并且使用 `init()` 来注册。
 
-For example:
+例如：
 
 ```go
 import (
@@ -91,6 +72,4 @@ func init() {
 }
 ```
 
-You may then record metrics to those collectors from any part of your
-reconcile loop, and those metrics will be available for prometheus or
-other openmetrics systems to scrape.
+然后就可以从你的接收循环部分中记录这些指标到收集器中了，并且这些指标就可以被 prometheus 或者其它开放指标系统来抓取了。