diff --git a/docs/document/content/features/governance/observability/metrics.cn.md b/docs/document/content/features/governance/observability/metrics.cn.md
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@@ -3,4 +3,65 @@
 weight = 2
 +++
 
-TODO
+## 背景
+`Metrics` 是一种评估系统在运行时的度量指标，通常一组度量指标可以帮助我们评估系统性能，为系统优化或业务策略给出相关的意见。
+Apache ShardingSphere 旨在打造一款分布式数据库解决方案，而对于数据库来说，分析它的运行状态，连接数据，事务数，吞吐量等相关指标，
+为数据库的调度，数据平滑迁移，分库分表等策略提供可视化的建议与帮助尤为重要。
+
+## 方案
+
+Apache ShardingSphere 遵循`Metrics`标准，定义了一套可插拔的`SPI` 标准，它并不存储,收集,展现 `Metrics`信息，
+只是负责在程序中对`Metrics` 进行埋点，目前默认的实现方案为:`Prometheus` 客户端API埋点，服务端通过
+`http` 协议来定时抓取`Metrics`数据。
+
+![流程图](https://shardingsphere.apache.org/document/current/img/control-pannel/metrics/metrics.png)
+
+## 指标
+
+目前定义了4种类型的指标
+
+ * Counter : 计数器是一个累积度量，它表示单个单调递增的计数器，其值在重新启动时只能增加或重置为零。
+ 
+ * Gauge : 仪表盘是一种度量标准，它表示一个可以任意上下移动的数值。
+
+ * Histogram : 直方图对观察结果(通常是请求持续时间或响应大小等)进行采样，并按可配置的桶进行计数。它还提供了所有观测值的和。
+ 
+ * Summary : 摘要是类似于柱状图的观察结果(通常是请求持续时间和响应大小之类的内容)。虽然它还提供了观察值的总数和所有观察值的总和，但它计算了一个滑动时间窗口上的可配置分位数。
+ 
+ |名称                       | 类型                  |标签名称       | 说明                  |
+ |:------------------------ |:--------------------- |:-------------|:-------------------- |
+ |request_total             |Counter                | 无           |收集ShardingSphere所有的请求 |
+ |sql_statement_count       |Counter                | sql_type     |收集执行的SQL类型,比如 (SELECT,UPDATE,INSERT...)| 
+ |channel_count             |Gauge                  | 无           |收集ShardingSphere-Proxy的连接数               | 
+ |requests_latency_histogram_millis |Histogram      | 无            |收集执行所有请求的迟延时间(单位:ms)              | 
+ |sharding_datasource       |Counter                | datasource   |收集执行SQL语句命中的分库                       | 
+ |sharding_table            |Counter                | table        |收集执行SQL语句命中的分表                       | 
+ |transaction               |Counter                | status       |收集所有的事务数量                              | 
+
+## 使用
+在ShardingSphere-Proxy 的server.yaml文件中新增以下配置:
+
+```yaml
+metrics:
+   name: prometheus # 指定类型为prometheus.
+   host:  127.0.0.1 # 指定host,如果为空，则获取默认
+   port:  9190  # 指定prometheus服务端抓取metrics端口
+props:
+  proxy.metrics.enabled: ture  # 设置为true代表开启，设置为false 代表关闭
+```
+
+用户自己搭建`Prometheus` 服务，在 prometheus.yml 文件中新增如下配置:
+
+```yaml
+scrape_configs:
+  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
+  - job_name: 'shardingSphere-proxy'
+    # metrics_path defaults to '/metrics'
+    # scheme defaults to 'http'.
+    static_configs:
+    - targets: ['localhost:9190']
+```
+
+## 面板
+
+推荐使用 `Granfana`，用户可以自定义查询来个性化显示面板盘，后续我们会提供默认的面板盘配置。
diff --git a/docs/document/content/features/governance/observability/metrics.en.md b/docs/document/content/features/governance/observability/metrics.en.md
index 04d6730..3c625bf 100644
--- a/docs/document/content/features/governance/observability/metrics.en.md
+++ b/docs/document/content/features/governance/observability/metrics.en.md
@@ -3,4 +3,69 @@
 weight = 2
 +++
 
-TODO
+## Background
+
+Metrics are measures of used to evaluate the performance of a system at run time. 
+Quantitative assessment can be used to evaluate the performance of a system and to give relevant opinions on system optimization or business strategy.
+Apache ShardingSphere aims to build a distributed database solution. 
+For the database,it analyzes its running status,connection data,transaction number,throughput and other relevant indicators.
+It is particularly important to provide visual advice and help for database scheduling,data smooth migration,sharding-database,sharding-table and other policies.
+
+## Plan
+
+Apache ShardingSphere follows the Metrics standard, which defines a pluggable SPI standard that does not store, collect, or display Metrics information,
+It is only responsible for embedding Metrics in the program. Currently, the default implementation scheme is: Prometheus client API burial point, through which the service side passes
+HTTP protocol to periodically grab Metrics data.
+
+![the follow image](https://shardingsphere.apache.org/document/current/img/control-pannel/metrics/metrics.png)
+
+## Metrics indicators
+
+Four types of metrics are currently defined.
+
+ * Counter : A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart.
+ 
+ * Gauge : A gauge is a metric that represents a single numerical value that can arbitrarily go up and down.
+
+ * Histogram : A histogram samples observations (usually things like request durations or response sizes) and counts them in configurable buckets. It also provides a sum of all observed values.
+ 
+ * Summary : Similar to a histogram, a summary samples observations (usually things like request durations and response sizes). While it also provides a total count of observations and a sum of all observed values, it calculates configurable quantiles over a sliding time window.
+ 
+ |name                      | type                  |labelName       | description                  |
+ |:------------------------ |:--------------------- |:-------------|:-------------------- |
+ |request_total             |Counter                |            |Collect all request of ShardingSphere-Proxy |
+ |sql_statement_count       |Counter                | sql_type     |Collect all the types of SQL , example (SELECT,UPDATE,INSERT...)| 
+ |channel_count             |Gauge                  |            |Collect all the connection number of ShardingSphere-Proxy               | 
+ |requests_latency_histogram_millis |Histogram      |            |Collect all the request latency time(ms)           | 
+ |sharding_datasource       |Counter                | datasource   |Collect all the sql sharding datasource                      | 
+ |sharding_table            |Counter                | table        |Collect all the sql sharding table                       | 
+ |transaction               |Counter                | status       |Collect all the sql transaction    
+ 
+ ## Use
+ 
+ Add the following configuration to the server.yaml file of ShardingSphere-Proxy:
+ 
+ ```yaml
+ metrics:
+    name: prometheus # The specified type is Prometheus..
+    host:  127.0.0.1 # Specify host and, if empty, get the default of ShardingSphere-Proxy
+    port:  9190  # Specify the Prometheus server fetching metrics port
+ props:
+   proxy.metrics.enabled: ture  # true for on and false for off
+ ```
+ 
+Users set up the Prometheus service by themselves, adding the following configuration in the prometheus.yml file:
+ 
+ ```yaml
+ scrape_configs:
+   # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
+   - job_name: 'shardingSphere-proxy'
+     # metrics_path defaults to '/metrics'
+     # scheme defaults to 'http'.
+     static_configs:
+     - targets: ['localhost:9190']
+ ```
+
+ ## Dashboard
+ 
+It is recommended to use Granfana. Users can customize the query to personalize the panel panel. Later we will provide the default panel panel configuration.
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