diff --git a/src/zh/guide/deploy_cluster/deploy_cluster_manual.md b/src/zh/guide/deploy_cluster/deploy_cluster_manual.md
index a1fc2560..8fe00b93 100644
--- a/src/zh/guide/deploy_cluster/deploy_cluster_manual.md
+++ b/src/zh/guide/deploy_cluster/deploy_cluster_manual.md
@@ -3,244 +3,522 @@ title: 手动部署
 order: 2
 ---
 
-::: info
-此文档旨在探索手动部署需要部署哪些组件，对熟悉 openGemini 集群工作原理有所帮助。
-:::
-
-集群部署可以把openGemini的三个组件都部署在一个节点上，也可以把组件分散部署在多个节点上。
-
-下载二进制包，参考[安装部署](../quick_start/get_started.md#二进制下载)
-## 部署伪集群
-
-把openGemini集群的所有组件都部署在同一个节点上，这种集群部署方式我们称之为伪集群部署。  
-目前社区提供了部署脚本install_cluster.sh。
-
-```shell
-> sh scripts/install_cluster.sh
-```
-:::tip
-执行该命令，在不修改配置文件的前提下，可直接在本地拉起一个openGemini集群，包括1个ts-sql、3个ts-meta和2个ts-store组件。但该集群仅在本地回环地址127.0.0.1上监听运行，可用于本地功能测试和学习，不能对外提供访问服务。
-:::
-若要让集群监听本机IP，让外部节点可以访问，配置上相对要复杂一点，虽然可行，但在生产环境中不推荐。  
-同样以部署1个ts-sql、3个ts-meta和2个ts-store组成的集群为例。
-
-### 分配端口
-所有节点均监听本机IP地址，如192.168.0.1，所以所有组件之间不能使用相同的端口，需重新分配。可以做如下分配（参考）： 
-
-![](../../../../static/img/guide/reference/single_node_cluster.png)
-
-### 配置文件修改
-openGemini的集群配置项都集中在openGemini.conf文件中，我们进行集群配置时，如果在同一个节点上只部署一个ts-meta、一个ts-sql和一个ts-store，或者合部其中两个或一个组件，不存在相同组件部署在同一个节点上的情况(因为没有IP和端口冲突)，则可以考虑在该节点上所有组件共用一个配置文件openGemini.conf
-
-显然部署伪集群是不能共用一个，因为在同一个节点上有3个ts-meta，2个ts-store，因为IP会有冲突，所以我们建议为每个组件对应一个配置文件。具体做法如下：
-```
-> cp –rf openGemini.conf sql.conf
-> cp –rf openGemini.conf meta-1.conf
-> cp –rf openGemini.conf meta-2.conf
-> cp –rf openGemini.conf meta-3.conf
-> cp –rf openGemini.conf store-1.conf
-> cp –rf openGemini.conf store-2.conf
-```
-**修改sql.conf，仅修改如下部分即可，本地IP地址以192.168.0.1为例**
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.1:8094", "192.168.0.1:8096"]
-[http]
-bind-address = "192.168.0.1:8086"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-```
-**修改meta-1.conf，仅修改如下部分即可**
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.1:8094", "192.168.0.1:8096"]
-[meta]
-bind-address = "192.168.0.1:8088"
-http-bind-address = "192.168.0.1:8091"
-rpc-bind-address = "192.168.0.1:8092"
-// 预防/tmp空间不足，建议替换/tmp目录
-dir = "/path/to/openGemini/data/meta/1"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-[gossip]
-bind-address = "192.168.0.1"
-meta-bind-port = 8010
-members = ["192.168.0.1:8010", "192.168.0.1:8012", "192.168.0.1:8013"]
-```
-**修改meta-2.conf，仅修改如下部分即可**
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.1:8094", "192.168.0.1:8096"]
-[meta]
-bind-address = "192.168.0.1:8089"
-http-bind-address = "192.168.0.1:8093"
-rpc-bind-address = "192.168.0.1:8094"
-// 预防/tmp空间不足，建议替换/tmp目录
-dir = "/path/to/openGemini/data/meta/2"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-[gossip]
-bind-address = "192.168.0.1"
-meta-bind-port = 8012
-members = ["192.168.0.1:8010", "192.168.0.1:8012", "192.168.0.1:8013"]
-```
-**修改meta-3.conf，仅修改如下部分即可**
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.1:8094", "192.168.0.1:8096"]
-[meta]
-bind-address = "192.168.0.1:8090"
-http-bind-address = "192.168.0.1:8095"
-rpc-bind-address = "192.168.0.1:8096"
-// 为防/tmp空间不足，建议替换/tmp目录
-dir = "/path/to/openGemini/data/meta/3"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-[gossip]
-bind-address = "192.168.0.1"
-meta-bind-port = 8013
-members = ["192.168.0.1:8010", "192.168.0.1:8012", "192.168.0.1:8013"]
-```
-**修改store-1.conf，仅修改如下部分即可，为防/tmp空间不足，建议替换/tmp目录**
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.1:8094", "192.168.0.1:8096"]
-[data]
-store-ingest-addr = "192.168.0.1:8400"
-store-select-addr = "192.168.0.1:8401"
-store-data-dir = "/path/to/openGemini/data/1"
-store-wal-dir = "/path/to/openGemini/data/1"
-store-meta-dir = "/path/to/openGemini/data/meta/1"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-[gossip]
-bind-address = "192.168.0.1"
-store-bind-port = 8011
-members = ["192.168.0.1:8010", "192.168.0.1:8012", "192.168.0.1:8013"]
-```
-**修改store-2.conf，仅修改如下部分即可**
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.1:8094", "192.168.0.1:8096"]
-[data]
-store-ingest-addr = "192.168.0.1:8402"
-store-select-addr = "192.168.0.1:8403"
-store-data-dir = "/path/to/openGemini/data/2"
-store-wal-dir = "/path/to/openGemini/data/2"
-store-meta-dir = "/path/to/openGemini/data/meta/2"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-[gossip]
-bind-address = "192.168.0.1"
-store-bind-port = 8014
-members = ["192.168.0.1:8010", "192.168.0.1:8012", "192.168.0.1:8013"]
-```
-**如果还需要新增ts-store,可按照该配置，更换一下端口，再拉起即可**
-
-### 拉起集群
-编辑脚本
-```
-> cp –rf scripts/install_cluster.sh  scripts/cluster.sh
-> vim scripts/cluster.sh
-```
-删除或注释cluster.sh脚本的第27-38行内容
-```
-# delete the following rows
-for((i = 1; i <= 3; i++))
-do
-rm -rf config/openGemini-$i.conf
-cp config/openGemini.conf config/openGemini-$i.conf
-sed -i "s/{{meta_addr_1}}/${nodes[1]}/g" config/openGemini-$i.conf
-sed -i "s/{{meta_addr_2}}/${nodes[2]}/g" config/openGemini-$i.conf
-sed -i "s/{{meta_addr_3}}/${nodes[3]}/g" config/openGemini-$i.conf
-sed -i "s/{{addr}}/${nodes[$i]}/g" config/openGemini-$i.conf
-
-sed -i "s/{{id}}/$i/g" config/openGemini-$i.conf
-done
-```
-然后再修改下启动命令中的配置文件和相关的日志目录
-```
-nohup build/ts-meta -config config/openGemini -1.conf -pidfile /tmp/openGemini/pid/meta1.pid > /tmp/openGemini/logs/1/meta_extra1.log 2>&1 &
-```
-改为
-```
-nohup build/ts-meta -config config/meta-1.conf -pidfile /path/openGemini/pid/meta1.pid > /path/openGemini/logs/1/meta_extra1.log 2>&1 &
-```
-以此类推
-
-修改完成，执行命令,便可拉起伪集群
-```
-> sh scripts/cluster.sh
-```
-
-## 标准集群部署
-
-openGemini集群拓扑图如下所示，集群有ts-meta (3x), ts-sql (2x), ts-store (2x)：
-
-![](../../../../static/img/guide/reference/cluster.png)
-
-这种部署方式，不存在两个相同组件被部署在同一个节点之上，没有端口竞争，则可以让同一个节点上的所有组件共用一个配置文件。
-
-以Node1：192.168.0.1为例，仅需修改配置文件openGemini.conf如下内容：
-
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.2:8092", "192.168.0.3:8092"]
-[meta]
-bind-address = "192.168.0.1:8088"
-http-bind-address = "192.168.0.1:8091"
-rpc-bind-address = "192.168.0.1:8092"
-# 建议修改目录
-dir = "/path/openGemini/data/meta/1"
-[http]
-bind-address = "192.168.0.1:8086"
-[data]
-store-ingest-addr = "192.168.0.1:8400"
-store-select-addr = "192.168.0.1:8401"
-# 建议修改目录
-store-data-dir = "/path/openGemini/data/1"
-store-wal-dir = "/path/openGemini/data/1"
-store-meta-dir = "/path/openGemini/data/meta/1"
-[logging]
-# 建议修改目录
-path = "/path/openGemini/logs"
-[gossip]
-bind-address = "192.168.0.1"
-store-bind-port = 8011
-meta-bind-port = 8010
-members = ["192.168.0.1:8010", "192.168.0.2:8010", "192.168.0.3:8010"]
-```
-Node2，Node3的配置文件，如下这些配置与Node1的配置文件保持一样：
-```
-[common]
-meta-join = ["192.168.0.1:8092", "192.168.0.2:8092", "192.168.0.3:8092"]
-[gossip]
-store-bind-port = 8011
-meta-bind-port = 8010
-members = ["192.168.0.1:8010", "192.168.0.2:8010", "192.168.0.3:8010"]
-```
-其他配置项的IP地址分别替换为Node2的IP(192.168.0.2) 和 Node3的IP(192.168.0.3) 即可，端口可以不用修改。
-:::tip
-openGemini拉起集群时对组件启动顺序有要求
-:::
-先启动所有三个节点之上的ts-meta组件（命令示例）：
-
-```
-> nohup ts-meta --config openGemini.conf -pidfile meta.pid > meta_extra.log 2>&1 &
-```
-然后启动ts-store组件（命令示例）：
-```
-> nohup ts-store --config openGemini.conf -pidfile store.pid > store_extra.log 2>&1 &
-```
-最后启动ts-sql组件（命令示例）：
-```
-> nohup ts-sql --config openGemini.conf -pidfile sql.pid > sql_extra.log 2>&1 &
-```
-客户端连接，参考 [ts-cli命令行](../quick_start/get_started.md#连接数据库-ts-cli)
 
+
+本教程分为5个部分，分别是
+
+1. 集群安装
+2. 搭建监控
+3. 压测（TSBS）
+4. 压测（手写工具）
+5. 性能调优
+
+## 安装
+
+这里只介绍集群安装部署，因为单机可直接运行`ts-server --config path/to/openGemini.singlenode.conf`即可。部署openGemini集群需要的组件有：
+
+- ts-sql，计算组件
+- ts-store，存储组件
+- ts-meta，集群元数据管理组件
+- ts-monitor，内核监控组件（在后面搭建监控部分介绍）
+
+1. ### 准备安装包
+
+   - 二进制下载地址：https://github.com/openGemini/openGemini/releases
+
+   - 源码编译(Linux 平台)，需要提前准备好编译环境
+
+     - [GO](https://go.dev/dl/) version v1.22+
+     - [Python](https://www.python.org/downloads/) version v3.7+
+
+     ```
+     > git clone https://github.com/openGemini/openGemini.git
+     > cd openGemini
+     > Python3 build.py
+     # 编译后的二进制在build目录
+     > cd build && ls
+     ts-data  ts-meta  ts-monitor  ts-recover  ts-server  ts-sql  ts-store
+     ```
+
+2. ### 规划网络拓扑
+
+   ![image-20250316165755673](../../../../static/img/guide/deploy_cluster/image-20250316165755673.png)
+
+   如上图所示，1台作为性能测试的执行机，同时也作为openGemini集群的监控服务器。其余3台部署openGemini集群（配置3副本需至少3节点），ts-sql可以部署多个，这里我们以部署1个ts-sql为例。
+
+3. ### 安装和配置
+
+   建议手动部署，不建议使用Gemix工具，因为：
+
+   - Gemix需要联网，多数环境在内网
+   - 工具生成的默认配置项太少
+   - 不稳定（缺少维护）
+
+   这里我们介绍`192.168.0.38`节点配置，**同一节点上的ts-sql、ts-meta、ts-store三个组件可以共用一个配置文件`openGemini.conf`**，其他节点照葫芦画瓢。
+
+   打开`openGemini.conf`，仅配置如下地方：
+
+   ```toml
+   [common]
+     meta-join = ["192.168.0.38:8092", "192.168.0.248:8092", "192.168.0.210:8092"]
+     # 多副本配置“replication”，非副本保持默认即可
+     ha-policy = "replication"
+     pprof-enabled = true
+   ```
+
+   ```toml
+   # 配置ts-meta
+   [meta]
+     bind-address = "192.168.0.38:8088"
+     http-bind-address = "192.168.0.38:8091"
+     rpc-bind-address = "192.168.0.38:8092"
+     dir = "/path/to/openGemini/data/meta"
+     # 如果机器规格高，ptnum-pernode可以配置3或者4，pt越多，占用系统资源越多。单机或者非3副本情况下，建议为1，最多为2
+     ptnum-pernode = 2
+   ```
+
+   如果配置3副本，请参考 [副本数据分布](https://docs.opengemini.org/zh/guide/features/replication.html#%E5%89%AF%E6%9C%AC%E6%95%B0%E6%8D%AE%E5%88%86%E5%B8%83) 理解`ptnum-pernode`
+
+   ```toml
+   # 配置ts-sql
+   [http]
+     bind-address = "192.168.0.38:8086"
+     # flight-address = "{{addr}}:8087" 注释
+     
+     # 以下部分可以根据实际需求配置
+     # auth-enabled = false  需要用户名密码鉴权，可以开启这个配置
+     # https-enabled = false 这里配置https和证书
+     # https-certificate = ""
+     # https-private-key = ""
+     # max-body-size = 0 
+     # max-connection-limit = 0 默认是cpu核数*125，8vcpu的最大连接数默认是1000
+     # max-concurrent-write-limit = 0 最大写并发限制，默认是cpu核数*4，8vcpu最大写并发是32
+     # max-concurrent-query-limit = 0 最大查询并发限制，默认是cpu核数，8vcpu最大查询并发是8
+   ```
+
+   ```toml
+   # 配置内核日志
+   [logging]
+     path = "/path/to/openGemini/logs"
+   ```
+
+   ```toml
+   # 配置ts-store
+   [data]
+     store-ingest-addr = "192.168.0.38:8400"
+     store-select-addr = "192.168.0.38:8401"
+     store-data-dir = "/path/to/openGemini/data"
+     store-wal-dir = "/path/to/openGemini/data"
+     store-meta-dir = "/path/to/openGemini/data/meta"
+   ```
+
+   ```toml
+   # 配置所有组件的运行时监控
+   [monitor]
+     pushers = "file"  #内核监控指标写到文件，供ts-monitor采集
+     store-enabled = true
+     store-database = "monitor" 
+     store-interval = "10s"
+     # 末尾的斜线不能丢
+     store-path = "/path/to/openGemini/metric/"
+   ```
+
+   ```toml
+   # 集群管理配置
+   [gossip]
+     enabled = true
+     log-enabled = true
+     bind-address = "192.168.0.38"
+     store-bind-port = 8011
+     meta-bind-port = 8010
+     sql-bind-port = 8012
+     members = ["192.168.0.38:8010", "192.168.0.248:8010", "192.168.0.210:8010"]
+   ```
+
+   ```toml
+   # 无人值守运维能力配置，当cpu、内存和Goroutine数量超过阈值后，自动抓取节点的火焰图，供事后根因分析
+   [sherlock]
+     sherlock-enable = true
+     collect-interval = "10s"
+     cpu-max-limit = 90
+     dump-path = "/tmp"  #Golang的火焰图文件保存目录
+     # max-num = 32 目录最多保留多少个火焰图文件数量  
+     # max-age = 7  目录中的火焰图文件最长保留时间
+   [sherlock.cpu]
+   	# 如下两种情况会抓取火焰图
+   	# 1. CPU利用率从30%开始，以25%的速度增长，持续10min
+   	# 2. CPU利用率持续10min超过80%
+     enable = true
+     min = 30
+     diff = 25
+     abs = 80
+     cool-down = "10m"
+   [sherlock.memory]
+     enable = true
+     min = 25
+     diff = 25
+     abs = 80
+     cool-down = "10m"
+   [sherlock.goroutine]
+     enable = true
+     min = 10000
+     diff = 20
+     abs = 20000
+     max = 100000
+     cool-down = "30m"
+   ```
+
+   启动顺序：先启动3个ts-meta，然后启动ts-sql和ts-store，二者没有先后顺序
+
+   **运行 ts-meta**（需指定配置文件路径和命令行输出日志路径）
+
+   ```shell
+   > nohup ts-meta -config /path/to/openGemini.conf -pidfile /path/to/openGemini/pid/meta.pid > /path/to/openGemini/logs/meta_extra.log 2>&1 &
+   ```
+
+   **运行 ts-sql和ts-store**（需指定配置文件路径和命令行输出日志路径）
+
+   ```shell
+   > nohup ts-sql -config /path/to/openGemini.conf -pidfile /path/to/openGemini/pid/sql.pid > /path/to/openGemini/logs/sql_extra.log 2>&1 &
+   > nohup ts-store -config /path/to/openGemini.conf -pidfile /path/to/openGemini/pid/store.pid > /path/to/openGemini/logs/store_extra.log 2>&1 &
+   ```
+
+   通过`ts-cli`查看集群状态，`status`列均为alive，表示集群正常。
+
+   ```sql
+   > show cluster
+   +---------------------+--------+--------------------+--------+----------+--------------+
+   |        time         | status |      hostname      | nodeID | nodeType | availability |
+   +---------------------+--------+--------------------+--------+----------+--------------+
+   | 1742128142135295990 | alive  | 192.168.0.38:8091  |      1 | meta     | unavailable  |
+   | 1742128142135295990 | alive  | 192.168.0.210:8091 |      2 | meta     | unavailable  |
+   | 1742128142135295990 | alive  | 192.168.0.248:8091 |      3 | meta     | unavailable  |
+   | 1742128142135295990 | alive  | 192.168.0.38:8400  |      4 | data     | available    |
+   | 1742128142135295990 | alive  | 192.168.0.248:8400 |      6 | data     | available    |
+   | 1742128142135295990 | alive  | 192.168.0.210:8400 |      7 | data     | available    |
+   +---------------------+--------+--------------------+--------+----------+--------------+
+   6 columns, 6 rows in set
+   
+   +------+-----------+----+------+-----------+-----------+-----------+----------+
+   | opId | eventType | db | ptId | srcNodeId | dstNodeId | currState | preState |
+   +------+-----------+----+------+-----------+-----------+-----------+----------+
+   +------+-----------+----+------+-----------+-----------+-----------+----------+
+   8 columns, 0 rows in set
+   ```
+
+## 搭建监控
+
+在openGemini.conf里必须配置`[monitor]`
+
+1. ### 在执行机上运行openGemini单机，用于接收ts-monitor写入的集群监控数据
+
+   配置单机配置文件`openGemini.singlenode.conf`，主要是配置监听地址和存储目录
+
+   ```toml
+   [common]
+     meta-join = ["192.168.0.244:8092"]
+     ha-policy = "write-available-first"
+     ignore-empty-tag = true
+   
+   [meta]
+     bind-address = "192.168.0.244:8088"
+     http-bind-address = "192.168.0.244:8091"
+     rpc-bind-address = "192.168.0.244:8092"
+     dir = "/root/openGemini/data/meta"
+   
+   [http]
+     bind-address = "192.168.0.244:8086"
+     # flight-address = "127.0.0.1:8087"
+     # flight-enabled = true
+     # flight-auth-enabled = false
+   
+   [data]
+     store-ingest-addr = "192.168.0.244:8400"
+     store-select-addr = "192.168.0.244:8401"
+     store-data-dir = "/root/openGemini/data"
+     store-wal-dir = "/root/openGemini/data"
+     store-meta-dir = "/root/openGemini/data"
+     enable-mmap-read = false
+     
+   [logging]
+     path = "/root/openGemini/logs"
+   
+   # 其余配置项都可以注释
+   ```
+
+   运行`ts-server`
+
+   ```shell
+   > nohup ts-server -config /path/to/openGemini.singlenode.conf -pidfile /path/to/openGemini/pid/meta.pid > /path/to/openGemini/logs/server_extra.log 2>&1 &
+   ```
+
+2. ### 配置和运行ts-monitor
+
+   回到openGemini集群节点上，打开ts-monitor配置文件`monitor.conf`，以节点 `192.168.0.38` 为例
+
+   ```toml
+   [monitor]
+     # 一般为节点IP，用于区分采集的数据
+     host = "192.168.0.38"
+     # 与openGemini.conf中【monitor】--> store-path 配置保持一致，这样ts-monitor才知道取哪里采集监控数据
+     metric-path = "/root/data/openGemini/metric"
+     # 监控慢日志，与openGemini.conf中【logging】--> path 配置保持一致
+     error-log-path = "/root/data/openGemini/logs"
+     # 监控openGemini的数据存储空间，与openGemini.conf中【data】-->store-data-dir 配置保持一致
+     disk-path = "/root/data/openGemini/"
+     # 监控openGemini的WAL数据存储空间，与openGemini.conf中【data】-->store-wal-dir 配置保持一致
+     # 特别要在路径末尾添加wal
+     aux-disk-path = "/root/data/openGemini/wal"
+     
+     # 其余配置保持默认即可，无需配置
+   
+   # 仅其中某一个节点配置【query】即可，不需要每个节点都配
+   [query]
+     # 监控集群有多少DB，多少表，时间线数量等，需要访问ts-sql，发送查询语句查询
+     query-enable = true
+     http-endpoint = "192.168.0.38:8086"
+     query-interval = "5m"
+     # username = ""
+     # password = ""
+     # https-enable = false
+   
+   [report]
+   	# 采集上来指标后，需要上报到执行机的ts-server数据库中，这里配置执行机的信息
+     address = "192.168.0.244:8086"
+   	# 写入的目标库
+     database = "monitor"
+     # 如果目标数据库设置了用户名和密码，在这里配上，否则数据上报失败
+     # username = ""
+     # password = ""
+     # https-enable = false
+     rp = "autogen"
+     rp-duration = "168h"
+     
+   [logging]
+     format = "auto"
+     level = "info"
+     path = "/root/openGemini/logs/"
+     max-size = "64m"
+     max-num = 30
+     max-age = 7
+     compress-enabled = true
+   ```
+
+   运行`ts-monitor`
+
+   ```shell
+   > nohup ts-monitor -config=/path/to/monitor.conf > /path/to/openGemini/logs/monitor_extra.log 2>&1 &
+   ```
+
+   使用`ts-cli`连接执行机上数据，可以查询到数据，表示配置都正确
+
+   ```
+   > show databases
+   name: databases
+   +---------+
+   |  name   |
+   +---------+
+   | monitor |
+   +---------+
+   1 columns, 1 rows in set
+   
+   > use monitor
+   > show measurements
+   name: measurements
+   +----------------+
+   |      name      |
+   +----------------+
+   | cluster_metric |
+   | err_log        |
+   | errno          |
+   | executor       |
+   | httpd          |
+   | meta           |
+   | metaRaft       |
+   | metadata       |
+   | runtime        |
+   | shelf          |
+   | spdy           |
+   | system         |
+   +----------------+
+   1 columns, 12 rows in set
+   ```
+
+   
+
+3. ### 配置Grafana，监控openGemini运行情况
+
+   下载Grafana，本文档以Grafana-11.5.0为例，选择其他版本可以访问[Grafana官网](https://grafana.com/grafana/download/11.5.0?edition=oss)
+
+   ```shell
+   > wget https://dl.grafana.com/oss/release/grafana-11.5.0.linux-amd64.tar.gz
+   > tar -zxvf grafana-11.5.0.linux-amd64.tar.gz
+   ```
+
+   如果自定义Dashboard，推荐安装openGemini数据源
+
+   ![image-20250316224430557](../../../../static/img/guide/deploy_cluster/image-20250316224430557.png)
+
+   ![image-20250316224530443](../../../../static/img/guide/deploy_cluster/image-20250316224530443.png)
+
+   配置openGemini数据源：配置访问执行机上ts-server的URL：http://192.168.0.244:8086, database：monitor
+
+   
+
+   如果使用社区提供的Dashboard模板，需要创建名为“DS_OPENGEMINI_TEST”的**InfluxDB**数据源（Data source）,并设为默认数据源。
+
+   再次提醒，是InfluxDB数据源，数据源名字必须是`DS_OPENGEMINI_TEST`
+
+   ![image-20250322215707097](../../../../static/img/guide/deploy_cluster/image-20250322215707097.png)
+
+   
+
+   ![image-20250322215631369](../../../../static/img/guide/deploy_cluster/image-20250322215631369.png)
+
+   导入dashboard模板，访问：https://github.com/openGemini/gemix/tree/main/embed/templates/dashboards
+
+   ![image-20250322215845904](../../../../static/img/guide/deploy_cluster/image-20250322215845904.png)
+
+   一般我们推荐导入红框内的4个Dashboard，导入具体步骤为（以overview.json文件为例）：
+
+   - 打开overview.json文件
+   - 复制文件内容（文件内容是json格式）
+   - 选择Grafana页面右上角`import dashboard`，粘贴内容，点击导入（load）按钮即可
+
+   ![image-20250316225236329](../../../../static/img/guide/deploy_cluster/image-20250316225236329.png)
+
+   整体的效果如下：
+
+   ![image-20250322220955262](../../../../static/img/guide/deploy_cluster/image-20250322220955262.png)
+
+   
+
+   **部分内容在Grafana新版本上显示不了数据，其原因是查询语句在新版本上不支持。举个例子，写WAL时延的Panel显示有问题：**
+
+   ![image-20250322220615022](../../../../static/img/guide/deploy_cluster/image-20250322220615022.png)
+
+   原因是如下查询语句在高版本的Grafanfa上不兼容：
+
+   ```sql
+   SELECT difference("WriteWalDurationNs")/difference("WriteRowsBatch") as "Duration" 
+   FROM $database.."performance" 
+   WHERE $timeFilter group by hostname
+   ```
+
+   需改为：
+
+   ```sql
+   SELECT difference("WriteWalDurationNs")/(difference("WriteRowsBatch")+0.0001) as "Duration" 
+   FROM $database.."performance" 
+   WHERE $timeFilter group by hostname
+   ```
+
+## TSBS压测
+
+1. tsbs下载地址：https://github.com/timescale/tsbs，需参考社区步骤自己编译
+
+2. Devops测试数据生成（IoT测试场景类似）
+
+   ```shell
+   > nohub tsbs_generate_data --use-case="cpu-only" --seed=123 --scale=300000 --timestamp-start="2024-11-11T00:00:00Z" --timestamp-end="2024-11-12T00:00:01Z" --log-interval="10s" --format="influx" | gzip > /path/to/openGemini-test-data.gz &
+   ```
+
+   `scale=300000`表示生成的数据，时间线（可以理解为设备数）规模是30万，必填
+
+   `timestamp-start`,`timestamp-end` 是生成的数据的起始和结束时间，必填
+
+   `format=influx`, 因为openGemini兼容influxDB接口，因此可以用influxdb的数据格式测试，必填
+
+   有两个地方需要提醒：
+
+   - 时间线越多，时间越长，数据量就越大，数据准备时间是小时级，甚至天级。
+   - 30万时间线，生成的数据量（压缩后）大约在80多GB，磁盘空余空间至少要100GB以上。
+
+3. 创建测试DB
+
+   `ts-cli` 客户端连接openGemini测试集群，创建测试数据库 *dbname*
+
+   ```
+   > create database dbname
+   ```
+
+4. 测试写性能
+
+   ```shell
+   > cat /path/to/openGemini-test-data.gz | gunzip | tsbs_load_influx --dbname="dbname" --urls="http://192.168.0.38:8086,http://192.168.0.248:8086" --workers=8 --batchsize=1000 --do-create-db=false --do-load=true
+   ```
+
+   `--dbname="dbname"` 是上面创建的DB名称。
+
+   `--urls` 是`ts-sql`地址，可以配置多个，用逗号隔开
+
+   `--workers=8` 是配置写数据并发量
+
+   `--batchsize=1000` 配置单批写入的数据量，1000表示一批数据有1000条。可以是2000，甚至5000，不同的值，性能也不相同。
+
+5. 生成查询语句
+
+   ```shell
+   > tsbs_generate_queries --use-case="cpu-only" --seed=123 --scale=300000 --timestamp-start="2024-11-11T00:00:00Z" --timestamp-end="2024-11-12T00:00:01Z" --queries=10 --queries-type="single-groupby-1-1-12" --format"influx" |gzip > /path/to/single-groupby-1-1-12.gz
+   ```
+
+   上述命令会生成一个文件，包含10个query，每个query仅查询时间范围不一致。执行时会统计平均查询时延，最大值最小值等性能指标。
+
+   tsbs有很多query type，需要为每个type生成一个查询语句文件。
+
+   ### Devops / cpu-only
+
+   | Query type            | Description                                                  |
+   | --------------------- | ------------------------------------------------------------ |
+   | single-groupby-1-1-1  | Simple aggregrate (MAX) on one metric for 1 host, every 5 mins for 1 hour |
+   | single-groupby-1-1-12 | Simple aggregrate (MAX) on one metric for 1 host, every 5 mins for 12 hours |
+   | single-groupby-1-8-1  | Simple aggregrate (MAX) on one metric for 8 hosts, every 5 mins for 1 hour |
+   | single-groupby-5-1-1  | Simple aggregrate (MAX) on 5 metrics for 1 host, every 5 mins for 1 hour |
+   | single-groupby-5-1-12 | Simple aggregrate (MAX) on 5 metrics for 1 host, every 5 mins for 12 hours |
+   | single-groupby-5-8-1  | Simple aggregrate (MAX) on 5 metrics for 8 hosts, every 5 mins for 1 hour |
+   | cpu-max-all-1         | Aggregate across all CPU metrics per hour over 1 hour for a single host |
+   | cpu-max-all-8         | Aggregate across all CPU metrics per hour over 1 hour for eight hosts |
+   | double-groupby-1      | Aggregate on across both time and host, giving the average of 1 CPU metric per host per hour for 24 hours |
+   | double-groupby-5      | Aggregate on across both time and host, giving the average of 5 CPU metrics per host per hour for 24 hours |
+   | double-groupby-all    | Aggregate on across both time and host, giving the average of all (10) CPU metrics per host per hour for 24 hours |
+   | high-cpu-all          | All the readings where one metric is above a threshold across all hosts |
+   | high-cpu-1            | All the readings where one metric is above a threshold for a particular host |
+   | lastpoint             | The last reading for each host                               |
+   | groupby-orderby-limit | The last 5 aggregate readings (across time) before a randomly chosen endpoint |
+
+6. 测试查询性能
+
+   ```shell
+   > cat /path/to/single-groupby-1-1-12.gz | gunzip | tsbs_run_queries_influx --workers=8 --print-interval=0 --dbname=dbname --urls="http://192.168.0.38:8086,http://192.168.0.248:8086"
+   ```
+
+   `--workers=8` 表示查询并发数。如果前面单个场景生成的查询语句为10，那么并发最大为10。
+
+## 压测（手写工具）
+
+这一章节，我们介绍如何结合自己业务手戳工具测试性能。通常，基准测试工具的测试场景和实际业务场景存在差异，这时，我们要获得性能数据，就需要手写工具。
+
+在这之前，我们需要明确几个需求：
+
+1. 查询场景：梳理业务要根据什么条件，查询什么数据，都有哪些查询场景。
+2. 数据模型：根据业务设计数据模型，业务如果用不到的数据，可以不存。具体需要做的事情：
+   - 设计哪些字段做tag，哪些字段做field。openGemini会在TAG字段上创建倒排索引，一般TAG的基数不能太大，且必须是字符串类型。
+   - openGemini的多值模型性能最好。何为多值模型，指一行数据存储多个指标数据，例如一行数据同时存储一台服务器的CPU和MEM指标。
+   - 设计表，不推荐一个指标（测点）一张表。如果所有指标数据都存到一个表中，导致TAG和Field字段过多，比如超过1000，甚至更大，建议分表存储。TAG过多，索引性能会变差。Field过多，写入时数据解析开销会比较大，同时也会加大后台数据合并负担。
+   - 一般来说，一个业务设计几十、几百张表是可以的。不建议设计出数万，甚至数十万表规模，对性能影响非常大。
+
+为了方便大家业务接入和测试，openGemini提供了Go、Java、Python等语言的SDK，支持负载均衡。
+
+- Go语言SDK：https://github.com/openGemini/opengemini-client-go
+- Java语言SDK：https://github.com/openGemini/opengemini-client-java
+- Python语言SDK：https://github.com/openGemini/opengemini-client-python
+
+需要C/C++客户端的同学可以单独联系社区。
+
+手写工具需要注意写入时间线数据的有序性。比如线程1在写设备A的数据，线程2也在写设备A的数据，这时可能造成数据乱序。openGemini虽然支持乱序数据处理，但是乱序数据太多的情况下，对性能影响比较大，主要是在乱序数据合并阶段。
+
+因此，最佳实践是一个线程只写一台或多台设备数据，互相不要交叉。
+
+## 性能调优
+
+参考 https://opengemini.org/zh/blog/best_practice.html
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