docs: move images

docs-cn/14-reference/03-connector/03-connector.mdx

@@ -4,7 +4,7 @@ title: 连接器
 
 TDengine 提供了丰富的应用程序开发接口，为了便于用户快速开发自己的应用，TDengine 支持了多种编程语言的连接器，其中官方连接器包括支持 C/C++、Java、Python、Go、Node.js、C# 和 Rust 的连接器。这些连接器支持使用原生接口（taosc）和 REST 接口（部分语言暂不支持）连接 TDengine 集群。社区开发者也贡献了多个非官方连接器，例如 ADO.NET 连接器、Lua 连接器和 PHP 连接器。
 
-![image-connector](/img/connector.png)
+![image-connector](./connector.png)
 
 ## 支持的平台
 

docs-cn/20-third-party/01-grafana.mdx

@@ -64,15 +64,15 @@ GF_PLUGINS_ALLOW_LOADING_UNSIGNED_PLUGINS=tdengine-datasource
 
 用户可以直接通过 http://localhost:3000 的网址，登录 Grafana 服务器（用户名/密码：admin/admin），通过左侧 `Configuration -> Data Sources` 可以添加数据源，如下图所示：
 
-![img](/img/connections/add_datasource1.jpg)
+![img](./add_datasource1.jpg)
 
 点击 `Add data source` 可进入新增数据源页面，在查询框中输入 TDengine 可选择添加，如下图所示：
 
-![img](/img/connections/add_datasource2.jpg)
+![img](./add_datasource2.jpg)
 
 进入数据源配置页面，按照默认提示修改相应配置即可：
 
-![img](/img/connections/add_datasource3.jpg)
+![img](./add_datasource3.jpg)
 
 - Host： TDengine 集群中提供 REST 服务 （在 2.4 之前由 taosd 提供， 从 2.4 开始由 taosAdapter 提供）的组件所在服务器的 IP 地址与 TDengine REST 服务的端口号(6041)，默认 http://localhost:6041。
 - User：TDengine 用户名。
@@ -80,13 +80,13 @@ GF_PLUGINS_ALLOW_LOADING_UNSIGNED_PLUGINS=tdengine-datasource
 
 点击 `Save & Test` 进行测试，成功会有如下提示：
 
-![img](/img/connections/add_datasource4.jpg)
+![img](./add_datasource4.jpg)
 
 ### 创建 Dashboard
 
 回到主界面创建 Dashboard，点击 Add Query 进入面板查询页面：
 
-![img](/img/connections/create_dashboard1.jpg)
+![img](./create_dashboard1.jpg)
 
 如上图所示，在 Query 中选中 `TDengine` 数据源，在下方查询框可输入相应 SQL 进行查询，具体说明如下：
 
@@ -96,7 +96,7 @@ GF_PLUGINS_ALLOW_LOADING_UNSIGNED_PLUGINS=tdengine-datasource
 
 按照默认提示查询当前 TDengine 部署所在服务器指定间隔系统内存平均使用量如下：
 
-![img](/img/connections/create_dashboard2.jpg)
+![img](./create_dashboard2.jpg)
 
 > 关于如何使用 Grafana 创建相应的监测界面以及更多有关使用 Grafana 的信息，请参考 Grafana 官方的[文档](https://grafana.com/docs/)。
 

docs-cn/21-tdinternal/01-arch.md

@@ -11,7 +11,7 @@ TDengine 的设计是基于单个硬件、软件系统不可靠，基于任何
 
 TDengine 分布式架构的逻辑结构图如下：
 
-![TDengine架构示意图](/img/architecture/structure.png)
+![TDengine架构示意图](./structure.png)
 
 <center> 图 1 TDengine架构示意图  </center>
 
@@ -63,7 +63,7 @@ TDengine 分布式架构的逻辑结构图如下：
 
 为解释 vnode、mnode、taosc 和应用之间的关系以及各自扮演的角色，下面对写入数据这个典型操作的流程进行剖析。
 
-![TDengine典型的操作流程](/img/architecture/message.png)
+![TDengine典型的操作流程](./message.png)
 
 <center> 图 2 TDengine 典型的操作流程 </center>
 
@@ -135,7 +135,7 @@ TDengine 除 vnode 分片之外，还对时序数据按照时间段进行分区
 
 Master Vnode 遵循下面的写入流程：
 
-![TDengine Master写入流程](/img/architecture/write_master.png)
+![TDengine Master写入流程](./write_master.png)
 
 <center> 图 3 TDengine Master 写入流程  </center>
 
@@ -150,7 +150,7 @@ Master Vnode 遵循下面的写入流程：
 
 对于 slave vnode，写入流程是：
 
-![TDengine Slave 写入流程](/img/architecture/write_slave.png)
+![TDengine Slave 写入流程](./write_slave.png)
 
 <center> 图 4 TDengine Slave 写入流程  </center>
 
@@ -284,7 +284,7 @@ SELECT COUNT(*) FROM d1001 WHERE ts >= '2017-7-14 00:00:00' AND ts < '2017-7-14
 
 TDengine 对每个数据采集点单独建表，但在实际应用中经常需要对不同的采集点数据进行聚合。为高效的进行聚合操作，TDengine 引入超级表（STable）的概念。超级表用来代表一特定类型的数据采集点，它是包含多张表的表集合，集合里每张表的模式（schema）完全一致，但每张表都带有自己的静态标签，标签可以有多个，可以随时增加、删除和修改。应用可通过指定标签的过滤条件，对一个 STable 下的全部或部分表进行聚合或统计操作，这样大大简化应用的开发。其具体流程如下图所示：
 
-![多表聚合查询原理图](/img/architecture/multi_tables.png)
+![多表聚合查询原理图](./multi_tables.png)
 
 <center> 图 5 多表聚合查询原理图  </center>
 

docs-cn/25-application/01-telegraf.md

@@ -16,7 +16,7 @@ IT 运维监测数据通常都是对时间特性比较敏感的数据，例如
 
 本文介绍不需要写一行代码，通过简单修改几行配置文件，就可以快速搭建一个基于 TDengine + Telegraf + Grafana 的 IT 运维系统。架构如下图：
 
-![IT-DevOps-Solutions-Telegraf.png](/img/IT-DevOps-Solutions-Telegraf.png)
+![IT-DevOps-Solutions-Telegraf.png](./IT-DevOps-Solutions-Telegraf.png)
 
 ## 安装步骤
 
@@ -75,7 +75,7 @@ sudo systemctl start telegraf
 点击左侧齿轮图标并选择 `Plugins`，应该可以找到 TDengine data source 插件图标。
 点击左侧加号图标并选择 `Import`，从 `https://github.com/taosdata/grafanaplugin/blob/master/examples/telegraf/grafana/dashboards/telegraf-dashboard-v0.1.0.json` 下载 dashboard JSON 文件后导入。之后可以看到如下界面的仪表盘：
 
-![IT-DevOps-Solutions-telegraf-dashboard.png](/img/IT-DevOps-Solutions-telegraf-dashboard.png)
+![IT-DevOps-Solutions-telegraf-dashboard.png]./IT-DevOps-Solutions-telegraf-dashboard.png)
 
 ## 总结
 

docs-cn/25-application/02-collectd.md

@@ -16,7 +16,7 @@ IT 运维监测数据通常都是对时间特性比较敏感的数据，例如
 
 本文介绍不需要写一行代码，通过简单修改几行配置文件，就可以快速搭建一个基于 TDengine + collectd / statsD + Grafana 的 IT 运维系统。架构如下图：
 
-![IT-DevOps-Solutions-Collectd-StatsD.png](/img/IT-DevOps-Solutions-Collectd-StatsD.png)
+![IT-DevOps-Solutions-Collectd-StatsD.png](./IT-DevOps-Solutions-Collectd-StatsD.png)
 
 ## 安装步骤
 
@@ -81,12 +81,12 @@ repeater 部分添加 { host:'<TDengine server/cluster host>', port: <port for S
 
 从 https://github.com/taosdata/grafanaplugin/blob/master/examples/collectd/grafana/dashboards/collect-metrics-with-tdengine-v0.1.0.json 下载 dashboard json 文件，点击左侧加号图标并选择 `Import`，按照界面提示选择 JSON 文件导入。之后可以看到如下界面的仪表盘：
 
-![IT-DevOps-Solutions-collectd-dashboard.png](/img/IT-DevOps-Solutions-collectd-dashboard.png)
+![IT-DevOps-Solutions-collectd-dashboard.png](./IT-DevOps-Solutions-collectd-dashboard.png)
 
 #### 导入 StatsD 仪表盘
 
 从 `https://github.com/taosdata/grafanaplugin/blob/master/examples/statsd/dashboards/statsd-with-tdengine-v0.1.0.json` 下载 dashboard json 文件，点击左侧加号图标并选择 `Import`，按照界面提示导入 JSON 文件。之后可以看到如下界面的仪表盘：
-![IT-DevOps-Solutions-statsd-dashboard.png](/img/IT-DevOps-Solutions-statsd-dashboard.png)
+![IT-DevOps-Solutions-statsd-dashboard.png](./IT-DevOps-Solutions-statsd-dashboard.png)
 
 ## 总结
 

docs-cn/25-application/03-immigrate.md

@@ -27,7 +27,7 @@ title: OpenTSDB 应用迁移到 TDengine 的最佳实践
 一个典型的 DevOps 应用场景的系统整体的架构如下图（图 1） 所示。
 
 **图 1. DevOps 场景中典型架构**
-![IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch](/img/IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch.jpg "图1. DevOps 场景中典型架构")
+![IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch](./IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch.jpg "图1. DevOps 场景中典型架构")
 
 在该应用场景中，包含了部署在应用环境中负责收集机器度量（Metrics）、网络度量（Metrics）以及应用度量（Metrics）的 Agent 工具、汇聚 Agent 收集信息的数据收集器，数据持久化存储和管理的系统以及监控数据可视化工具（例如：Grafana 等）。
 
@@ -70,7 +70,7 @@ LoadPlugin write_tsdb
 TDengine 提供了默认的两套 Dashboard 模板，用户只需要将 Grafana 目录下的模板导入到 Grafana 中即可激活使用。
 
 **图 2. 导入 Grafana 模板**
-![](/img/IT-DevOps-Solutions-Immigrate-OpenTSDB-Dashboard.jpg "图2. 导入 Grafana 模板")
+![](./IT-DevOps-Solutions-Immigrate-OpenTSDB-Dashboard.jpg "图2. 导入 Grafana 模板")
 
 操作完以上步骤后，就完成了将 OpenTSDB 替换成为 TDengine 的迁移工作。可以看到整个流程非常简单，不需要写代码，只需要对某些配置文件进行调整即可完成全部的迁移工作。
 
@@ -83,7 +83,7 @@ TDengine 提供了默认的两套 Dashboard 模板，用户只需要将 Grafana
 如果你的应用特别复杂，或者应用领域并不是 DevOps 场景，你可以继续阅读后续的章节，更加全面深入地了解将 OpenTSDB 的应用迁移到 TDengine 的高级话题。
 
 **图 3. 迁移完成后的系统架构**
-![IT-DevOps-Solutions-Immigrate-TDengine-Arch](/img/IT-DevOps-Solutions-Immigrate-TDengine-Arch.jpg "图 3. 迁移完成后的系统架构")
+![IT-DevOps-Solutions-Immigrate-TDengine-Arch](./IT-DevOps-Solutions-Immigrate-TDengine-Arch.jpg "图 3. 迁移完成后的系统架构")
 
 ## 其他场景的迁移评估与策略
 

docs-en/14-reference/03-connector/03-connector.mdx

@@ -4,7 +4,7 @@ title: Connector
 
 TDengine provides a rich set of APIs (application development interface). To facilitate users to develop their applications quickly, TDengine supports connectors for multiple programming languages, including official connectors for C/C++, Java, Python, Go, Node.js, C#, and Rust. These connectors support connecting to TDengine clusters using both native interfaces (taosc) and REST interfaces (not supported in a few languages yet). Community developers have also contributed several unofficial connectors, such as the ADO.NET connector, the Lua connector, and the PHP connector.
 
-![image-connector](/img/connector.png)
+![image-connector](./connector.png)
 
 ## Supported platforms
 

docs-en/25-application/01-telegraf.md

@@ -16,7 +16,7 @@ Current mainstream IT DevOps system usually include a data collection module, a
 
 This article introduces how to quickly build a TDengine + Telegraf + Grafana based IT DevOps visualization system without writing even a single line of code and by simply modifying a few lines of configuration files. The architecture is as follows.
 
-![IT-DevOps-Solutions-Telegraf.png](/img/IT-DevOps-Solutions-Telegraf.png)
+![IT-DevOps-Solutions-Telegraf.png](./IT-DevOps-Solutions-Telegraf.png)
 
 ## Installation steps
 
@@ -75,7 +75,7 @@ Log in to the Grafana interface using a web browser at `IP:3000`, with the syste
 Click on the gear icon on the left and select `Plugins`, you should find the TDengine data source plugin icon.
 Click on the plus icon on the left and select `Import` to get the data from `https://github.com/taosdata/grafanaplugin/blob/master/examples/telegraf/grafana/dashboards/telegraf-dashboard- v0.1.0.json`, download the dashboard JSON file and import it. You will then see the dashboard in the following screen.
 
-![IT-DevOps-Solutions-telegraf-dashboard.png](/img/IT-DevOps-Solutions-telegraf-dashboard.png)
+![IT-DevOps-Solutions-telegraf-dashboard.png](./IT-DevOps-Solutions-telegraf-dashboard.png)
 
 ## Wrap-up
 

docs-en/25-application/02-collectd.md

@@ -17,7 +17,7 @@ The new version of TDengine supports multiple data protocols and can accept data
 
 This article introduces how to quickly build an IT DevOps visualization system based on TDengine + collectd / StatsD + Grafana without writing even a single line of code but by simply modifying a few lines of configuration files. The architecture is shown in the following figure.
 
-![IT-DevOps-Solutions-Collectd-StatsD.png](/img/IT-DevOps-Solutions-Collectd-StatsD.png)
+![IT-DevOps-Solutions-Collectd-StatsD.png](./IT-DevOps-Solutions-Collectd-StatsD.png)
 
 ## Installation Steps
 
@@ -83,19 +83,19 @@ Click on the gear icon on the left and select `Plugins`, you should find the TDe
 Download the dashboard json from `https://github.com/taosdata/grafanaplugin/blob/master/examples/collectd/grafana/dashboards/collect-metrics-with-tdengine-v0.1.0.json`, click the plus icon on the left and select Import, follow the instructions to import the JSON file. After that, you can see
 The dashboard can be seen in the following screen.
 
-![IT-DevOps-Solutions-collectd-dashboard.png](/img/IT-DevOps-Solutions-collectd-dashboard.png)
+![IT-DevOps-Solutions-collectd-dashboard.png](./IT-DevOps-Solutions-collectd-dashboard.png)
 
 #### import collectd dashboard
 
 Download the dashboard json file from `https://github.com/taosdata/grafanaplugin/blob/master/examples/collectd/grafana/dashboards/collect-metrics-with-tdengine-v0.1.0.json`. Download the dashboard json file, click the plus icon on the left side and select `Import`, and follow the interface prompts to select the JSON file to import. After that, you can see
 dashboard with the following interface.
 
-![IT-DevOps-Solutions-collectd-dashboard.png](/img/IT-DevOps-Solutions-collectd-dashboard.png)
+![IT-DevOps-Solutions-collectd-dashboard.png](./IT-DevOps-Solutions-collectd-dashboard.png)
 
 #### Importing the StatsD dashboard
 
 Download the dashboard json from `https://github.com/taosdata/grafanaplugin/blob/master/examples/statsd/dashboards/statsd-with-tdengine-v0.1.0.json`. Click on the plus icon on the left and select `Import`, and follow the interface prompts to import the JSON file. You will then see the dashboard in the following screen.
-![IT-DevOps-Solutions-statsd-dashboard.png](/img/IT-DevOps-Solutions-statsd-dashboard.png)
+![IT-DevOps-Solutions-statsd-dashboard.png](./IT-DevOps-Solutions-statsd-dashboard.png)
 
 ## Wrap-up
 

docs-en/25-application/03-immigrate.md

@@ -32,7 +32,7 @@ We will explain how to migrate OpenTSDB applications to TDengine quickly, secure
 The following figure (Figure 1) shows the system's overall architecture for a typical DevOps application scenario.
 
 **Figure 1. Typical architecture in a DevOps scenario**
-![IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch](/img/IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch.jpg "Figure 1. Typical architecture in a DevOps scenario")
+![IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch](./IT-DevOps-Solutions-Immigrate-OpenTSDB-Arch.jpg "Figure 1. Typical architecture in a DevOps scenario")
 
 In this application scenario, there are Agent tools deployed in the application environment to collect machine metrics, network metrics, and application metrics. Data collectors to aggregate information collected by agents, systems for persistent data storage and management, and tools for monitoring data visualization (e.g., Grafana, etc.).
 
@@ -75,7 +75,7 @@ After writing the data to TDengine properly, you can adapt Grafana to visualize
 TDengine provides two sets of Dashboard templates by default, and users only need to import the templates from the Grafana directory into Grafana to activate their use.
 
 **Importing Grafana Templates** Figure 2.
-![](/img/IT-DevOps-Solutions-Immigrate-OpenTSDB-Dashboard.jpg "Figure 2. Importing a Grafana Template")
+![](./IT-DevOps-Solutions-Immigrate-OpenTSDB-Dashboard.jpg "Figure 2. Importing a Grafana Template")
 
 After the above steps, you completed the migration to replace OpenTSDB with TDengine. You can see that the whole process is straightforward, there is no need to write any code, and only some configuration files need to be adjusted to meet the migration work.
 
@@ -88,7 +88,7 @@ In most DevOps scenarios, if you have a small OpenTSDB cluster (3 or fewer nodes
 Suppose your application is particularly complex, or the application domain is not a DevOps scenario. You can continue reading subsequent chapters for a more comprehensive and in-depth look at the advanced topics of migrating an OpenTSDB application to TDengine.
 
 **Figure 3. System architecture after migration**
-![IT-DevOps-Solutions-Immigrate-TDengine-Arch](/img/IT-DevOps-Solutions-Immigrate-TDengine-Arch.jpg "Figure 3. System architecture after migration completion")
+![IT-DevOps-Solutions-Immigrate-TDengine-Arch](./IT-DevOps-Solutions-Immigrate-TDengine-Arch.jpg "Figure 3. System architecture after migration completion")
 
 ## Migration evaluation and strategy for other scenarios