move remote WAL under the disaster recovery

docs/user-guide/operations/admin.md

@@ -36,7 +36,7 @@ The `INFORMATION_SCHEMA` database provides access to system metadata, such as th
 ## Data management
 
 * [The Storage Location](/user-guide/concepts/storage-location.md).
-* Cluster Failover for GreptimeDB by [Setting Remote WAL](./remote-wal/quick-start.md).
+* Cluster Failover for GreptimeDB by [Setting Remote WAL](/user-guide/operations/disaster-recovery/remote-wal/quick-start.md).
 * [Flush and Compaction for Table & Region](/reference/sql/admin.md#admin-functions).
 * Partition the table by regions, read the [Table Sharding](/contributor-guide/frontend/table-sharding.md) reference.
  * [Migrate the Region](./region-migration.md) for Load Balance.

docs/user-guide/operations/disaster-recovery/overview.md

@@ -36,7 +36,7 @@ Before digging into the specific DR solution, let's explain the architecture of
 GreptimeDB is designed with a cloud-native architecture based on storage-compute separation：
 * **Frontend**: the ingestion and query service layer, which forwards requests to Datanode and processes, and merges responses from Datanode.
 * **Datanode**: the storage layer of GreptimeDB, and is an LSM storage engine. Region is the basic unit for storing and scheduling data in Datanode. A region is a table partition, a collection of data rows. The data in region is saved into Object Storage (such as AWS S3). Unflushed Memtable data is written into WAL and can be recovered in DR.
-* **WAL**: persists the unflushed Memtable data in memory. It will be truncated when the Memtable is flushed into SSTable files. It can be local disk-based (local WAL) or Kafka cluster-based (remote WAL).
+* **WAL**: persists the unflushed Memtable data in memory. It will be truncated when the Memtable is flushed into SSTable files. It can be local disk-based (local WAL) or [Kafka cluster-based (remote WAL)](./remote-wal/quick-start.md).
 * **Object Storage**: persists the SSTable data and index.
 
 The GreptimeDB stores data in object storage such as [AWS S3](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DataDurability.html) or its compatible services, which is designed to provide 99.999999999% durability and 99.99% availability of objects over a given year. And services such as S3 provide [replications in Single-Region or Cross-Region](https://docs.aws.amazon.com/AmazonS3/latest/userguide/replication.html), which is naturally capable of DR.
@@ -118,6 +118,7 @@ By comparing these DR solutions, you can decide on the final option based on the
 
 ## References
 
+* [Remote WAL](./remote-wal/quick-start.md)
 * [Backup & restore data](./back-up-&-restore-data.md)
 * [DR solution for GreptimeDB Standalone](./dr-solution-for-standalone.md)
 * [DR solution based on Active-Active Failover ](./dr-solution-based-on-active-active-failover.md)

docs/user-guide/operations/overview.md

@@ -5,5 +5,4 @@
 * [Disaster Recovery](./disaster-recovery/overview.md)
 * [Monitoring](./monitoring.md)
 * [Tracing](./tracing.md)
-* [Remote WAL](./remote-wal/quick-start.md)
 * [Region Migration](./region-migration.md)

i18n/zh/docusaurus-plugin-content-docs/current.json

@@ -64,7 +64,7 @@
  "description": "The label for category Disaster Recovery in sidebar docs"
  },
  "sidebar.docs.category.Remote WAL": {
- "message": "Remote WAL",
+ "message": "远程 WAL",
  "description": "The label for category Remote WAL in sidebar docs"
  },
  "sidebar.docs.category.GreptimeCloud": {

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/operations/admin.md

@@ -36,7 +36,7 @@ ORDER BY datanode_id ASC
 ## 数据管理
 
 * [存储位置说明](/user-guide/concepts/storage-location.md)。
-* 通过 [设置Remote WAL](./remote-wal/quick-start.md) 实现 GreptimeDB 的集群容灾。
+* 通过 [设置Remote WAL](/user-guide/operations/disaster-recovery/remote-wal/quick-start.md) 实现 GreptimeDB 的集群容灾。
 * [Table 和 Region 的 Flush 和 Compaction](/reference/sql/admin.md##管理函数)。
 * 通过 Region 对表进行分区，请阅读 [表的分片](/contributor-guide/frontend/table-sharding.md) 参考。
  * [迁移 Region](./region-migration.md) 以实现负载均衡。

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/operations/disaster-recovery/overview.md

@@ -42,7 +42,7 @@ GreptimeDB 基于存储计算分离的云原生架构设计：
 
 * **Frontend**：数据插入和查询的服务层，将请求转发到 Datanode 并处理和合并 Datanode 的响应。
 * **Datanode**：GreptimeDB 的存储层，是一个 LSM 存储引擎。Region 是在 Datanode 中存储和调度数据的基本单元。Region 是一个表分区，是一组数据行的集合。Region 中的数据保存在对象存储中（例如 AWS S3）。未刷新的 Memtable 数据被写入 WAL，并可以在灾难发生时恢复。
-* **WAL**：持久化内存中未刷新的 Memtable 数据。当 Memtable 被刷新到 SSTable 文件时，WAL 将被截断。它可以是基于本地磁盘的（本地 WAL）或基于 Kafka 集群的（远程 WAL）。
+* **WAL**：持久化内存中未刷新的 Memtable 数据。当 Memtable 被刷新到 SSTable 文件时，WAL 将被截断。它可以是基于本地磁盘的（本地 WAL）或[基于 Kafka 集群的（远程 WAL）](./remote-wal/quick-start.md)。
 * **对象存储**：持久化 SSTable 数据和索引。
 
 GreptimeDB 将数据存储在对象存储（如 [AWS S3](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DataDurability.html)）或兼容的服务中，这些服务在年度范围内提供了 99.999999999％ 的持久性和 99.99％ 的可用性。像 S3 这样的服务提供了[单区域或跨区域的复制](https://docs.aws.amazon.com/AmazonS3/latest/userguide/replication.html)，天然具备灾难恢复能力。
@@ -135,6 +135,7 @@ BR 进程持续定期将数据从 Cluster 1 备份到 Region 2。
 
 ## 参考资料
 
+* [远程 WAL](./remote-wal/quick-start.md)
 * [备份与恢复数据](./back-up-&-restore-data.md)
 * [GreptimeDB Standalone 的 DR 解决方案](./dr-solution-for-standalone.md)
 * [基于双活-备份的 DR 解决方案](./dr-solution-based-on-active-active-failover.md)

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/operations/remote-wal/quick-start.md → i18n/zh/docusaurus-plugin-content-docs/current/user-guide/operations/disaster-recovery/remote-wal/quick-start.md

@@ -1,13 +1,13 @@
 # 快速开始
 
-## 什么是 Remote WAL
+## 什么是远程 WAL（Remote WAL）
 
 [WAL](/contributor-guide/datanode/wal.md#introduction)(Write-Ahead Logging) 是 GreptimeDB 中的一个关键组件，它持久记录每一次数据修改，以确保不会丢失缓存在内存中的数据。我们在 [Datanode](/user-guide/concepts/why-greptimedb.md) 服务中用持久的嵌入式存储引擎 [raft-engine](https://github.com/tikv/raft-engine) 将 WAL 实现为一个模块。在公共云中部署 GreptimeDB 时，我们可以在云存储（AWS EBS、GCP 持久盘等）中持久存储 WAL 数据，以实现 0 RPO。然而，由于 WAL 与 Datanode 紧密耦合，导致部署过程中的 RTO（Recovery Time Objective）较长。此外，由于 raft-engine 无法支持多日志订阅，这使得实现 region 热备份和 region 迁移变得困难。
 
 为了解决上述问题，我们决定设计并实现一个远程 WAL。远程 WAL 将 WAL 从 Datanode 分离到远程服务，我们选择了 Apache Kafka 作为远程服务。Apache Kafka 在流处理中被广泛采用，展现出卓越的分布式容错能力和基于主题的订阅机制。在发布 v0.5.0 版本时，我们引入了 Apache Kafka 作为 WAL 的可选存储引擎。
 
 
-## 运行带有 Remote WAL 的 Standalone GreptimeDB
+## 运行带有远程 WAL 的 Standalone GreptimeDB
 
 通过以下步骤使用 Docker 体验远程 WAL 非常简单。在这个快速开始中，我们将创建一个采用 KRaft 模式的 Kafka 集群，并将其作为独立 GreptimeDB 的远程 WAL。
 

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/operations/overview.md

@@ -5,5 +5,4 @@
 * [灾难恢复](./disaster-recovery/overview.md)
 * [监控](./monitoring.md)
 * [Tracing](./tracing.md)
-* [Remote WAL](./remote-wal/quick-start.md)
 * [Region 迁移](./region-migration.md)

sidebars.ts

@@ -185,16 +185,18 @@ const sidebars: SidebarsConfig = {
  label: 'Disaster Recovery',
  items: [
  'user-guide/operations/disaster-recovery/overview',
+ {
+ type: 'category',
+ label: 'Remote WAL',
+ items: [
+ 'user-guide/operations/disaster-recovery/remote-wal/quick-start',
+ 'user-guide/operations/disaster-recovery/remote-wal/cluster-deployment'],
+ },
  'user-guide/operations/disaster-recovery/back-up-&-restore-data',
  'user-guide/operations/disaster-recovery/dr-solution-based-on-active-active-failover',
  'user-guide/operations/disaster-recovery/dr-solution-based-on-cross-region-deployment-in-single-cluster',
  ],
  },
- {
- type: 'category',
- label: 'Remote WAL',
- items: ['user-guide/operations/remote-wal/quick-start', 'user-guide/operations/remote-wal/cluster-deployment'],
- },
  'user-guide/operations/region-migration',
  'user-guide/operations/region-failover',
  'user-guide/operations/compaction',