This is an automated email from the ASF dual-hosted git repository.
davidzollo pushed a commit to branch dev
in repository https://gitbox.apache.org/repos/asf/seatunnel.git
The following commit(s) were added to refs/heads/dev by this push:
new 60e026bd0a [Docs] Improve new user onboarding flow (#11152)
60e026bd0a is described below
commit 60e026bd0a4669f7578d343e5ec6b35524095ac6
Author: Daniel <[email protected]>
AuthorDate: Mon Jun 22 18:59:44 2026 +0800
[Docs] Improve new user onboarding flow (#11152)
Co-authored-by: David Zollo <[email protected]>
---
docs/en/connectors/formats/overview.md | 19 ++
docs/en/connectors/overview.md | 39 ++++
docs/en/connectors/sink-overview.md | 21 ++
docs/en/connectors/source-overview.md | 21 ++
docs/en/getting-started/job-configuration-guide.md | 1 +
docs/en/getting-started/locally/deployment.md | 7 +
docs/en/getting-started/locally/overview.md | 29 +++
docs/en/getting-started/overview.md | 3 +
docs/en/getting-started/recipes/http-to-jdbc.md | 4 +-
docs/en/getting-started/recipes/overview.md | 25 +++
docs/en/introduction/about.md | 101 +++++----
docs/en/introduction/concepts/config.md | 68 +++---
docs/en/introduction/how-it-works.md | 34 +++
docs/en/transforms/overview.md | 23 ++
docs/sidebars.js | 244 +++++++++------------
docs/zh/connectors/connector-faq.md | 65 ------
.../zh/connectors/connector-isolated-dependency.md | 25 +--
docs/zh/connectors/formats/overview.md | 19 ++
docs/zh/connectors/overview.md | 39 ++++
docs/zh/connectors/sink-overview.md | 21 ++
docs/zh/connectors/source-overview.md | 21 ++
docs/zh/getting-started/job-configuration-guide.md | 5 +-
docs/zh/getting-started/locally/deployment.md | 7 +
docs/zh/getting-started/locally/overview.md | 29 +++
docs/zh/getting-started/overview.md | 23 +-
.../getting-started/recipes/file-to-starrocks.md | 2 +-
docs/zh/getting-started/recipes/http-to-jdbc.md | 4 +-
docs/zh/getting-started/recipes/overview.md | 25 +++
docs/zh/introduction/about.md | 109 +++++----
docs/zh/introduction/concepts/config.md | 64 +++---
docs/zh/introduction/how-it-works.md | 52 ++++-
docs/zh/transforms/overview.md | 23 ++
32 files changed, 743 insertions(+), 429 deletions(-)
diff --git a/docs/en/connectors/formats/overview.md
b/docs/en/connectors/formats/overview.md
new file mode 100644
index 0000000000..3153b525ec
--- /dev/null
+++ b/docs/en/connectors/formats/overview.md
@@ -0,0 +1,19 @@
+---
+slug: /connectors/formats
+sidebar_position: 1
+---
+
+# Formats
+
+Format docs explain how SeaTunnel maps between its internal row model and
external data encodings such as Avro, Debezium JSON, or Protobuf. Read this
section when the connector itself is not enough and you also need to control
the payload shape.
+
+## When You Should Read Format Docs
+
+- your source or sink exchanges schema-based payloads
+- your CDC pipeline depends on a specific envelope format
+- you need to align external serialization with downstream consumers
+
+## Useful Next Pages
+
+- [Data Format Handling](../../architecture/data-format-handling.md)
+- [Connector FAQ](../connector-faq.md)
diff --git a/docs/en/connectors/overview.md b/docs/en/connectors/overview.md
new file mode 100644
index 0000000000..c5cb7707a9
--- /dev/null
+++ b/docs/en/connectors/overview.md
@@ -0,0 +1,39 @@
+---
+slug: /connectors
+---
+
+# Connectors Overview
+
+This page is the shortest path for choosing the right SeaTunnel connector
entry point. Start by answering three questions: where does data come from,
where does it go, and do you need CDC or special formats.
+
+## Choose An Entry Point
+
+| What you need right now | Start here |
+| --- | --- |
+| Read data from an external system | [Source
Connectors](./source-overview.md) |
+| Write data into a target system | [Sink Connectors](./sink-overview.md) |
+| Follow a real source-to-sink example | [Scenario
Recipes](../getting-started/recipes/overview.md) |
+| Understand shared connector parameters | [Source Common
Options](./common-options/source-common-options.md) and [Sink Common
Options](./common-options/sink-common-options.md) |
+| Build a CDC pipeline | [CDC Production
Cookbook](./cdc-production-cookbook.md) |
+| Troubleshoot plugin installation or dependency conflicts | [Connector
FAQ](./connector-faq.md) and [Connector Isolated Dependency
Loading](./connector-isolated-dependency.md) |
+
+## Recommended Reading Order For New Users
+
+1. Run one local job first, then come back to choose real connectors.
+2. Pick the source and sink before comparing transform or format details.
+3. Check plugin installation and third-party driver requirements before
copying connector examples.
+4. Read CDC and recovery details only when your pipeline actually needs them.
+
+## What To Verify Before You Commit To A Connector
+
+- whether the connector supports your runtime engine
+- whether extra drivers or plugin jars are required
+- whether the connector supports batch, streaming, CDC, or exactly-once
semantics
+- whether the parameter names and examples match your SeaTunnel version
+
+## Useful Next Pages
+
+- [Job Configuration Guide](../getting-started/job-configuration-guide.md)
+- [Scenario Recipes](../getting-started/recipes/overview.md)
+- [Transforms Overview](../transforms)
+- [Quick Start With SeaTunnel
Engine](../getting-started/locally/quick-start-seatunnel-engine.md)
diff --git a/docs/en/connectors/sink-overview.md
b/docs/en/connectors/sink-overview.md
new file mode 100644
index 0000000000..c3e28f4593
--- /dev/null
+++ b/docs/en/connectors/sink-overview.md
@@ -0,0 +1,21 @@
+---
+slug: /connectors/sink
+sidebar_position: 1
+---
+
+# Sink Connectors
+
+Use this page when your first question is "where should SeaTunnel write data?"
Start by matching the target system, then verify write guarantees, table
behavior, driver requirements, and any connector-specific delivery constraints.
+
+## Before You Pick A Sink
+
+- confirm the target system and table or object layout
+- confirm whether you need at-least-once, exactly-once, or idempotent writes
+- confirm whether extra drivers, SDKs, or cloud credentials are required
+- confirm whether the connector supports the write mode your job expects
+
+## Useful Next Pages
+
+- [Sink Common Options](../common-options/sink-common-options.md)
+- [Connector FAQ](../connector-faq.md)
+- [Connector Isolated Dependency Loading](../connector-isolated-dependency.md)
diff --git a/docs/en/connectors/source-overview.md
b/docs/en/connectors/source-overview.md
new file mode 100644
index 0000000000..7d4cb295d5
--- /dev/null
+++ b/docs/en/connectors/source-overview.md
@@ -0,0 +1,21 @@
+---
+slug: /connectors/source
+sidebar_position: 1
+---
+
+# Source Connectors
+
+Use this page when your first question is "where should SeaTunnel read data
from?" Start by matching your external system, then verify plugin installation,
driver dependencies, and whether the connector supports batch, streaming, or
CDC behavior that your job needs.
+
+## Before You Pick A Source
+
+- confirm the external system you want to read from
+- confirm whether you need snapshot, incremental, or CDC semantics
+- confirm whether extra drivers, SDKs, or authentication setup are required
+- confirm the connector examples match your current SeaTunnel version
+
+## Useful Next Pages
+
+- [Source Common Options](../common-options/source-common-options.md)
+- [CDC Production Cookbook](../cdc-production-cookbook.md)
+- [Connector FAQ](../connector-faq.md)
diff --git a/docs/en/getting-started/job-configuration-guide.md
b/docs/en/getting-started/job-configuration-guide.md
index 6ed9f01e74..a24f65a6e3 100644
--- a/docs/en/getting-started/job-configuration-guide.md
+++ b/docs/en/getting-started/job-configuration-guide.md
@@ -172,6 +172,7 @@ Before running a job, verify these points:
## Next Steps
- Need a runnable first example: [Quick Start With SeaTunnel
Engine](./locally/quick-start-seatunnel-engine.md)
+- Need end-to-end examples built from real connectors: [Scenario
Recipes](./recipes/overview.md)
- Need connector parameters: [Source Connectors](../connectors/source) and
[Sink Connectors](../connectors/sink)
- Need transform capabilities: [Transforms](../transforms)
- Need engine-level details: [Engine Overview](../engines/overview.md)
diff --git a/docs/en/getting-started/locally/deployment.md
b/docs/en/getting-started/locally/deployment.md
index b0a91931b7..a0fd3ca14b 100644
--- a/docs/en/getting-started/locally/deployment.md
+++ b/docs/en/getting-started/locally/deployment.md
@@ -83,6 +83,13 @@ When built from the source code, all the connector plugins
and some necessary de
Now you have downloaded the SeaTunnel binary package and the connector
plugins. Next, you can choose different engine option to run synchronization
tasks.
+:::tip
+
+If you are new to SeaTunnel, start with [Quick Start With SeaTunnel
Engine](quick-start-seatunnel-engine.md).
+It is the default engine and usually the shortest path to a successful first
run.
+
+:::
+
If you use Flink to run the synchronization task, there is no need to deploy
the SeaTunnel Engine service cluster. You can refer to [Quick Start With
Flink](quick-start-flink.md) to run your synchronization task.
If you use Spark to run the synchronization task, there is no need to deploy
the SeaTunnel Engine service cluster. You can refer to [Quick Start With
Spark](quick-start-spark.md) to run your synchronization task.
diff --git a/docs/en/getting-started/locally/overview.md
b/docs/en/getting-started/locally/overview.md
new file mode 100644
index 0000000000..668d78001d
--- /dev/null
+++ b/docs/en/getting-started/locally/overview.md
@@ -0,0 +1,29 @@
+---
+slug: /getting-started/locally
+---
+
+# Local Quick Start
+
+Use this page when you want the shortest path to run SeaTunnel on your
machine. For most new users, the default recommendation is still **SeaTunnel
Engine (Zeta)** because it has the fastest feedback loop and the least setup
friction.
+
+## Pick A Local Starting Path
+
+| Your situation | Start here |
+| --- | --- |
+| I need the default first-run path | [Quick Start With SeaTunnel
Engine](./quick-start-seatunnel-engine.md) |
+| I need installation and plugin setup first | [Deployment](./deployment.md) |
+| My team already runs Flink | [Quick Start With
Flink](./quick-start-flink.md) |
+| My team already runs Spark | [Quick Start With
Spark](./quick-start-spark.md) |
+
+## Recommended First-Run Order
+
+1. Read [Deployment](./deployment.md).
+2. Install the sample plugins you need.
+3. Run your first local job with [Run Your First Job](./run-your-first-job.md)
or the [SeaTunnel Engine quick start](./quick-start-seatunnel-engine.md).
+4. Move to the [Job Configuration Guide](../job-configuration-guide.md) after
the sample succeeds.
+
+## When To Read The Other Paths
+
+- Use the Flink path only when you already operate Flink and want SeaTunnel to
fit that environment.
+- Use the Spark path only when your workload is already centered on Spark.
+- Use this local section first, then move to cluster deployment after you have
one working pipeline.
diff --git a/docs/en/getting-started/overview.md
b/docs/en/getting-started/overview.md
index 487e1d4f4b..ba242ea2af 100644
--- a/docs/en/getting-started/overview.md
+++ b/docs/en/getting-started/overview.md
@@ -50,6 +50,7 @@ If you want to validate your installation in the shortest
path:
- [Source Connectors](../connectors/source)
- [Sink Connectors](../connectors/sink)
- [Transforms](../transforms)
+- [Scenario Recipes](./recipes/overview.md)
### Path C: I need to understand architecture first
@@ -77,5 +78,7 @@ Once the sample job is working, the next step is usually one
of these:
Use these pages next:
- [Job Configuration Guide](./job-configuration-guide.md)
+- [Scenario Recipes](./recipes/overview.md)
- [SeaTunnel Engine(Zeta) Deployment](../engines/zeta/deployment.md)
- [REST API And Web UI](../engines/zeta/rest-api-and-web-ui.md)
+- [Submitting Jobs to a Remote Zeta
Cluster](../getting-started/submit-job-to-remote-zeta-cluster.md)
diff --git a/docs/en/getting-started/recipes/http-to-jdbc.md
b/docs/en/getting-started/recipes/http-to-jdbc.md
index 45bfb660be..9d239fa053 100644
--- a/docs/en/getting-started/recipes/http-to-jdbc.md
+++ b/docs/en/getting-started/recipes/http-to-jdbc.md
@@ -1,9 +1,9 @@
---
sidebar_position: 4
-title: Http to JDBC
+title: HTTP to JDBC
---
-# Http to JDBC
+# HTTP to JDBC
Use this recipe when you want to pull structured data from an HTTP API and
store the result in a relational database.
diff --git a/docs/en/getting-started/recipes/overview.md
b/docs/en/getting-started/recipes/overview.md
new file mode 100644
index 0000000000..9bab5d5a73
--- /dev/null
+++ b/docs/en/getting-started/recipes/overview.md
@@ -0,0 +1,25 @@
+---
+slug: /getting-started/recipes
+---
+
+# Scenario Recipes
+
+These recipes are best read after your first local job succeeds. Instead of
reading every example in order, start with the pipeline shape that is closest
to your real source and sink.
+
+## Choose A Recipe By Pipeline Goal
+
+| Goal | Start here |
+| --- | --- |
+| CDC from MySQL into an analytics database | [MySQL CDC to
Doris](./mysql-cdc-to-doris.md) |
+| JDBC extraction into object storage | [JDBC to S3](./jdbc-to-s3.md) |
+| Streaming from Kafka into a table format | [Kafka to
Iceberg](./kafka-to-iceberg.md) |
+| HTTP ingestion into a relational target | [HTTP to JDBC](./http-to-jdbc.md) |
+| File-based loading into an analytical system | [File to
StarRocks](./file-to-starrocks.md) |
+| Multi-table CDC orchestration | [Multi-Table CDC](./multi-table-cdc.md) |
+
+## How To Read A Recipe
+
+1. Confirm the source and sink combination matches your target pipeline.
+2. Compare the `env`, `source`, `transform`, and `sink` sections with your own
job.
+3. Replace only one system at a time when adapting the sample.
+4. If the sample depends on CDC, drivers, or extra plugins, verify those
prerequisites before running it.
diff --git a/docs/en/introduction/about.md b/docs/en/introduction/about.md
index 99d51a5cf4..0a8b0f9564 100644
--- a/docs/en/introduction/about.md
+++ b/docs/en/introduction/about.md
@@ -5,11 +5,12 @@
[](https://s.apache.org/seatunnel-slack)
[](https://x.com/ASFSeaTunnel)
-SeaTunnel is a multimodal, ultra-high-performance, distributed data
integration tool, capable of synchronizing vast amounts of data daily. It's
trusted by numerous companies for its efficiency and stability.
+SeaTunnel is a multimodal, high-performance, distributed data integration
platform.
+It helps teams move and synchronize data across databases, files, data lakes,
and streaming systems with one unified job model.
## Start Here
-If you are new to SeaTunnel, use this short reading path:
+If this is your first time using SeaTunnel, follow this reading path:
<div
style={{
@@ -38,77 +39,73 @@ If you are new to SeaTunnel, use this short reading path:
- [Getting Started Overview](../getting-started/overview.md) for the shortest
path into the docs
- [Quick Start With SeaTunnel
Engine](../getting-started/locally/quick-start-seatunnel-engine.md) for the
first local run
- [Job Configuration Guide](../getting-started/job-configuration-guide.md) for
writing real jobs
-- [Architecture Overview](../architecture/overview.md) if you want the system
view first
+- [How It Works](how-it-works.md) for the execution model before going deeper
-## Get Help And Join The Community
-
-If you are evaluating SeaTunnel or running into issues, use these entry points
first:
-
-- [FAQ](../faq.md) for common usage, CDC, and configuration questions
-- [Developer Setup](../developer/setup.md) if you want to build or debug
SeaTunnel locally
-- [Contribution Path](../developer/contribution-path.md) if you want to start
contributing with the smallest reasonable scope
-- [Contribute Plugin](../developer/contribute-plugin.md) if you want to
contribute a connector or transform
-- [GitHub Issues](https://github.com/apache/seatunnel/issues), and the [dev
mailing list](https://lists.apache.org/[email protected]) if
you need community help
+If you already operate Flink or Spark clusters, you can also jump directly to
+[Quick Start With Flink](../getting-started/locally/quick-start-flink.md) or
+[Quick Start With Spark](../getting-started/locally/quick-start-spark.md).
-## Why We Need SeaTunnel
+## What SeaTunnel Helps You Do
-SeaTunnel focuses on data integration and data synchronization, and is mainly
designed to solve common problems in the field of data integration:
+SeaTunnel is designed for the jobs data teams usually need to deliver first:
-* **Various data sources**: There are hundreds of commonly-used data sources
with incompatible versions. With the emergence of new technologies, more data
sources are appearing. It is difficult for users to find a tool that can fully
and quickly support these data sources.
-* **Multimodal data integration**: In addition to structured data, users also
need to integrate video, images, binary files, structured and unstructured text
data. However, existing data integration tools are mainly focused on structured
data.
-* **Complex synchronization scenarios**: Data synchronization needs to support
various synchronization scenarios such as offline-full synchronization,
offline-incremental synchronization, CDC, real-time synchronization, and full
database synchronization.
-* **High resource demand**: Existing data integration and data synchronization
tools often require vast computing resources or JDBC connection resources to
complete real-time synchronization of massive small tables. This has increased
the burden on enterprises.
-* **Lack of quality and monitoring**: Data integration and synchronization
processes often experience loss or duplication of data. The synchronization
process lacks monitoring, and it is impossible to intuitively understand the
real situation of the data during the task process.
-* **Complex technology stack**: The technology components used by enterprises
are different, and users need to develop corresponding synchronization programs
for different components to complete data integration.
-* **Difficulty in management and maintenance**: Limited to different
underlying technology components (Flink/Spark), offline synchronization and
real-time synchronization often have be developed and managed separately, which
increases the difficulty of management and maintenance.
+- **Move data between many systems**: databases, message queues, file systems,
object storage, data lakes, and SaaS systems
+- **Handle both batch and streaming workloads**: one connector model can serve
full loads, incremental loads, CDC, and real-time synchronization
+- **Keep job definitions understandable**: a SeaTunnel job is still mainly
`env`, `source`, `transform`, and `sink`
+- **Reduce operational cost**: SeaTunnel focuses on high throughput, lower
dependency overhead, and practical observability
-## Features Of SeaTunnel
+## Why Teams Choose SeaTunnel
-* **Rich and extensible Connector**: SeaTunnel provides a Connector API that
does not depend on a specific execution engine. Connectors (Source, Transform,
Sink) developed based on this API can run on many different engines, such as
SeaTunnel Engine(Zeta), Flink, and Spark.
-* **Connector plugin**: The plugin design allows users to easily develop their
own Connector and integrate it into the SeaTunnel project. SeaTunnel currently
supports more than 160 connectors, and the ecosystem continues to expand.
-* **Batch-stream integration**: Connectors developed based on the SeaTunnel
Connector API are perfectly compatible with offline synchronization, real-time
synchronization, full-synchronization, incremental synchronization and other
scenarios. They greatly reduce the difficulty of managing data integration
tasks.
-* **Distributed snapshot**: Supports a distributed snapshot algorithm to
ensure data consistency.
-* **Multi-engine support**: SeaTunnel uses the SeaTunnel Engine(Zeta) for data
synchronization by default. SeaTunnel also supports the use of Flink or Spark
as the execution engine of the Connector to adapt to the enterprise's existing
technical components. SeaTunnel supports multiple versions of Spark and Flink.
-* **JDBC multiplexing, database log multi-table parsing**: SeaTunnel supports
multi-table or whole database synchronization, which solves the problem of
over-JDBC connections; and supports multi-table or whole database log reading
and parsing, which solves the need for CDC multi-table synchronization
scenarios to deal with problems with repeated reading and parsing of logs.
-* **High throughput and low latency**: SeaTunnel supports parallel reading and
writing, providing stable and reliable data synchronization capabilities with
high throughput and low latency.
-* **Perfect real-time monitoring**: SeaTunnel supports detailed monitoring
information of each step in the data synchronization process, allowing users to
easily understand the number of data, data size, QPS and other information read
and written by the synchronization task.
-* **Two job development methods are supported**: coding and canvas design. The
SeaTunnel web project https://github.com/apache/seatunnel-web provides visual
management of jobs, scheduling, running and monitoring capabilities.
+- **Connector-first design**: SeaTunnel provides a unified Connector API, so
Source, Transform, and Sink plugins can be reused across engines
+- **Flexible engine choice**: start with SeaTunnel Engine (Zeta), or run on
Flink or Spark when that better fits your environment
+- **Built for data synchronization**: multi-table sync, CDC scenarios, and
large-scale job execution are first-class use cases
+- **Operational visibility**: jobs expose runtime metrics and task information
that help you understand throughput and stability
+- **Room to grow**: teams can begin with a single local job and later move to
larger clusters and more advanced deployments
-## SeaTunnel Work Flowchart
+## Understand SeaTunnel In One Picture
-The runtime process of SeaTunnel is shown in the figure above.
+You can understand the runtime flow in three ideas:
-The user configures the job information and selects the execution engine to
submit the job.
+### 1. A SeaTunnel job is a pipeline
-The Source Connector is responsible for parallel reading and sending the data
to the downstream Transform or directly to the Sink, and the Sink writes the
data to the destination. It is worth noting that Source, Transform and Sink can
be easily developed and extended by yourself.
+You describe the job in a config file, then SeaTunnel runs a pipeline from
**Source** to **Transform** to **Sink**.
-SeaTunnel is an EtL(T) data integration tool. Therefore, in SeaTunnel,
transform can only be used to perform some simple transformations on data, such
as converting the data of a column to uppercase or lowercase, changing the
column name, or splitting a column into multiple columns.
+### 2. Connectors define what you read and write
-The default engine used by SeaTunnel is [SeaTunnel
Engine](../engines/zeta/about.md). If you choose to use the Flink or Spark
engine, SeaTunnel will package the Connector into a Flink or Spark program and
submit it to Flink or Spark to run.
+SeaTunnel supports a broad set of [source connectors](../connectors/source),
+[sink connectors](../connectors/sink), and [transforms](../transforms).
+If you need custom behavior, you can also extend these plugin types.
-## Connector
+### 3. The engine defines where the job runs
-- **Source Connectors** SeaTunnel supports reading data from various
relational, graph, NoSQL, document, and memory databases; distributed file
systems such as HDFS; and a variety of cloud storage solutions, such as S3 and
OSS. We also support data reading of many common SaaS services. You can access
the detailed list [Here](../connectors/source). If you want, You can develop
your own source connector and easily integrate it into SeaTunnel.
+[SeaTunnel Engine (Zeta)](../engines/zeta/about.md) is the default choice and
the recommended starting point for most new users.
+If you already rely on Flink or Spark, SeaTunnel can submit the same
connector-based job model there as well.
-- **Transform Connector** If the schema is different between source and Sink,
You can use the Transform Connector to change the schema read from source and
make it the same as the Sink schema.
+## Choose An Engine
-- **Sink Connector** SeaTunnel supports writing data to various relational,
graph, NoSQL, document, and memory databases; distributed file systems such as
HDFS; and a variety of cloud storage solutions, such as S3 and OSS. We also
support writing data to many common SaaS services. You can access the detailed
list [Here](../connectors/sink). If you want, you can develop your own Sink
connector and easily integrate it into SeaTunnel.
+| Engine | Best starting point | When to use it |
+| --- | --- | --- |
+| [SeaTunnel Engine (Zeta)](../engines/zeta/about.md) | Recommended for most
new users | You want the simplest path to run SeaTunnel jobs end to end |
+| [Apache Flink](../engines/flink.md) | Good for existing Flink users | You
already operate Flink and want SeaTunnel to fit that platform |
+| [Apache Spark](../engines/spark.md) | Good for existing Spark users | You
already run Spark for batch workloads and want to reuse that stack |
-## Who Uses SeaTunnel
+## Continue Learning
-SeaTunnel has lots of users. You can find more information about them in
[Users](https://seatunnel.apache.org/user).
+- [How It Works](how-it-works.md) for the runtime model without the full
architecture deep dive
+- [Intro To Config File](concepts/config.md) for how to write real jobs
+- [Connector documentation](../connectors/source) for choosing the systems you
want to read from and write to
+- [Architecture Overview](../architecture/overview.md) for the deeper system
design
+- [FAQ](../faq.md) for common usage, CDC, and configuration questions
-## Landscapes
+## Get Help And Join The Community
-<p align="center">
-<br/><br/>
-<img src="https://landscape.cncf.io/images/left-logo.svg"; width="150"
alt=""/> <img src="https://landscape.cncf.io/images/right-logo.svg";
width="200" alt=""/>
-<br/><br/>
-SeaTunnel enriches the <a
href="https://landscape.cncf.io/?item=app-definition-and-development--streaming-messaging--seatunnel";>CNCF
CLOUD NATIVE Landscape</a >.
-</p >
+- [Developer Setup](../developer/setup.md) if you want to build or debug
SeaTunnel locally
+- [Contribution Path](../developer/contribution-path.md) if you want to start
contributing with the smallest reasonable scope
+- [Contribute Plugin](../developer/contribute-plugin.md) if you want to
contribute a connector or transform
+- [GitHub Issues](https://github.com/apache/seatunnel/issues),
[Slack](https://s.apache.org/seatunnel-slack), and the [dev mailing
list](https://lists.apache.org/[email protected]) if you need
community help
-## Learn more
+## Who Uses SeaTunnel
-You can see [Run your first
job](../getting-started/locally/run-your-first-job.md) for the next steps.
+SeaTunnel has lots of users. You can find more information about them in
[Users](https://seatunnel.apache.org/user).
diff --git a/docs/en/introduction/concepts/config.md
b/docs/en/introduction/concepts/config.md
index 19855ffc9c..9a7e0891e4 100644
--- a/docs/en/introduction/concepts/config.md
+++ b/docs/en/introduction/concepts/config.md
@@ -1,19 +1,14 @@
# Intro To Config File
-In SeaTunnel, the most important thing is the config file, through which users
can customize their own data
-synchronization requirements to maximize the potential of SeaTunnel. So next,
I will introduce you how to
-configure the config file.
+If you are writing your first real SeaTunnel job, this page is the fastest way
to understand the four blocks that appear in almost every config: `env`,
`source`, `transform`, and `sink`.
-The main format of the config file is `hocon`, for more details you can refer
to [HOCON-GUIDE](https://github.com/lightbend/config/blob/main/HOCON.md),
-BTW, we also support the `json` format, but you should keep in mind that the
name of the config file should end with `.json`.
+SeaTunnel supports `hocon`, `json`, and `SQL` config formats. HOCON is the
most common format in quick starts and production examples. For SQL format, see
[SQL configuration](../configuration/sql-config.md).
-We also support the `SQL` format, please refer to [SQL
configuration](../configuration/sql-config.md) for more details.
+If you want the shortest first-run path before reading this page, start with
[Getting Started Overview](../../getting-started/overview.md) and [Quick Start
With SeaTunnel
Engine](../../getting-started/locally/quick-start-seatunnel-engine.md).
## Example
-Before you read on, you can find config file
-examples
[Here](https://github.com/apache/seatunnel/tree/dev/seatunnel-e2e/seatunnel-connector-v2-e2e/connector-jdbc-e2e/connector-jdbc-e2e-part-1/src/test/resources)
from the binary package's
-config directory.
+Before you read on, you can find example configs
[here](https://github.com/apache/seatunnel/tree/dev/seatunnel-e2e/seatunnel-connector-v2-e2e/connector-jdbc-e2e/connector-jdbc-e2e-part-1/src/test/resources)
and in the binary package's `config` directory.
## Config File Structure
@@ -67,33 +62,25 @@ sink {
}
```
-As you can see, the config file contains several sections: env, source,
transform, sink. Different modules
-have different functions. After you understand these modules, you will see how
SeaTunnel works.
+Most SeaTunnel jobs follow this structure: `env`, `source`, `transform`, and
`sink`. Once you understand these four sections, it becomes much easier to read
quick starts and connector examples.
### env
-Used to add some engine optional parameters, no matter which engine (Zeta,
Spark or Flink), the corresponding
-optional parameters should be filled in here.
+Use `env` for job-level and engine-level settings such as `job.mode`,
`parallelism`, checkpoint options, and engine-specific parameters.
-Note that we have separated the parameters by engine, and for the common
parameters, we can configure them as before.
-For flink and spark engine, the specific configuration rules of their
parameters can be referred to [JobEnvConfig](../configuration/JobEnvConfig.md).
+Common parameters are shared across engines. Engine-specific parameters are
separated by prefix. For Flink and Spark, see
[JobEnvConfig](../configuration/JobEnvConfig.md).
<!-- TODO add supported env parameters -->
### source
-Source is used to define where SeaTunnel needs to fetch data, and use the
fetched data for the next step.
-Multiple sources can be defined at the same time. The supported source can be
found
-in [Source of SeaTunnel](../../connectors/source). Each source has its own
specific parameters to define how to
-fetch data, and SeaTunnel also extracts the parameters that each source will
use, such as
-the `plugin_output` parameter, which is used to specify the name of the data
generated by the current
-source, which is convenient for follow-up used by other modules.
+`source` defines where SeaTunnel reads data from. You can declare multiple
sources in one job. Each connector has its own parameters, plus common wiring
fields such as `plugin_output`, which names the dataset produced by that source.
+
+See the full list in [Source Connectors](../../connectors/source).
### transform
-When we have the data source, we may need to further process the data, so we
have the transform module. Of
-course, this uses the word 'may', which means that we can also directly treat
the transform as non-existent,
-directly from source to sink. Like below.
+`transform` is optional. Use it when you need field mapping, filtering, type
conversion, SQL processing, or other intermediate shaping between source and
sink. If you do not need that layer, a job can go directly from source to sink,
like this:
```hocon
env {
@@ -127,28 +114,22 @@ sink {
}
```
-Like source, transform has specific parameters that belong to each module. The
supported transform can be found
-in [Transform V2 of SeaTunnel](../../transforms)
+Like source connectors, each transform has its own parameters. See
[Transforms](../../transforms).
### sink
-Our purpose with SeaTunnel is to synchronize data from one place to another,
so it is critical to define how
-and where data is written. With the sink module provided by SeaTunnel, you can
complete this operation quickly
-and efficiently. Sink and source are very similar, but the difference is
reading and writing. So please check out
-[Supported Sinks](../../connectors/sink).
+`sink` defines where the processed data is written. Sink connectors are
similar to source connectors, but they focus on write behavior, destination
schema, commit mode, and delivery guarantees.
+
+See [Supported Sinks](../../connectors/sink).
+
+### How `plugin_output` And `plugin_input` Work
+
+When a job contains multiple sources, transforms, or sinks, SeaTunnel needs a
way to describe which dataset flows into which next step. That wiring is done
by `plugin_output` and `plugin_input`.
-### Other Information
+- `plugin_output` names the dataset produced by the current source or transform
+- `plugin_input` tells a transform or sink which upstream dataset to consume
-You will find that when multiple sources and multiple sinks are defined, which
data is read by each sink, and
-which is the data read by each transform? We introduce two key configurations
called `plugin_output` and
-`plugin_input`. Each source module will be configured with a `plugin_output`
to indicate the name of the
-data source generated by the data source, and other transform and sink modules
can use `plugin_input` to
-refer to the corresponding data source name, indicating that I want to read
the data for processing. Then
-transform, as an intermediate processing module, can use both `plugin_output`
and `plugin_input`
-configurations at the same time. But you will find that in the above example
config, not every module is
-configured with these two parameters, because in SeaTunnel, there is a default
convention, if these two
-parameters are not configured, then the generated data from the last module of
the previous node will be used.
-This is much more convenient when there is only one source.
+In simple one-source jobs, you can often omit them because SeaTunnel uses a
default convention and passes the previous module's output forward
automatically.
## Multi-line Support
@@ -337,5 +318,6 @@ sink {
## What's More
-- Start write your own config file now, choose the
[connector](../../connectors/source) you want to use, and configure the
parameters according to the connector's documentation.
-- If you want to know the details of the format configuration, please see
[HOCON](https://github.com/lightbend/config/blob/main/HOCON.md).
+- Start writing your own config file now, choose the
[connector](../../connectors/source) you want to use, and configure it
according to the connector documentation.
+- See [JobEnvConfig](../configuration/JobEnvConfig.md) when you need
engine-specific settings.
+- See [HOCON](https://github.com/lightbend/config/blob/main/HOCON.md) if you
want the full syntax details.
diff --git a/docs/en/introduction/how-it-works.md
b/docs/en/introduction/how-it-works.md
index e7d1957502..a855a0a9c8 100644
--- a/docs/en/introduction/how-it-works.md
+++ b/docs/en/introduction/how-it-works.md
@@ -4,6 +4,18 @@ sidebar_position: 2
# How it works
+## What New Users Should Know First
+
+You do not need to understand every internal module before running SeaTunnel.
+For most first-time users, the practical order is:
+
+1. run one job locally
+2. learn the config structure
+3. choose the right connectors and engine
+4. come back here when you want to understand the runtime model better
+
+SeaTunnel is easiest to understand as a config-driven pipeline that runs on a
chosen execution engine.
+
## Overview
SeaTunnel is a distributed multimodal data integration tool with a pluggable
architecture. It decouples the connector layer from the execution engine,
allowing the same connectors to run on different engines.
@@ -35,6 +47,28 @@ flowchart TD
linkStyle default stroke:#5db8e2,stroke-width:2px;
```
+## The Four Building Blocks
+
+### 1. Job Configuration
+
+Your config file describes what to read, how to transform it, where to write
it, and which engine settings should be used.
+
+### 2. SeaTunnel Core
+
+SeaTunnel parses the config, builds an execution plan, loads plugins, and
coordinates submission to the selected engine.
+
+### 3. Source -> Transform -> Sink
+
+This is the data path most users should remember first:
+
+- **Source** reads from external systems
+- **Transform** optionally reshapes or filters the data
+- **Sink** writes the result to the target system
+
+### 4. Execution Engine
+
+The engine decides where the job runs. Most new users should start with
[SeaTunnel Engine (Zeta)](../engines/zeta/about.md), then move to Flink or
Spark only when their environment already depends on those platforms.
+
## Recommended Reading Path
If you are building your first system-level understanding, read in this order:
diff --git a/docs/en/transforms/overview.md b/docs/en/transforms/overview.md
new file mode 100644
index 0000000000..c4bcb62430
--- /dev/null
+++ b/docs/en/transforms/overview.md
@@ -0,0 +1,23 @@
+---
+slug: /transforms
+---
+
+# Transforms Overview
+
+Transforms sit between source and sink. They are used for field mapping,
filtering, SQL processing, table routing, and other mid-pipeline operations.
New users do not need to read every transform first; come here after you
already know what you want to read and where you want to write it.
+
+## Pick A Starting Point
+
+| Goal | Start here |
+| --- | --- |
+| Understand how transforms connect datasets | [Transform Common
Options](./common-options/common-options.md) |
+| Filter rows or trim fields | [Filter](./filter.md) and [Field
Mapper](./field-mapper.md) |
+| Use SQL-style expressions | [SQL](./sql.md) and [SQL
Functions](./sql-functions.md) |
+| Rename or reshape fields | [Field Rename](./field-rename.md) and
[Split](./split.md) |
+| Work with multiple tables | [Transform Multi
Table](./transform-multi-table.md) and [Table Merge](./table-merge.md) |
+
+## Recommended Order For New Users
+
+1. Read the common options page first so `plugin_input` and `plugin_output`
are clear.
+2. Choose the simplest transform that matches your goal before moving to SQL
or multi-table orchestration.
+3. Add transforms one step at a time and keep the pipeline readable while you
validate the job.
diff --git a/docs/sidebars.js b/docs/sidebars.js
index 863de991a0..eda13f8e29 100644
--- a/docs/sidebars.js
+++ b/docs/sidebars.js
@@ -30,74 +30,9 @@ const sidebars = {
"type": "category",
"label": "Concepts",
"items": [
- "introduction/concepts/config",
"introduction/concepts/connector-v2-features",
"introduction/concepts/schema-feature"
]
- },
- {
- "type": "category",
- "label": "Configuration",
- "items": [
- "introduction/configuration/JobEnvConfig",
- "introduction/configuration/sql-config",
-
"introduction/configuration/config-encryption-decryption",
- "introduction/configuration/metalake",
- "introduction/configuration/sink-options-placeholders",
- "introduction/configuration/schema-evolution",
- "introduction/configuration/speed-limit"
- ]
- }
- ]
- },
- {
- "type": "category",
- "label": "Architecture",
- "items": [
- "architecture/overview",
- "architecture/design-philosophy",
- "architecture/configuration-and-option-system",
- "architecture/core-api-design",
- "architecture/transform-plugin-system",
- "architecture/cdc-pipeline-architecture",
- "architecture/data-format-handling",
- "architecture/table-schema-and-type-system",
- "architecture/plugin-discovery-and-class-loading",
- {
- "type": "category",
- "label": "API Design",
- "items": [
- "architecture/api-design/source-architecture",
- "architecture/api-design/sink-architecture",
- "architecture/api-design/catalog-table",
- "architecture/api-design/translation-layer",
- "architecture/api-design/flink-translation-layer",
- "architecture/api-design/spark-translation-layer"
- ]
- },
- {
- "type": "category",
- "label": "Engine",
- "items": [
- "architecture/engine/engine-architecture",
- "architecture/engine/dag-execution",
- "architecture/engine/resource-management"
- ]
- },
- {
- "type": "category",
- "label": "Fault Tolerance",
- "items": [
- "architecture/fault-tolerance/checkpoint-mechanism",
- "architecture/fault-tolerance/exactly-once"
- ]
- },
- {
- "type": "category",
- "label": "Features",
- "items": [
- "architecture/features/multi-table"
- ]
}
]
},
@@ -110,12 +45,8 @@ const sidebars = {
"type": "category",
"label": "Locally",
"link": {
- "type": "generated-index",
- "title": "Local Getting Started",
- "description": "Use SeaTunnel locally, run your first
job, and validate common pipelines before moving to larger environments.",
- "slug": "/getting-started/locally",
- "keywords": ["getting-started", "local"],
- "image": "/img/favicon.ico"
+ "type": "doc",
+ "id": "getting-started/locally/overview"
},
"items": [
"getting-started/locally/run-your-first-job",
@@ -125,28 +56,6 @@ const sidebars = {
"getting-started/locally/quick-start-spark"
]
},
- {
- "type": "category",
- "label": "Recipes",
- "link": {
- "type": "generated-index",
- "title": "Scenario Recipes",
- "description": "Practical SeaTunnel recipes for common
source-to-sink pipelines.",
- "slug": "/getting-started/recipes",
- "keywords": ["recipes", "examples"],
- "image": "/img/favicon.ico"
- },
- "items": [
- "getting-started/recipes/mysql-cdc-to-doris",
- "getting-started/recipes/jdbc-to-s3",
- "getting-started/recipes/kafka-to-iceberg",
- "getting-started/recipes/http-to-jdbc",
- "getting-started/recipes/file-to-starrocks",
- "getting-started/recipes/multi-table-cdc"
- ]
- },
- "getting-started/job-configuration-guide",
- "getting-started/submit-job-to-remote-zeta-cluster",
{
"type": "category",
"label": "Docker",
@@ -164,23 +73,35 @@ const sidebars = {
}
]
},
+ {
+ "type": "category",
+ "label": "Configuration",
+ "items": [
+ "introduction/concepts/config",
+ "getting-started/job-configuration-guide",
+ "introduction/configuration/JobEnvConfig",
+ "introduction/configuration/sql-config",
+ "introduction/configuration/config-encryption-decryption",
+ "introduction/configuration/metalake",
+ "introduction/configuration/sink-options-placeholders",
+ "introduction/configuration/schema-evolution",
+ "introduction/configuration/speed-limit"
+ ]
+ },
{
"type": "category",
"label": "Connectors",
+ "link": {
+ "type": "doc",
+ "id": "connectors/overview"
+ },
"items": [
- "connectors/connector-isolated-dependency",
- "connectors/connector-faq",
- "connectors/cdc-production-cookbook",
{
"type": "category",
"label": "Source",
"link": {
- "type": "generated-index",
- "title": "Source Connectors",
- "description": "List all source connectors supported
by Apache SeaTunnel.",
- "slug": "/connectors/source",
- "keywords": ["source"],
- "image": "/img/favicon.ico"
+ "type": "doc",
+ "id": "connectors/source-overview"
},
"items": [
{
@@ -193,12 +114,8 @@ const sidebars = {
"type": "category",
"label": "Sink",
"link": {
- "type": "generated-index",
- "title": "Sink Connectors",
- "description": "List all sink connectors supported by
Apache SeaTunnel.",
- "slug": "/connectors/sink",
- "keywords": ["sink"],
- "image": "/img/favicon.ico"
+ "type": "doc",
+ "id": "connectors/sink-overview"
},
"items": [
{
@@ -207,16 +124,20 @@ const sidebars = {
}
]
},
+ {
+ "type": "category",
+ "label": "Common Options",
+ "items": [
+ "connectors/common-options/source-common-options",
+ "connectors/common-options/sink-common-options"
+ ]
+ },
{
"type": "category",
"label": "Formats",
"link": {
- "type": "generated-index",
- "title": "Formats",
- "description": "List some special formats supported by
Apache SeaTunnel.",
- "slug": "/connectors/formats",
- "keywords": ["formats"],
- "image": "/img/favicon.ico"
+ "type": "doc",
+ "id": "connectors/formats/overview"
},
"items": [
{
@@ -225,44 +146,33 @@ const sidebars = {
}
]
},
+ "connectors/cdc-production-cookbook",
{
"type": "category",
- "label": "Common Options",
- "items": [
- "connectors/common-options/source-common-options",
- "connectors/common-options/sink-common-options"
- ]
- },
- {
- "type": "category",
- "label": "Changelog",
+ "label": "Scenario Recipes",
"link": {
- "type": "generated-index",
- "title": "Connector Changelog",
- "description": "Changelog for all connectors supported
by Apache SeaTunnel.",
- "slug": "/connectors/changelog",
- "keywords": ["changelog"],
- "image": "/img/favicon.ico"
+ "type": "doc",
+ "id": "getting-started/recipes/overview"
},
"items": [
- {
- "type": "autogenerated",
- "dirName": "connectors/changelog"
- }
+ "getting-started/recipes/mysql-cdc-to-doris",
+ "getting-started/recipes/jdbc-to-s3",
+ "getting-started/recipes/kafka-to-iceberg",
+ "getting-started/recipes/http-to-jdbc",
+ "getting-started/recipes/file-to-starrocks",
+ "getting-started/recipes/multi-table-cdc"
]
- }
+ },
+ "connectors/connector-faq",
+ "connectors/connector-isolated-dependency"
]
},
{
"type": "category",
"label": "Transforms",
"link": {
- "type": "generated-index",
- "title": "Transforms",
- "description": "List all transforms supported by Apache
SeaTunnel.",
- "slug": "/transforms",
- "keywords": ["transforms"],
- "image": "/img/favicon.ico"
+ "type": "doc",
+ "id": "transforms/overview"
},
"items": [
{
@@ -322,12 +232,13 @@ const sidebars = {
"engines/zeta/separated-cluster-deployment"
]
},
+ "engines/zeta/rest-api-and-web-ui",
+ "getting-started/submit-job-to-remote-zeta-cluster",
"engines/zeta/checkpoint-storage",
"engines/zeta/state-storage-and-recovery",
"engines/zeta/engine-jar-storage-mode",
"engines/zeta/tcp",
"engines/zeta/resource-isolation",
- "engines/zeta/rest-api-and-web-ui",
{
"type": "category",
"label": "REST API",
@@ -359,6 +270,57 @@ const sidebars = {
"engines/spark"
]
},
+ {
+ "type": "category",
+ "label": "Architecture",
+ "items": [
+ "architecture/overview",
+ "architecture/design-philosophy",
+ "architecture/configuration-and-option-system",
+ "architecture/core-api-design",
+ "architecture/transform-plugin-system",
+ "architecture/cdc-pipeline-architecture",
+ "architecture/data-format-handling",
+ "architecture/table-schema-and-type-system",
+ "architecture/plugin-discovery-and-class-loading",
+ {
+ "type": "category",
+ "label": "API Design",
+ "items": [
+ "architecture/api-design/source-architecture",
+ "architecture/api-design/sink-architecture",
+ "architecture/api-design/catalog-table",
+ "architecture/api-design/translation-layer",
+ "architecture/api-design/flink-translation-layer",
+ "architecture/api-design/spark-translation-layer"
+ ]
+ },
+ {
+ "type": "category",
+ "label": "Engine",
+ "items": [
+ "architecture/engine/engine-architecture",
+ "architecture/engine/dag-execution",
+ "architecture/engine/resource-management"
+ ]
+ },
+ {
+ "type": "category",
+ "label": "Fault Tolerance",
+ "items": [
+ "architecture/fault-tolerance/checkpoint-mechanism",
+ "architecture/fault-tolerance/exactly-once"
+ ]
+ },
+ {
+ "type": "category",
+ "label": "Features",
+ "items": [
+ "architecture/features/multi-table"
+ ]
+ }
+ ]
+ },
{
"type": "category",
"label": "Tools",
diff --git a/docs/zh/connectors/connector-faq.md
b/docs/zh/connectors/connector-faq.md
deleted file mode 100644
index 53f90bf07c..0000000000
--- a/docs/zh/connectors/connector-faq.md
+++ /dev/null
@@ -1,65 +0,0 @@
----
-sidebar_position: 10
----
-
-# Connector 常见问题
-
-本页面是按 Connector 类别组织的常见问题索引，每个条目均链接到对应 Connector 文档页面的 FAQ 小节。
-
-这些 FAQ 的定位是“快速导航”，不是另一套独立事实源。涉及精确配置项名称、默认值和完整示例时，应以
-各 Connector 页面中的 option 表和对应详细章节为准。
-
-关于 SeaTunnel 通用问题（引擎部署、变量替换、调度等），请查阅[通用 FAQ](../faq.md)。
-
----
-
-## CDC 类 Connector
-
-CDC（变更数据捕获）Connector 从数据库事务日志中实时读取 INSERT / UPDATE / DELETE 变更事件。
-
-| Connector | 常见问题主题 |
-|---|---|
-| [MySQL CDC](./source/MySQL-CDC.md#常见问题) | 所需权限、binlog 配置、从库支持、无主键表、快照阶段、DDL
传播、server-id 冲突、快照性能、时区/字符集 |
-| [PostgreSQL CDC](./source/PostgreSQL-CDC.md#常见问题) |
所需权限、逻辑解码插件、备库限制、无主键表、复制槽管理、复制滞后 |
-| [Oracle CDC](./source/Oracle-CDC.md#常见问题) | LogMiner 权限、附加日志、CDB/PDB
多租户、无主键表、LogMiner 性能、支持的 Oracle 版本 |
-
----
-
-## 消息队列类 Connector
-
-| Connector | 常见问题主题 |
-|---|---|
-| [Kafka Source](./source/Kafka.md#常见问题) | `start_mode` 各取值对比、按消息 key
过滤、支持的格式、SASL/Kerberos 认证、消费组 offset 提交 |
-| [Kafka Sink](./sink/Kafka.md#常见问题) | 自动创建 topic（Broker
端行为说明）、`partition_key_fields` 为空时的行为、精确一次、SASL/Kerberos 认证、支持的格式 |
-
----
-
-## Sink 类 Connector
-
-### OLAP / 分析型存储
-
-| Connector | 常见问题主题 |
-|---|---|
-| [Doris Sink](./sink/Doris.md#常见问题) | 自动建表、2PC 精确一次、"Label already exists"
报错、DELETE 传播、列名大小写、Stream Load 格式 |
-| [StarRocks Sink](./sink/StarRocks.md#常见问题) | 自动建表、Upsert/DELETE
支持、`labelPrefix` 用法、列名大小写、`nodeUrls` 与 `base-url` 的区别 |
-| [ClickHouse Sink](./sink/Clickhouse.md#常见问题) | 自动建表、批量写入调优、支持的数据类型、"Table
doesn't exist" 报错 |
-
-### 关系型数据库
-
-| Connector | 常见问题主题 |
-|---|---|
-| [JDBC Sink](./sink/Jdbc.md#常见问题) | 自动建表、XA 精确一次、Upsert/主键配置、多表写入、JDBC 驱动未找到 |
-
-### 数据湖 / 文件系统
-
-| Connector | 常见问题主题 |
-|---|---|
-| [Hive Sink](./sink/Hive.md#常见问题) | 支持的文件格式、分区表、Kerberos 认证、小文件问题、Schema 演变 |
-
----
-
-## 找答案的建议
-
-1. **Connector 特定问题** → 直接进入对应 Connector 页面，滚动到 **FAQ** 小节。
-2. **跨 Connector 通用问题**（如"SeaTunnel 是否支持 CDC？""什么是 `schema_save_mode`？"）→
查阅[通用 FAQ](../faq.md)。
-3. **仍未解决？** → 搜索 [GitHub Issues](https://github.com/apache/seatunnel/issues)
或通过[邮件列表](https://lists.apache.org/[email protected])联系社区。
diff --git a/docs/zh/connectors/connector-isolated-dependency.md
b/docs/zh/connectors/connector-isolated-dependency.md
index 0ef0031615..951fdd5a77 100644
--- a/docs/zh/connectors/connector-isolated-dependency.md
+++ b/docs/zh/connectors/connector-isolated-dependency.md
@@ -1,25 +1,25 @@
-# Connector 依赖隔离加载机制
+# 连接器依赖隔离加载机制
-SeaTunnel 提供了针对每个 connector 的依赖隔离加载机制，方便用户管理不同连接器单独的依赖，同时避免依赖冲突并提升系统的可扩展性。
-当加载 connector 时，SeaTunnel 会从 `${SEATUNNEL_HOME}` 下的 `plugins/connector-xxx`
目录中，查找并加载该 connector 独立的依赖 jar。这种方式确保了不同 connector 所需的依赖不会相互影响，便于在复杂环境下管理大量
connector。
+SeaTunnel 提供了针对每个连接器的依赖隔离加载机制，方便用户管理不同连接器各自的依赖，同时避免依赖冲突并提升系统可扩展性。
+当加载连接器时，SeaTunnel 会从 `${SEATUNNEL_HOME}` 下的 `plugins/connector-xxx`
目录中，查找并加载该连接器独立的依赖 jar。这种方式确保不同连接器所需的依赖不会相互影响，便于在复杂环境下管理大量连接器。
## 实现原理
-每个 connector 需要将自己的依赖 jar 放置在 `${SEATUNNEL_HOME}/plugins/connector-xxx`
目录下的独立子目录中（需要手动创建）。
-子目录名称由 `plugin-mapping` 文件中的 value 值指定。SeaTunnel 启动并加载 connector 时，只会加载对应目录下的
jar，从而实现依赖的隔离。
+每个连接器都需要将自己的依赖 jar 放置在 `${SEATUNNEL_HOME}/plugins/connector-xxx`
目录下的独立子目录中（需要手动创建）。
+子目录名称由 `plugin-mapping` 文件中的 value 值指定。SeaTunnel 启动并加载连接器时，只会加载对应目录下的
jar，从而实现依赖隔离。
-目前，Zeta 引擎会保证同一个任务不同connector的jar分开加载。其他两个引擎仍然会将所有 connector 的依赖 jar
一起加载，同一个任务放置了不同版本的jar在Spark/Flink环境可能导致依赖冲突。
+目前，Zeta 引擎会保证同一个任务中的不同连接器 jar 分开加载。其他两个引擎仍然会将所有连接器依赖 jar 一起加载，同一个任务如果放置了不同版本的
jar，在 Spark/Flink 环境中可能导致依赖冲突。
## 目录结构示例
-- 通过`${SEATUNNEL_HOME}/connectors/plugin-mapping.properties`
获取每个connector对应的文件夹目录命名。
+- 通过 `${SEATUNNEL_HOME}/connectors/plugin-mapping.properties` 获取每个连接器对应的目录名称。
以AmazonDynamodb为例，假设在 `plugin-mapping` 文件中有以下配置：
```
seatunnel.source.AmazonDynamodb = connector-amazondynamodb
```
-则对应的connector依赖目录就是value值 `connector-amazondynamodb`。
+则对应的连接器依赖目录就是 value 值 `connector-amazondynamodb`。
最终的目录结构如下所示：
@@ -36,15 +36,14 @@ SEATUNNEL_HOME/
## 限制说明
-- 在Zeta引擎中，请确保所有节点的 `${SEATUNNEL_HOME}/plugins/` 目录结构一致。都需要包含相同的子目录和依赖 jar。
-- 任何没有以`connector-`开头的目录或者jar都将被当作通用依赖目录处理，所有引擎和connector都会加载此类jar。
-- 在Zeta引擎中，可以通过将通用的jar放到 `${SEATUNNEL_HOME}/lib/` 目录下来实现所有 connector 的共享依赖。
+- 在 Zeta 引擎中，请确保所有节点的 `${SEATUNNEL_HOME}/plugins/` 目录结构一致，都包含相同的子目录和依赖 jar。
+- 任何没有以 `connector-` 开头的目录或 jar 都会被当作通用依赖目录处理，所有引擎和连接器都会加载此类 jar。
+- 在 Zeta 引擎中，可以通过将通用 jar 放到 `${SEATUNNEL_HOME}/lib/` 目录下，实现所有连接器共享依赖。
## 验证
-- 通过追踪任务日志，确认每个 connector 只加载了其独立的依赖 jar。
+- 通过追踪任务日志，确认每个连接器只加载了自己独立的依赖 jar。
```log
2025-08-13T17:55:48.7732601Z [] 2025-08-13 17:55:47,270 INFO
org.apache.seatunnel.plugin.discovery.AbstractPluginDiscovery - find connector
jar and dependency for PluginIdentifier{engineType='seatunnel',
pluginType='source', pluginName='Jdbc'}:
[file:/tmp/seatunnel/plugins/Jdbc/lib/vertica-jdbc-12.0.3-0.jar,
file:/tmp/seatunnel/connectors/connector-jdbc-3.0.0-SNAPSHOT-2.12.15.jar]
```
-
diff --git a/docs/zh/connectors/formats/overview.md
b/docs/zh/connectors/formats/overview.md
new file mode 100644
index 0000000000..b7148995c6
--- /dev/null
+++ b/docs/zh/connectors/formats/overview.md
@@ -0,0 +1,19 @@
+---
+slug: /connectors/formats
+sidebar_position: 1
+---
+
+# 数据格式
+
+格式文档关注的是 SeaTunnel 内部数据模型与外部编码之间如何对应，例如 Avro、Debezium JSON、Protobuf
等。当连接器本身还不够，任务还需要你明确控制消息体、Schema 或 CDC 包装格式时，就进入这一节。
+
+## 什么时候需要看格式文档
+
+- source 或 sink 读写的是带 Schema 的外部载荷
+- CDC 链路依赖特定的 envelope 格式
+- 需要让外部序列化格式与下游消费方保持一致
+
+## 常用下一步
+
+- [数据格式处理](../../architecture/data-format-handling.md)
+- [连接器常见问题](../connector-faq.md)
diff --git a/docs/zh/connectors/overview.md b/docs/zh/connectors/overview.md
new file mode 100644
index 0000000000..956e6968cf
--- /dev/null
+++ b/docs/zh/connectors/overview.md
@@ -0,0 +1,39 @@
+---
+slug: /connectors
+---
+
+# 数据连接器总览
+
+这一页不是参数大全，而是帮助第一次选择 SeaTunnel 连接器的用户先找到正确入口。建议先确认“从哪里读”“写到哪里”“是否需要 CDC
或特殊格式”，再进入具体连接器参数页。
+
+## 先按任务目标选入口
+
+| 你现在要做什么 | 先看这里 |
+| --- | --- |
+| 从外部系统读取数据 | [数据来源连接器](./source-overview.md) |
+| 把数据写入目标系统 | [数据写入连接器](./sink-overview.md) |
+| 先找一条接近真实业务的链路示例 | [场景示例](../getting-started/recipes/overview.md) |
+| 先理解连接器共有参数 | [来源端通用参数](./common-options/source-common-options.md) 和
[写入端通用参数](./common-options/sink-common-options.md) |
+| 构建 CDC 链路 | [CDC 生产实战手册](./cdc-production-cookbook.md) |
+| 排查插件安装或依赖冲突 | [连接器常见问题](./connector-faq.md) 和
[连接器依赖隔离加载机制](./connector-isolated-dependency.md) |
+
+## 新用户推荐顺序
+
+1. 先跑通一个本地任务，再回来选择真实连接器。
+2. 先确定来源端和写入端，再判断是否需要额外的数据转换或格式处理。
+3. 在复制示例参数前，先确认插件安装和第三方驱动是否齐全。
+4. 只有在任务真的涉及多表、增量或恢复语义时，再深入 CDC 和容错细节。
+
+## 选择连接器时重点关注什么
+
+- 是否支持你正在使用的执行引擎
+- 是否需要额外驱动或插件安装
+- 是否支持批处理、流处理、CDC、精确一次等能力
+- 参数名、默认值和示例是否与你的 SeaTunnel 版本一致
+
+## 常用下一步
+
+- [作业配置指南](../getting-started/job-configuration-guide.md)
+- [场景示例](../getting-started/recipes/overview.md)
+- [数据转换总览](../transforms)
+- [SeaTunnel
引擎快速开始](../getting-started/locally/quick-start-seatunnel-engine.md)
diff --git a/docs/zh/connectors/sink-overview.md
b/docs/zh/connectors/sink-overview.md
new file mode 100644
index 0000000000..c7dc48c2e1
--- /dev/null
+++ b/docs/zh/connectors/sink-overview.md
@@ -0,0 +1,21 @@
+---
+slug: /connectors/sink
+sidebar_position: 1
+---
+
+# 数据写入连接器
+
+当你的第一个问题是“SeaTunnel
最终要把数据写到哪里”时，就先看这一页。更稳妥的顺序是先匹配目标系统，再确认写入保证、表结构行为、驱动依赖，以及连接器本身的投递约束。
+
+## 选择 Sink 前先确认什么
+
+- 最终目标系统以及表、对象或主题的落点形态
+- 任务需要至少一次、精确一次还是幂等写入
+- 是否依赖额外驱动、SDK 或云鉴权配置
+- 该连接器是否支持你要使用的写入模式
+
+## 常用下一步
+
+- [Sink 常用选项](../common-options/sink-common-options.md)
+- [连接器常见问题](../connector-faq.md)
+- [连接器依赖隔离加载机制](../connector-isolated-dependency.md)
diff --git a/docs/zh/connectors/source-overview.md
b/docs/zh/connectors/source-overview.md
new file mode 100644
index 0000000000..fdfa8df16c
--- /dev/null
+++ b/docs/zh/connectors/source-overview.md
@@ -0,0 +1,21 @@
+---
+slug: /connectors/source
+sidebar_position: 1
+---
+
+# 数据来源连接器
+
+当你的第一个问题是“SeaTunnel 要从哪里读取数据”时，就先看这一页。更好的顺序是先按外部系统找到合适的
Source，再确认插件安装、驱动依赖，以及当前任务是否需要批处理、流处理或 CDC 语义。
+
+## 选择 Source 前先确认什么
+
+- 你实际要读取的是哪一种外部系统
+- 任务需要快照、增量还是 CDC 语义
+- 是否依赖额外驱动、SDK 或鉴权配置
+- 示例参数是否与你当前使用的 SeaTunnel 版本一致
+
+## 常用下一步
+
+- [Source 常用选项](../common-options/source-common-options.md)
+- [CDC 生产实战手册](../cdc-production-cookbook.md)
+- [连接器常见问题](../connector-faq.md)
diff --git a/docs/zh/getting-started/job-configuration-guide.md
b/docs/zh/getting-started/job-configuration-guide.md
index a749979e8f..b5cdf3793b 100644
--- a/docs/zh/getting-started/job-configuration-guide.md
+++ b/docs/zh/getting-started/job-configuration-guide.md
@@ -172,6 +172,7 @@ SeaTunnel 支持多种配置方式：
## 下一步
- 需要先跑通一个可执行示例：查看 [SeaTunnel 引擎快速开始](./locally/quick-start-seatunnel-engine.md)
-- 需要具体参数说明：查看 [Source 连接器](../connectors/source) 和 [Sink
连接器](../connectors/sink)
-- 需要了解转换能力：查看 [Transforms](../transforms)
+- 需要看一条更接近真实业务的完整链路：查看 [场景示例](./recipes/overview.md)
+- 需要具体参数说明：查看 [数据来源连接器总览](../connectors/source-overview.md) 和
[数据写入连接器总览](../connectors/sink-overview.md)
+- 需要了解转换能力：查看 [数据转换总览](../transforms)
- 需要理解引擎差异：查看 [执行引擎概览](../engines/overview.md)
diff --git a/docs/zh/getting-started/locally/deployment.md
b/docs/zh/getting-started/locally/deployment.md
index 0c5510b782..1ecad85398 100644
--- a/docs/zh/getting-started/locally/deployment.md
+++ b/docs/zh/getting-started/locally/deployment.md
@@ -83,6 +83,13 @@ tar -xzvf "apache-seatunnel-${version}-bin.tar.gz"
现在您已经下载了SeaTunnel二进制包和连接器插件。接下来，您可以选择不同的引擎选项来运行同步任务。
+:::tip 提示
+
+如果您是第一次使用 SeaTunnel，建议优先从 [SeaTunnel 引擎快速开始](quick-start-seatunnel-engine.md)
入手。
+这是默认引擎，通常也是第一次跑通任务的最短路径。
+
+:::
+
如果您使用Flink来运行同步任务，则无需部署SeaTunnel引擎服务集群。您可以参考[Flink
引擎快速开始](quick-start-flink.md)来运行您的同步任务。
如果您使用Spark来运行同步任务，则无需部署SeaTunnel引擎服务集群。您可以参考[Spark
引擎快速开始](quick-start-spark.md)来运行您的同步任务。
diff --git a/docs/zh/getting-started/locally/overview.md
b/docs/zh/getting-started/locally/overview.md
new file mode 100644
index 0000000000..0d108397c2
--- /dev/null
+++ b/docs/zh/getting-started/locally/overview.md
@@ -0,0 +1,29 @@
+---
+slug: /getting-started/locally
+---
+
+# 本地快速开始
+
+如果你的目标是用最短路径把 SeaTunnel 在本机跑起来，就先看这一页。对大多数第一次接触 SeaTunnel 的用户来说，默认最推荐的仍然是
**SeaTunnel 引擎（Zeta）**，因为它部署最短、反馈最快、最适合作为首跑路径。
+
+## 先选一条本地起步路径
+
+| 你的情况 | 推荐入口 |
+| --- | --- |
+| 我想走默认的首跑路径 | [SeaTunnel 引擎快速开始](./quick-start-seatunnel-engine.md) |
+| 我需要先完成安装和插件准备 | [部署](./deployment.md) |
+| 团队已经有 Flink 环境 | [Flink 引擎快速开始](./quick-start-flink.md) |
+| 团队已经有 Spark 环境 | [Spark 引擎快速开始](./quick-start-spark.md) |
+
+## 推荐首跑顺序
+
+1. 先看 [部署](./deployment.md)。
+2. 安装示例任务所需插件。
+3. 通过 [跑第一个任务](./run-your-first-job.md) 或 [SeaTunnel
引擎快速开始](./quick-start-seatunnel-engine.md) 跑通首个本地作业。
+4. 示例成功后，再进入 [作业配置指南](../job-configuration-guide.md) 编写真实作业。
+
+## 什么时候再看其他路径
+
+- 只有在你已经维护 Flink 集群时，才优先走 Flink 路径。
+- 只有在你的现有作业体系本来就围绕 Spark 时，才优先走 Spark 路径。
+- 更稳妥的顺序仍然是先把本地链路跑通，再进入集群部署或远程提交。
diff --git a/docs/zh/getting-started/overview.md
b/docs/zh/getting-started/overview.md
index bcb6d4ebfd..c78bd054f9 100644
--- a/docs/zh/getting-started/overview.md
+++ b/docs/zh/getting-started/overview.md
@@ -8,22 +8,22 @@ sidebar_position: 1
## SeaTunnel 能帮你做什么
-SeaTunnel 是一个分布式数据集成平台，用统一的 Connector 模型处理异构系统之间的数据流转。常见场景包括：
+SeaTunnel 是一个分布式数据集成平台，用统一的连接器模型处理异构系统之间的数据流转。常见场景包括：
- 数据库、文件、数据仓库之间的批量同步
- CDC 与实时同步
- 多表同步或全库迁移
- 结构化、非结构化和二进制数据的多模态集成
-如果你是第一次评估 SeaTunnel，建议优先从内置的 **SeaTunnel Engine (Zeta)**
开始。它的部署路径最短，也是新项目的默认推荐执行引擎。
+如果你是第一次评估 SeaTunnel，建议优先从内置的 **SeaTunnel 引擎（Zeta）** 开始。它的部署路径最短，也是新项目的默认推荐执行引擎。
## 如何选择执行引擎
| 引擎 | 适用场景 | 推荐入口 |
| --- | --- | --- |
-| SeaTunnel Engine (Zeta) | 新项目、CDC、低资源环境、本地快速验证 | [SeaTunnel
引擎快速开始](./locally/quick-start-seatunnel-engine.md) |
-| Flink | 已有 Flink 集群和运维体系 | [Flink 快速开始](./locally/quick-start-flink.md) |
-| Spark | 已有 Spark 集群和运维体系 | [Spark 快速开始](./locally/quick-start-spark.md) |
+| SeaTunnel 引擎（Zeta） | 新项目、CDC、低资源环境、本地快速验证 | [SeaTunnel
引擎快速开始](./locally/quick-start-seatunnel-engine.md) |
+| Flink 引擎 | 已有 Flink 集群和运维体系 | [Flink 快速开始](./locally/quick-start-flink.md) |
+| Spark 引擎 | 已有 Spark 集群和运维体系 | [Spark 快速开始](./locally/quick-start-spark.md) |
如需更完整的引擎比较，请查看 [执行引擎概览](../engines/overview.md)。
@@ -34,7 +34,7 @@ SeaTunnel 是一个分布式数据集成平台，用统一的 Connector 模型
1. 阅读 [安装部署](./locally/deployment.md)，完成二进制包安装。
2. 安装示例任务所需的插件。
3. 使用 `FakeSource -> FieldMapper -> Console` 跑通本地 SeaTunnel Engine 快速开始。
-4. 示例成功后，再替换成真实的 Source 和 Sink。
+4. 示例成功后，再替换成真实连接器，开始编写真正的同步链路。
## 推荐阅读路径
@@ -47,9 +47,10 @@ SeaTunnel 是一个分布式数据集成平台，用统一的 Connector 模型
### 路径 B：我已经知道要接什么数据源
- [作业配置指南](./job-configuration-guide.md)
-- [Source 连接器列表](../connectors/source)
-- [Sink 连接器列表](../connectors/sink)
-- [Transform 列表](../transforms)
+- [数据来源连接器总览](../connectors/source-overview.md)
+- [数据写入连接器总览](../connectors/sink-overview.md)
+- [数据转换总览](../transforms)
+- [场景示例](./recipes/overview.md)
### 路径 C：我想先理解整体架构
@@ -77,5 +78,7 @@ SeaTunnel 是一个分布式数据集成平台，用统一的 Connector 模型
推荐继续阅读：
- [作业配置指南](./job-configuration-guide.md)
-- [SeaTunnel Engine(Zeta) 安装部署](../engines/zeta/deployment.md)
+- [场景示例](./recipes/overview.md)
+- [SeaTunnel 引擎（Zeta）安装部署](../engines/zeta/deployment.md)
- [REST API 与 Web UI](../engines/zeta/rest-api-and-web-ui.md)
+- [向远程 Zeta 集群提交作业](./submit-job-to-remote-zeta-cluster.md)
diff --git a/docs/zh/getting-started/recipes/file-to-starrocks.md
b/docs/zh/getting-started/recipes/file-to-starrocks.md
index 167356cf99..9662c95308 100644
--- a/docs/zh/getting-started/recipes/file-to-starrocks.md
+++ b/docs/zh/getting-started/recipes/file-to-starrocks.md
@@ -3,7 +3,7 @@ sidebar_position: 5
title: File 到 StarRocks
---
-# File 到 StarRocks
+# 文件到 StarRocks
当你想把本地 CSV 或文本文件导入 StarRocks，供后续高性能分析查询使用时，可以使用这条链路。
diff --git a/docs/zh/getting-started/recipes/http-to-jdbc.md
b/docs/zh/getting-started/recipes/http-to-jdbc.md
index 420d02ee18..5aa6873ae8 100644
--- a/docs/zh/getting-started/recipes/http-to-jdbc.md
+++ b/docs/zh/getting-started/recipes/http-to-jdbc.md
@@ -1,9 +1,9 @@
---
sidebar_position: 4
-title: Http 到 JDBC
+title: HTTP 到 JDBC
---
-# Http 到 JDBC
+# HTTP 到 JDBC
当你想从 HTTP API 拉取结构化数据，并把结果落到关系型数据库中时，可以使用这条链路。
diff --git a/docs/zh/getting-started/recipes/overview.md
b/docs/zh/getting-started/recipes/overview.md
new file mode 100644
index 0000000000..f4fa7c3dfd
--- /dev/null
+++ b/docs/zh/getting-started/recipes/overview.md
@@ -0,0 +1,25 @@
+---
+slug: /getting-started/recipes
+---
+
+# 场景示例
+
+这些示例更适合在你已经跑通第一个本地任务之后再阅读。不要按顺序把所有示例都看一遍，而是优先找到最接近你真实 source 和 sink 组合的那条链路。
+
+## 按业务目标选择示例
+
+| 目标 | 推荐入口 |
+| --- | --- |
+| 从 MySQL CDC 同步到分析型数据库 | [MySQL CDC 到 Doris](./mysql-cdc-to-doris.md) |
+| 把 JDBC 数据抽取到对象存储 | [JDBC 到 S3](./jdbc-to-s3.md) |
+| 从 Kafka 流式写入表格式存储 | [Kafka 到 Iceberg](./kafka-to-iceberg.md) |
+| 把 HTTP 数据写入关系型数据库 | [HTTP 到 JDBC](./http-to-jdbc.md) |
+| 把文件数据加载到分析型系统 | [文件到 StarRocks](./file-to-starrocks.md) |
+| 多表 CDC 编排 | [多表 CDC](./multi-table-cdc.md) |
+
+## 阅读示例时建议这样看
+
+1. 先确认 source 和 sink 组合与你的目标链路是否一致。
+2. 再对照 `env`、`source`、`transform`、`sink` 四段结构理解参数。
+3. 改造示例时，一次只替换一个系统，避免同时改太多变量。
+4. 如果示例依赖 CDC、额外驱动或插件安装，先确认前置条件再运行。
diff --git a/docs/zh/introduction/about.md b/docs/zh/introduction/about.md
index 89c2d6073c..1e8cd4b2fd 100644
--- a/docs/zh/introduction/about.md
+++ b/docs/zh/introduction/about.md
@@ -5,11 +5,12 @@
[](https://s.apache.org/seatunnel-slack)
[](https://x.com/ASFSeaTunnel)
-SeaTunnel是一个多模态、超高性能、分布式的海量数据集成工具，每天可稳定高效同步数百亿数据，已被数千家企业应用于生产，以其高效和稳定性深受众多企业信赖。
+SeaTunnel 是一个多模态、高性能、分布式的数据集成平台。
+它用统一的作业模型帮助团队在数据库、文件系统、数据湖、消息系统之间完成数据读取、转换与同步。
## 从这里开始
-如果你是第一次接触 SeaTunnel，建议按下面路径进入文档：
+如果您是第一次接触 SeaTunnel，建议按下面的顺序阅读：
<div
style={{
@@ -35,80 +36,76 @@ SeaTunnel是一个多模态、超高性能、分布式的海量数据集成工
</a>
</div>
-- [快速入门总览](../getting-started/overview.md)，先建立整体路径
-- [SeaTunnel
引擎快速开始](../getting-started/locally/quick-start-seatunnel-engine.md)，先跑通第一个本地任务
-- [作业配置指南](../getting-started/job-configuration-guide.md)，开始编写真实作业
-- [架构概览](../architecture/overview.md)，从系统层面理解 SeaTunnel
+- [快速入门总览](../getting-started/overview.md)：先建立整体路径
+- [SeaTunnel
引擎快速开始](../getting-started/locally/quick-start-seatunnel-engine.md)：先跑通第一个任务
+- [作业配置指南](../getting-started/job-configuration-guide.md)：开始编写真实作业
+- [工作原理](how-it-works.md)：先理解运行模型，再进入更深层架构
-## 获取帮助与加入社区
-
-如果你正在评估 SeaTunnel，或者在使用过程中遇到问题，建议优先从这些入口进入：
-
-- [常见问题解答](../faq.md)，快速解决常见使用、CDC 与配置问题
-- [开发环境搭建](../developer/setup.md)，如果你要本地构建或调试 SeaTunnel
-- [贡献路径](../developer/contribution-path.md)，如果你想从最小、最稳妥的范围开始参与贡献
-- [贡献插件](../developer/contribute-plugin.md)，如果你准备贡献 connector 或 transform
-- [GitHub Issues](https://github.com/apache/seatunnel/issues) 和 [dev
邮件列表](https://lists.apache.org/[email protected])，如果你需要社区帮助
+如果您已经有 Flink 或 Spark 运行环境，也可以直接跳到
+[Flink 引擎快速开始](../getting-started/locally/quick-start-flink.md) 或
+[Spark 引擎快速开始](../getting-started/locally/quick-start-spark.md)。
-## 为什么需要 SeaTunnel
+## SeaTunnel 能帮您做什么
-SeaTunnel专注于数据集成和数据同步，主要旨在解决数据集成领域的常见问题：
+SeaTunnel 面向的是数据团队最常见、也最先要交付的几类任务：
-* **数据源多样**：常用数据源有数百种，版本不兼容。 随着新技术的出现，更多的数据源不断出现。 用户很难找到一个能够全面、快速支持这些数据源的工具。
-* **多模态数据集成**：除了结构化数据外，用户还需要集成视频、图像、二进制文件、结构化和非结构化文本数据。
但是，现有的数据集成工具主要集中在结构化数据上。
-* **同步场景复杂**：数据同步需要支持离线全量同步、离线增量同步、CDC、实时同步、全库同步等多种同步场景。
-* **资源需求高**：现有的数据集成和数据同步工具往往需要大量的计算资源或JDBC连接资源来完成海量小表的实时同步。 这增加了企业的负担。
-* **缺乏质量和监控**：数据集成和同步过程经常会出现数据丢失或重复的情况。 同步过程缺乏监控，无法直观了解任务过程中数据的真实情况。
-* **技术栈复杂**：企业使用的技术组件不同，用户需要针对不同组件开发相应的同步程序来完成数据集成。
-* **管理和维护困难**：受限于底层技术组件（Flink/Spark）不同，离线同步和实时同步往往需要分开开发和管理，增加了管理和维护的难度。
+- **在多种系统之间搬运数据**：包括数据库、消息队列、文件系统、对象存储、数据湖和 SaaS 系统
+- **同时支持批处理和流处理**：同一套连接器模型可以覆盖全量、增量、CDC 和实时同步
+- **让作业定义保持清晰**：一个 SeaTunnel 作业仍然主要由 `env`、`source`、`transform`、`sink` 四部分组成
+- **降低运行复杂度**：SeaTunnel 关注高吞吐、较低依赖成本和实用的运行可观测性
-## SeaTunnel 相关特性
+## 团队为什么会选择 SeaTunnel
-* **丰富且可扩展的Connector**：SeaTunnel提供了不依赖于特定执行引擎的Connector API。
基于该API开发的Connector（Source、Transform、Sink）可以运行在很多不同的引擎上，例如目前支持的SeaTunnel引擎（Zeta）、Flink、Spark等。
-* **Connector插件**：插件式设计让用户可以轻松开发自己的Connector并将其集成到SeaTunnel项目中。 目前，SeaTunnel
已支持超过 160 个连接器，并且生态仍在持续扩展。
-* **批流集成**：基于SeaTunnel Connector API开发的Connector完美兼容离线同步、实时同步、全量同步、增量同步等场景。
它们大大降低了管理数据集成任务的难度。
-* **分布式快照**：支持分布式快照算法，保证数据一致性。
-* **多引擎支持**：SeaTunnel默认使用SeaTunnel引擎（Zeta）进行数据同步。
SeaTunnel还支持使用Flink或Spark作为Connector的执行引擎，以适应企业现有的技术组件。 SeaTunnel 支持 Spark 和
Flink 的多个版本。
-* **JDBC复用、数据库日志多表解析**：SeaTunnel支持多表或全库同步，解决了过度JDBC连接的问题；
支持多表或全库日志读取解析，解决了CDC多表同步场景下需要处理日志重复读取解析的问题。
-* **高吞吐量、低延迟**：SeaTunnel支持并行读写，提供稳定可靠、高吞吐量、低延迟的数据同步能力。
-* **完善的实时监控**：SeaTunnel支持数据同步过程中每一步的详细监控信息，让用户轻松了解同步任务读写的数据数量、数据大小、QPS等信息。
-* **支持两种作业开发方法**：编码和画布设计。 SeaTunnel Web 项目
https://github.com/apache/seatunnel-web 提供作业、调度、运行和监控功能的可视化管理。
+- **连接器优先的设计**：SeaTunnel 提供统一的连接器接口（Connector API），Source、Transform、Sink
可以跨引擎复用
+- **引擎选择灵活**：可以直接从 SeaTunnel 引擎（Zeta）起步，也可以运行在 Flink 或 Spark 上
+- **面向真实同步场景**：多表同步、CDC、大规模作业执行都是第一类使用场景
+- **运行态可观察**：作业能够暴露运行指标和任务信息，方便理解吞吐、延迟和稳定性
+- **适合从小到大演进**：既可以本地先跑一个简单任务，也可以逐步扩展到更复杂的集群部署
-## SeaTunnel 工作流图
+## 用一张图理解 SeaTunnel
-
+
-SeaTunnel的运行流程如上图所示。
+您可以先抓住三个最重要的理解点：
-用户配置作业信息并选择提交作业的执行引擎。
+### 1. SeaTunnel 作业本质上是一条数据管道
-Source Connector负责并行读取数据并将数据发送到下游Transform或直接发送到Sink，Sink将数据写入目的地。
值得注意的是，Source、Transform 和 Sink 可以很容易地自行开发和扩展。
+您用配置文件描述作业，SeaTunnel 再把它执行成一条从 **Source（读取）** 到 **Transform（转换）** 再到
**Sink（写入）** 的数据处理链路。
-SeaTunnel 是一个 EtL(T) 数据集成工具。
因此，在SeaTunnel中，transform(t)只能用于对数据进行一些简单的转换，例如将一列的数据转换为大写或小写，更改列名，或者将一列拆分为多列。
+### 2. 连接器决定读什么、写到哪里
-SeaTunnel 使用的默认引擎是 [SeaTunnel Zeta Engine](../engines/zeta/about.md)。
如果您选择使用Flink或Spark引擎，SeaTunnel会将Connector打包成Flink或Spark程序并提交给Flink或Spark运行。
+SeaTunnel 提供了丰富的 [源连接器](../connectors/source-overview.md)、
+[目标连接器](../connectors/sink-overview.md) 和 [数据转换](../transforms)。
+如果有特殊需求，您也可以自行扩展这些插件类型。
-## 连接器
+### 3. 引擎决定这条作业跑在哪儿
-- **源连接器** SeaTunnel 支持从各种关系、图形、NoSQL、文档和内存数据库读取数据； 分布式文件系统，例如HDFS；
以及各种云存储解决方案，例如S3和OSS。 我们还支持很多常见SaaS服务的数据读取。 您可以在[此处](../connectors/source)
访问详细列表。 如果您愿意，您可以开发自己的源连接器并将其轻松集成到 SeaTunnel 中。
+[SeaTunnel 引擎（Zeta）](../engines/zeta/about.md) 是默认选择，也是大多数新用户最推荐的起点。
+如果您已经在使用 Flink 或 Spark，SeaTunnel 也可以把同一套连接器作业模型运行在这些平台上。
-- **转换连接器** 如果源和接收器之间的架构不同，您可以使用转换连接器更改从源读取的架构，使其与接收器架构相同。
+## 如何选择运行引擎
-- **Sink Connector** SeaTunnel 支持将数据写入各种关系型、图形、NoSQL、文档和内存数据库； 分布式文件系统，例如HDFS；
以及各种云存储解决方案，例如S3和OSS。 我们还支持将数据写入许多常见的 SaaS 服务。
您可以在[此处](../connectors/sink)访问详细列表。 如果您愿意，您可以开发自己的 Sink 连接器并轻松将其集成到 SeaTunnel 中。
+| 引擎 | 推荐起点 | 适用场景 |
+| --- | --- | --- |
+| [SeaTunnel 引擎（Zeta）](../engines/zeta/about.md) | 推荐大多数新用户先从这里开始 | 希望以最短路径跑通
SeaTunnel 作业 |
+| [Apache Flink](../engines/flink.md) | 适合已有 Flink 环境的团队 | 已经维护 Flink 集群，希望让
SeaTunnel 接入现有平台 |
+| [Apache Spark](../engines/spark.md) | 适合已有 Spark 环境的团队 | 主要是批处理任务，希望复用现有
Spark 技术栈 |
-## 谁在使用 SeaTunnel
+## 继续阅读
-SeaTunnel 拥有大量用户。
您可以在[用户](https://seatunnel.apache.org/zh-CN/user)中找到有关他们的更多信息.
+- [工作原理](how-it-works.md)：以新手能接受的层次理解运行模型
+- [配置文件简介](concepts/config.md)：开始写真实作业
+- [数据连接器总览](../connectors)：先确认读写方向，再进入具体连接器参数页
+- [系统架构概览](../architecture/overview.md)：当您需要深入内部设计时再继续往下读
+- [常见问题](../faq.md)：快速处理常见使用、CDC 与配置问题
-## 展望
+## 获取帮助与加入社区
-<p align="center">
-<br/><br/>
-<img src="https://landscape.cncf.io/images/left-logo.svg"; width="150"
alt=""/> <img src="https://landscape.cncf.io/images/right-logo.svg";
width="200" alt=""/>
-<br/><br/>
-SeaTunnel 丰富了<a
href="https://landscape.cncf.io/?item=app-definition-and-development--streaming-messaging--seatunnel";>CNCF
云原生景观</a >。
-</p >
+- [开发环境搭建](../developer/setup.md)：如果您要本地构建或调试 SeaTunnel
+- [贡献路径](../developer/contribution-path.md)：如果您想从最小、最稳妥的范围开始参与贡献
+- [贡献插件](../developer/contribute-plugin.md)：如果您准备贡献连接器或 transform 插件
+- [GitHub
Issues](https://github.com/apache/seatunnel/issues)、[Slack](https://s.apache.org/seatunnel-slack)
和 [dev
邮件列表](https://lists.apache.org/[email protected])：如果您需要社区帮助
-## 了解更多
+## 谁在使用 SeaTunnel
-您可以参阅[跑第一个任务](../getting-started/locally/run-your-first-job.md) 了解后续相关步骤。
+SeaTunnel 拥有大量用户。您可以在[用户](https://seatunnel.apache.org/zh-CN/user)中找到有关他们的更多信息。
diff --git a/docs/zh/introduction/concepts/config.md
b/docs/zh/introduction/concepts/config.md
index ab482f66c7..980629988b 100644
--- a/docs/zh/introduction/concepts/config.md
+++ b/docs/zh/introduction/concepts/config.md
@@ -1,15 +1,14 @@
# 配置文件简介
-在SeaTunnel中，最重要的事情就是配置文件，尽管用户可以自定义他们自己的数据同步需求以发挥SeaTunnel最大的潜力。那么接下来我将会向你介绍如何设置配置文件。
+如果您正在编写第一个真正可用的 SeaTunnel
作业，这一页最重要的目标，就是帮您先理解几乎所有配置里都会出现的四个部分：`env`、`source`、`transform`、`sink`。
-配置文件的主要格式是 `hocon`,
有关该格式类型的更多信息你可以参考[HOCON-GUIDE](https://github.com/lightbend/config/blob/main/HOCON.md),
-顺便提一下，我们也支持 `json`格式，但你应该知道配置文件的名称应该是以 `.json`结尾。
+SeaTunnel 支持 `hocon`、`json` 和 `SQL` 三种配置格式。其中 **HOCON** 是快速开始和生产示例中最常见的格式。SQL
格式请参考 [SQL 配置文件](../configuration/sql-config.md)。
-我们同时提供了以 `SQL` 格式，详细可以参考[SQL配置文件](../configuration/sql-config.md)。
+如果您还没有跑通过第一个任务，建议先阅读 [快速入门总览](../../getting-started/overview.md) 和 [SeaTunnel
引擎快速开始](../../getting-started/locally/quick-start-seatunnel-engine.md)，再回到这一页。
## 例子
-在你阅读之前，你可以在发布包中的config目录[这里](https://github.com/apache/seatunnel/tree/dev/config)找到配置文件的例子。
+继续往下看之前，您可以先在发布包的 `config` 目录，或者
[这里](https://github.com/apache/seatunnel/tree/dev/seatunnel-e2e/seatunnel-connector-v2-e2e/connector-jdbc-e2e/connector-jdbc-e2e-part-1/src/test/resources)
查看示例配置。
## 配置文件结构
@@ -21,7 +20,7 @@
:::
-### hocon
+### HOCON 示例
```hocon
env {
@@ -63,28 +62,25 @@ sink {
}
```
-正如你看到的，配置文件包括几个部分：env, source, transform, sink。不同的模块具有不同的功能。
-当你了解了这些模块后，你就会懂得SeaTunnel到底是如何工作的。
+大多数 SeaTunnel 作业都会遵循 `env`、`source`、`transform`、`sink`
这四段结构。只要先理解这四段，后面读快速开始、连接器示例和真实任务配置都会容易很多。
-### env
+### `env`：作业与引擎参数
-用于添加引擎可选的参数，不管是什么引擎（Zeta、Spark 或者 Flink），对应的可选参数应该在这里填写。
+`env` 用来放作业级和引擎级参数，比如 `job.mode`、`parallelism`、checkpoint 相关配置，以及引擎特有参数。
-注意，我们按照引擎分离了参数，对于公共参数我们可以像以前一样配置。对于Flink和Spark引擎，其参数的具体配置规则可以参考[JobEnvConfig](../configuration/JobEnvConfig.md)。
+公共参数可以直接配置；引擎专属参数则按前缀区分。Flink 和 Spark 的具体写法请参考
[JobEnvConfig](../configuration/JobEnvConfig.md)。
<!-- TODO add supported env parameters -->
-### source
+### `source`：数据读取入口
-source用于定义SeaTunnel在哪儿检索数据，并将检索的数据用于下一步。
-可以同时定义多个source。目前支持的source请看[Source of
SeaTunnel](../../connectors/source)。每种source都有自己特定的参数用来
-定义如何检索数据，SeaTunnel也抽象了每种source所使用的参数，例如 `plugin_output`
参数，用于指定当前source生成的数据的名称，
-方便后续其他模块使用。
+`source` 用来定义 SeaTunnel 从哪里读取数据。一个作业中可以同时声明多个
source。每个连接器都有自己的参数，同时也有一些通用的链路字段，例如 `plugin_output`，它用于给当前 source
产出的数据集命名，方便后续模块引用。
-### transform
+完整列表请查看 [数据来源连接器](../../connectors/source-overview.md)。
-当我们有了数据源之后，我们可能需要对数据进行进一步的处理，所以我们就有了transform模块。当然，这里使用了“可能”这个词，
-这意味着我们也可以直接将transform视为不存在，直接从source到sink，像下面这样：
+### `transform`：中间处理步骤
+
+`transform` 是可选的。当您需要做字段映射、过滤、类型转换、SQL 处理，或者其它中间加工时，就使用这一层；如果不需要，也可以直接从 source
到 sink，例如下面这样：
```hocon
env {
@@ -118,22 +114,22 @@ sink {
}
```
-与source类似, transform也有属于每个模块的特定参数。目前支持的source请看。目前支持的transform请看 [Transform V2
of SeaTunnel](../../transforms)
+和 source 一样，每个 transform 也有自己的专属参数。完整列表请查看 [数据转换目录](../../transforms)。
+
+### `sink`：数据写入目标
+
+`sink` 用来定义处理后的数据写到哪里去。它和 source 很相似，但更关注写入行为、目标表结构、提交方式以及投递保证。
-<!-- TODO missing source links --->
+完整列表请查看 [数据写入连接器](../../connectors/sink-overview.md)。
-### sink
+### `plugin_output` 和 `plugin_input` 是怎么工作的
-我们使用SeaTunnel的作用是将数据从一个地方同步到其它地方，所以定义数据如何写入，写入到哪里是至关重要的。通过SeaTunnel提供的
-sink模块，你可以快速高效地完成这个操作。Sink和source非常相似，区别在于读取和写入。所以去看看我们[Sink of
SeaTunnel](../../connectors/sink)吧。
+当一个作业里同时存在多个 source、transform 或 sink 时，SeaTunnel 需要知道“哪一份数据流向下一步的哪个模块”。这就是
`plugin_output` 和 `plugin_input` 的作用。
-### 其它
+- `plugin_output` 给当前 source 或 transform 产出的数据集命名
+- `plugin_input` 告诉下游 transform 或 sink 应该消费哪一个上游数据集
-你会疑惑当定义了多个source和多个sink时，每个sink读取哪些数据，每个transform读取哪些数据？我们使用`plugin_output` 和
-`plugin_input`
两个配置。每个source模块都会配置一个`plugin_output`来指示数据源生成的数据源名称，其它transform和sink
-模块可以使用`plugin_input` 引用相应的数据源名称，表示要读取数据进行处理。然后transform，作为一个中间的处理模块，可以同时使用
-`plugin_output` 和 `plugin_input`
配置。但你会发现在上面的配置例子中，不是每个模块都配置了这些参数，因为在SeaTunnel中，
-有一个默认的约定，如果这两个参数没有配置，则使用上一个节点的最后一个模块生成的数据。当只有一个source时这是非常方便的。
+如果只是单一 source 的简单链路，很多时候可以省略它们，因为 SeaTunnel 会按默认约定自动把上一个模块的输出继续往下传递。
## 多行文本支持
@@ -148,7 +144,7 @@ distributed, massive data integration tool.
sql = """ select * from "table" """
```
-## Json格式支持
+## JSON 格式支持
在编写配置文件之前，请确保配置文件的名称应以 `.json` 结尾。
@@ -198,7 +194,7 @@ sql = """ select * from "table" """
## 配置变量替换
-在配置文件中,我们可以定义一些变量并在运行时替换它们。但是注意仅支持 hocon 格式的文件。
+在配置文件中，我们可以定义一些变量并在运行时替换它们。但请注意，目前仅支持 HOCON 格式的文件。
变量使用方法：
- `${varName}`，如果变量未传值，则抛出异常。
@@ -324,4 +320,6 @@ sink {
-
不能使用指定系统保留字符，它将不会被`-i`替换，如:`${database_name}`、`${schema_name}`、`${table_name}`、`${schema_full_name}`、`${table_full_name}`、`${primary_key}`、`${unique_key}`、`${field_names}`、`${partition_keys}`。具体可参考[Sink参数占位符](../configuration/sink-options-placeholders.md)
## 此外
-如果你想了解更多关于格式配置的详细信息，请查看
[HOCON](https://github.com/lightbend/config/blob/main/HOCON.md)。
+- 现在就可以开始写自己的配置文件，选择要使用的 [连接器](../../connectors/source-overview.md)，再按对应文档填写参数。
+- 如果您需要按引擎配置参数，请继续阅读 [JobEnvConfig](../configuration/JobEnvConfig.md)。
+- 如果您想了解更完整的语法细节，请查看
[HOCON](https://github.com/lightbend/config/blob/main/HOCON.md)。
diff --git a/docs/zh/introduction/how-it-works.md
b/docs/zh/introduction/how-it-works.md
index 5ea92db16f..d68633cb00 100644
--- a/docs/zh/introduction/how-it-works.md
+++ b/docs/zh/introduction/how-it-works.md
@@ -4,6 +4,18 @@ sidebar_position: 2
# 工作原理
+## 新用户先抓住这几点
+
+在第一次使用 SeaTunnel 时，您不需要先理解所有内部模块。
+对大多数新用户来说，更实用的顺序是：
+
+1. 先在本地跑通一个任务
+2. 再理解配置文件结构
+3. 然后选择合适的连接器和执行引擎
+4. 当您需要理解运行模型时，再回到这一页
+
+把 SeaTunnel 先理解成“一条由配置驱动、运行在某个执行引擎上的数据管道”，通常最容易入门。
+
## 概述
SeaTunnel 是一个分布式多模态数据集成工具，采用插件化架构。连接器层与执行引擎解耦，同一套连接器可在不同引擎上运行。
@@ -35,6 +47,28 @@ flowchart TD
linkStyle default stroke:#5db8e2,stroke-width:2px;
```
+## 四个核心构件
+
+### 1. 作业配置
+
+配置文件描述了读什么、怎么转换、写到哪里，以及需要使用哪些引擎参数。
+
+### 2. SeaTunnel 核心层
+
+SeaTunnel 会解析配置、生成执行计划、加载插件，并把作业提交到选定的执行引擎。
+
+### 3. 数据链路：Source -> Transform -> Sink
+
+这是大多数新用户最应该先记住的数据路径：
+
+- **Source（读取）** 负责从外部系统读取数据
+- **Transform（转换）** 负责按需做字段映射、过滤或简单转换
+- **Sink（写入）** 负责把结果写入目标系统
+
+### 4. 执行引擎
+
+引擎决定作业最终跑在哪儿。对大多数新用户来说，建议先从 [SeaTunnel 引擎（Zeta）](../engines/zeta/about.md)
开始；只有在现有环境已经依赖 Flink 或 Spark 时，再切换到对应引擎。
+
## 推荐阅读路径
如果你希望先建立一套系统级理解，建议按下面顺序阅读：
@@ -43,26 +77,26 @@ flowchart TD
- 本页，先建立执行模型的整体图景
- [引擎概览](../engines/overview.md)，理解执行引擎如何选择
- [架构概览](../architecture/overview.md)，再进入更完整的分层视图
-- [核心 API 设计](../architecture/core-api-design.md)，理解 connector 与元数据契约
+- [核心 API 设计](../architecture/core-api-design.md)，理解连接器与元数据契约
- 如果你还需要理解数据集编排与 transform 行为，再看 [Transform
插件体系](../architecture/transform-plugin-system.md)
## 核心组件
-### 1. Connector API
+### 1. 连接器接口（Connector API）
-与引擎无关的统一 API，用于开发 Source、Transform、Sink 连接器。
+与引擎无关的统一接口，用于开发 Source、Transform、Sink 连接器。
| 组件 | 说明 |
|------|------|
-| **Source** | 从外部系统读取数据（数据库、文件、消息队列） |
-| **Transform** | 数据转换（字段映射、过滤、类型转换） |
-| **Sink** | 将数据写入目标系统 |
+| **Source（读取）** | 从外部系统读取数据（数据库、文件、消息队列） |
+| **Transform（转换）** | 数据转换（字段映射、过滤、类型转换） |
+| **Sink（写入）** | 将数据写入目标系统 |
### 2. 执行引擎
| 引擎 | 适用场景 |
|------|---------|
-| **SeaTunnel Engine (Zeta)** | 数据同步、CDC、低资源消耗 |
+| **SeaTunnel 引擎（Zeta）** | 数据同步、CDC、低资源消耗 |
| **Apache Flink** | 复杂流处理、已有 Flink 基础设施 |
| **Apache Spark** | 大规模批处理、已有 Spark 基础设施 |
@@ -99,7 +133,7 @@ flowchart LR
| `seatunnel-api` | 核心 API 定义 |
| `seatunnel-connectors-v2` | Source 和 Sink 连接器 |
| `seatunnel-transforms-v2` | Transform 插件 |
-| `seatunnel-engine` | SeaTunnel Engine (Zeta) |
+| `seatunnel-engine` | SeaTunnel 引擎（Zeta） |
| `seatunnel-translation` | Flink 和 Spark 的引擎适配器 |
| `seatunnel-core` | 作业提交与 CLI |
| `seatunnel-formats` | 数据格式处理 |
@@ -119,4 +153,4 @@ flowchart LR
- [快速入门总览](../getting-started/overview.md)
- [SeaTunnel
引擎快速开始](../getting-started/locally/quick-start-seatunnel-engine.md)
- [架构概览](../architecture/overview.md)
-- [连接器列表](../connectors)
+- [数据连接器总览](../connectors)
diff --git a/docs/zh/transforms/overview.md b/docs/zh/transforms/overview.md
new file mode 100644
index 0000000000..ae14283ba4
--- /dev/null
+++ b/docs/zh/transforms/overview.md
@@ -0,0 +1,23 @@
+---
+slug: /transforms
+---
+
+# 数据转换总览
+
+Transform 位于 source 和 sink 之间，用来做字段映射、过滤、SQL 处理、表级编排等中间加工。第一次上手时，不需要先把所有
transform 都看完；更合适的顺序是先确定数据从哪来、写到哪去，再回来选择需要的转换能力。
+
+## 先按目标找入口
+
+| 目标 | 推荐入口 |
+| --- | --- |
+| 先理解 transform 如何连接数据集 | [转换通用参数](./common-options/common-options.md) |
+| 做行过滤或字段裁剪 | [数据过滤（Filter）](./filter.md) 和 [字段映射（Field
Mapper）](./field-mapper.md) |
+| 用 SQL 表达式处理数据 | [SQL 转换](./sql.md) 和 [SQL 函数](./sql-functions.md) |
+| 重命名或重组字段 | [字段重命名（Field Rename）](./field-rename.md) 和
[字段拆分（Split）](./split.md) |
+| 处理多表链路 | [多表转换（Transform Multi Table）](./transform-multi-table.md) 和
[表合并（Table Merge）](./table-merge.md) |
+
+## 新用户推荐顺序
+
+1. 先看通用参数页，把 `plugin_input` 和 `plugin_output` 的作用理解清楚。
+2. 先选择最简单、最贴近目标的 transform，再进入 SQL 或多表编排。
+3. 每次只新增一个 transform 步骤，让整条 pipeline 在验证时保持可读、可排障。
![https://landscape.cncf.io/images/left-logo.svg"](https://landscape.cncf.io/images/left-logo.svg"){kind=link}
![https://landscape.cncf.io/images/right-logo.svg"](https://landscape.cncf.io/images/right-logo.svg"){kind=link}