add docs

Author: sthulb

docs/index.md

@@ -210,6 +210,19 @@ You can install Powertools for AWS Lambda (Python) using your favorite dependenc
 
         You'll find the pre-signed URL under `Location` key as part of the CLI command output.
 
+=== "Lambda Layer (China)"
+
+    [Lambda Layer](https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html){target="_blank"} is a .zip file archive that can contain additional code, pre-packaged dependencies, data,  or configuration files. We compile and optimize [all dependencies](#install), and remove duplicate dependencies [already available in the Lambda runtime](https://github.com/aws-powertools/powertools-lambda-python/blob/develop/layer_v3/docker/Dockerfile#L34){target="_blank"} to achieve the most optimal size.
+
+    For the latter, make sure to replace `{python_version}` without the period (.), e.g., `python313` for `Python 3.13`.
+
+    **AWS China Beijing (cn-north-1)**
+
+    | Architecture | Layer ARN                                                                                                 |
+    | ------------ | --------------------------------------------------------------------------------------------------------- |
+    | x86_64          | __arn:aws-cn:lambda:cn-north-1:498634801083:layer:AWSLambdaPowertoolsPythonV3-{python_version}-x86_64:18__{: .copyMe}:clipboard:       |
+    | ARM          | __arn:aws-cn:lambda:cn-north-1:498634801083:layer:AWSLambdaPowertoolsPythonV3-{python_version}-arm64:18__{: .copyMe}:clipboard: |
+
 === "Lambda Layer (GovCloud)"
 
     [Lambda Layer](https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html){target="_blank"} is a .zip file archive that can contain additional code, pre-packaged dependencies, data,  or configuration files. We compile and optimize [all dependencies](#install), and remove duplicate dependencies [already available in the Lambda runtime](https://github.com/aws-powertools/powertools-lambda-python/blob/develop/layer_v3/docker/Dockerfile#L34){target="_blank"} to achieve the most optimal size.