diff --git a/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/amazon-sagemaker.rst b/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/amazon-sagemaker.rst
index 718c202814..f5721e6725 100644
--- a/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/amazon-sagemaker.rst
+++ b/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/amazon-sagemaker.rst
@@ -127,7 +127,5 @@ in :ref:`gsp-examining-output`.
 Run distributed partitioning and training on Amazon SageMaker
 -------------------------------------------------------------
 
-With the data now processed you can follow the
-`GraphStorm Amazon SageMaker guide
-<https://graphstorm.readthedocs.io/en/latest/scale/sagemaker.html#run-graphstorm-on-sagemaker>`_
+With the data now processed you can follow the :ref:`GraphStorm Amazon SageMaker guide<distributed-sagemaker>`
 to partition your data and run training on AWS.
diff --git a/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr-serverless.rst b/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr-serverless.rst
index 028c8c37d5..986ce26e6f 100644
--- a/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr-serverless.rst
+++ b/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr-serverless.rst
@@ -290,6 +290,5 @@ Run distributed partitioning and training on Amazon SageMaker
 -------------------------------------------------------------
 
 With the data now processed you can follow the
-`GraphStorm Amazon SageMaker guide
-<https://graphstorm.readthedocs.io/en/latest/scale/sagemaker.html#run-graphstorm-on-sagemaker>`_
+:ref:`GraphStorm Amazon SageMaker guide<distributed-sagemaker>`
 to partition your data and run training on AWS.
diff --git a/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr.rst b/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr.rst
index 9deb72010a..22cd1cb459 100644
--- a/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr.rst
+++ b/docs/source/cli/graph-construction/distributed/gsprocessing/aws-infra/emr.rst
@@ -201,6 +201,5 @@ Run distributed partitioning and training on Amazon SageMaker
 -------------------------------------------------------------
 
 With the data now processed you can follow the
-`GraphStorm Amazon SageMaker guide
-<https://graphstorm.readthedocs.io/en/latest/scale/sagemaker.html#run-graphstorm-on-sagemaker>`_
+:ref:`GraphStorm Amazon SageMaker guide<distributed-sagemaker>`
 to partition your data and run training on AWS.
diff --git a/docs/source/cli/graph-construction/distributed/gsprocessing/distributed-processing-setup.rst b/docs/source/cli/graph-construction/distributed/gsprocessing/distributed-processing-setup.rst
index e36efc7d12..d49cccbe6b 100644
--- a/docs/source/cli/graph-construction/distributed/gsprocessing/distributed-processing-setup.rst
+++ b/docs/source/cli/graph-construction/distributed/gsprocessing/distributed-processing-setup.rst
@@ -28,12 +28,12 @@ You can clone the GraphStorm repository using
 
     git clone https://github.com/awslabs/graphstorm.git
 
-You can then navigate to the ``graphstorm-processing/docker`` directory
+You can then navigate to the ``graphstorm-processing/`` directory
 that contains the relevant code:
 
 .. code-block:: bash
 
-    cd ./graphstorm/graphstorm-processing/docker
+    cd ./graphstorm/graphstorm-processing/
 
 Install Docker
 --------------