diff --git a/doc/source/autoscaling.rst b/doc/source/autoscaling.rst
index 96b3b60b6..c2f4a2826 100644
--- a/doc/source/autoscaling.rst
+++ b/doc/source/autoscaling.rst
@@ -38,8 +38,6 @@ Test that it works by running the following commands from your local machine:
 
 .. tip:: For the AWS node configuration, you can set ``"ImageId: latest_dlami"`` to automatically use the newest `Deep Learning AMI <https://aws.amazon.com/machine-learning/amis/>`_ for your region. For example, ``head_node: {InstanceType: c5.xlarge, ImageId: latest_dlami}``.
 
-.. note:: You may see a message like: ``bash: cannot set terminal process group (-1):`` ``Inappropriate ioctl for device bash: no job control in this shell`` This is a harmless error. If the cluster launcher fails, it is most likely due to some other factor.
-
 Azure
 ~~~~~
 
diff --git a/doc/source/tune/_tutorials/tune-distributed.rst b/doc/source/tune/_tutorials/tune-distributed.rst
index a89b65388..41b562ae5 100644
--- a/doc/source/tune/_tutorials/tune-distributed.rst
+++ b/doc/source/tune/_tutorials/tune-distributed.rst
@@ -129,8 +129,6 @@ Ray currently supports AWS and GCP. Follow the instructions below to launch node
 
 ``ray submit --start`` starts a cluster as specified by the given cluster configuration YAML file, uploads ``tune_script.py`` to the cluster, and runs ``python tune_script.py [args]``.
 
-.. note:: You may see a message like: ``bash: cannot set terminal process group (-1): Inappropriate ioctl for device bash: no job control in this shell`` This is a harmless error. If the cluster launcher fails, it is most likely due to some other factor.
-
 .. code-block:: bash
 
     ray submit tune-default.yaml tune_script.py --start -- --ray-address=localhost:6379