Update getting_started.md

Author: sudivate

docs/getting_started.md

@@ -204,6 +204,7 @@ Specify task parameters as it is shown in the table below:
 **Note:** Creating of a Kubernetes cluster on AKS is out of scope of this tutorial, so you should take care of it on your own.
 
 **Deploy trained model to Azure Web App for containers**
+Note: This is optional step and can be used only if you are deploying your scoring services on web apps. 
 
 [Create Image Script](./ml_service/util/create_scoring_image.py)
 can be used to create a scoring image from the release pipeline. Image created by this script will be registered under Azure Container Registry(ACR) instance that belongs to Azure Machine Learning Service. Any dependencies that scoring file depends on can also be packaged with the container with Image config. To learn more on how to create a container with AML SDK click [here](https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.image.image.image?view=azure-ml-py#create-workspace--name--models--image-config-).