add a link to the comparison table

Author: shohei1029

articles/machine-learning/how-to-deploy-with-triton.md

@@ -27,9 +27,9 @@ ms.devlang: azurecli
 
 Learn how to use [NVIDIA Triton Inference Server](https://aka.ms/nvidia-triton-docs) in Azure Machine Learning with [online endpoints](concept-endpoints.md#what-are-online-endpoints).
 
-Triton is multi-framework, open-source software that is optimized for inference. It supports popular machine learning frameworks like TensorFlow, ONNX Runtime, PyTorch, NVIDIA TensorRT, and more. It can be used for your CPU or GPU workloads.
+Triton is multi-framework, open-source software that is optimized for inference. It supports popular machine learning frameworks like TensorFlow, ONNX Runtime, PyTorch, NVIDIA TensorRT, and more. It can be used for your CPU or GPU workloads. No-code deployment for Triton models are supported in both [managed online endpoints and Kubernetes online endpoints](concept-endpoints.md#managed-online-endpoints-vs-kubernetes-online-endpoints).
 
-In this article, you will learn how to deploy Triton and a model to a **[managed online endpoint](concept-endpoints.md#managed-online-endpoints)**. Information is provided on using the CLI (command line), Python SDK v2, and Azure Machine Learning studio.
+In this article, you will learn how to deploy Triton and a model to a [managed online endpoint](concept-endpoints.md#managed-online-endpoints). Information is provided on using the CLI (command line), Python SDK v2, and Azure Machine Learning studio. 
 
 > [!NOTE]
 > * [NVIDIA Triton Inference Server](https://aka.ms/nvidia-triton-docs) is an open-source third-party software that is integrated in Azure Machine Learning.