add more info

jiaochenlu · jiaochenlu · commit fab324f8a050 · 2023-03-30T11:25:26.000+08:00
diff --git a/articles/machine-learning/how-to-access-resources-from-endpoints-managed-identities.md b/articles/machine-learning/how-to-access-resources-from-endpoints-managed-identities.md
@@ -557,7 +557,7 @@ Then, get the Principal ID of the System-assigned managed identity:
 
 [!notebook-python[] (~/azureml-examples-main/sdk/python/endpoints/online/managed/managed-identities/online-endpoints-managed-identity-sai.ipynb?name=6-get-sai-details)]
 
-Next, give assign the `Storage Blob Data Reader` role to the endpoint. The Role Definition is retrieved by name and passed along with the Principal ID of the endpoint. The role is applied at the scope of the storage account created above and allows the endpoint to read the file. 
+Next, assign the `Storage Blob Data Reader` role to the endpoint. The Role Definition is retrieved by name and passed along with the Principal ID of the endpoint. The role is applied at the scope of the storage account created above and allows the endpoint to read the file. 
 
 [!notebook-python[] (~/azureml-examples-main/sdk/python/endpoints/online/managed/managed-identities/online-endpoints-managed-identity-sai.ipynb?name=6-give-permission-user-storage-account)]
 
diff --git a/articles/machine-learning/how-to-attach-kubernetes-to-workspace.md b/articles/machine-learning/how-to-attach-kubernetes-to-workspace.md
@@ -117,7 +117,7 @@ Attaching a Kubernetes cluster makes it available to your workspace for training
 
 ### [Azure SDK](#tab/sdk)
 
-The following python SDK v2 code show how to attach an AKS and Azure Arc-enabled Kubernetes cluster, and use it as a compute target with managed identity enabled.
+The following python SDK v2 code shows how to attach an AKS and Azure Arc-enabled Kubernetes cluster, and use it as a compute target with managed identity enabled.
 
 **AKS cluster**
 
diff --git a/articles/machine-learning/how-to-manage-quotas.md b/articles/machine-learning/how-to-manage-quotas.md
@@ -131,8 +131,8 @@ Azure Machine Learning kubernetes online endpoints have limits described in the
 
 | **Resource** | **Limit** |
 | --- | --- |
-| Endpoint name| Endpoint names must <li> Begin with a letter <li> Be 3-32 characters in length  <li> Only consist of letters and numbers <sup>1</sup> |
-| Deployment name| Deployment names must <li> Begin with a letter <li> Be 3-32 characters in length  <li>  Only consist of letters and numbers <sup>1</sup> |
+| Endpoint name| Same as [managed online endpoint](#azure-machine-learning-managed-online-endpoints) |
+| Deployment name| Same as [managed online endpoint](#azure-machine-learning-managed-online-endpoints)|
 | Number of endpoints per subscription | 50 |
 | Number of deployments per subscription | 200 |
 | Number of deployments per endpoint | 20 |
@@ -233,11 +233,11 @@ When you're requesting a quota increase, select the service that you have in min
  
 1. Scroll to **Machine Learning Service: Virtual Machine Quota**.
  
-    :::image type="content" source="./media/how-to-manage-quotas/virtual-machine-quota.png" lightbox="./media/how-to-manage-quotas/virtual-machine-quota.png" alt-text="Screenshot of the VM quota details form.":::
+    :::image type="content" source="./media/how-to-manage-quotas/virtual-machine-quota.png" lightbox="./media/how-to-manage-quotas/virtual-machine-quota.png" alt-text="Screenshot of the VM quota details.":::
 
-2. Under **Additonal Details** specify the request details with the number of additional vCPUs required to run your Machine Learning Endpoint.
+2. Under **Additional Details** specify the request details with the number of additional vCPUs required to run your Machine Learning Endpoint.
  
-    :::image type="content" source="./media/how-to-manage-quotas/vm-quota-request-additional-info.png" lightbox="./media/how-to-manage-quotas/vm-quota-request-additional-info.png" alt-text="Screenshot of the VM quota additional details form.":::
+    :::image type="content" source="./media/how-to-manage-quotas/vm-quota-request-additional-info.png" lightbox="./media/how-to-manage-quotas/vm-quota-request-additional-info.png" alt-text="Screenshot of the VM quota additional details.":::
 
 > [!NOTE]
 > [Free trial subscriptions](https://azure.microsoft.com/offers/ms-azr-0044p) are not eligible for limit or quota increases. If you have a free trial subscription, you can upgrade to a [pay-as-you-go](https://azure.microsoft.com/offers/ms-azr-0003p/) subscription. For more information, see [Upgrade Azure free trial to pay-as-you-go](../cost-management-billing/manage/upgrade-azure-subscription.md) and [Azure free account FAQ](https://azure.microsoft.com/free/free-account-faq).
diff --git a/articles/machine-learning/v1/how-to-enable-data-collection.md b/articles/machine-learning/v1/how-to-enable-data-collection.md
@@ -32,7 +32,18 @@ Once collection is enabled, the data you collect helps you:
 
 * The model data collection feature can only work with Ubuntu 18.04 image.
 
+>[!IMPORTANT]
+>
+> As of 03/10/2023, the Ubuntu 18.04 image is now deprecated. **Support for Ubuntu 18.04 images will be dropped starting January 2023 when it reaches EOL on April 30, 2023.** 
+>
+> The MDC feature is incompatible with any other image than Ubuntu 18.04, which is no available after the Ubuntu 18.04 image is deprecated.
+>
+> mMore information you can refer to:
+> * [openmpi3.1.2-ubuntu18.04 release-notes](https://github.com/Azure/AzureML-Containers/blob/master/base/cpu/openmpi3.1.2-ubuntu18.04/release-notes.md)
+> * [data science virtual machine release notes](../data-science-virtual-machine/release-notes.md#september-20-2022)
+
 >[!NOTE]
+>
 > The data collection feature is currently in preview, any preview features are not recommended for production workloads.
 
 ## What is collected and where it goes
