Merge pull request #180115 from Blackmist/1879094-diagnostic-api

documenting workspace diagnostis

Author: johne2021

articles/machine-learning/how-to-create-workspace-template.md

@@ -653,4 +653,5 @@ To avoid this problem, we recommend one of the following approaches:
 
 * [Deploy resources with Resource Manager templates and Resource Manager REST API](../azure-resource-manager/templates/deploy-rest.md).
 * [Creating and deploying Azure resource groups through Visual Studio](../azure-resource-manager/templates/create-visual-studio-deployment-project.md).
-* [For other templates related to Azure Machine Learning, see the Azure Quickstart Templates repository](https://github.com/Azure/azure-quickstart-templates)
+* [For other templates related to Azure Machine Learning, see the Azure Quickstart Templates repository](https://github.com/Azure/azure-quickstart-templates).
+* To check for problems with your workspace, see [How to use workspace diagnostics](how-to-workspace-diagnostic-api.md).

articles/machine-learning/how-to-manage-workspace-cli.md

@@ -392,4 +392,6 @@ The Azure Machine Learning workspace uses Azure Container Registry (ACR) for som
 
 ## Next steps
 
-For more information on the Azure CLI extension for machine learning, see the [az ml](/cli/azure/ml) documentation.
+For more information on the Azure CLI extension for machine learning, see the [az ml](/cli/azure/ml) documentation.
+
+To check for problems with your workspace, see [How to use workspace diagnostics](how-to-workspace-diagnostic-api.md).

articles/machine-learning/how-to-manage-workspace.md

@@ -399,4 +399,6 @@ Examples of creating a workspace:
 
 Once you have a workspace, learn how to [Train and deploy a model](tutorial-train-models-with-aml.md).
 
-To learn more about planning a workspace for your organization's requirements, see [Organize and set up Azure Machine Learning](/azure/cloud-adoption-framework/ready/azure-best-practices/ai-machine-learning-resource-organization).
+To learn more about planning a workspace for your organization's requirements, see [Organize and set up Azure Machine Learning](/azure/cloud-adoption-framework/ready/azure-best-practices/ai-machine-learning-resource-organization).
+
+To check for problems with your workspace, see [How to use workspace diagnostics](how-to-workspace-diagnostic-api.md).

articles/machine-learning/how-to-workspace-diagnostic-api.md

@@ -0,0 +1,81 @@
+---
+title: Workspace diagnostics
+titleSuffix: Azure Machine Learning
+description: Learn how to use Azure Machine Learning workspace diagnostics in the Azure portal or with the Python SDK.
+services: machine-learning
+ms.service: machine-learning
+ms.subservice: enterprise-readiness
+ms.author: jhirono
+author: jhirono
+ms.reviewer: larryfr
+ms.date: 11/18/2021
+ms.topic: how-to
+
+---
+
+# How to use workspace diagnostics
+
+Azure Machine Learning provides a diagnostic API that can be used to identify problems with your workspace. Errors returned in the diagnostics report include information on how to resolve the problem.
+
+You can use the workspace diagnostics from the Azure Machine Learning studio or Python SDK.
+
+## Prerequisites
+
+* An Azure Machine learning workspace. If you don't have one, see [Create a workspace](quickstart-create-resources.md).
+* The [Azure Machine Learning SDK for Python](/python/api/overview/azure/ml).
+## Diagnostics from studio
+
+From [Azure Machine Learning studio](https://ml.azure.com) or the Python SDK, you can run diagnostics on your workspace to check your setup. To run diagnostics, select the '__?__' icon from the upper right corner of the page. Then select __Run workspace diagnostics__.
+
+:::image type="content" source="./media/how-to-workspace-diagnostic-api/diagnostics.png" alt-text="Screenshot of the workspace diagnostics button":::
+
+After diagnostics run, a list of any detected problems is returned. This list includes links to possible solutions.
+
+## Diagnostics from Python
+
+The following snippet demonstrates how to use workspace diagnostics from Python
+
+```python
+from azureml.core import Workspace
+
+ws = Workspace.from_config()
+
+diag_param = {
+      "value": {
+      }
+    }
+
+resp = ws.diagnose_workspace(diag_param)
+print(resp)
+```
+
+The response is a JSON document that contains information on any problems detected with the workspace. The following JSON is an example response:
+
+```json
+{
+    'value': {
+        'user_defined_route_results': [], 
+        'network_security_rule_results': [], 
+        'resource_lock_results': [], 
+        'dns_resolution_results': [{
+            'code': 'CustomDnsInUse', 
+            'level': 'Warning', 
+            'message': "It is detected VNet '/subscriptions/<subscription-id>/resourceGroups/<resource-group-name>/providers/Microsoft.Network/virtualNetworks/<virtual-network-name>' of private endpoint '/subscriptions/<subscription-id>/resourceGroups/larrygroup0916/providers/Microsoft.Network/privateEndpoints/<workspace-private-endpoint>' is not using Azure default dns. You need to configure your DNS server and check https://docs.microsoft.com/azure/machine-learning/how-to-custom-dns to make sure the custom dns is set up correctly."
+        }], 
+        'storage_account_results': [], 
+        'key_vault_results': [], 
+        'container_registry_results': [], 
+        'application_insights_results': [], 
+        'other_results': []
+    }
+}
+```
+
+If no problems are detected, an empty JSON document is returned.
+
+For more information, see the [Workspace.diagnose_workspace()](/python/api/azureml-core/azureml.core.workspace(class)#diagnose-workspace-diagnose-parameters-) reference.
+
+## Next steps
+
+* [Workspace.diagnose_workspace()](/python/api/azureml-core/azureml.core.workspace(class)#diagnose-workspace-diagnose-parameters-)
+* [How to manage workspaces in portal or SDK](how-to-manage-workspace.md)

includes/media/machine-learning-workspace-diagnostics/diagnostics.png renamed to articles/machine-learning/media/how-to-workspace-diagnostic-api/diagnostics.png

@@ -299,6 +299,8 @@
                 href: how-to-manage-rest.md
               - name: Link to Azure Synapse Analytics workspace
                 href: how-to-link-synapse-ml-workspaces.md
+              - name: Workspace Diagnostics
+                href: how-to-workspace-diagnostic-api.md
           - name: Create & manage compute resources
             items:
               - name: Compute instance

articles/machine-learning/toc.yml

@@ -2,12 +2,9 @@
 author: Blackmist
 ms.service: machine-learning
 ms.topic: include
-ms.date: 08/12/2021
+ms.date: 11/16/2021
 ms.author: larryfr
 ---
 
-From [Azure Machine Learning studio](https://ml.azure.com), you can run diagnostics on your workspace to check your setup. To run diagnostics, select the '__?__' icon from the upper right corner of the page. Then select __Run workspace diagnostics__.
+You can run diagnostics on your workspace from Azure Machine Learning studio or the Python SDK. After diagnostics run, a list of any detected problems is returned. This list includes links to possible solutions. For more information, see [How to use workspace diagnostics](/azure/machine-learning/how-to-workspace-diagnostic-api).
 
-:::image type="content" source="./media/machine-learning-workspace-diagnostics/diagnostics.png" alt-text="Screenshot of the workspace diagnostics button":::
-
-After diagnostics run, a list of any detected problems is returned. This list includes links to possible solutions.