Merge pull request #287246 from dominicbetts/release-aio-m2-qs-updates

AIO: quickstarts updates

Author: JamesJBarnett

articles/iot-operations/get-started-end-to-end-sample/media/quickstart-get-insights/query-kql.png

@@ -99,12 +99,6 @@ To add an asset endpoint:
     kubectl get assetendpointprofile -n azure-iot-operations
     ```
 
-1. In the current release, you need to patch the asset endpoint by using the following command:
-
-    ```console
-    kubectl patch AssetEndpointProfile opc-ua-connector-0 -n azure-iot-operations --type=merge -p '{"spec":{"additionalConfiguration":"{}"}}'
-    ```
-
 ## Manage your assets
 
 After you select your instance in operations experience, you see the available list of assets on the **Assets** page. If there are no assets yet, this list is empty:

articles/iot-operations/get-started-end-to-end-sample/media/quickstart-upload-telemetry-to-cloud/event-hubs-data-viewer.png

@@ -86,8 +86,9 @@ In this section, you create a KQL database in your Microsoft Fabric workspace to
 
     | Column name | Data type |
     | --- | --- |
-    | Temperature | decimal | 
-    | Humidity | decimal | 
+    | AssetId | string |
+    | Temperature | decimal |
+    | Humidity | decimal |
     | Timestamp | datetime |
 
 1. After the *OPCUA* table has been created, select it and use the **Explore your data** button to open a query window for the table.
@@ -97,7 +98,7 @@ In this section, you create a KQL database in your Microsoft Fabric workspace to
 1. Run the following KQL query to create a data mapping for your table. The data mapping will be called *opcua_mapping*.
 
     ```kql
-    .create table ['OPCUA'] ingestion json mapping 'opcua_mapping' '[{"column":"Temperature", "Properties":{"Path":"$.Temperature.Value"}},{"column":"Humidity", "Properties":{"Path":"$.Humidity.Value"}},{"column":"Timestamp", "Properties":{"Path":"$[\'EventProcessedUtcTime\']"}}]'
+    .create table ['OPCUA'] ingestion json mapping 'opcua_mapping' '[{"column":"AssetId", "Properties":{"Path":"$[\'AssetId\']"}},{"column":"Temperature", "Properties":{"Path":"$.Temperature.Value"}},{"column":"Humidity", "Properties":{"Path":"$.Humidity.Value"}},{"column":"Timestamp", "Properties":{"Path":"$[\'EventProcessedUtcTime\']"}}]'
     ``` 
 
 ### Add data table as a destination

articles/iot-operations/get-started-end-to-end-sample/media/quickstart-upload-telemetry-to-cloud/incoming-messages.png

@@ -131,9 +131,23 @@ Invoke-WebRequest -Uri https://raw.githubusercontent.com/Azure-Samples/explore-i
 kubectl apply -f dataflow.yaml
 ```
 
-
 ---
 
+## Verify data is flowing
+
+To verify that data is flowing to the cloud, you can view your Event Hubs instance in the Azure portal.
+
+If messages are flowing to the instance, you can see the count on incoming messages on the instance **Overview** page:
+
+:::image type="content" source="media/quickstart-upload-telemetry-to-cloud/incoming-messages.png" alt-text="Screenshot that shows the Event Hubs instance overview page with incoming messages.":::
+
+If messages are flowing, you can use the **Data Explorer** to view the messages:
+
+:::image type="content" source="media/quickstart-upload-telemetry-to-cloud/event-hubs-data-viewer.png" alt-text="Screenshot of the Event Hubs instance **Data Explorer** page.":::
+
+> [!TIP]
+> You may need to assign yourself to the **Azure Event Hubs Data Receiver** role for the Event Hubs namespace to view the messages.
+
 ## How did we solve the problem?
 
 In this quickstart, you used a dataflow to connect an MQTT topic to an event hub in your Azure Event Hubs namespace. In the next quickstart, you use Microsoft Fabric Real-Time Intelligence to visualize the data.