Line edits

Author: lootle1

learn-pr/aspnetcore/implement-observability-cloud-native-app-with-opentelemetry/includes/1-introduction.md

@@ -1,4 +1,4 @@
-Because of the distributed nature of cloud-native applications, they should be closely monitored to ensure they're healthy and that their behavior is fast and reliable. If problems develop, you need to know before users do. You can achieve observability by including a telemetry package such as OpenTelemetry.
+Because of the distributed nature of cloud-native applications, they should be closely monitored to ensure they're healthy, and their behavior is fast and reliable. If problems develop, you need to know before users do. You can achieve observability by including a telemetry package such as OpenTelemetry.
 
 Imagine you work for an online outdoor clothing retailer that has a microservice-based web app it uses for stock management. While testing the cloud-native app, you're asked to ensure that its behavior can be monitored. You want to see how .NET supports observability.
 

learn-pr/aspnetcore/implement-observability-cloud-native-app-with-opentelemetry/includes/4-exercise-add-observability-cloud-native-app.md

@@ -11,18 +11,19 @@ This step takes several minutes while GitHub creates and configures the codespac
 To use **Visual Studio Code**, clone the [https://github.com/MicrosoftDocs/mslearn-dotnet-cloudnative](https://github.com/MicrosoftDocs/mslearn-dotnet-cloudnative) repository to your local machine. Then:
 
 1. Install any [system requiements](https://code.visualstudio.com/docs/devcontainers/containers) to run Dev Container in Visual Studio Code.
-1. Make sure Docker is running. 
-1. In a new Visual Studio Code window open the folder of the cloned repository
+1. Make sure Docker is running.
+1. In a new Visual Studio Code window open the folder of the cloned repository.
 1. Press <kbd>Ctrl</kbd>+<kbd>Shift</kbd>+<kbd>P</kbd> to open the command palette.
-1. Search: **>Dev Containers: Rebuild and Reopen in Container**
+1. Search: **>Dev Containers: Rebuild and Reopen in Container**.
 1. Select **eShopLite - dotnet-observability** from the drop down. Visual Studio Code creates your development container locally.
+
 ### Add a diagnostic project to the solution
 
 The first step to adding observability to the **:::no-loc text="eShopLite":::** app is to introduce a new diagnostic project to the solution. This project contains all the OpenTelemetry packages and configurations that you'll use to add observability to the app.
 
 1. In the Visual Studio Code command palette, enter **>.NET: Open Solution**.
 1. Select **dotnet-observability/eShopLite/eShopLite.sln**.
-1. In the **Solution Explorer**, at the bottom of the **EXPLORER** pane, right-click the **eShopLite** solution and then select **New Project**.
+1. In the **Solution Explorer**, at the bottom of the **EXPLORER** pane, right-click the **eShopLite** solution, and then select **New Project**.
 1. In the **Select a template to create a new .NET project** dialog, select **Class Library (Common, Library)**.
 1. In the **Name** field, enter **Diagnostics**.
 1. In the **Project will be created in** dropdown, select **Default directory**.
@@ -69,7 +70,7 @@ Now add the OpenTelemetry packages to the new diagnostic project.
 
 With the OpenTelemetry packages added, you now introduce the code to make use of them.
 
-1. On the **EXPLORER** pane, right-click the *Class1.cs* file and then select **Rename**.
+1. On the **EXPLORER** pane, right-click the *Class1.cs* file, and then select **Rename**.
 1. Rename the file to **DiagnosticServiceCollectionExtensions.cs**.
 1. Replace the code in the file with the following code:
 
@@ -140,11 +141,11 @@ With the OpenTelemetry packages added, you now introduce the code to make use of
         0 Warning(s)
         0 Error(s)
     ```
-    
+
 1. The **Diagnostics** project is now ready to be used by the **Products** service.
-1. On the **EXPLORER** pane, under **SOLUTION EXPLORER**, right-click the **Products** project and then select **Add Project Reference**.
+1. On the **EXPLORER** pane, under **SOLUTION EXPLORER**, right-click the **Products** project, and then select **Add Project Reference**.
 1. Select **Diagnostics**.
-1. On the **EXPLORER** pane, expand the *Products* folder and then select **Program.cs**.
+1. On the **EXPLORER** pane, expand the *Products* folder, and then select **Program.cs**.
 1. Under the code comment `// Add observability code here`, add a call to the Diagnostics method:
 
     ```csharp
@@ -197,7 +198,7 @@ With the OpenTelemetry packages added, you now introduce the code to make use of
 
     :::image type="content" source="../media/eshoplite-products.png" alt-text="A screenshot that shows the Products page in the eShopLite app. The page shows a list of products with a name, description, and price and a button to update the stock." lightbox="../media/eshoplite-products.png":::
 
-1. Select **Update Stock** for several of the products. Then, in the dialog, change the stock value and select **Update**.
+1. Select **Update Stock** for several of the products. Then, in the dialog, change the stock value, and select **Update**.
 
 1. Select the **TERMINAL** tab and scroll through the messages. Note there are messages from OpenTelemetry like:
 

learn-pr/aspnetcore/implement-observability-cloud-native-app-with-opentelemetry/includes/5-view-telemetry-data.md

@@ -1,12 +1,12 @@
-Your app is collecting telemetry data and you now need a more comprehensive way to view it. In this unit, you'll see how to view telemetry data in many different tools.
+Your app is collecting telemetry data, and you now need a more comprehensive way to view it. In this unit, you'll see how to view telemetry data in many different tools.
 
 ## Monitor and view telemetry data
 
 A common way to view telemetry data is to use Prometheus and Grafana together. Prometheus is an open-source monitoring system that collects metrics from your cloud-native app. Grafana is an open-source visualization tool that you use to create dashboards to view the metrics collected by Prometheus.
 
 ### Prometheus
 
-The first step is to add a Prometheus container and configure it to collect data from each microservice in your app. You then add the Prometheus .NET client library to collect metrics from the app.
+The first step is to add a Prometheus container, and configure it to collect data from each microservice in your app. You then add the Prometheus .NET client library to collect metrics from the app.
 
 :::image type="content" source="../media/prometheus.png" alt-text="Screenshot that shows the configured Prometheus app showing the health of the eShopLite app." lightbox="../media/prometheus.png":::
 
@@ -29,7 +29,7 @@ scrape_configs:
 
 ### Grafana
 
-Grafana is an open-source visualization tool that you can use to create dashboards to view the metrics collected by Prometheus. You can configure Grafana to connect to Prometheus and display the metrics in a dashboard. Like before, you add a Grafana container to your app and configure it to connect to Prometheus.
+Grafana is an open-source visualization tool that you can use to create dashboards to view the metrics collected by Prometheus. You can configure Grafana to connect to Prometheus, and display the metrics in a dashboard. Like before, you add a Grafana container to your app, and configure it to connect to Prometheus.
 
 :::image type="content" source="../media/grafana.png" alt-text="Screenshot that shows an ASP.NET dashboard in Grafana." lightbox="../media/grafana.png":::
 
@@ -57,8 +57,8 @@ In your diagnostics project, you need to add support for Zipkin via the `OpenTel
 
 ### Go deeper with Application Insights
 
-There's a tool that can combine looking at metrics and viewing distributed tracing and then merge it with data from logs. Application Insights is an extensible Application Performance Management (APM) service. You can use it to monitor your live web application. Application Insights automatically detects performance anomalies. It includes powerful analytics tools to help you diagnose issues and understand what users actually do with your app.
+There's a tool that can combine looking at metrics and viewing distributed tracing, and then merge it with data from logs. Application Insights is an extensible Application Performance Management (APM) service. You can use it to monitor your live web application. Application Insights automatically detects performance anomalies. It includes powerful analytics tools to help you diagnose issues and understand what users actually do with your app.
 
 :::image type="content" source="../media/app-insights.png" alt-text="Screenshot that shows Application Insights showing the health of the eShopLite app." lightbox="../media/app-insights.png":::
 
-Like the preceding tools, you need to add a NuGet package to your solution `Azure.Monitor.OpenTelemetry.AspNetCore` and then introduce Azure Monitor as an exporter to your diagnostics project.
+Like the preceding tools, you need to add a NuGet package to your solution `Azure.Monitor.OpenTelemetry.AspNetCore`, and then introduce Azure Monitor as an exporter to your diagnostics project.

learn-pr/aspnetcore/implement-observability-cloud-native-app-with-opentelemetry/includes/6-exercise-use-opentelemetry-data-cloud-native-application.md

@@ -1,4 +1,4 @@
-In this exercise, you get better visibility of all the data generated by OpenTelemetry in your app. You finish adding diagnostics capability to the Store service. With that in place, you add Prometheus and Grafana to the **:::no-loc text="eShopLite":::** services and look at some of the metrics being captured. The next step is to add Zipkin and view the distributed traces. Finally, you add Application Insights to your app and use it to view the data.
+In this exercise, you get better visibility of all the data generated by OpenTelemetry in your app. You finish adding diagnostics capability to the Store service. With that in place, you add Prometheus and Grafana to the **:::no-loc text="eShopLite":::** services and look at some of the metrics being captured. The next step is to add Zipkin and view the distributed traces. Finally, you add Application Insights to your app, and use it to view the data.
 
 ## Add Prometheus and Grafana
 
@@ -38,9 +38,9 @@ The preceding Docker yaml adds two new services, **Prometheus** and **Grafana**.
 
 Prometheus needs to be configured so that it knows where to collect the metrics. You add a *prometheus.yml* file to the *prometheus* folder.
 
-1. In Visual Studio Code, on the **EXPLORER** pane, right-click the *dotnet-observability* folder and then select **New Folder**.
-1. In the name field, enter<!--CE:Please check: Should 'prometheus' be capitalized here and in steps 3 and 4?--> **prometheus**.
-1. On the **EXPLORER** pane, right-click the *prometheus* folder and then select **New File**.
+1. In Visual Studio Code, on the **EXPLORER** pane, right-click the *dotnet-observability* folder, and then select **New Folder**.
+1. In the name field, enter **prometheus**.
+1. On the **EXPLORER** pane, right-click the *prometheus* folder, and then select **New File**.
 1. In the name field, enter **prometheus.yml**.
 1. In the file editor, enter this YAML:
 
@@ -67,9 +67,9 @@ Grafana needs to be configured so that it knows where to collect the metrics.
 
 1. In Visual Studio Code, on the **EXPLORER** pane, right-click the *dotnet-observability* folder and then select **New Folder**.
 1. In the name field, enter **grafana**.
-1. Right-click the *grafana* folder and then select **New Folder**.
+1. Right-click the *grafana* folder, and then select **New Folder**.
 1. In the name field, enter **datasource**.
-1. Right-click the *grafana* folder and then select **New Folder**.
+1. Right-click the *grafana* folder, and then select **New Folder**.
 1. In the name field, enter **dashboard**.
 1. Expand the *grafana* folder, right-click the *datasource* folder, and then select **New File**.
 1. In the name field, enter **datasource.yml**.
@@ -115,7 +115,7 @@ Now, the diagnostics project is only configured to expose metrics to the console
     dotnet add package OpenTelemetry.Exporter.Prometheus.AspNetCore --prerelease
     ```
 
-1. On the **EXPLORER** pane, expand the *Diagnostics* folder and then select **DiagnosticServiceCollectionExtensions.cs**.
+1. On the **EXPLORER** pane, expand the *Diagnostics* folder, and then select **DiagnosticServiceCollectionExtensions.cs**.
 1. Replace the console exporter `.AddConsoleExporter();` with this code:
 
     ```csharp
@@ -139,9 +139,9 @@ Now, the diagnostics project is only configured to expose metrics to the console
 
 The app is currently only configured to expose metrics for the **Products** service. You update the app to expose metrics for the **Store** service too.
 
-1. On the **EXPLORER** pane, under **SOLUTION EXPLORER**, right-click the **Store** project and then select **Add Project Reference**.
+1. On the **EXPLORER** pane, under **SOLUTION EXPLORER**, right-click the **Store** project, and then select **Add Project Reference**.
 1. Select **Diagnostics**.
-1. On the **EXPLORER** pane, expand the *Store* folder and then select **Program.cs**.
+1. On the **EXPLORER** pane, expand the *Store* folder, and then select **Program.cs**.
 1. Under the code comment `// Add observability code here`, add a call to the Diagnostics method:
 
     ```csharp
@@ -185,7 +185,6 @@ You now test the new observability features you added to the app.
     ```dotnetcli
     dotnet publish /p:PublishProfile=DefaultContainer 
     ```
-    
 
 1. Go to the *dotnet-observability* folder, and start the app with Docker:
 
@@ -222,7 +221,7 @@ You now test the new observability features you added to the app.
 
 ## Add Zipkin
 
-You now extend the tracing capabilities of the app by adding Zipkin. As you did before, you add a Zipkin container to your app and configure it to connect to the OpenTelemetry collector. Then you add the OpenTelemetry Zipkin exporter to your app.
+You now extend the tracing capabilities of the app by adding Zipkin. As you did before, you add a Zipkin container to your app, and configure it to connect to the OpenTelemetry collector. Then you add the OpenTelemetry Zipkin exporter to your app.
 
 1. In Visual Studio Code, on the **EXPLORER** pane, select the *docker-compose.yml* file inside the *dotnet-observability* folder.
 
@@ -306,7 +305,7 @@ You now extend the tracing capabilities of the app by adding Zipkin. As you did
     dotnet add package OpenTelemetry.Exporter.Zipkin --prerelease
     ```
 
-1. On the **EXPLORER** pane, expand the *Diagnostics* folder and then select **DiagnosticServiceCollectionExtensions.cs**.
+1. On the **EXPLORER** pane, expand the *Diagnostics* folder, and then select **DiagnosticServiceCollectionExtensions.cs**.
 1. At the bottom of the tracing providers, add Zipkin:
 
     ```csharp

learn-pr/aspnetcore/implement-observability-cloud-native-app-with-opentelemetry/includes/7-exercise-extend-telemetry.md

@@ -50,7 +50,7 @@ You want to have greater visibility of how a stock changes over time, so you cre
     This code adds the `ProductsMetrics` class to the dependency injection container.
 
 1. Select <kbd>Ctrl</kbd>+<kbd>S</kbd> to save the file.
-1. On the **EXPLORER** pane, in the *Products* folder, expand the *Endpoint* folder and then select **ProductEndpoints.cs**.
+1. On the **EXPLORER** pane, in the *Products* folder, expand the *Endpoint* folder, and then select **ProductEndpoints.cs**.
 1. Replace the existing stock update `MapPut` endpoint with this code:
 
       ```csharp
@@ -128,12 +128,12 @@ You now add the metric to OpenTelemetry so that it can be exported to your obser
 1. Open the **:::no-loc text="eShopLite":::** app in a browser at `http://localhost:32000`.
 1. Go to the **Products** page and change the stock amount on several products.
 1. Open the **Prometheus** dashboard at `http://localhost:9090`.
-1. In the search box, enter the`eshoplite_products_stock_change_total` metric and then select **Execute**.
+1. In the search box, enter the`eshoplite_products_stock_change_total` metric, and then select **Execute**.
 
     You should see it listed in a table.
 
 1. Select the **Graph** tab. You should see the stock amount change over time.
 
     :::image type="content" source="../media/new-metric.png" alt-text="Screenshot that shows Prometheus showing the new custom metric on a graph."  lightbox="../media/new-metric.png":::
 
-1. On the **TERMINAL** pane, press <kbd>Ctrl</kbd>+<kbd>C</kbd> to stop the app.
+1. On the **TERMINAL** pane, press <kbd>Ctrl</kbd>+<kbd>C</kbd> to stop the app.

learn-pr/aspnetcore/implement-observability-cloud-native-app-with-opentelemetry/includes/9-summary.md

@@ -2,4 +2,4 @@ In most cloud-native applications, it's critical to generate telemetry data that
 
 ## Clean up codespace
 
-You can delete the codespace on [GitHub](https://github.com/codespaces) under **By repository** where you see *MicrosoftDocs/mslearn-dotnet-cloudnative*.
+You can delete the codespace on [GitHub](https://github.com/codespaces) under **By repository** where you see *MicrosoftDocs/mslearn-dotnet-cloudnative*.