Final checks.

Author: madeline-underwood

content/learning-paths/servers-and-cloud-computing/net-aspire/aws.md

@@ -21,7 +21,7 @@ To set up an Arm-powered EC2 instance, follow these steps:
 ![Figure 5 alt-text#center](figures/05.png "Figure 5: Search for the EC2 Service in the AWS Management Console.")
 
 3. In the EC2 Dashboard, click **Launch Instance** and add the following information in these corresponding data fields to configure your setup:
-* Name: type "arm-server".
+* Name: enter **arm-server**.
 * AMI: select **Arm-compatible Amazon Machine Image, Ubuntu 22.04 LTS for Arm64**.
 * Architecture: select **64-bit (Arm)**.
 * Instance Type: select **t4g.small**.
@@ -31,7 +31,7 @@ The configuration should look like the configuration fields that Figure 6 shows:
 ![Figure 6 alt-text#center](figures/06.png "Figure 6: Configuration Fields.")
 
 4. Scroll down to **Key pair** (login), and click **Create new key pair**. 
-  This displays the "Create key pair" window. 
+  This displays the **Create key pair** window. 
   Now configure the following fields:
 * Key pair name: **arm-key-pair**.
 * Key pair type: **RSA**.
@@ -40,30 +40,32 @@ The configuration should look like the configuration fields that Figure 6 shows:
 
 ![fig7](figures/07.png)
 
-5. Scroll down to "Network Settings", and confgure the settings:
+5. Scroll down to **Network Settings**, and configure the settings:
 * VPC: select the default.
 * Subnet: select **No preference**.
 * Auto-assign public IP: **Enable**.
 * Firewall: Check **Create security group**.
-* Security group name: arm-security-group.
-* Description: arm-security-group.
+* Security group name: **arm-security-group**.
+* Description: **arm-security-group**.
 * Inbound security groups. 
 
 ![fig8](figures/08.png)
 
-6. Configure "Inbound Security Group Rules" by selecting **Add Rule** and then setting the following details:
-* Type: Custom TCP.
-* Protocol: TCP.
-* Port Range: 7133.
-* Source: Select "Anywhere (0.0.0.0/0)" for public access or restrict access to your specific IP for better security.
+6. Configure **Inbound Security Group Rules** by selecting **Add Rule** and then setting the following details:
+* Type: **Custom TCP**.
+* Protocol: **TCP**.
+* Port Range: **7133**.
+* Source: Select **Anywhere (0.0.0.0/0)** for public access or restrict access to your specific IP for better security.
 
 Repeat this step for all three ports that the application is using. This example demonstrates setup using ports 7133, 7511, and 17222. These must match the values that you have when you run the app locally.
 
 The configuration should look like:
 
 ![fig9](figures/09.png)
 
-7. Launch an instance by clicking the **Launch instance** button. You should see the green box with the Success label. This box also contains a link to the EC2 instance. Click it, and it takes you to the instance dashboard, which looks like Figure 10:
+7. Launch an instance by clicking the **Launch instance** button. You should see the green box with the **Success** label. 
+
+This box also contains a link to the EC2 instance. Click on it, and it takes you to the instance dashboard, as Figure 10 shows:
 
 ![fig10](figures/10.png)
 

content/learning-paths/servers-and-cloud-computing/net-aspire/gcp.md

@@ -121,4 +121,4 @@ To make your application publicly-accessible, configure the firewall rules:
 5. Click the **Save** button.
 
 ### Summary
-You have successfully deployed the Aspire app onto an Arm-powered GCP virtual machine. This deployment demonstrates the compatibility of .NET applications with Arm architecture and GCP, offering high performance and cost-efficiency.
+You have successfully deployed the Aspire app onto an Arm-powered GCP virtual machine. This deployment demonstrates the compatibility of .NET applications with Arm architecture and GCP, offering high performance and cost efficiency.

content/learning-paths/servers-and-cloud-computing/net-aspire/modify_project.md

@@ -6,7 +6,7 @@ weight: 5
 layout: learningpathall
 ---
 
-## Modify the Project
+## Add additional computations
 
 Now you can move on to add additional computations to mimic computationally-intensive work. 
 
@@ -45,11 +45,11 @@ static class ComputationService
 }
 ```
 
-This code defines a static class, ComputationService, designed to perform computationally-intensive tasks; in particular, matrix multiplication. It contains a public method, PerformIntensiveCalculations, which generates two matrices of a specified size, multiplies them, and stores the resulting matrix.
+This code defines a static class, **ComputationService**, designed to perform computationally-intensive tasks; in particular, matrix multiplication. It contains a public method, **PerformIntensiveCalculations**, which generates two matrices of a specified size, multiplies them, and stores the resulting matrix.
 
-* The private method, GenerateMatrix, creates a one-dimensional array representing a matrix of the given size (matrixSize x matrixSize). Each element in the matrix is initialized with a random double-value generated using Random.Shared.NextDouble().
+* The private method, **GenerateMatrix**, creates a one-dimensional array representing a matrix of the given size (matrixSize x matrixSize). Each element in the matrix is initialized with a random double-value generated using **Random.Shared.NextDouble()**.
 
-* The public method, PerformIntensiveCalculations, multiplies two matrices (matrix1 and matrix2) element-by-element using nested loops and LINQ. It iterates through each row of the first matrix and each column of the second matrix, calculating the dot product for each element in the resulting matrix. The result of the multiplication is stored in a flattened one-dimensional array, called matrixResult.
+* The public method, **PerformIntensiveCalculations**, multiplies two matrices (matrix1 and matrix2) element-by-element using nested loops and LINQ. It iterates through each row of the first matrix and each column of the second matrix, calculating the dot product for each element in the resulting matrix. The result of the multiplication is stored in a flattened one-dimensional array, called **matrixResult**.
 
 This code is provided for demonstrating heavy computational operations, such as large matrix manipulations, and can simulate workloads in scenarios that mimic intensive data processing or scientific calculations.
 

content/learning-paths/servers-and-cloud-computing/net-aspire/run_app.md

@@ -5,7 +5,7 @@ weight: 4
 ### FIXED, DO NOT MODIFY
 layout: learningpathall
 ---
-## Run the Project
+## Using the dashboard
 The application will issue a certificate. Before you run the application, add support to trust the HTTPS development certificate by running:
 
 ```console
@@ -33,11 +33,17 @@ info: Aspire.Hosting.DistributedApplication[0]
       Login to the dashboard at https://localhost:17222/login?t=81f99566c9ec462e66f5eab5aa9307b0
 ```
 
-Click on the link generated for the dashboard. In this case it is: [https://localhost:17222/login?t=81f99566c9ec462e66f5eab5aa9307b0](https://localhost:17222/login?t=81f99566c9ec462e66f5eab5aa9307b0). This directs you to the application dashboard, as shown in Figure 1:
+Click on the link generated for the dashboard. 
+
+In this case, it is: [https://localhost:17222/login?t=81f99566c9ec462e66f5eab5aa9307b0](https://localhost:17222/login?t=81f99566c9ec462e66f5eab5aa9307b0). 
+
+This directs you to the application dashboard, as Figure 1 shows:
 
 ![fig1 alt-text#center](figures/01.png "Figure 1: Application Dashboard.")
 
-On the dashboard, locate and click the endpoint link for `NetAspire.Arm.Web`. This takes you to the Blazor-based web application. In the Blazor app, navigate to the Weather section to access and display data retrieved from the WeatherForecast API:
+On the dashboard, locate and click the endpoint link for `NetAspire.Arm.Web`. 
+
+This takes you to the Blazor-based web application. In the Blazor app, navigate to the Weather section to access and display data retrieved from the WeatherForecast API:
 
 ![fig2 alt-text#center](figures/02.png "Figure 2: Data Displayed from WeatherForecast API.")