Fix style and formatting issues in RabbitMQ GCP Learning Path

Co-authored-by: DougAnsonAustinTX <4755232+DougAnsonAustinTX@users.noreply.github.com>

Author: Copilot

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/background.md

@@ -12,7 +12,7 @@ Google Axion C4A is a family of Arm-based virtual machines built on Google’s c
 
 The C4A series provides a cost-effective alternative to x86 virtual machines while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud.
 
-To learn more about Google Axion, refer to the [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu) blog.
+To learn more about Google Axion, see the [Introducing Google Axion Processors, Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu) blog.
 
 ## RabbitMQ
 

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/baseline.md

@@ -126,7 +126,7 @@ You should see an output similar to:
 | testqueue    | 1        |
 ```
 
-Baseline Validation Summary
+### Baseline validation summary
 
 - RabbitMQ node is running and healthy
 - The management plugin is enabled and accessible

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/firewall_setup.md

@@ -8,35 +8,29 @@ layout: learningpathall
 
 ## Overview
 
-In this section, you will learn how to create a Firewall Rule within Google Cloud Console.  For this learning path, we need to expose TCP port 15672.
+In this section, you create a Firewall Rule within Google Cloud Console to expose TCP port 15672.
 
 {{% notice Note %}}
 For support on GCP setup, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
 {{% /notice %}}
 
 ## Create a Firewall Rule in GCP
 
-For this learning path, we need to expose TCP port 15672.  To accomplish this, we first need to create a firewall rule.
-- Navigate to the [Google Cloud Console](https://console.cloud.google.com/).
-- Go to **VPC Network > Firewall** and press **Create firewall rule**.
+To expose TCP port 15672, create a firewall rule.
+
+Navigate to the [Google Cloud Console](https://console.cloud.google.com/), go to **VPC Network > Firewall**, and select **Create firewall rule**.
 
 ![Create a firewall rule](images/firewall-rule.png "Create a firewall rule")
 
-- Next, we create the firewall rule that will expose TCP port 15672 for our learning path.
-- Set the "Name" of the new rule to "allow-tcp-15672"
-- Select your network that you intend to bind to your VM (default is "autoscaling-net" but your organization might have others that you need to use)
-- Direction of traffic should be set to "Ingress"
-- Allow on match should be set to "Allow" and the "Targets" should be set to "Specified target tags".
-- Enter "allow-tcp-15672" to the "Target tags" text field
-- Set the "Source IPv4 ranges" text value to "0.0.0.0/0"
+Next, create the firewall rule that exposes TCP port 15672.
+Set the **Name** of the new rule to "allow-tcp-15672". Select your network that you intend to bind to your VM (default is "autoscaling-net" but your organization might have others).
+
+Set **Direction of traffic** to "Ingress". Set **Allow on match** to "Allow" and **Targets** to "Specified target tags". Enter "allow-tcp-15672" in the **Target tags** text field. Set **Source IPv4 ranges** to "0.0.0.0/0".
 
 ![Create a firewall rule](images/network-rule.png "Creating the TCP/15672 firewall rule")
 
-- Lastly, we select "Specified protocols and ports" under the "Protocols and ports" section
-- Select the "TCP" checkbox
-- Enter "15672" in the "Ports" text field
-- Press "Create"
+Finally, select **Specified protocols and ports** under the **Protocols and ports** section. Select the **TCP** checkbox, enter "15672" in the **Ports** text field, and select **Create**.
 
 ![Specifying the TCP port to expose](images/network-port.png "Specifying the TCP port to expose")
 
-Our network firewall rule is now created so we can continue with the VM creation!
+The network firewall rule is now created and you can continue with the VM creation.

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/installation.md

@@ -62,10 +62,10 @@ sudo rpm -Uvh rabbitmq-server-4.2.0-1.el8.noarch.rpm
 ```
 
 {{% notice Note %}}
-RabbitMQ version 3.11.0 introduced significant performance enhancements for Arm-based architectures. This version requires Erlang 25.0 or later, which brings Just-In-Time (JIT) compilation and modern flame graph profiling tooling to both x86 and ARM64 CPUs. These features result in improved performance on ARM64 architectures.
+RabbitMQ version 3.11.0 introduced significant performance enhancements for Arm-based architectures. This version needs Erlang 25.0 or later, which brings Just-In-Time (JIT) compilation and modern flame graph profiling tooling to both x86 and Arm64 CPUs. These features result in improved performance on Arm64 architectures.
 You can view [this release note](https://github.com/rabbitmq/rabbitmq-server/blob/main/release-notes/3.11.0.md)
 
-The [Arm Ecosystem Dashboard](https://developer.arm.com/ecosystem-dashboard/) recommends RabbitMQ version 3.11.0, the minimum recommended on the Arm platforms.
+The [Arm Ecosystem Dashboard](https://developer.arm.com/ecosystem-dashboard/) recommends RabbitMQ version 3.11.0, the minimum recommended on Arm platforms.
 {{% /notice %}}
 
 ### Enable and Start RabbitMQ Service
@@ -112,11 +112,9 @@ You should see an output similar to:
 ```
 
 ### Access RabbitMQ Management UI
-Create a new RabbitMQ user for remote access
+Create a new RabbitMQ user for remote access.
 
-- Create a new `admin` user
-
-**Run these commands on the VM:**
+Create a new `admin` user by running these commands on the VM:
 
 ```console
 sudo rabbitmqctl add_user admin StrongPassword123
@@ -126,15 +124,15 @@ sudo rabbitmqctl set_permissions -p / admin ".*" ".*" ".*"
 
 **Log in to Management UI**
 
-Now, let’s test it from outside the VM. Open a web browser on your LOCAL machine (Chrome, Firefox, Edge, etc.) and enter the following URL and credentials in the address bar:
+Now, test it from outside the VM. Open a web browser on your local machine (Chrome, Firefox, Edge, etc.) and enter the following URL and credentials in the address bar:
 
 - **URL**: http://<VM_IP>:15672
 - **Username**: admin
 - **Password**: StrongPassword123
 
 Replace `<VM_IP>` with the public IP of your GCP VM.
 
-If everything is set up correctly, you will see a RabbitMQ login page in your browser. It looks like this:
+If everything is configured correctly, you see a RabbitMQ login page in your browser that looks like this:
 
 ![RabbitMQ page alt-text#center](images/rabbitmq.png "Figure 1: RabbitMQ Login page")
 

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/instance.md

@@ -8,42 +8,32 @@ layout: learningpathall
 
 ## Overview
 
-In this section, you will learn how to provision a Google Axion C4A Arm virtual machine on Google Cloud Platform (GCP) using the `c4a-standard-4` (4 vCPUs, 16 GB memory) machine type in the Google Cloud Console.  
+In this section, you provision a Google Axion C4A Arm virtual machine on Google Cloud Platform (GCP) using the `c4a-standard-4` (4 vCPUs, 16 GB memory) machine type in the Google Cloud Console.  
 
 {{% notice Note %}}
 For support on GCP setup, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
 {{% /notice %}}
 
 ## Provision a Google Axion C4A Arm VM in Google Cloud Console
 
-To create a virtual machine based on the C4A instance type:
-- Navigate to the [Google Cloud Console](https://console.cloud.google.com/).
-- Go to **Compute Engine > VM Instances** and select **Create Instance**. 
-- Under **Machine configuration**:
-   - Populate fields such as **Instance name**, **Region**, and **Zone**.
-   - Set **Series** to `C4A`.
-   - Select `c4a-standard-4` for machine type.
+To create a virtual machine based on the C4A instance type, navigate to the [Google Cloud Console](https://console.cloud.google.com/) and go to **Compute Engine > VM Instances**. Select **Create Instance**.
+
+Under **Machine configuration**, populate fields such as **Instance name**, **Region**, and **Zone**. Set **Series** to `C4A` and select `c4a-standard-4` for machine type.
 
    ![Create a Google Axion C4A Arm virtual machine in the Google Cloud Console with c4a-standard-4 selected alt-text#center](images/gcp-vm.png "Creating a Google Axion C4A Arm virtual machine in Google Cloud Console")
 
+Under **OS and Storage**, select **Change**, then choose an Arm64-based OS image. For this Learning Path, use **SUSE Linux Enterprise Server**. Select "Pay As You Go" for the license type and select **Select**.
 
-- Under **OS and Storage**, select **Change**, then choose an Arm64-based OS image. For this Learning Path, use **SUSE Linux Enterprise Server**. 
-- If using use **SUSE Linux Enterprise Server**. Select "Pay As You Go" for the license type. 
-- Once appropriately selected, please Click **Select**. 
-- Under **Networking**, enable **Allow HTTP traffic**.
-- Also under **Networking**, in the "Network tags" text field add "allow-tcp-15672" as an additional tag
+Under **Networking**, enable **Allow HTTP traffic** and add "allow-tcp-15672" as a network tag in the **Network tags** text field.
 
-![Adding the TCP/15672 firewall rule to our VM](images/network-config.png "Adding the TCP/15672 firewall rule to our VM")
+![Adding the TCP/15672 firewall rule to the VM](images/network-config.png "Adding the TCP/15672 firewall rule to the VM")
 
-- Click **Create** to launch the instance.
-- Once created, you should see a "SSH" option to the right in your list of VM instances. You should also see the public IP address for your VM.
-- Save off the public IP address for your VM as you will need this in the next step.
-- Click on this to launch a SSH shell into your VM instance:
+Select **Create** to launch the instance. Once created, you see an **SSH** option and the public IP address for your VM in the list of VM instances. Save the public IP address as you need it in the next step. Select the **SSH** option to launch an SSH shell into your VM instance.
 
-![Invoke a SSH session via your browser alt-text#center](images/gcp-pubip-ssh.png "Invoke a SSH session into your running VM instance")
+![Invoke an SSH session via your browser alt-text#center](images/gcp-pubip-ssh.png "Invoke an SSH session into your running VM instance")
 
-- A window from your browser should come up and you should now see a shell into your VM instance:
+A window opens from your browser and you see a shell into your VM instance.
 
 ![Terminal Shell in your VM instance alt-text#center](images/gcp-shell.png "Terminal shell in your VM instance")
 
-Next, let's install RabbitMQ!
+Next, install RabbitMQ.

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/use-case1.md

@@ -46,7 +46,7 @@ Create a durable topic exchange to route events based on routing keys.
 ```
 
 - Creates a durable topic exchange named events.
-- Routes messages using wildcard-based routing keys (e.g., order.*).
+- Routes messages using wildcard-based routing keys (for example, order.*).
 - Ensures the exchange survives broker restarts.
 
 ### Declare a Durable Queue
@@ -115,7 +115,7 @@ Create a Python worker file to process messages from a queue.
 
 A **Python worker** was created to process messages from a RabbitMQ queue (jobs) using the pika library. The queue is durable, ensuring message persistence. The worker implements fair dispatch (prefetch_count=1) and manual acknowledgments to reliably process each job without loss. Messages were successfully published to the queue using rabbitmqadmin, and the worker consumed them as expected.
 
-Using your favorite editor (example is using "edit" below...) create your "worker.py" file:
+Using your favorite editor (the example uses "edit") create your "worker.py" file:
 
 ```console
 edit worker.py
@@ -200,7 +200,7 @@ Publish another job:
 Worker started. Waiting for jobs...
 [Worker] Received job: {'job': 'hello1'}
 ```
-Now press "CTRL-C" to exit the worker application.
+Press "CTRL-C" to exit the worker application.
 
 ## Use Case Validation
 

content/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/use-case2.md

@@ -260,15 +260,15 @@ WhatsApp Worker started. Waiting for messages...
 - Queue consumption is successful
 - Manual acknowledgments are applied
 
-End-to-end message flow validated.
+This validates the end-to-end message flow.
 
 ### Verify Queue State
 
 ```console
 ./rabbitmqadmin list queues name messages consumers
 ```
 
-Expected output should be similar to:
+Expected output is similar to:
 
 ```output
 +------------------------+----------+-----------+
@@ -281,7 +281,7 @@ Expected output should be similar to:
 +------------------------+----------+-----------+
 ```
 
-**This confirms that:**
+This confirms that:
 
 - Messages were consumed successfully
 - One active consumer is connected