Fix based on User comments

docs/install-ai-unlimited/prod-aws-console-deploy-ai-unlimited.md

@@ -25,7 +25,7 @@ For installation support, ask the [community](https://support.teradata.com/commu
 
 CloudFormation templates for the manager are here in the AI Unlimited GitHub repository you cloned:
 
-`/deployments/aws/templates/ai-unlimited/`
+`deployments/aws/templates/ai-unlimited/`
 
 1. Choose a template based on the type of [load balancer](/docs/glossary.md#glo-load-balancer) you want to use.<br /> 
    :::note

docs/install-ai-unlimited/prod-azure-portal-deploy-manager.md

@@ -14,7 +14,7 @@ Before you begin, make sure you have the [prerequisites](/docs/install-ai-unlimi
 
 The AI Unlimited manager orchestrates the engine's deployment and includes a web-based user interface for monitoring projects. And the manager is where you'll set up AI Unlimited. 
 
-You'll use an Azure Resource Manager (ARN) template provided by Teradata to install the manager from the Azure Portal. You'll deploy a server instance, on which the manager runs in a container controlled by [systemd](/docs/glossary.md#glo-systemd)
+You'll use an Azure Resource Manager (ARM) template provided by Teradata to install the manager from the Azure Portal. You'll deploy a server instance, on which the manager runs in a container controlled by [systemd](/docs/glossary.md#glo-systemd)
 
 :::tip
 For installation support, ask the [community](https://support.teradata.com/community?id=community_forum&sys_id=b0aba91597c329d0e6d2bd8c1253affa).
@@ -23,7 +23,17 @@ For installation support, ask the [community](https://support.teradata.com/commu
 
 ## Download the manager template
 
-Download the Azure Resource Manager (ARM) template (`/deployments/azure/ai-unlimited.json`) from the AI Unlimited GitHub repository you cloned.
+Azure Resource Manager (ARM) templates for the manager are here in the AI Unlimited GitHub repository you cloned:
+
+`develop/deployments/azure/templates/arm/ai-unlimited`
+
+Choose a template based on the type of [load balancer](/docs/glossary.md#glo-load-balancer) you want to use.<br /> 
+   :::note
+   You might want to ask a cloud admin at your organization for guidance.
+   :::
+    - `ai-unlimited-with-alb.yaml`&mdash;Hosts the manager behind an [application load balancer](/docs/glossary.md#glo-application-load-balancer)
+    - `ai-unlimited-with-nlb.yaml`&mdash;Hosts the manager behind a [network load balancer](/docs/glossary.md#glo-network-load-balancer)
+    - `ai-unlimited-without-lb.yaml`&mdash;No load balancer. If you're unsure about which template to use, we recommend this one.
 
 
 ## Load the template
@@ -61,7 +71,7 @@ Review the parameters. Provide values for the required parameters. Your organiza
 | AI Unlimited GRPC Port | The port to access the AI Unlimited API. | Required with default<br/>Default: 3282 | 
 | Source App Sec Groups | The source application security groups (ASG) that have permission to connect to the AI Unlimited instance. ASGs let you organize your virtual machines (VMs) based on their specific network security policies. These security policies determine what traffic is or is not permissible on your virtual machine. |Optional<br/>Default: NA<br/> Select an application security group in the same region as the network interface. |
 | Destination App Sec Groups | The destination application security groups that have permission to connect to the AI Unlimited instance. | Optional<br/>Default: NA<br/>Select an application security group in the same region as the network interface.  |
-| Role Definition ID | The ID of the role to use with AI Unlimited.| Required<br/>Default: NA<br/>Use Azure CLI command- Get-AzRoleDefinition command to get your Role Definition ID. |
+| Role Definition ID | The ID of the role to use with AI Unlimited.| Required<br/>Default: NA<br/>Use Azure CLI command- Get-AzRoleDefinition to get your Role Definition ID. |
 | Allow Public SSH | Specifies whether you can use secure shell (SSH) keys to connect to VMs in Azure.|  Optional<br/>Default: true |
 | Use Key Vault | Specifies whether to use Key Vault to retrieve the secured password during a deployment. | Optional<br/>Default: New |
 | Use Persistent Volume | Specifies whether you want to use a persistent volume to store data. See *Learn more: Why use a persistent volume?* below the parameters section. | Optional with default<br/>Default: New <br/>Supported options: New, None, Existing, depending on your use case. |

docs/install-ai-unlimited/setup-ai-unlimited.md

@@ -161,7 +161,7 @@ Select **Login**. Then, if prompted, sign in.
 <br />
 **GitLab base URL**&mdash;The URL for your GitLab account.
 
-**GitLab client ID** and **GitLab client secret**&mdash;The credentials received from GitLab when your [OAuth app was created](/docs/install-ai-unlimited/git-requirements.md).
+**GitLab client ID** and **GitLab client secret**&mdash;The credentials received from GitLab when your [OAuth app was created](/docs/resources/git-requirements.md).
 
 **Group access**
 

docs/resources/aws-requirements.md

@@ -10,11 +10,9 @@ pagination_next: null
 
 # AWS account requirements
 
-Prepare your AWS account:
-
 - Work with your cloud admin to ensure you have the [IAM](https://aws.amazon.com/iam/) permissions you need to create the cloud resources defined in your choice of [AI Unlimited template](https://github.com/Teradata/ai-unlimited/tree/develop/deployments/aws/templates/ai-unlimited).
 
-- If you'll need to access the manager instance, after it is installed, to run commands or debug, you can connect to it one of these ways:
+- If you'll need to access the manager instance to run commands or debug, you can connect to it one of these ways:
 	- Use a [key pair](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-key-pairs.html) that you generate to securely connect using Secure Shell (SSH). You will need the key pair when you [specify the stack details](/docs/install-ai-unlimited/prod-aws-console-deploy-ai-unlimited.md#aws-parms).
 	- Use AWS Session Manager to connect. To enable this, attach the [session-manager.json](https://github.com/Teradata/ai-unlimited/blob/develop/deployments/aws/policies/session-manager.json) policy to a [role you provide](#provide-roles) to the manager.
 
@@ -29,7 +27,7 @@ The manager needs a role that allows it to deploy the engine. The engine needs a
 
 **Role for the manager**
 
-To let Unlimited create this role for you, when you [specify the stack details](/docs/install-ai-unlimited/prod-aws-console-deploy-ai-unlimited.md#aws-parms), provide these values for these parameters:
+To let AI Unlimited create this role for you, when you [specify the stack details](/docs/install-ai-unlimited/prod-aws-console-deploy-ai-unlimited.md#aws-parms), provide these values for these parameters:
     - `IamRole`: **New**
     - `IamRoleName`: leave blank
 

docs/resources/jupyterlab/install-jupyterlab-aws.md

@@ -38,7 +38,7 @@ References to the AWS Management Console are accurate as of April 11, 2024.
 
 CloudFormation templates for JupyterLab are here in the AI Unlimited GitHub repository you cloned:
 
-`/deployments/aws/templates/jupyter/`
+`deployments/aws/templates/jupyter/`
 
 1. Choose a template based on whether you intend to use a [load balancer](/docs/glossary.md#glo-load-balancer) and what type.
 

docs/resources/jupyterlab/install-jupyterlab-azure.md

@@ -38,7 +38,7 @@ References to the Azure Portal are accurate as of April 14, 2024.
 
 ## Download the Jupyter template
 
-Download the template (`/deployments/azure/jupyter.json`) from the AI Unlimited GitHub repository you cloned.
+Download the template (`deployments/azure/jupyter.json`) from the AI Unlimited GitHub repository you cloned.
 
 ## Load the template
 

docs/resources/jupyterlab/run-jupyterlab-docker.md

@@ -31,14 +31,16 @@ Learn about [AWS](https://docs.aws.amazon.com/sdkref/latest/guide/environment-va
 
 ## Start JupyterLab
 
-1. Go to the directory where `jupyter.yaml` is located, and start JupyterLab.
+1. Download the [jupyter.yaml](https://github.com/Teradata/ai-unlimited/blob/develop/deployments/docker/jupyter.yaml) file.
+
+2. Go to the directory where `jupyter.yaml` is located, and start JupyterLab.
 
 	```bash title="Run the Docker Compose file in the background "
 	docker compose -f jupyter.yaml -d up 
 	```
 	The command downloads and starts the JupyterLab container.
 
-2. To retrieve the Jupyter token, list the currently running containers.
+3. To retrieve the Jupyter token, list the currently running containers.
 
 	```bash
 	docker ps 

docs/resources/quickstart/docker-install-ai-unlimited-jupyter.md

@@ -68,12 +68,14 @@ This QuickStart uses the first method.
 		</TabItem>
 	</Tabs>
 
-2. In the [Teradata AI Unlimited GitHub repository](https://github.com/Teradata/ai-unlimited), open the `[AWS or Azure]-credentials-env-vars.yaml` file and update the environment variable values.
+2. In the [Teradata AI Unlimited GitHub repository](https://github.com/Teradata/ai-unlimited/tree/develop/deployments/docker), open the `[AWS or Azure]-credentials-env-vars.yaml` file and update the environment variable values.
 
 
 ## Start the manager and JupyterLab
 
-1. Go to the directory where `ai-unlimited.yaml` and `jupyter.yaml` are located, and start the manager and JupyterLab.
+1. Download the [ai-unlimited.yaml](https://github.com/Teradata/ai-unlimited/blob/develop/deployments/docker/ai-unlimited.yaml) and [jupyter.yaml](https://github.com/Teradata/ai-unlimited/blob/develop/deployments/docker/jupyter.yaml) files.
+
+2. Go to the directory where `ai-unlimited.yaml` and `jupyter.yaml` are located, and start the manager and JupyterLab.
 
 	<Tabs>
 		<TabItem value="aws" label="AWS" default>
@@ -90,7 +92,7 @@ This QuickStart uses the first method.
 
 	The command downloads and starts the manager and JupyterLab containers.
 
-2. To retrieve the Jupyter token, list the currently running containers.
+3. To retrieve the Jupyter token, list the currently running containers.
 
 	```bash
 	docker ps