Automating AWS VPC and Account Creation with GitHub and AWS CodePipeline

Goal

Automate the process of creating an AWS VPC or AWS account to ensure efficiency, reduce manual configuration errors, and maintain consistency across deployments. This automation will streamline infrastructure provisioning, improve collaboration through version control, and accelerate development and operations.

Scenario

NovaTech, a large enterprise with a rapidly growing cloud infrastructure needs to automate the creation of AWS resources, such as VPCs and AWS accounts. The existing manual process is time-consuming, prone to errors, and difficult to track. The IT Operations team aims to leverage GitHub for version control, Terraform for Infrastructure as Code (IaC), and AWS CodePipeline for automating deployments.

By implementing this Symphony AI Service Automation, the company can efficiently provision AWS infrastructure, maintain compliance, and streamline the approval and deployment processes across multiple environments.

Solution

By utilizing Service Automation to automate AWS account creation and VPC management, organizations can build a more reliable, secure, and efficient cloud infrastructure. This allows IT teams to focus on strategic initiatives rather than routine network configuration tasks. The process includes validating the successful creation and proper configuration of AWS accounts and VPCs, as well as establishing monitoring for ongoing management.

Automating AWS account creation streamlines the provisioning of new environments while ensuring adherence to organizational policies. Additionally, defining and deploying Virtual Private Clouds with Terraform guarantees a standardized, secure, and scalable network architecture.

Here's an exciting sneak peek into the automation of AWS VPC and Account Creation with GitHub and AWS CodePipeline flow!

For an in-depth understanding of Automating AWS VPC and Account Creation with GitHub and AWS CodePipeline process with SymphonyAI Service Automation refer the below segment:

Step 1: Pull the Latest Changes from the Main Repository and Create a New Branch

Goal: Ensure the working environment is up to date with the latest changes from the main branch to prevent conflicts.

Solution:

1. Use Git commands to pull the latest updates from the main repository.

2. Create a new branch for making and testing changes.

Step 2: Modify the Terraform File with Necessary Configurations and Commit the Changes

Goal: Use Terraform to define and configure AWS resources, specifying all necessary details for either VPC or AWS account creation.

Solution:

1. Open the Terraform file (.tf).

2. For AWS VPC: Define resources such as VPCs, subnets, route tables, and internet gateways.

   Note

   Before proceeding with the VPC creation, verify the existence of the AWS Account. This will help prevent errors arising from misconfigured or non-existent accounts.

3. For AWS Account Creation: Specify the account name, email, and Organizational Unit (OU) for organizational placement.

4. Save and commit the changes in the new branch.

Step 3: Push the Branch, Create a Pull Request (PR), and Monitor It

Goal: Push the changes to the remote repository and initiate a code review.

Solution:

1. Push the branch to GitHub.

2. Create a Pull Request (PR) and request a review from team members.

3. Monitor the PR for comments, address feedback, and wait for approval.

Step 4: Validate Whether the AWS Account or VPC Is Created

Goal: Ensure the successful creation of AWS resources.

Solution:

1. Use the AWS Management Console or AWS CLI to confirm that the AWS VPC or AWS account has been created correctly.

2. Check for the presence of all specified configurations and validate functionality.

Step 5: Send Notification and Close the Request

Goal: Inform stakeholders of the successful completion and close the request.

Solution:

1. Configure an email notification system (e.g., AWS Simple Email Service - SES) to notify stakeholders.

2. Send an automated email with the status update, including resource details.

3. Mark the service request as complete and close it in the tracking system.

Note

Automation Triggers: The process can be initiated through updates on GitHub or configured to run automatically via AWS CodePipeline.

Manual Steps: If any manual validation or configuration is required, create follow-up tasks for team members to address.

This automated approach ensures a streamlined, consistent, and error-free process for provisioning AWS resources.