AWS Organizations is a service that helps to manage multiple AWS accounts. AWS Control Tower is a service that makes it easy to set up and govern secure, compliant multi-account AWS environments. Account Factory for Terraform (AFT) is an AWS Control Tower feature that provisions new accounts using Terraformtemplates. To provision new accounts with the Enterprise Support plan, the DevOps engineer can set the aft_feature_enterprise_support feature flag to True in the AFT deployment input configuration. This flag enables the Enterprise Support plan for newly provisioned accounts.
https://docs.aws.amazon.com/controltower/latest/userguide/aft-feature-options.html

The Auto Scaling group service-linked role must have a specific grant in the source account in order to decrypt the encrypted AMI. This is because the service-linked role does not have permissions to assume the default IAM role in the source account.
The following steps are required to meet the requirements:
In the source account, copy the unencrypted AMI to an encrypted AMI. Specify the KMS key in the copy action.
In the source account, create a KMS grant that delegates permissions to the Auto Scaling group service-linked role in the target account.
In the source account, share the encrypted AMI with the target account.
In the target account, attach the KMS grant to the Auto Scaling group service-linked role.
The first three steps are the same as the steps that I described earlier. The fourth step is required to grant the Auto Scaling group service-linked role permissions to decrypt the AMI in the target account.

Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer documents only:
Use CodePipeline with a Git source to orchestrate the flow, CodeBuild to produce versioned artifacts in S3, and CodeDeploy to EC2 with lifecycle hooks (e.g., BeforeInstall) to run cache-clearing and unpack steps.
This gives end-to-end visibility, rollbacks, and standardized deployments.

Creating an AWS CodeCommit repository for each project, using the main branch for production code, and creating a testing branch for code deployed to testing will meet the requirements. AWS CodeCommit is a managed revision control service that hosts Git repositories and works with all Git-based tools1. By using feature branches to develop new features and pull requests to merge code to testing and main branches, the developers can avoid code conflicts and lost work, and also implement code reviews and approvals. Option B is incorrect because creating another S3 bucket for each project for testing code and using an AWS Lambda function to promote code changes between testing and production buckets will not provide the benefits of revision control, such as tracking changes, branching, merging, and collaborating. Option C is incorrect because using the main branch for production and test code with different deployment pipelines for each environment will not allow the developers to test their code changes before deploying them to production.
Option D is incorrect because enabling versioning and branching on each S3 bucket will not work with Git- based tools and will not provide the same level of revision control as AWS CodeCommit. References:
AWS CodeCommit
Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 182)

https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.
html#LambdaFunctionExample
https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html