https://aws.amazon.com/blogs/mt/monitor-changes-and-auto-enable-logging-in-aws-cloudtrail/

The correct answer is D. Creating an AWS Config conformance pack that contains the AWS Config rules and remediation actions and deploying it from the delegated administrator account by using AWS Config will meet the requirements. A conformance pack is a collection of AWS Config rules and remediation actions that can be easily deployed as a single entity in an account and a region or across an organization in AWS Organizations1. By using the delegated administrator account, the DevOps engineer can centrally manage the conformance pack and prevent non-administrator users from modifying it in the member accounts. Option A is incorrect because creating a CloudFormation template that contains the AWS Config rules and remediation actions and deploying it from the Organizations management account by using CloudFormation StackSets will not prevent non-administrator users from modifying the AWS Config rules in the member accounts. Option B is incorrect because deploying the conformance pack from the Organizations management account by using CloudFormation StackSets will not use the trusted access feature of AWS Config and will require additional permissions and resources. Option C is incorrect because creating a CloudFormation template that contains the AWS Config rules and remediation actions and deploying it from the delegated administrator account by using AWS Config will not leverage the benefits of conformance packs, such as simplified deployment and management. Reference:
Conformance Packs - AWS Config
Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 176)

These solutions will meet the requirement because they will prevent the loss of notification messages in the future. An Amazon SQS queue is a service that provides a reliable, scalable, and secure message queue for asynchronous communication between distributed components. You can use an SQS queue to buffer messages from an SNS topic and ensure that they are delivered and processed by a Lambda function, even if the function or the database is temporarily unavailable.
Option C will configure an SQS dead-letter queue for the SNS topic. A dead-letter queue is a queue that receives messages that could not be delivered to any subscriber after a specified number of retries. You can use a dead-letter queue to store and analyze failed messages, or to reprocess them later. This way, you can avoid losing messages that could not be delivered to the Lambda function due to network errors, throttling, or other issues.
Option D will subscribe an SQS queue to the SNS topic and configure the Lambda function to process messages from the SQS queue. This will decouple the SNS topic from the Lambda function and provide more flexibility and control over the message delivery and processing. You can use an SQS queue to store messages from the SNS topic until they are ready to be processed by the Lambda function, and also to retry processing in case of failures. This way, you can avoid losing messages that could not be processed by the Lambda function due to database errors, timeouts, or other issues.

B and E
Short To meet the requirements of failover and disaster recovery, the company should use the following deployment strategies:
Create an Amazon Aurora global database in two AWS Regions as the data store. In the event of a failure, promote the secondary Region to the primary for the application. Update the application to use the Aurora cluster endpoint in the secondary Region. This strategy can provide a low RPO and RTO for the data, as Aurora global database replicates data with minimal latency across Regions and allows fast and easy failover12. The company can use the Amazon Aurora cluster endpoint to connect to the current primary DB cluster without needing to change any application code1.
Set up the application in two AWS Regions. Configure AWS Global Accelerator to point to Application Load Balancers (ALBs) in both Regions. Add both ALBs to a single endpoint group. Use health checks and Auto Scaling groups in each Region. This strategy can provide high availability and performance for the application, as AWS Global Accelerator uses the AWS global network to route traffic to the closest healthy endpoint3. The company can also use static IP addresses that are assigned by Global Accelerator as a fixed entry point for their application1. By using health checks and Auto Scaling groups, the company can ensure that their application can scale up or down based on demand and handle any instance failures4.
The other options are incorrect because:
Creating an Amazon Aurora Single-AZ cluster in multiple AWS Regions as the data store would not provide a fast failover or disaster recovery solution, as the company would need to manually restore data from backups or snapshots in another Region in case of a failure.
Creating an Amazon Aurora cluster in multiple AWS Regions as the data store and using a Network Load Balancer to balance the database traffic in different Regions would not work, as Network Load Balancers do not support cross-Region routing. Moreover, this strategy would not provide a consistent view of the data across Regions, as Aurora clusters do not replicate data automatically between Regions unless they are part of a global database.
Setting up the application in two AWS Regions and using Amazon Route 53 failover routing that points to Application Load Balancers in both Regions would not provide a low RTO, as Route 53 failover routing relies on DNS resolution, which can take time to propagate changes across different DNS servers and clients. Moreover, this strategy would not provide deterministic routing, as Route 53 failover routing depends on DNS caching behavior, which can vary depending on different factors.

B) Update the CodeBuild project role with the necessary permissions and then remove the AWS credentials from the environment variable. C. Store the DB_PASSWORD as a SecureString value in AWS Systems Manager Parameter Store and then remove the DB_PASSWORD from the environment variables. E. Use AWS Systems Manager run command versus scp and ssh commands directly to the instance.