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The solution that meets the requirements with the least operational overhead is to create a **Regional AWS WAF web ACL with a rate-based rule** and associate the web ACL with the API Gateway stage. This solution will protect the application from HTTP flood attacks by monitoring incoming requests and blocking requests from IP addresses that exceed the predefined rate. Amazon CloudFront distribution with Lambda@Edge in front of the API Gateway Regional API endpoint is also a good solution but it requires more operational overhead than the previous solution. Using Amazon CloudWatch metrics to monitor the Count metric and alerting the security team when the predefined rate is reached is not a solution that can protect against HTTP flood attacks. Creating an Amazon CloudFront distribution in front of the API Gateway Regional API endpoint with a maximum TTL of 24 hours is not a solution that can protect against HTTP flood attacks.

The data retention period of a Kinesis data stream is the time period from when a record is added to when it is no longer accessible1. The default retention period for a Kinesis data stream is 24 hours, which can be extended up to 8760 hours (365 days)1. The data retention period can be updated by using the AWS Management Console, the AWS CLI, or the Kinesis Data Streams API1.

To meet the requirements of the scenario, the solutions architect should update the Kinesis Data Streams default settings by modifying the data retention period. The solutions architect should increase the retention period to a value that is greater than or equal to the frequency of consuming the data and writing it to S32. This way, the company can ensure that S3 receives all the data that the application sends to Kinesis Data Streams.

Configure provisioned concurrency for the Lambda function that handles the requests. Provisioned concurrency allows you to set the amount of compute resources that are available to the Lambda function, so that it can handle more requests at once and reduce latency. Caching the results of the queries in Amazon S3 could also help to reduce latency, but it would not be as effective as setting up provisioned concurrency. Increasing the size of the database would not help to reduce latency, as this would not increase the number of connections the Lambda function could establish, and establishing a direct connection between the frontend application and the database would bypass the API, which would not be the best solution either.

Using AWS Lambda with Amazon API Gateway - AWS Lambda

https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway.html

AWS Lambda FAQs

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This option is the most efficient because it uses AWS Key Management Service (AWS KMS), which is a service that makes it easy for you to create and manage cryptographic keys and control their use across a wide range of AWS services and with your applications running on AWS1. It also uses AWS KMS to encrypt the EBS volumes and Aurora database storage at rest, which provides data protection by encrypting your data with encryption keys that you manage23. It also uses AWS Certificate Manager (ACM), which is a service that lets you easily provision, manage, and deploy public and private Secure Sockets Layer/Transport Layer Security (SSL/TLS) certificates for use with AWS services and your internal connected resources. It also attaches an ACM certificate to the ALB to encrypt data in transit, which provides data protection by enabling SSL/TLS encryption for connections between clients and the load balancer. This solution meets the requirement of encrypting all data for the application at rest and in transit. Option A is less efficient because it uses AWS KMS certificates on the ALB to encrypt data in transit, which is not possible as AWS KMS does not provide certificates but only keys. It also uses AWS Certificate Manager (ACM) to encrypt the EBS volumes and Aurora database storage at rest, which is not possible as ACM does not provide encryption but only certificates. Option B is less efficient because it uses the AWS root account to log in to the AWS Management Console, which is not recommended as it has unrestricted access to all resources in your account. It also uploads the company’s encryption certificates, which is not necessary as ACM can provide certificates for free. It also selects the option to turn on encryption for all data at rest and in transit for the account, which is not possible as encryption settings are specific to each service and resource. Option D is less efficient because it uses BitLocker to encrypt all data at rest, which is a Windows feature that provides encryption for volumes on Windows servers. However, this does not provide encryption for Aurora database storage at rest, as Aurora runs on Linux servers. It also imports the company’s TLS certificate keys to AWS KMS, which is not necessary as ACM can provide certificates for free. It also attaches the KMS keys to the ALB to encrypt data in transit, which is not possible as ALB requires certificates and not keys.