Amazon Web Services Updated SAP-C02 Exam Questions and Answers by amirah

Enable DynamoDB Auto Scaling:

Navigate to the DynamoDB console and select the table experiencing high demand.

Go to the "Capacity" tab and enable auto scaling for both read and write capacity units. Auto scaling adjusts the provisioned throughput capacity automatically in response to actual traffic patterns, ensuring the table can handle the increased load.

Configure Auto Scaling Policies:

Set the minimum and maximum capacity units to define the range within which auto scaling can adjust the provisioned throughput.

Specify target utilization percentages for read and write operations, typically around 70%, to maintain a balance between performance and cost.

Monitor and Adjust:

Use Amazon CloudWatch to monitor the auto scaling activity and ensure it is effectively handling the increased demand.

Adjust the auto scaling settings if necessary to better match the traffic patterns and application requirements.

By enabling DynamoDB auto scaling, you ensure that the database can handle the fluctuating traffic volumes without manual intervention, improving response times and reducing errors.

References

AWS Compute Blog on Using API Gateway as a Proxy for DynamoDB【60】.

AWS Database Blog on DynamoDB Accelerator (DAX)【59】.

The CAPABILITY_NAMED_IAM capability is required when creating or updating CloudFormation stacks that contain IAM resources with custom names. This capability acknowledges that the template might create IAM resources that have broad permissions or affect other resources in the AWS account. The stack set’s template contains an IAM role that has a custom name, so this capability is needed. Enabling the new Regions in all relevant accounts is also necessary to deploy the stack set across multiple Regions and accounts.

Option B is incorrect because the Service Quotas console is used to view and manage the quotas for AWS services, not for CloudFormation stacks. The number of stacks per Region per account is not a service quota that can be increased.

Option C is incorrect because the SELF_MANAGED permissions model is used when the administrator wants to retain full permissions to manage stack sets and stack instances. This model does not affect the creation of the stack set or the requirement for the CAPABILITY_NAMED_IAM capability.

Option D is incorrect because an administration role ARN is optional when creating a stack set. It is used to specify a role that CloudFormation assumes to create stack instances in the target accounts. It does not affect the creation of the stack set or the requirement for the CAPABILITY_NAMED_IAM capability.

References:

1: AWS CloudFormation stack sets

2: Acknowledging IAM resources in AWS CloudFormation templates

3: AWS CloudFormation stack set permissions

Store the PGP Private Key:

Step 1: In the AWS Management Console, navigate to AWS Secrets Manager.

Step 2: Store the PGP private key in Secrets Manager. Ensure the key is encrypted and properly secured.

Set Up the Transfer Family Managed Workflow:

Step 1: In the AWS Transfer Family console, create a new managed workflow.

Step 2: Add a nominal step to the workflow that includes the decryption of the files. Configure this step with the PGP decryption parameters, referencing the PGP private key stored in Secrets Manager.

Step 3: Associate this workflow with the Transfer Family SFTP server, ensuring that incoming files are automatically decrypted upon receipt.

This solution ensures that the data is securely decrypted as it is transferred from the SFTP server to the S3 bucket, automating the decryption process and leveraging AWS Secrets Manager for key management.

References

AWS Transfer Family Documentation

Using AWS Secrets Manager for Managing Secrets

AWS Transfer Family Managed Workflows

The correct answer is D. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSQL Multi-AZ DB cluster. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event. Fail over to the larger Aurora Replica. Create another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event.

This solution will meet the requirements of maximizing availability during the sale events. A scheduled scaling policy for the EC2 instances will allow the application to scale up and down according to the predefined schedule of the sale events. Hosting the database on an Amazon Aurora PostgreSQL Multi-AZ DB cluster will provide high availability and durability, as well as compatibility with PostgreSQL. Creating an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event will ensure that the database can handle the increased read traffic during the peak periods. Failing over to the larger Aurora Replica will make it the primary instance, which will also improve the write performance of the database. Creating another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event will reduce the cost and resources of the database.