Free Amazon Web Services SAP-C02 Practice Exam with Questions & Answers | Set: 12

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 company should configure a cross-Region read replica for the RDS database in the new Region. The company should change the Route 53 record to latency-based routing to connect to the API Gateway API. This solution will meet the requirements because a cross-Region read replica is a feature that enables you to create a MariaDB, MySQL, Oracle, PostgreSQL, or SQL Server read replica in a different Region from the source DB instance. You can use cross-Region read replicas to improve availability and disaster recovery, scale out globally, or migrate an existing database to a new Region1. By creating a cross-Region read replica for the RDS database in the new Region, the company can have a standby copy of its primary database that can serve read-only traffic from users in Europe. A latency-based routing policy is a feature that enables you to route traffic based on the latency between your users and your resources. You can use latency-based routing to route traffic to the resource that provides the best latency2. By changing the Route 53 record to latency-based routing, the company can minimize latency for users who download reports by connecting them to the API Gateway API in the Region that provides the best response time.

The other options are not correct because:

Using AWS Database Migration Service (AWS DMS) to replicate the primary database in the original Region to the database in the new Region would not be as cost-effective or simple as using a cross-Region read replica. AWS DMS is a service that enables you to migrate relational databases, data warehouses, NoSQL databases, and other types of data stores. You can use AWS DMS to perform one-time migrations or continuous data replication with high availability and consolidate databases intoa petabyte-scale data warehouse3. However, AWS DMS requires more configuration and management than creating a cross-Region read replica, which is fully managed by Amazon RDS. AWS DMS also incurs additional charges for replication instances and tasks.

Creating an Amazon API Gateway Data API service integration with Amazon Redshift would not help with disaster recovery or minimizing latency. The Data API is a feature that enables you to query your Amazon Redshift cluster using HTTP requests, without needing a persistent connection or a SQL client. It is useful forbuilding applications that interact with Amazon Redshift, but not for replicating or recovering data from an RDS database.

Creating an AWS Data Exchange datashare by connecting AWS Data Exchange to the Redshift cluster would not help with disaster recovery or minimizing latency. AWS Data Exchange is a service that makes it easy for AWS customers to exchange data in the cloud. You can use AWS Data Exchange to subscribe to a diverse selection of third-party data products or offer your own data products to other AWS customers. A datashare is a feature that enables you to share live and secure access to your Amazon Redshift data across your accounts or with third parties without copying or moving the underlying data. It is useful for sharing query results and views with other users, but not for replicating or recovering data from an RDS database.

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/DownloadDistS3AndCustomOrigins.html

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/high_availability_origin_failover.html

You can set up CloudFront with origin failover for scenarios that require high availability. To get started, you create an origin group with two origins: a primary and a secondary. If the primary origin is unavailable, or returns specific HTTP response status codes that indicate a failure, CloudFront automatically switches to the secondary origin.

Comprehensive and Detailed Explanation:

A. Using AWS CloudFormation templates allows for the automation of infrastructure deployment. By parameterizing the templates, resources can be provisioned consistently across multiple Regions, reducing administrative overhead and ensuring infrastructure as code practices.

D. Amazon Route 53 latency-based routing directs user requests to the AWS Region that provides the lowest latency, improving access times for users globally and enhancing the user experience.

E. Enabling DynamoDB Streams and adding a second Region to create a global table ensures that data is replicated across Regions, providing high availability and disaster recovery capabilities.

This combination of steps ensures that the application stack is replicated efficiently across Regions, providing disaster recovery, improved performance, and scalability, all while minimizing manual administrative tasks.

(Store the uploaded images in an S3 bucket and use S3 event notification with SQS queue) is the most suitable design. Amazon S3 provides highly scalable and durable storage for theuploaded images. Configuring S3 event notifications to send messages to an SQS queue allows for decoupling the processing of images from the upload process. A fleet of EC2 instances can pull messages from the SQS queue to process the images and store them in another S3 bucket. Scaling out the EC2 instances based on SQS queue depth using CloudWatch metrics ensures efficient utilization of resources. Enabling Amazon CloudFront with the origin set to the S3 bucket containing the processed images improves the global availability and performance of image delivery.

Comprehensive and Detailed Explanation:

Option C is the most comprehensive and aligns with AWS best practices for cost optimization without compromising availability or performance:

AWS Compute Optimizer provides recommendations to rightsize EC2 instances, EBS volumes, and Lambda functions based on utilization metrics. By opting in, the company can receive tailored suggestions for optimizing resource configurations.

AWS Trusted Advisor offers cost optimization checks, including identifying idle or underutilized resources, which can be rightsized or terminated to reduce costs.

Implementing recommendations from Compute Optimizer and Trusted Advisor ensures that resources are appropriately sized, leading to cost savings without affecting performance.

Auto Scaling groups help maintain application availability and allow automatic scaling of EC2 instances based on demand, ensuring that compute capacity aligns with workload requirements.

Compute Savings Plans provide flexible pricing for EC2, AWS Lambda, and AWS Fargate usage, offering significant savings over On-Demand pricing in exchange for a commitment to a consistent amount of usage.

This approach ensures cost optimization while maintaining the necessary compute capacity and availability for production workloads.

Option A, Deploy the security tool on EC2 instances in a new Auto Scaling group in the existing VPC, allows the company to use its existing security tool while still running it within the AWS environment. This ensures that all packets coming in and out of the VPC are inspected by the security tool in real time. Option D, Provision a Gateway Load Balancer for each Availability Zone to redirect the traffic to the security tool, allows for high availability within an AWS Region. By provisioning a Gateway Load Balancer for each Availability Zone, the traffic is redirected to the security tool in the event of any failures or outages. This ensures that the security tool is always available to inspect the traffic, even in the event of a failure.

migrating the data processing script to an AWS Lambda function and using an S3 event notification to invoke the Lambda function to process the objects when the company uploads the objects. This solution meets the company ' s requirements of high availability and scalability, as well as reducing long-term management overhead, and is likely to be the most cost-effective option.

CORS errors occur when a web page hosted on one domain tries to make a request to a server hosted on another domain. In this scenario, the registration form hosted on the static website is trying to make a request to the API Gateway API endpoint hosted on a different domain, which is causing the error. To resolve this error, the Access-Control-Allow-Origin header needs to be set to the domain from which the request is being made. In this case, the header is already set to www.example.com on the CloudFront distribution origin. Therefore, the solutions architect should enable the CORS setting on the API Gateway API endpoint and ensure that the API endpoint is configured to return all responses that have the Access-Control-Allow-Origin header set to www.example.com. This will allow the API endpoint to respond to requests from the static website without a CORS error.

https://aws.amazon.com/premiumsupport/knowledge-center/api-gateway-cors-errors/

This explanation is based on AWS documentation and best practices but is paraphrased, not a literal extract.

The current CI/CD pipeline uses an IAM user with long-lived access keys stored in GitHub Actions. The new requirement is that pipelines must not use long-lived secret keys. Instead, the solution should provide short-lived credentials with minimal operational overhead.

GitHub Actions natively supports integration with cloud providers using OpenID Connect (OIDC). With OIDC, GitHub acts as an identity provider that can issue OIDC tokens to workflows. On the AWS side, IAM supports configuring an OIDC identity provider and roles that can be assumed by principals presenting valid OIDC tokens through the sts:AssumeRoleWithWebIdentity API. This pattern enables short-lived, automatically rotated credentials for CI/CD jobs without storing long-lived secrets.

In the correct solution (option B), you configure an IAM OIDC identity provider for GitHub in the AWS account. You then create a new IAM role with a trust policy that allows the Github OIDC provider to call sts:AssumeRoleWithWebIdentity, with conditions that restrict which repositories or workflows can assume the role. The existing IAM policy that grants deployment permissions is attached to that role. In GitHub Actions, you update the pipeline configuration to request an OIDC token and assume the IAM role at runtime. Each workflow run receives short-lived credentials without storing static keys, and AWS automatically handles the token verification and temporary credential issuance. This approach is the AWS-recommended pattern for integrating GitHub Actions with AWS without long-lived secrets and has low operational overhead once configured.

Option A uses SAML 2.0, which is typically used for enterprise single sign-on for users, not for GitHub Actions workflows. GitHub does not natively use SAML to obtain AWS credentials for CI/CD pipelines in the same streamlined way as OIDC, and implementing a SAML-based integration would add unnecessary complexity.

Option C introduces Amazon Cognito as an indirection layer. Although Cognito can federate with external identity providers, including social providers, using it as an intermediary to obtain temporary AWS credentials for a machine-to-machine CI/CD pipeline is not necessary when IAM OIDC federation with GitHub is directly supported. This adds additional configuration and operational overhead.

Option D uses IAM Roles Anywhere with client certificates from AWS Private CA. Roles Anywhere is designed for workloads running outside AWS that need to assume IAM roles using X.509 certificates instead of access keys. While technically possible, it requires managing private certificates, trust anchors, and a credential helper tool, which is more complex and operationally heavier than the direct OIDC integration specifically designed for GitHub Actions.

Therefore, configuring an IAM OIDC identity provider for GitHub and creating an IAM role to be assumed via sts:AssumeRoleWithWebIdentity (option B) meets the requirement to replace long-lived secret keys with short-lived credentials with the least operational overhead.

Using Amazon API Gateway with an SQS queue ensures all data sent to the API is durably stored for processing, even during traffic surges.

API Gateway service integration with SQS provides a managed, serverless ingestion layer that absorbs unpredictable traffic bursts without data loss.

The AWS Lambda function processes messages from SQS, providing scalable, on-demand compute to handle environmental data efficiently.

This solution aligns with AWS best practices for building resilient, serverless, event-driven architectures that can handle high-volume, bursty workloads.

AWS DMS can migrate data from a source database to a target database in AWS, using change data capture (CDC) to replicate ongoing changes and keep the databases in sync. Setting Amazon S3 as a target allows storing the migrated data in a durable and cost-effective storage service. When the source and destination are fully synchronized, the data can be loaded from Amazon S3 into an Amazon RDS for Microsoft SQL Server DB instance, which is a managed database service that simplifies database administration tasks. References:

https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.SQLServer.html

https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Target.S3.html

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_SQLServer.html

AWS Backup is a fully managed service that makes it easy to centralize and automate the creation, retention, and restoration of backups across AWS services. It provides a way to schedule automatic backups for CodeCommit repositories on an hourly basis. Additionally, it also supports cross-Region replication, which allows you to copy the backups to a second Region for disaster recovery.

By using AWS Backup, the company can set up an automatic and regular backup schedule for the CodeCommit repository, ensuring that the data is regularly backed up and stored in a second Region. This can provide a way to recover quickly from any disaster event that might occur.

The company wants backups to be stored in an isolated central account designed for WORM storage. With AWS Organizations, AWS Backup supports centralized, cross-account backup management through delegated administration, backup policies, and cross-account backup vault usage. This provides the least operational overhead and scales to dozens of databases.

A key constraint is encryption. The databases are encrypted with the default RDS AWS KMS key. AWS-managed KMS keys (including the default RDS KMS key) are not customer-managed and generally cannot be shared across accounts for cross-account snapshot copy and cross-account backup workflows that require key sharing and explicit grants. For cross-account backup copies, the source backups must be encrypted with a customer managed KMS key that can be shared (via key policy and grants) with the destination account. Therefore, the company must move away from using the default RDS AWS-managed key for encryption of snapshots that will be copied across accounts.

Option A uses the correct managed approach: enable trusted access and backup policies in Organizations, make the central account the delegated administrator, and use AWS Backup to manage cross-account backups into a central backup vault. It also correctly introduces a customer managed KMS key in the central account for the backup vault and shares that key with the production account. Because the existing databases are encrypted with the default RDS AWS-managed key, option A includes the necessary remediation step: restore (or otherwise recreate) the databases so they are encrypted with the shared customer managed KMS key, enabling future backups and copies to be encrypted with a shareable key and stored in the central vault.

Option B is not workable because it requires “sharing the default RDS KMS key” with another account and using it for the central vault. AWS-managed keys are not shared and are not controlled by customers in a way that supports this cross-account backup model. Therefore, this option fails the encryption requirement.

Option C and option D rely on decrypting snapshots, copying them as unencrypted, and then re-encrypting. This is not a valid or safe operational pattern for RDS automated backups at scale, and it conflicts with typical constraints around snapshot encryption transitions. It also introduces substantial custom automation and operational overhead, and it undermines the objective of a controlled WORM backup account by manipulating encryption state through custom code. Additionally, “decrypting snapshots” is not how encrypted RDS snapshots are typically handled; encrypted snapshots remain encrypted and are copied re-encrypted with a different KMS key that the destination can use, which requires a customer managed key and proper permissions.

Therefore, the successful and scalable solution is to centralize backups with AWS Backup and ensure the databases are encrypted with a customer managed KMS key that can be shared cross-account, as described in option A.