SAP-C02 Exam Dumps - Amazon Web Services AWS Certified Professional Questions and Answers

Utilizing an IP access control group rule with the list of public addresses from branch offices and associating it with the Amazon WorkSpaces directory is the most operationally efficient solution. This method ensures that access to WorkSpaces is restricted to specified locations, aligning with the corporate security policy. This approach offers simplicity and flexibility, especially with the potential addition of a new branch office, as updating the IP access control group is straightforward.

AWS Documentation on Amazon WorkSpaces and IP Access Control Groups provides detailed instructions on how to implement access restrictions based on IP addresses. This solution aligns with best practices for securing virtual desktops while maintaining operational efficiency.

Provision an Aurora Replica in a different Region will meet the requirement of the application being able to recover to a separate AWS Region in the event of an application failure, and no data can be lost, with the least amount of operational overhead.

A. In the production account, create a new IAM policy that allows read and write access to the S3 bucket. The policy grants the necessary permissions to access the assets in the production S3 bucket.

C. In the production account, create a role. Attach the new policy to the role. Define the development account as a trusted entity. By creating a role and attaching the policy, and then defining the development account as a trusted entity, the development account can assume the role and access the production S3 bucket with the read and write permissions.

E. In the development account, create a group that contains all the IAM users of the design team. Attach a different IAM policy to the group to allow the sts:AssumeRole action on the role in the production account. The IAM policy attached to the group allows the design team members to assume the role created in the production account, thereby giving them access to the production S3 bucket.

Step 1: Create a role in the Production Account; create the role in the Production account and specify the Development account as a trusted entity. You also limit the role permissions to only read and write access to the productionapp bucket. Anyone granted permission to use the role can read and write to the productionapp bucket. Step 2: Grant access to the role Sign in as an administrator in the Development account and allow the AssumeRole action on the UpdateApp role in the Production account. So, recap, production account you create the policy for S3, and you set development account as a trusted entity. Then on the development account you allow the sts:assumeRole action on the role in production account.https://docs.aws.amazon.com/IAM/latest/UserGuide/tutorial_cross-account-with-roles.html

There are three core requirements: reduce/manage active database connections, keep communication private without internet exposure, and scale to many consumer accounts over time.

To manage and pool database connections to an Amazon RDS for PostgreSQL DB instance, the AWS-managed service designed for this purpose is Amazon RDS Proxy. RDS Proxy maintains a pool of database connections and multiplexes application connections onto fewer database connections. This reduces connection overhead on the database, improves resiliency during failovers, and helps control the number of active connections that reach the DB instance.

Next, the connectivity must be private across accounts and scalable as more consumer accounts are added. AWS PrivateLink provides scalable, private connectivity between VPCs and services across accounts without requiring VPC peering, transitive routing, or exposing traffic to the public internet. With PrivateLink, the database account can publish an endpoint service backed by a Network Load Balancer, and consumer accounts create interface endpoints in their VPCs to connect privately to that service. This is operationally scalable because adding new consumer accounts does not require managing a growing mesh of VPC peering relationships or complex route propagation; each consumer adds an interface endpoint.

Option B is the only option that addresses connection management by introducing RDS Proxy and uses PrivateLink to provide private, cross-account, scalable connectivity. The proxy endpoint being in private subnets aligns with the requirement that traffic stays private.

Option A is incorrect because a NAT gateway in a public subnet is used for outbound internet access from private subnets. It is not needed for private cross-account database access and introduces unnecessary public subnet components. Also, NAT gateways do not manage database connections. Transit gateway can provide private connectivity, but it does not address connection pooling, and the NAT gateway component is not appropriate for the stated requirement of avoiding internet exposure.

Option C is incorrect because an Application Load Balancer is not used to proxy raw PostgreSQL database traffic. PostgreSQL uses TCP, and ALB is primarily for HTTP/HTTPS and higher-layer routing. Also, VPC peering to each consumer VPC does not scale well as the number of accounts grows, and it creates operational overhead to manage many peering connections and route tables. It also does not manage DB connections.

Option D is incorrect because it uses VPC peering and NAT gateway. NAT gateway is again not the correct mechanism for private database access and does not provide connection pooling. VPC peering per consumer is not scalable and increases operational overhead.

Therefore, using RDS Proxy to manage connections and AWS PrivateLink (via an NLB-backed endpoint service) to provide private, scalable cross-account access is the correct solution.

Mountpoint for Amazon S3allows EC2 instances to directly access files in S3 as aPOSIX-compliant mount point, ensuring they always get the latest data without copying or syncing.

It’s simple and cost-effective for read-heavy patterns.

Mountpoint for Amazon S3

Create Amazon S3 gateway endpoint in the VPC and add a VPC endpoint policy. This VPC endpoint policy will have a statement that allows S3 access only via access points owned by the organization.

D is correct because thehealth check grace perioddefines how long Auto Scaling waits after launching an instance before checking its health status. With the larger content added to the S3 bucket, the instance initialization (via user data) is taking longer. Increasing the grace period allows the instance time to complete startup tasks before it’s marked as unhealthy.

Option A would not necessarily reduce startup time — the issue is likely network latency or the size of the content.

Option B only affects the timeout for health check responses, not the delay before they begin.

Option C is not applicable unless the health check path itself is invalid (which isn't mentioned).

To effectively gather information about network dependencies between VMs in an on-premises data center for migration to AWS, it's crucial to use tools that can capture detailed application and server dependencies. The AWS Application Discovery Service is designed for this purpose, particularly when migrating from environments like Linux-based VMware VMs. By installing the AWS Application Discovery Agent on the on-premises servers, the service can collect necessary data such as host IP addresses, hostnames, and network connection information. This data is crucial for creating a comprehensive network diagram that outlines the interactions and dependencies between various components of the on-premises infrastructure. The integration with AWS Migration Hub enhances this process by allowing the visualization of these dependencies in a network diagram format, aiding in the planning and execution of the migration process. This approach ensures a thorough understanding of the on-premises environment, which is essential for a successful migration to AWS.

Enable AWS Security Hub:

Navigate to the AWS Security Hub console in your management account and enable Security Hub. This process integrates Security Hub with AWS Control Tower, allowing you to manage and monitor security findings across all accounts within your organization.

Designate a Delegated Administrator:

In AWS Organizations, designate one of the AWS accounts as the delegated administrator for Security Hub. This account will have the responsibility to manage and oversee the security posture of all accounts within the organization.

Deploy Controls Across Accounts:

Use AWS Security Hub to automatically enable security controls across all AWS accounts in the organization. This provides a centralized view of the security state of all accounts and ensures continuous monitoring and compliance.

Utilize AWS Security Hub Features:

Leverage the capabilities of Security Hub to aggregate security alerts, run continuous security checks, and generate findings based on the AWS Foundational Security Best Practices. Security Hub integrates with other AWS services like AWS Config, Amazon GuardDuty, and AWS IAM Access Analyzer to enhance security monitoring and remediation.

By integrating AWS Security Hub with AWS Control Tower and using a delegated administrator account, you can achieve a centralized and comprehensive view of your organization’s security posture, facilitating effective management and remediation of security issues.

References

AWS Security Hub now integrates with AWS Control Tower【77】

AWS Control Tower and Security Hub Integration【76】

AWS Security Hub Features【79】

The company should use Migration Evaluator to generate a list of servers and build a report for a business case. The company should use AWS Migration Hub to view the portfolio and use AWS Application Discovery Service to gain an understanding of application dependencies. This solution will meet the requirements because Migration Evaluator is a migration assessment service that helps create a data-driven business case for AWS cloud planning and migration. Migration Evaluator provides a clear baseline of what the company is running today and projects AWS costs based on measured on-premises provisioning and utilization1. Migration Evaluator can use an agentless collector to conduct broad-based discovery or securely upload exports from existinginventory tools2. Migration Evaluator integrates with AWS Migration Hub, which is a service that provides a single location to track the progress of applicationmigrations across multiple AWS and partner solutions3. Migration Hub also supports AWS Application Discovery Service, which is a service that helps systems integrators quickly and reliably plan application migration projects by automatically identifying applications running in on-premises data centers, their associated dependencies, and their performance profile4.

https://aws.amazon.com/migration-evaluator/

https://docs.aws.amazon.com/migration-evaluator/latest/userguide/what-is.html

https://aws.amazon.com/migration-hub/

https://aws.amazon.com/application-discovery/

https://aws.amazon.com/server-migration-service/

https://aws.amazon.com/dms/

https://docs.aws.amazon.com/controltower/latest/userguide/what-is-control-tower.html

https://aws.amazon.com/application-migration-service/

https://aws.amazon.com/storagegateway/

Creating a quota request template in the us-east-1 Region of the management account ensures it applies to all newly provisioned accounts in the organization.

By specifying the required ml.p2.xlarge training job and endpoint usage quotas in ap-southeast-2, the accounts will automatically receive these higher quotas upon creation, supporting the student lab environments without additional manual quota requests.

This process integrates seamlessly with AWS Organizations for automated and standardized account provisioning.

Comprehensive and Detailed Explanation From Exact Extract:

B is correct because the requirement is to allocate shared EC2 infrastructure costs (ECS on EC2, shared cluster) down to the business groups with the least operational effort. With shared compute, the EC2 line-item charges are not naturally per “task,” so you need a cost allocation feature that can split shared costs using workload metadata. Split cost allocation data combined with the AWS Cost and Usage Report (CUR) and resource tags provides the standard AWS mechanism to distribute (“split”) shared resource costs across consumers for chargeback/showback reporting. This avoids operationally heavy changes (like redesigning clusters) and supports automated reporting.

Why the other options are incorrect:

A: Tagging the Auto Scaling group can only attribute costs at the ASG level, not split costs between multiple business groups sharing the same cluster capacity. It does not solve per-business-group allocation when capacity is shared.

C: Separate clusters per group would work but is higher operational overhead (more clusters to manage, scaling policies, capacity planning, governance), which violates the “least operational overhead” requirement.

D: Cost Categories are useful for mapping and organizing costs, but by themselves they do not solve the underlying need to split shared EC2 costs among multiple consumers unless you already have an accurate split basis. Option B directly targets split allocation of shared costs with tagging and CUR.

This option allows the company to use Amazon CloudFront to improve the latency and availability of the API requests by caching the responses at the edge locations closest to the clients1. By enabling caching in the production stage, the company can reduce the number of calls made to the backend services, such as Lambda functions and Aurora Serverless DB cluster, and save on costs and resources2. This option also helps to handle traffic spikes and reduce database memory errors by serving cached responses instead of querying the database repeatedly.

Choosing an API endpoint type

Enabling API caching to enhance responsiveness