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

The goal is to ensure the application operates across multiple Availability Zones. That means removing single points of failure in compute, database, and network egress for private subnets.

For compute, the Auto Scaling group currently has min=1 and max=1, which guarantees only one instance is running at a time. Even if the Auto Scaling group spans multiple subnets, a single-instance configuration cannot provide multi-AZ active capacity because a failure of the Availability Zone hosting the single instance would cause downtime until a new instance is launched in a different zone. To operate across multiple Availability Zones, the solution should run multiple instances across different AZs, which implies increasing the minimum capacity above 1 and allowing the group to launch across multiple subnets/AZs.

For the database, a single-AZ RDS for MySQL instance is a single point of failure. Converting to an RDS Multi-AZ configuration provides synchronous replication to a standby in a different Availability Zone and managed failover to maintain availability when the primary AZ or instance fails.

For NAT, a single NAT gateway is an AZ-scoped managed resource. If private subnets in other AZs route to a NAT gateway in one AZ, an AZ outage can break outbound connectivity for workloads that depend on NAT. The resilient pattern is to deploy a NAT gateway in each Availability Zone and configure each private subnet’s route table to use the NAT gateway in the same AZ.

Option A addresses all three: it deploys additional NAT gateways per AZ and updates route tables accordingly, converts RDS to Multi-AZ, and adjusts Auto Scaling to launch across AZs with min and max set to 3 so there are instances running in multiple AZs simultaneously. This ensures the application remains available across AZ failures, meeting the requirement.

Option B replaces NAT with a virtual private gateway, which is used for VPN/Direct Connect connectivity, not for internet egress from private subnets. It does not satisfy the NAT functionality requirement. Although Aurora can provide high availability, the NAT replacement is not correct for the described architecture.

Option C increases operational overhead by replacing NAT gateway with NAT instances, which are self-managed and less resilient without additional design. It also changes the database engine to PostgreSQL unnecessarily and does not directly address the requirement with minimal change.

Option D improves NAT resiliency but only enables RDS automatic backups, which is a durability feature, not a high availability feature. Backups do not provide automatic failover and do not ensure the application will operate across multiple AZs. Also, keeping Auto Scaling min/max at 1 still leaves the application compute layer single-AZ at any given moment.

Therefore, option A is the correct solution.

The correct answer is A, D, and F. Existing AWS accounts can be invited into an AWS Organizations organization, and SCPs are the correct organization-level mechanism to enforce preventive controls such as required tagging. Because OUs contain accounts, not individual EC2 instances, development workloads must be recreated or migrated into an account that is placed under the development OU. Amazon Inspector is the correct service for automated EC2 vulnerability scanning, and Security Hub can aggregate and centralize findings across an organization. For patching, AWS Systems Manager Patch Manager can be managed across an organization through delegated administration and organization-wide patch policies, which reduces operational overhead compared with configuring each account separately. Trusted Advisor is not the right vulnerability scanning service, and configuring Patch Manager separately in every account creates unnecessary administration.

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

To minimize EKS compute costs:

A. Rebuild the application container images to support ARM64 architecture: Graviton instances (ARM-based) require container images built for the ARM64 architecture. This ensures compatibility and allows leveraging Graviton-based compute.

C. Migrate the EKS nodes to the most recent generation of Graviton-based instances: AWS Graviton instances (e.g., c7g, m7g) offer significant price/performance benefits over x86_64 instances. By migrating EKS worker nodes to Graviton, the company can reduce compute costs substantially.

E. Purchase a new EC2 Instance Savings Plan for the newly selected Graviton instance family: Savings Plans provide cost savings compared to On-Demand pricing. After moving to Graviton, purchasing a new Savings Plan tailored for these instance families ensures continued cost savings.This approach aligns with AWS cost optimization best practices—migrating to the latest instance types and purchasing Savings Plans to match the new usage pattern—while ensuring full compatibility with EKS.

A Lambda function alias allows you to point to a specific version of a function and also can be updated to point to a new version of the function without modifying the client application. This way, the company can test different versions of the function with different environment variables and,once the optimal parameters are found, update the alias to point to the new version, without the need to update the client application.

By using this approach, the company can simplify the process of updating the environment variables, minimize disruption to users, and reduce the operational overhead.

D is correct because the requirement explicitly calls for (1) dedicated private connectivity, (2) automated and centrally managed operation, and (3) connectivity between on-premises data centers and multiple AWS Regions.

AWS Direct Connect provides dedicated private connectivity from on-premises environments to AWS. This is the key differentiator versus internet-based connectivity options when performance and consistency are required to meet strict SLAs.

AWS Cloud WAN provides centralized, policy-based management of a global network across Regions and on-premises attachments. Using Direct Connect attachments to Cloud WAN lets the company centrally define routing/segmentation policies and connect multiple data centers to multiple Regions in a consistent, automated way—well aligned to “automated and centrally managed” requirements for a multi-Region payment platform.

Why the other options are incorrect:

A (Global Accelerator) improves performance for internet-facing endpoints using Anycast and edge routing, but it does not provide private, dedicated connectivity between on-premises networks and AWS services. It is not the right tool for private HSM-to-AWS service connectivity.

B (Site-to-Site VPN + Transit Gateway) can be centrally routed with Transit Gateway, but VPN tunnels run over the public internet and are not “dedicated private connectivity.” They can be acceptable for many cases, but they do not best meet “dedicated private connectivity” and strict SLA expectations compared to Direct Connect.

C (CloudHSM) changes the architecture by moving tokenization into AWS-managed HSM infrastructure. The question states the company manages on-premises HSMs and needs private connectivity between those HSMs and AWS payment services, so replacing them with CloudHSM does not satisfy the stated connectivity requirement.

This solution will allow the external auditors to have read-only access to the company ' s AWS account while being compliant with AWS security best practices. By creating an IAM role, which is a secure and flexible way of granting access to AWS resources, and trusting the auditors ' AWS account, the company can ensure that the auditors only have the permissions that are required for their role and nothing more. Assigning a unique external ID to the role ' s trust policy, it will ensure that only the auditors ' AWS account can assume the role.

https://aws.amazon.com/premiumsupport/knowledge-center/cross-account-access-denied-error-s3/

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).

https://aws.amazon.com/premiumsupport/knowledge-center/waf-analyze-count-action-rules/

This solution will improve the reliability of the application by addressing the issues of scalability, availability, and performance. Containerizing the application will make it easier to deploy and manage on AWS. Migrating the application to an Amazon ECS cluster will allow the application to run on a fully managed container orchestration service. Using the AWS Fargate launch type for the tasks that host the application will enable the application to run on serverless compute engines that are automatically provisioned and scaled by AWS. Creating an Amazon EFS file system for the static content will provide a scalable and shared storage solution that can be accessed by multiple containers. Mounting the EFS file system to each container will eliminate the need to copy the static content to each EBS volume and ensure that the content is always up to date. Configuring AWS Application Auto Scaling on the ECS cluster will enable the application to scale up and down based on demand or a predefined schedule. Setting the ECS service as a target for the ALB will distribute the incoming requests across multiple tasks in the ECS cluster and improve the availability and fault tolerance of the application. Migrating the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance will provide a fully managed, compatible, and scalable relational database service that can handle high throughput and concurrent connections. Using a reader DB instance will offload some of the read load from the primary DB instance and improve the performance of the database.

In this solution, the company can use Amazon SES to send email messages, which will minimize operational overhead as SES is a fully managed service that handles sending and receiving email messages. The company can store the email template on Amazon SES with parameters for the customer data and use an AWS Lambda function to call the SendTemplatedEmail API operation, passing in the customer data to replace the parameters and the email destination. This solution eliminates the need to set up and manage an SMTP server on EC2 instances, which can be costly and time-consuming.

The IAM policy simulator will generate a policy that contains only the necessary permissions for the application to access Secrets Manager, providing the least privilege necessary to get the job done. This is the most efficient solution as it will not require additional steps such as analyzing CloudTrail events or manually creating and testing an IAM policy.

You can use the IAM policy simulator to generate an IAM policy for an IAM role by specifying the role and the API actions and resources that the application or service requires. The simulator will then generate an IAM policy that grants the least privilege access to those actions and resources.

Once you have generated an IAM policy using the simulator, you can replace the existing SecretsManagerReadWnte policy that is attached to the IAM role with the newly generated policy. This will ensure that the application or service has the least privilege access to the Secrets Manager actions that it requires.

You can access the IAM policy simulator through the IAM console, AWS CLI, and AWS SDKs. Here is the link for more information:https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_simulator.html

Dis the right choice:EFS with Max I/O modeis designed formassively parallel workloadslike big data. It supports high throughput and concurrent access from many EC2 nodes across AZs.

A(Storage Gateway) is not optimized for high-performance, low-latency compute clusters.

Bis limited in performance (latency optimized for single-threaded workloads).

C(EBS) cannot be shared across AZs and is not POSIX-compatible for concurrent multi-node access.

https://joe.blog.freemansoft.com/2020/04/protect-data-in-cloud-with-s3-access.html