Amazon Web Services SAP-C02 Study & Exam Dumps 2025

AWS Certified Solutions Architect - Professional Questions and Answers

Question 1

A solutions architect must analyze a company ' s Amazon EC2 Instances and Amazon Elastic Block Store (Amazon EBS) volumes to determine whether the company is using resources efficiently The company is running several large, high-memory EC2 instances lo host database dusters that are deployed in active/passive configurations The utilization of these EC2 instances varies by the applications that use the databases, and the company has not identified a pattern

The solutions architect must analyze the environment and take action based on the findings.

Which solution meets these requirements MOST cost-effectively?

Options:

Create a dashboard by using AWS Systems Manager OpsConter Configure visualizations tor Amazon CloudWatch metrics that are associated with the EC2 instances and their EBS volumes Review the dashboard periodically and identify usage patterns Right size the EC2 instances based on the peaks in the metrics

Turn on Amazon CloudWatch detailed monitoring for the EC2 instances and their EBS volumes Create and review a dashboard that is based on the metrics Identify usage patterns Right size the FC? instances based on the peaks In the metrics

Install the Amazon CloudWatch agent on each of the EC2 Instances Turn on AWS Compute Optimizer, and let it run for at least 12 hours Review the recommendations from Compute Optimizer, and right size the EC2 instances as directed

Sign up for the AWS Enterprise Support plan Turn on AWS Trusted Advisor Wait 12 hours Review the recommendations from Trusted Advisor, and rightsize the EC2 instances as directed

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Question 2

A retail company is mounting IoT sensors in all of its stores worldwide. During the manufacturing of each sensor, the company ' s private certificate authority (CA) issues an X.509 certificate that contains a unique serial number. The company then deploys each certificate to its respective sensor.

A solutions architect needs to give the sensors the ability to send data to AWS after they are installed. Sensors must not be able to send data to AWS until they are installed.

Which solution will meet these requirements?

Options:

Create an AWS Lambda function that can validate the serial number. Create an AWS IoT Core provisioning template. Include the SerialNumber parameter in the Parameters section. Add the Lambda function as a pre-provisioning hook. During manufacturing, call the RegisterThing API operation and specify the template and parameters.

Create an AWS Step Functions state machine that can validate the serial number. Create an AWS IoT Core provisioning template. Include the SerialNumber parameter in the Parameters section. Specify the Step Functions state machine to validate parameters. Call the StartThingRegistrationTask API operation during installation.

Create an AWS Lambda function that can validate the serial number. Create an AWS IoT Core provisioning template. Include the SerialNumber parameter in the Parameters section. Add the Lambda function as a pre-provisioning hook. Register the CA with AWS IoT Core, specify the provisioning template, and set the allow-auto-registration parameter.

Create an AWS IoT Core provisioning template. Include the SerialNumber parameter in the Parameters section. Include parameter validation in the template. Provision a claim certificate and a private key for each device that uses the CA. Grant AWS IoT Core service permissions to update AWS IoT things during provisioning.

Question 3

A company hosts a multi-tier data processing application that consists of a static web application frontend and APIs that are hosted on multiple Amazon EC2 instances. The application stores search data on a single-node Amazon OpenSearch Service cluster that runs on an EC2 instance. The application stores additional data in a PostgreSQL database that runs on another EC2 instance. An NGINX server that is hosted on an EC2 instance serves the web application.

The company has experienced some support issues with the application and wants to modernize the application.

Which solution meets these requirements with the LEAST operational overhead?

Options:

Create an Amazon ECS cluster that runs on AWS Fargate. Configure the ECS cluster to pull images from the Amazon ECR public repositories for OpenSearch Service, PostgreSQL, and NGINX and from a private repository for the APIs.

Host the web application on Amazon CloudFront by using an Amazon S3 origin. Use OpenSearch Service to store the search data and migrate the PostgreSQL database to an Amazon Aurora PostgreSQL cluster. Run the APIs on AWS App Runner.

Create an Amazon EKS cluster that has a managed node group. Configure the EKS cluster to pull images from the Amazon ECR public repositories for OpenSearch Service, PostgreSQL, and NGINX and from a private repository for the APIs.

Configure AWS App Runner to pull images from the Amazon ECR public repositories for OpenSearch Service, PostgreSQL, and NGINX and from a private repository for the APIs. Deploy the images to App Runner.

Answer:

Explanation:

The company’s goal is to modernize the application while minimizing operational overhead. The current architecture relies heavily on self-managed EC2 instances for web serving, APIs, search, and relational data storage. This increases operational burden related to patching, scaling, availability, and troubleshooting.

Option B replaces self-managed components with fully managed AWS services that are purpose-built for each workload type. Hosting the static web application on Amazon S3 with Amazon CloudFront removes the need to manage web servers such as NGINX and provides global content delivery with built-in scalability and high availability. Migrating the search data to Amazon OpenSearch Service eliminates the need to manage an EC2-based OpenSearch node, providing a managed search service with built-in scaling, patching, and monitoring. Migrating PostgreSQL to Amazon Aurora PostgreSQL removes the operational overhead of managing database instances on EC2 and provides managed backups, high availability, and performance optimizations. Running APIs on AWS App Runner further reduces operational effort by abstracting infrastructure management, scaling, and deployment, allowing the team to focus on application code.

Option A still requires running and operating containerized databases and search engines, which is not recommended and does not significantly reduce operational overhead compared to EC2-based deployments. Databases and OpenSearch are better consumed as managed services rather than as containers.

Option C introduces Amazon EKS, which adds significant operational complexity. Even with managed node groups, Kubernetes requires cluster management, networking configuration, upgrades, and ongoing operational expertise. This contradicts the requirement for the least operational overhead.

Option D attempts to run databases and OpenSearch on AWS App Runner. App Runner is designed for stateless web services and APIs, not for stateful services such as databases or search engines. This architecture is not aligned with AWS best practices and would introduce reliability and operational challenges.

Therefore, using managed services such as Amazon CloudFront, Amazon S3, Amazon OpenSearch Service, Amazon Aurora PostgreSQL, and AWS App Runner provides the most modern architecture with the least operational overhead.

[References:AWS documentation on application modernization best practices using managed services to reduce operational responsibility.AWS documentation on Amazon CloudFront and Amazon S3 for hosting static web applications.AWS documentation on Amazon OpenSearch Service as a managed search and analytics service.AWS documentation on Amazon Aurora PostgreSQL for managed relational databases.AWS documentation on AWS App Runner for running containerized APIs without infrastructure management., , , ]

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