CertsTopics Logo

Spring Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

Amazon Web Services SAP-C02 Exam With Confidence Using Practice Dumps

Exam Code:
SAP-C02
Exam Name:
AWS Certified Solutions Architect - Professional
Certification:
AWS Certified Professional
Vendor:
Amazon Web Services
Questions:
614
Last Updated:
Feb 19, 2026
Exam Status:
Stable
Amazon Web Services SAP-C02

SAP-C02: AWS Certified Professional Exam 2025 Study Guide Pdf and Test Engine

Are you worried about passing the Amazon Web Services SAP-C02 (AWS Certified Solutions Architect - Professional) exam? Download the most recent Amazon Web Services SAP-C02 braindumps with answers that are 100% real. After downloading the Amazon Web Services SAP-C02 exam dumps training , you can receive 99 days of free updates, making this website one of the best options to save additional money. In order to help you prepare for the Amazon Web Services SAP-C02 exam questions and verified answers by IT certified experts, CertsTopics has put together a complete collection of dumps questions and answers. To help you prepare and pass the Amazon Web Services SAP-C02 exam on your first attempt, we have compiled actual exam questions and their answers. 

Our (AWS Certified Solutions Architect - Professional) Study Materials are designed to meet the needs of thousands of candidates globally. A free sample of the CompTIA SAP-C02 test is available at CertsTopics. Before purchasing it, you can also see the Amazon Web Services SAP-C02 practice exam demo.

Get SAP-C02 Full Access

Related Amazon Web Services Exams

AWS Certified Solutions Architect - Professional Questions and Answers

Get Free SAP-C02 Questions and Answers
Question 1

A solutions architect is investigating an issue in which a company cannot establish new sessions in Amazon Workspaces. An initial analysis indicates that the issue involves user profiles. The AmazonWorkspaces environment is configured to use Amazon FSx for Windows File Server as the profile share storage. The FSx for Windows File Server file system is configured with 10 TB of storage.

The solutions architect discovers that the file system has reached its maximum capacity. The solutions architect must ensure that users can regain access. The solution also must prevent the problem from occurring again.

Which solution will meet these requirements?

Options:

A.

Remove old user profiles to create space. Migrate the user profiles to an Amazon FSx for Lustre file system.

B.

Increase capacity by using the update-file-system command. Implement an Amazon CloudWatch metric that monitors free space. Use Amazon EventBridge to invoke an AWS Lambda function to increase capacity as required.

C.

Monitor the file system by using the FreeStorageCapacity metric in Amazon CloudWatch. Use AWS Step Functions to increase the capacity as required.

D.

Remove old user profiles to create space. Create an additional FSx for Windows File Server file system. Update the user profile redirection for 50% of the users to use the new file system.

Buy Now
Question 2

A company runs a content management application on a single Windows Amazon EC2 instance in a development environment. The application reads and writes static content to a 2 TB Amazon Elastic Block Store (Amazon EBS) volume that is attached to the instance as the root device. The company plans to deploy this application in production as a highly available and fault-tolerant solution that runs on at least three EC2 instances across multiple Availability Zones.

A solutions architect must design a solution that joins all the instances that run the application to an Active Directory domain. The solution also must implement Windows ACLs to control access to file contents. The application always must maintain exactly the same content on all running instances at any given point in time.

Which solution will meet these requirements with the LEAST management overhead?

Options:

A.

Create an Amazon Elastic File System (Amazon EFS) file share. Create an Auto Scaling group that extends across three Availability Zones and maintains a minimum size of three instances. Implement a user data script to install the application, join the instance to the AD domain, and mount the EFS file share.

B.

Create a new AMI from the current EC2 instance that is running. Create an Amazon FSx for Lustre file system. Create an Auto Scaling group that extends across three Availability Zones and maintains a minimum size of three instances. Implement a user data script to join the instance to the AD domain and mount the FSx for Lustre file system.

C.

Create an Amazon FSx for Windows File Server file system. Create an Auto Scaling group that extends across three Availability Zones and maintains a minimum size of three instances. Implement a user data script to install the application and mount the FSx for Windows File Server file system. Perform a seamless domain join to join the instance to the AD domain.

D.

Create a new AMI from the current EC2 instance that is running. Create an Amazon Elastic File System (Amazon EFS) file system. Create an Auto Scaling group that extends across three Availability Zones and maintains a minimum size of three instances. Perform a seamless domain join to join the instance to the AD domain.

Question 3

A manufacturing company is building an inspection solution for its factory. The company has IPcameras at the end of each assembly line. The company has used Amazon SageMaker to train a machine learning (ML) model to identify common defects from still images.

The company wants to provide local feedback to factory workers when a defect is detected. The company must be able to provide this feedback even if the factory’s internet connectivity is down. The company has a local Linux server that hosts an API that provides local feedback to the workers.

How should the company deploy the ML model to meet these requirements?

Options:

A.

Set up an Amazon Kinesis video stream from each IP camera to AWS. Use Amazon EC2 instances to take still images of the streams. Upload the images to an Amazon S3 bucket. Deploy a SageMaker endpoint with the ML model. Invoke an AWS Lambda function to call the inference endpoint when new images are uploaded. Configure the Lambda function to call the local API when a defect is detected.

B.

Deploy AWS IoT Greengrass on the local server. Deploy the ML model to the Greengrass server. Create a Greengrass component to take still images from the cameras and run inference. Configure the component to call the local API when a defect is detected.

C.

Order an AWS Snowball device. Deploy a SageMaker endpoint the ML model and an Amazon EC2 instance on the Snowball device. Take still images from the cameras. Run inference from the EC2 instance. Configure the instance to call the local API when a defect is detected.

D.

Deploy Amazon Monitron devices on each IP camera. Deploy an Amazon Monitron Gateway on premises. Deploy the ML model to the Amazon Monitron devices. Use Amazon Monitron health state alarms to call the local API from an AWS Lambda function when a defect is detected.

Get Free SAP-C02 Questions and Answers