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Amazon Web Services SAA-C03 Exam With Confidence Using Practice Dumps

Exam Code:
SAA-C03
Exam Name:
AWS Certified Solutions Architect - Associate (SAA-C03)
Certification:
AWS Certified Associate
Vendor:
Amazon Web Services
Questions:
911
Last Updated:
Jul 2, 2026
Exam Status:
Stable
Amazon Web Services SAA-C03

SAA-C03: AWS Certified Associate Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified Solutions Architect - Associate (SAA-C03) Questions and Answers

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Question 1

A company is developing a containerized web application that needs to be highly available and scalable. The application requires access to GPU resources.

Options:

A.

Package the application as an AWS Lambda function in a container image. Use Lambda to run the containerized application on a runtime with GPU access.

B.

Deploy the application container to Amazon Elastic Kubernetes Service (Amazon EKS). Use AWS Fargate to manage compute resources and access to GPU resources.

C.

Deploy the application container to Amazon Elastic Container Registry (Amazon ECR). Use Amazon ECR to run the containerized application with an attached GPU.

D.

Run the application on Amazon EC2 instances from a GPU instance family by using Amazon Elastic Container Service (Amazon ECS) for orchestration.

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Question 2

A company runs a multi-tier web application that hosts news content. The application runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an EC2 Auto Scaling group across multiple Availability Zones and use an Amazon Aurora database.

A solutions architect needs to make the application more resilient to periodic increases in request rates.

Which architecture should the solutions architect implement? (Select TWO.)

Options:

A.

Add AWS Shield

B.

Add Aurora Replicas

C.

Add AWS Direct Connect

D.

Add AWS Global Accelerator

E.

Add an Amazon CloudFront distribution in front of the Application Load Balancer

Question 3

A company wants to build a generative AI (GenAI) model for a medical use case. The company has 50 TB of medical image data that is stored in an Amazon S3 bucket. The company plans to train the GenAI model by using Amazon SageMaker AI with multiple GPU-powered instances.

The company needs a storage solution that helps ensure that the data can be loaded from storage fast enough to avoid GPU instance idle time. The storage solution needs to achieve tens of gigabits per second (Gbps) of throughput.

Which solution will meet these requirements?

Options:

A.

Configure the existing S3 bucket as the SageMaker AI data source by using file mode.

B.

Create an Amazon FSx for Lustre file system. Move the data from Amazon S3 to Lustre by using data repository association. Mount the file system on the instances.

C.

Configure the existing S3 bucket as the SageMaker AI data source by using fast file mode.

D.

Move the data to the S3 Glacier Flexible Retrieval storage class. Configure the S3 bucket as the SageMaker AI data source by using fast file mode.

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