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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:
645
Last Updated:
May 7, 2026
Exam Status:
Stable
Amazon Web Services SAP-C02

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

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AWS Certified Solutions Architect - Professional Questions and Answers

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Question 1

A company has its cloud infrastructure on AWS A solutions architect needs to define the infrastructure as code. The infrastructure is currently deployed in one AWS Region. The company's business expansion plan includes deployments in multiple Regions across multiple AWS accounts

What should the solutions architect do to meet these requirements?

Options:

A.

Use AWS CloudFormation templates Add IAM policies to control the various accounts Deploy the templates across the multiple Regions

B.

Use AWS Organizations Deploy AWS CloudFormation templates from the management account Use AWS Control Tower to manage deployments across accounts

C.

Use AWS Organizations and AWS CloudFormation StackSets Deploy a CloudFormation template from an account that has the necessary IAM permissions

D.

Use nested stacks with AWS CloudFormation templates Change the Region by using nested stacks

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Question 2

A company plans to migrate a three-tiered web application from an on-premises data center to AWS The company developed the Ui by using server-side JavaScript libraries The business logic and API tier uses a Python-based web framework The data tier runs on a MySQL database

The company custom built the application to meet business requirements The company does not want to re-architect the application The company needs a solution to replatform the application to AWS with the least possible amount of development The solution needs to be highly available and must reduce operational overhead

Which solution will meet these requirements?

Options:

A.

Deploy the UI to a static website on Amazon S3 Use Amazon CloudFront to deliver the website Build the business logic in a Docker image Store the image in AmazonElastic Container Registry (Amazon ECR) Use Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to host the website with an Application Load Balancer in front Deploy the data layer to an Amazon Aurora MySQL DB cluster

B.

Build the UI and business logic in Docker images Store the images in Amazon Elastic Container Registry (Amazon ECR) Use Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to host the UI and business logic applications with an Application LoadBalancer in front Migrate the database to an Amazon RDS for MySQL Multi-AZ DB instance

C.

Deploy the UI to a static website on Amazon S3 Use Amazon CloudFront to deliver the website Convert the business logic to AWS Lambda functions Integrate the functions with Amazon API Gateway Deploy the data layer to an Amazon Aurora MySQL DB cluster

D.

Build the UI and business logic in Docker images Store the images in Amazon Elastic Container Registry (Amazon ECR) Use Amazon Elastic Kubernetes Service(Amazon EKS) with Fargate profiles to host the UI and business logic Use AWS Database Migration Service (AWS DMS) to migrate the data layer to Amazon DynamoDB

Question 3

A team of data scientists is using Amazon SageMaker instances and SageMaker APIs to train machine learning (ML) models. The SageMaker instances are deployed in a

VPC that does not have access to or from the internet. Datasets for ML model training are stored in an Amazon S3 bucket. Interface VPC endpoints provide access to Amazon S3 and the SageMaker APIs.

Occasionally, the data scientists require access to the Python Package Index (PyPl) repository to update Python packages that they use as part of their workflow. A solutions architect must provide access to the PyPI repository while ensuring that the SageMaker instances remain isolated from the internet.

Which solution will meet these requirements?

Options:

A.

Create an AWS CodeCommit repository for each package that the data scientists need to access. Configure code synchronization between the PyPl repositoryand the CodeCommit repository. Create a VPC endpoint for CodeCommit.

B.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet with a network ACL that allows access to only the PyPl repositoryendpoint.

C.

Create a NAT instance in the VPC. Configure VPC routes to allow access to the internet. Configure SageMaker notebook instance firewall rules that allow access to only the PyPI repository endpoint.

D.

Create an AWS CodeArtifact domain and repository. Add an external connection for public:pypi to the CodeArtifact repository. Configure the Python client touse the CodeArtifact repository. Create a VPC endpoint for CodeArtifact.

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