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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:
691
Last Updated:
Sep 4, 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 runs a processing engine in the AWS Cloud The engine processes environmental data from logistics centers to calculate a sustainability index The company has millions of devices in logistics centers that are spread across Europe The devices send information to the processing engine through a RESTful API

The API experiences unpredictable bursts of traffic The company must implement a solution to process all data that the devices send to the processing engine Data loss is unacceptable

Which solution will meet these requirements?

Options:

A.

Create an Application Load Balancer (ALB) for the RESTful API Create an Amazon Simple Queue Service (Amazon SQS) queue Create a listener and a target group for the ALB Add the SQS queue as the target Use a container that runs in Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to process messages in the queue

B.

Create an Amazon API Gateway HTTP API that implements the RESTful API Create an Amazon Simple Queue Service (Amazon SQS) queue Create an API Gateway service integration with the SQS queue Create an AWS Lambda function toprocess messages in the SQS queue

C.

Create an Amazon API Gateway REST API that implements the RESTful API Create a fleet of Amazon EC2 instances in an Auto Scaling group Create an API Gateway Auto Scaling group proxy integration Use the EC2 instances to process incoming data

D.

Create an Amazon CloudFront distribution for the RESTful API Create a data stream in Amazon Kinesis Data Streams Set the data stream as the origin for the distribution Create an AWS Lambda function to consume and process data in the data stream

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Question 2

A company uses a software package for surveys. During surveys, data is uploaded from a field operator ' s device to an Amazon S3 bucket. A custom application that runs on several Amazon EC2 instances polls the S3 bucket for new data. When new data is available, the software processes the data.

The data uploads are infrequent. The processing software can take up to 25 minutes to analyze each data upload. The company wants to optimize the application workflow to process the S3 data.

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

Options:

A.

Modify the application to accept new S3 object keys as inputs. Containerize the application. Deploy the container to an Amazon ECS cluster that uses the AWS Fargate launch type. Configure S3 bucket notifications to send events to Amazon EventBridge when new objects are uploaded. Create an EventBridge rule that invokes an ECS task to run the application when a new S3 object event occurs.

B.

Modify the application to accept new S3 object keys as inputs. Containerize the application. Deploy the container image to AWS Lambda functions. Create a new AWS Step Functions state machine to invoke the Lambda functions. Configure the state machine with a Task state that calls the Lambda functions. Set the Task state ' s Timeout property to 30 minutes.

C.

Modify the application to accept new S3 object keys as inputs. Move the application from EC2 instances to Amazon ECS by using the EC2 capacity provider. Create an AWS Glue crawler to check the S3 bucket and invoke the application. Configure the application to process the data when the data is uploaded to Amazon S3.

D.

Modify the application to use HTTP to poll new S3 object keys that reference data to process. Containerize the application. Deploy the container image to AWS Lambda functions. Configure S3 bucket notifications to send events to Amazon EventBridge when new objects are uploaded. Create an EventBridge rule that invokes the Lambda functions to post the new objects to HTTP endpoints by using fan-out.

Question 3

Question:

A company is migrating a monolithic on-premises .NET Framework production application to AWS. Application demand will grow exponentially in the next 6 months. The company must ensure that the application can scale appropriately.

The application currently connects to a Microsoft SQL Server transactional database. The company has well-documented source code for the application. Some business logic is contained within stored procedures.

A solutions architect must recommend a solution to redesign the application to meet the growth in demand.

Which solution will meet this requirement MOST cost-effectively?

Options:

A.

Use Amazon API Gateway APIs and Amazon EC2 Spot Instances to rehost the application with a scalable microservices architecture. Deploy the EC2 instances in a cluster placement group. Configure EC2 Auto Scaling. Store the data and stored procedures in Amazon RDS for SQL Server.

B.

Use AWS Application Migration Service to migrate the application to AWS Elastic Beanstalk. Deploy Elastic Beanstalk packages to configure and deploy the application as microservices. Deploy Elastic Beanstalk across multiple Availability Zones and configure auto scaling. Store the data and stored procedures in Amazon RDS for MySQL.

C.

Migrate the applications by using AWS App2Container. Use AWS Fargate in multiple AWS Regions to host the containers. Use Amazon API Gateway APIs and AWS Lambda functions to call the containers. Store the data and stored procedures in Amazon DynamoDB Accelerator (DAX).

D.

Use Amazon API Gateway APIs and AWS Lambda functions to decouple the application into microservices. Use the AWS Schema Conversion Tool (AWS SCT) to review and modify the stored procedures. Store the data in Amazon Aurora Serverless v2.

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