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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
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

Question 1

A company has a transit gateway that connects multiple VPCs in the same AWS Region. The company needs a centralized way to inspect network traffic and allow internet access for the workload VPCs.

Which solution meets these requirements?

Options:

A.

Create a Gateway Load Balancer (GWLB), GWLB endpoints, and a network virtual appliance in an existing workload VPC. Update the route table in the remaining workload VPCs to send traffic to the transit gateway. Configure the transit gateway route tables to forward traffic to the GWLB endpoints. Enable appliance mode on the GWLB.

B.

Create a Gateway Load Balancer (GWLB) in an existing workload VPC. Create GWLB endpoints and network virtual appliances in a different workload VPC. Update the route tables in all workload VPCs to send traffic to the transit gateway. Configure the transit gateway route tables to forward traffic to the GWLB endpoints. Enable appliance mode on the GWLB endpoints.

C.

Create an inspection VPC and an internet access VPC. Create a Gateway Load Balancer (GWLB) and GWLB endpoints in the inspection VPC. Create a network virtual appliance in the internet VPC. Enable flow logs in the workload VPCs to route traffic to the transit gateway. Enable appliance mode on the network virtual appliance.

D.

Create an inspection VPC that contains a Gateway Load Balancer (GWLB), GWLB endpoints, and a network virtual appliance. Update the route tables in all workload VPCs to send traffic to the transit gateway. Configure the transit gateway route tables to forward traffic to the GWLB endpoints. Enable appliance mode on the transit gateway.

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Question 2

A company has a sales system that stores transactions as .csv files in an Amazon S3 bucket. The S3 bucket is configured to use S3 Intelligent-Tiering. Most of the .csv files are between 64 KB and 100 KB in size. All rows and columns of the .csv files must be read when the data is processed. The company must keep the data for 5 years.

The company stores several million xsv files every day. The company must minimize the cost of storing and querying the xsv files.

Which solution will meet these requirements?

Options:

A.

Create an AWS Glue job to convert the .csv files into Apache Parquet format. Use Amazon S3 to invoke the AWS Glue job every time a .csv file arrives.

B.

Create an AWS Glue job to compress the .csv files. Schedule the AWS Glue job every hour to compress the files for the previous hour into one .csv file.

C.

Create an AWS Lambda function to convert the .csv files into Apache Parquet format. Use Amazon S3 to invoke the Lambda function every time a .csv file arrives.

D.

Create an AWS Lambda function to compress the .csv files. Use Amazon S3 to invoke the Lambda function every time a .csv file arrives.

Question 3

A company is migrating its legacy .NET workload to AWS. The company has a containerized setup that includes a base container image. The base image is tens of

gigabytes in size because of legacy libraries and other dependencies. The company has images for custom developed components that are dependent on the base image.

The company will use Amazon Elastic Container Registry (Amazon ECR) as part of its solution on AWS.

Which solution will provide the LOWEST container startup time on AWS?

Options:

A.

Use Amazon ECR to store the base image and the images for the custom developed components. Use Amazon Elastic Container Service (Amazon ECS) onAWS Fargate to run the workload.

B.

Use Amazon ECR to store the base image and the images for the custom developed components. Use AWS App Runner to run the workload.

C.

Use Amazon ECR to store the images for the custom developed components. Create an AMI that contains the base image. Use Amazon Elastic Container Service (Amazon ECS) on Amazon EC2 instances that are based on the AMI to run the workload

D.

Use Amazon ECR to store the images for the custom developed components. Create an AMI that contains the base image. Use Amazon Elastic Kubernetes Service (Amazon EKS) on AWS Fargate with the AMI to run the workload.