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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:
683
Last Updated:
Jul 22, 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 data lake in Amazon S3 that needs to be accessed by hundreds of applications across many AWS accounts. The company ' s information security policy states that the S3 bucket must not be accessed over the public internet and that each application should have the minimum permissions necessary to function.

To meet these requirements, a solutions architect plans to use an S3 access point that is restricted to specific VPCs for each application.

Which combination of steps should the solutions architect take to implement this solution? (Select TWO.)

Options:

A.

Create an S3 access point for each application in the AWS account that owns the S3 bucket. Configure each access point to be accessible only from the application ' s VPC. Update the bucket policy to require access from an access point.

B.

Create an interface endpoint for Amazon S3 in each application ' s VPC. Configure the endpoint policy to allow access to an S3 access point. Create a VPC gateway attachment for the S3 endpoint.

C.

Create a gateway endpoint for Amazon S3 in each application ' s VPC. Configure the endpoint policy to allow access to an S3 access point. Specify the route table that is used to access the access point.

D.

Create an S3 access point for each application in each AWS account and attach the access points to the S3 bucket. Configure each access point to be accessible only from the application ' s VPC. Update the bucket policy to require access from an access point.

E.

Create a gateway endpoint for Amazon S3 in the data lake ' s VPC. Attach an endpoint policy to allow access to the S3 bucket. Specify the route table that is used to access the bucket.

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Question 2

A life sciences company is using a combination of open source tools to manage data analysis workflows and Docker containers running on servers in its on-premises data center to process genomics data Sequencing data is generated and stored on a local storage area network (SAN), and then the data is processed. The research and development teams are running into capacity issues and have decided to re-architect their genomics analysis platform on AWS to scale based on workload demands and reduce the turnaround time from weeks to days

The company has a high-speed AWS Direct Connect connection Sequencers will generate around 200 GB of data for each genome, and individual jobs can take several hours to process the data with ideal compute capacity. The end result will be stored in Amazon S3. The company is expecting 10-15 job requests each day

Which solution meets these requirements?

Options:

A.

Use regularly scheduled AWS Snowball Edge devices to transfer the sequencing data into AWS When AWS receives the Snowball Edge device and the data is loaded into Amazon S3 use S3 events to trigger an AWS Lambda function to process the data

B.

Use AWS Data Pipeline to transfer the sequencing data to Amazon S3 Use S3 events to trigger an Amazon EC2 Auto Scaling group to launch custom-AMI EC2 instances running the Docker containers to process the data

C.

Use AWS DataSync to transfer the sequencing data to Amazon S3 Use S3 events to trigger an AWS Lambda function that starts an AWS Step Functions workflow Store the Docker images in Amazon Elastic Container Registry (Amazon ECR) and trigger AWS Batch to run the container and process the sequencing data

D.

Use an AWS Storage Gateway file gateway to transfer the sequencing data to Amazon S3 Use S3 events to trigger an AWS Batch job that runs on Amazon EC2 instances running the Docker containers to process the data

Question 3

A company has an application that runs on Amazon EC2 instances in an Amazon EC2 Auto Scaling group. The company uses AWS CodePipeline to deploy the application. The instances that run in the Auto Scaling group are constantly changing because of scaling events.

When the company deploys new application code versions, the company installs the AWS CodeDeploy agent on any new target EC2 instances and associates the instances with the CodeDeploy deployment group. The application is set to go live within the next 24 hours.

What should a solutions architect recommend to automate the application deployment process with the LEAST amount of operational overhead?

Options:

A.

Configure Amazon EventBridge to invoke an AWS Lambda function when a new EC2 instance is launched into the Auto Scaling group. Code the Lambda function to associate the EC2 instances with the CodeDeploy deployment group.

B.

Write a script to suspend Amazon EC2 Auto Scaling operations before the deployment of new code When the deployment is complete, create a new AMI and configure the Auto Scaling group ' s launch template to use the new AMI for new launches. Resume Amazon EC2 Auto Scaling operations.

C.

Create a new AWS CodeBuild project that creates a new AMI that contains the new code Configure CodeBuild to update the Auto Scaling group ' s launch template to the new AMI. Run an Amazon EC2 Auto Scaling instance refresh operation.

D.

Create a new AMI that has the CodeDeploy agent installed. Configure the Auto Scaling group ' s launch template to use the new AMI. Associate the CodeDeploy deployment group with the Auto Scaling group instead of the EC2 instances.