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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:
Aug 17, 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 needs to gather data from an experiment in a remote location that does not have internet connectivity. During the experiment, sensors that are connected to a total network will generate 6 TB of data in a preprimary formal over the course of 1 week. The sensors can be configured to upload their data files to an FTP server periodically, but the sensors do not have their own FTP server. The sensors also do not support other protocols. The company needs to collect the data centrally and move lie data to object storage in the AWS Cloud as soon. as possible after the experiment.

Which solution will meet these requirements?

Options:

A.

Order an AWS Snowball Edge Compute Optimized device. Connect the device to the local network. Configure AWS DataSync with a target bucket name, and unload the data over NFS to the device. After the experiment return the device to AWS so that the data can be loaded into Amazon S3.

B.

Order an AWS Snowcone device, including an Amazon Linux 2 AMI. Connect the device to the local network. Launch an Amazon EC2 instance on the device. Create a shell script that periodically downloads data from each sensor. After the experiment, return the device to AWS so that the data can be loaded as an Amazon Elastic Block Store [Amazon EBS) volume.

C.

Order an AWS Snowcone device, including an Amazon Linux 2 AMI. Connect the device to the local network. Launch an Amazon EC2 instance on the device. Install and configure an FTP server on the EC2 instance. Configure the sensors to upload data to the EC2 instance. After the experiment, return the device to AWS so that the data can be loaded into Amazon S3.

D.

Order an AWS Snowcone device. Connect the device to the local network. Configure the device to use Amazon FSx. Configure the sensors to upload data to the device. Configure AWS DataSync on the device to synchronize the uploaded data with an Amazon S3 bucket Return the device to AWS so that the data can be loaded as an Amazon Elastic Block Store (Amazon EBS) volume.

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Question 2

A company built an ecommerce website on AWS using a three-tier web architecture. The application is Java-based and composed of an Amazon CloudFront distribution, an Apache web server layer of Amazon EC2 instances in an Auto Scaling group, and a backend Amazon Aurora MySQL database.

Last month, during a promotional sales event, users reported errors and timeouts while adding items to their shopping carts. The operations team recovered the logs created by the web servers and reviewed Aurora DB cluster performance metrics. Some of the web servers were terminated before logs could be collected and the Aurora metrics were not sufficient for query performance analysis.

Which combination of steps must the solutions architect take to improve application performance visibility during peak traffic events? (Choose three.)

Options:

A.

Configure the Aurora MySQL DB cluster to publish slow query and error logs to Amazon CloudWatch Logs.

B.

Implement the AWS X-Ray SDK to trace incoming HTTP requests on the EC2 instances and implement tracing of SQL queries with the X-Ray SDK for Java.

C.

Configure the Aurora MySQL DB cluster to stream slow query and error logs to Amazon Kinesis

D.

Install and configure an Amazon CloudWatch Logs agent on the EC2 instances to send the Apache logs to CloudWatch Logs.

E.

Enable and configure AWS CloudTrail to collect and analyze application activity from Amazon EC2 and Aurora.

F.

Enable Aurora MySQL DB cluster performance benchmarking and publish the stream to AWS X-Ray.

Question 3

A company is planning to migrate workloads from its on-premises data center to Amazon EC2 instances. The workloads run on physical servers and VMware virtual servers. The company has gathered details about each on-premises server and virtual server, including server specification, CPU utilization, and memory utilization. The company has stored these details in a .csv file named onprem.csv.

Before the migration, the company must estimate the cost of running the servers on AWS and must determine recommended EC2 instance types for the servers. The company must export this information to a different .csv file.

Which solution will meet these requirements?

Options:

A.

Configure AWS Compute Optimizer to generate recommendations from an external source. Import the onprem.csv file. Export the Compute Optimizer recommendations to a new .csv file.

B.

Import the onprem.csv file into AWS Migration Hub by using AWS Migration Hub import. Use EC2 instance recommendations from Migration Hub to generate recommendations. Export the recommendations to a new .csv file.

C.

Deploy AWS Application Discovery Service Agentless Collector on premises. Use Agentless Collector to import the onprem.csv file. Send the file to AWS Migration Hub. Use EC2 instance recommendations from Migration Hub to generate recommendations. Export the recommendations to a new .csv file.

D.

Upload the onprem.csv file to an Amazon S3 bucket. Configure Migration Evaluator to import the data from the S3 bucket. Generate and confirm recommendations by using Migration Evaluator Quick Insights. Export the final recommendations to a new .csv file in the S3 bucket.

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