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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:
691
Last Updated:
Sep 8, 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 loT sensors that monitor traffic patterns throughout a large city. The company wants to read and collect data from the sensors and perform aggregations on the data.

A solutions architect designs a solution in which the loT devices are streaming to Amazon Kinesis Data Streams. Several applications are reading from the stream. However, several consumers are experiencing throttling and are periodically and are periodically encountering a RealProvisioned Throughput Exceeded error.

Which actions should the solution architect take to resolve this issue? (Select THREE.)

Options:

A.

Reshard the stream to increase the number of shards s in the stream.

B.

Use the Kinesis Producer Library KPL). Adjust the polling frequency.

C.

Use consumers with the enhanced fan-out feature.

D.

Reshard the stream to reduce the number of shards in the stream.

E.

Use an error retry and exponential backoff mechanism in the consumer logic.

F.

Configure the stream to use dynamic partitioning.

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Question 2

A company ' s CISO has asked a Solutions Architect to re-engineer the company ' s current CI/CD practices to make sure patch deployments to its applications can happen as quickly as possible with minimal downtime if vulnerabilities are discovered. The company must also be able to quickly roll back a change in case of errors.

The web application is deployed in a fleet of Amazon EC2 instances behind an Application Load Balancer. The company is currently using GitHub to host the application source code, and has configured an AWS CodeBuild project to build the application. The company also intends to use AWS CodePipeline to trigger builds from GitHub commits using the existing CodeBuild project.

What CI/CD configuration meets all of the requirements?

Options:

A.

Configure CodePipeline with a deploy stage using AWS CodeDeploy configured for in-place deployment. Monitor the newly deployed code, and, if there are any issues, push another code update.

B.

Configure CodePipeline with a deploy stage using AWS CodeDeploy configured for blue/green deployments. Monitor the newly deployed code, and, if there are any issues, trigger a manual rollback using CodeDeploy.

C.

Configure CodePipeline with a deploy stage using AWS CloudFormation to create a pipeline for test and production stacks. Monitor the newly deployed code, and, if there are any issues, push another code update.

D.

Configure the CodePipeline with a deploy stage using AWS OpsWorks and in-place deployments. Monitor the newly deployed code, and, if there are any issues, push another code update.

Question 3

A financial services company receives a regular data feed from its credit card servicing partner Approximately 5.000 records are sent every 15 minutes in plaintext, delivered over HTTPS directly into an Amazon S3 bucket with server-side encryption. This feed contains sensitive credit card primary account number (PAN) data The company needs to automatically mask the PAN before sending the data to another S3 bucket for additional internal processing. The company also needs to remove and merge specific fields, and then transform the record into JSON format Additionally, extra feeds are likely to be added in the future, so any design needs to be easily expandable.

Which solutions will meet these requirements?

Options:

A.

Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Trigger another Lambda function when new messages arrive in the SQS queue to process the records, writing the results to a temporary location in Amazon S3. Trigger a final Lambda function once the SQS queue is empty to transform the records into JSON format and send the results to another S3 bucket for internal processing.

B.

Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Configure an AWS Fargate container application to automatically scale to a single instance when the SQS queue contains messages. Have the application process each record, and transform the record into JSON format. When the queue is empty, send the results to another S3bucket for internal processing and scale down the AWS Fargate i

C.

Create an AWS Glue crawler and custom classifier based on the data feed formats and build a table definition to match. Trigger an AWS Lambda function on file delivery to start an AWS Glue ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, have the ETL job send the results to another S3 bucket for internal processing.

D.

Create an AWS Glue crawler and custom classifier based upon the data feed formats and build a table definition to match. Perform an Amazon Athena query on file delivery to start an Amazon EMR ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, send the results to another S3 bucket for internal processing and scale down the EMR cluster.