Amazon SAP-C02 Online Practice
Questions and Exam Preparation
SAP-C02 Exam Details
Exam Code
:SAP-C02
Exam Name
:AWS Certified Solutions Architect - Professional (SAP-C02)
Certification
:Amazon Certifications
Vendor
:Amazon
Total Questions
:761 Q&As
Last Updated
:May 25, 2026
Amazon SAP-C02 Online Questions &
Answers
Question 471:
A company is planning to migrate its business-critical applications from an on-premises data center to AWS. The company has an on-premises installation of a
Microsoft SQL Server Always On cluster. The company wants to migrate to an AWS managed database service. A solutions architect must design a heterogeneous database migration on AWS.
Which solution will meet these requirements?
A. Migrate the SQL Server databases to Amazon RDS for MySQL by using backup and restore utilities. B. Use an AWS Snowball Edge Storage Optimized device to transfer data to Amazon S3. Set up Amazon RDS for MySQL. Use S3 integration with SQL Server features, such as BULK INSERT. C. Use the AWS Schema Conversion Tool to translate the database schema to Amazon RDS for MeSQL. Then use AWS Database Migration Service (AWS DMS) to migrate the data from on-premises databases to Amazon RDS. D. Use AWS DataSync to migrate data over the network between on-premises storage and Amazon S3. Set up Amazon RDS for MySQL. Use S3 integration with SQL Server features, such as BULK INSERT.
C. Use the AWS Schema Conversion Tool to translate the database schema to Amazon RDS for MeSQL. Then use AWS Database Migration Service (AWS DMS) to migrate the data from on-premises databases to Amazon RDS.
AWS Schema Conversion Tool (SCT) can automatically convert the database schema from Microsoft SQL Server to Amazon RDS for MySQL. This allows for a smooth transition of the database schema without any manual intervention. AWS
DMS can then be used to migrate the data from the on-premises databases to the newly created Amazon RDS for MySQL instance. This service can perform a one-time migration of the data or can set up ongoing replication of data changes
to keep the on-premises and AWS databases in sync.
Question 472:
A company is running an application in the AWS Cloud. The application consists of microservices that run on a fleet of Amazon EC2 instances in multiple Availability Zones behind an Application Load Balancer. The company recently added a new REST API that was implemented in Amazon API Gateway. Some of the older microservices that run on EC2 instances need to call this new API
The company does not want the API to be accessible from the public internet and does not want proprietary data to traverse the public internet
What should a solutions architect do to meet these requirements?
A. Create an AWS Site-to-Site VPN connection between the VPC and the API Gateway Use API Gateway to generate a unique API key for each microservice. Configure the API methods to require the key. B. Create an interface VPC endpoint for API Gateway, and set an endpoint policy to only allow access to the specific API Add a resource policy to API Gateway to only allow access from the VPC endpoint Change the API Gateway endpoint type to private. C. Modify the API Gateway to use IAM authentication Update the IAM policy for the IAM role that is assigned to the EC2 instances to allow access to the API Gateway Move the API Gateway into a new VPC Deploy a transit gateway and connect the VPCs. D. Create an accelerator in AWS Global Accelerator and connect the accelerator to the API Gateway. Update the route table for all VPC subnets with a route to the created Global Accelerator endpoint IP address. Add an API key for each service to use for authentication.
B. Create an interface VPC endpoint for API Gateway, and set an endpoint policy to only allow access to the specific API Add a resource policy to API Gateway to only allow access from the VPC endpoint Change the API Gateway endpoint type to private.
An entertainment company recently launched a new game. To ensure a good experience for players during the launch period, the company deployed a static quantity of 12 r6g.16xlarge (memory optimized) Amazon EC2 instances behind a Network Load Balancer. The company's operations team used the Amazon CloudWatch agent and a custom metric to include memory utilization in its monitoring strategy.
Analysis of the CloudWatch metrics from the launch period showed consumption at about one quarter of the CPU and memory that the company expected. Initial demand for the game has subsided and has become more variable. The company decides to use an Auto Scaling group that monitors the CPU and memory consumption to dynamically scale the instance fleet. A solutions architect needs to configure the Auto Scaling group to meet demand in the most cost-effective way.
Which solution will meet these requirements?
A. Configure the Auto Scaling group to deploy c6g.4xlarge (compute optimized) instances. Configure a minimum capacity of 3, a desired capacity of 3, and a maximum capacity of 12. B. Configure the Auto Scaling group to deploy m6g.4xlarge (general purpose) instances. Configure a minimum capacity of 3, a desired capacity of 3, and a maximum capacity of 12. C. Configure the Auto Scaling group to deploy r6g.4xlarge (memory optimized) instances. Configure a minimum capacity of 3, a desired capacity of 3, and a maximum capacity of 12. D. Configure the Auto Scaling group to deploy r6g.8xlarge (memory optimized) instances. Configure a minimum capacity of 2, a desired capacity of 2, and a maximum capacity of 6.
C. Configure the Auto Scaling group to deploy r6g.4xlarge (memory optimized) instances. Configure a minimum capacity of 3, a desired capacity of 3, and a maximum capacity of 12.
Explanation
Question 474:
A company is refactoring its on-premises order-processing platform in the AWS Cloud. The platform includes a web front end that is hosted on a fleet of VMs RabbitMQ to connect the front end to the backend, and a Kubernetes cluster to run a containerized backend system to process the orders. The company does not want to make any major changes to the application
Which solution will meet these requirements with the LEAST operational overhead?
A. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up Amazon MQ to replace the on- premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend B. Create a custom AWS Lambda runtime to mimic the web server environment Create an Amazon API Gateway API to replace the front-end web servers Set up Amazon MQ to replace the on-premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend C. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up Amazon MQ to replace the on- premises messaging queue Install Kubernetes on a fleet of different EC2 instances to host the order-processing backend D. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up an Amazon Simple Queue Service (Amazon SQS) queue to replace the on-premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend
A. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up Amazon MQ to replace the on- premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend
A company has a solution that analyzes weather data from thousands of weather stations. The weather stations send the data over an Amazon API Gateway REST API that has an AWS Lambda function integration. The Lambda function calls a third-party service for data pre-processing. The third-party service gets overloaded and fails the pre-processing, causing a loss of data.
A solutions architect must improve the resiliency of the solution. The solutions architect must ensure that no data is lost and that data can be processed later if failures occur.
What should the solutions architect do to meet these requirements?
A. Create an Amazon Simple Queue Service (Amazon SQS) queue. Configure the queue as the dead-letter queue for the API. B. Create two Amazon Simple Queue Service (Amazon SQS) queues: a primary queue and a secondary queue. Configure the secondary queue as the dead-letter queue for the primary queue. Update the API to use a new integration to the primary queue. Configure the Lambda function as the invocation target for the primary queue. C. Create two Amazon EventBridge event buses: a primary event bus and a secondary event bus. Update the API to use a new integration to the primary event bus. Configure an EventBridge rule to react to all events on the primary event bus. Specify the Lambda function as the target of the rule. Configure the secondary event bus as the failure destination for the Lambda function. D. Create a custom Amazon EventBridge event bus. Configure the event bus as the failure destination for the Lambda function.
B. Create two Amazon Simple Queue Service (Amazon SQS) queues: a primary queue and a secondary queue. Configure the secondary queue as the dead-letter queue for the primary queue. Update the API to use a new integration to the primary queue. Configure the Lambda function as the invocation target for the primary queue.
Explanation
B is the best solution. It uses two Amazon SQS queues to ensure that incoming data is not lost and can be processed later in case of failures. The primary queue acts as the initial landing point for data from the API Gateway, and the secondary queue serves as a dead-letter queue, capturing data that could not be processed due to third-party service failures or other issues. This setup maintains data integrity and allows for later processing, effectively improving the solution's resiliency.
Question 476:
A live-events company is designing a scaling solution for its ticket application on AWS. The application has high peaks of utilization during sale events. Each sale event is a one-time event that is scheduled. The application runs on Amazon EC2 instances that are in an Auto Scaling group.
The application uses PostgreSQL for the database layer.
The company needs a scaling solution to maximize availability during the sale events.
Which solution will meet these requirements?
A. Use a predictive scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSQL Serverless v2 Multi-AZ DB instance with automatically scaling read replicas. Create an AWS Step Functions state machine to run parallel AWS Lambda functions to pre-warm the database before a sale event. Create an Amazon EventBridge rule to invoke the state machine. B. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazon RDS for PostgreSQL Multi-AZ DB instance with automatically scaling read replicas. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger read replica before a sale event. Fail over to the larger read replica. Create another EventBridge rule that invokes another Lambda function to scale down the read replica after the sale event. C. Use a predictive scaling policy for the EC2 instances. Host the database on an Amazon RDS for PostgreSQL Multi-AZ DB instance with automatically scaling read replicas. Create an AWS Step Functions state machine to run parallel AWS Lambda functions to pre-warm the database before a sale event. Create an Amazon EventBridge rule to invoke the state machine. D. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSQL Multi-AZ DB cluster. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event. Fail over to the larger Aurora Replica. Create another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event.
D. Use a scheduled scaling policy for the EC2 instances. Host the database on an Amazon Aurora PostgreSQL Multi-AZ DB cluster. Create an Amazon EventBridge rule that invokes an AWS Lambda function to create a larger Aurora Replica before a sale event. Fail over to the larger Aurora Replica. Create another EventBridge rule that invokes another Lambda function to scale down the Aurora Replica after the sale event.
Explanation
: The correct answer is
D.
D. This solution meets the requirements because it uses a scheduled scaling policy for the EC2 instances, which can adjust the capacity according to the known sale events. It also uses Amazon Aurora PostgreSQL Multi-AZ DB cluster, which provides high availability and durability for the database. It uses Amazon EventBridge rules and AWS Lambda functions to create a larger Aurora Replica before a sale event and fail over to it, which can improve the performance and handle the increased traffic. It also uses another EventBridge rule and Lambda function to scale down the Aurora Replica after the sale event, which can save costs123 A. This solution is incorrect because it uses predictive scaling policy for the EC2 instances, which is not suitable for one-time events that are scheduled. Predictive scaling is based on historical data and machine learning, which may not accurately forecast the demand for sale events. It also uses Amazon Aurora PostgreSQL Serverless v2 Multi-AZ DB instance, which does not support read replicas. The use of AWS Step Functions state machine and Lambda functions to pre- warm the database is unnecessary and adds complexity45
B. This solution is incorrect because it uses Amazon RDS for PostgreSQL Multi-AZ DB instance with automatically scaling read replicas, which may not provide enough performance improvement for the sale events. The use of EventBridge rules and Lambda functions to create a larger read replica and fail over to it is risky and may cause downtime or data loss. The use of another EventBridge rule and Lambda function to scale down the read replica is also risky and may cause inconsistency or data loss67
C. This solution is incorrect because it uses predictive scaling policy for the EC2 instances, which is not suitable for one-time events that are scheduled. Predictive scaling is based on historical data and machine learning, which may not accurately forecast the demand for sale events. The use of AWS Step Functions state machine and Lambda functions to pre- warm the database is unnecessary and adds complexity45
References:
1: Scheduled scaling for Amazon EC2 Auto Scaling 2: Amazon Aurora PostgreSQL features 3: Amazon EventBridge rules 4: Predictive scaling for Amazon EC2 Auto Scaling
5: Amazon Aurora Serverless v2 6: Multi-AZ DB instance deployments - Amazon Relational Database Service 7: Working with PostgreSQL read replicas - Amazon Relational Database Service
Question 477:
A company has an application that uses an on-premises Oracle database. The company is migrating the database to the AWS Cloud. The database contains customer data and stored procedures.
The company needs to migrate the database as quickly as possible with minimum downtime. The solution on AWS must provide high availability and must use managed services for the database.
Which solution will meet these requirements?
A. Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon RDS for Oracle database. Transfer the database files to an Amazon S3 bucket. Configure the RDS database to use the S3 bucket as database storage. Set up S3 replication for high availability. Redirect the application to the RDS DB instance. B. Create a database backup of the on-premises Oracle database. Upload the backup to an Amazon S3 bucket. Shut down the on-premises Oracle database to avoid any new transactions. Restore the backup to a new Oracle cluster that consists of Amazon EC2 instances across two Availability Zones. Redirect the application to the EC2 instances. C. Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon DynamoDB table. Use DynamoDB Accelerator (DAX) and implement global tables for high availability. Rewrite the stored procedures in AWS Lambda. Run the stored procedures in DAX. After replication, redirect the application to the DAX cluster endpoint. D. Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon Aurora PostgreSQL database. Use AWS SCT to convert the schema and stored procedures. Redirect the application to the Aurora DB cluster.
D. Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon Aurora PostgreSQL database. Use AWS SCT to convert the schema and stored procedures. Redirect the application to the Aurora DB cluster.
Explanation
Question 478:
A company needs to run a software package that has a license that must be run on the same physical host for the duration of Its use. The software package is only going to be used for 90 days The company requires patching and restarting of all instances every 30 days
How can these requirements be met using AWS?
A. Run a dedicated instance with auto-placement disabled. B. Run the instance on a dedicated host with Host Affinity set to Host. C. Run an On-Demand Instance with a Reserved Instance to ensure consistent placement. D. Run the instance on a licensed host with termination set for 90 days.
B. Run the instance on a dedicated host with Host Affinity set to Host.
Explanation
Host Affinity is configured at the instance level. It establishes a launch relationship between an instance and a Dedicated Host. (This set which host the instance can run on) Auto-placement allows you to manage whether instances that you launch are launched onto a specific host, or onto any available host that has matching configurations. Auto-placement must be configured at the host level. (This sets which instance the host can run.) When affinity is set to Host, an instance launched onto a specific host always restarts on the same host if stopped. This applies to both targeted and untargeted launches.https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/how-dedicated-hosts- work.html When affinity is set to Off, and you stop and restart the instance, it can be restarted on any available host. However, it tries to launch back onto the last Dedicated Host on which it ran (on a best-effort basis).
Question 479:
A solutions architect is designing a solution to connect a company's on-premises network with all the company's current and future VPCs on AWS. The company is running VPCs in five different AWS Regions and has at least 15 VPCs in each Region.
The company's AWS usage is constantly increasing and will continue to grow. Additionally, all the VPCs throughout all five Regions must be able to communicate with each other.
The solution must maximize scalability and ease of management.
Which solution meets these requirements?
A. Set up a transit gateway in each Region Establish a redundant AWS Site-to-Site VPN connection between the on-premises firewalls and the transit gateway in the Region that is closest to the on-premises network Peer all the transit gateways with each other Connect all the VPCs to the transit gateway in their Region B. Create an AWS CloudFormation template for a redundant AWS Site-to-Site VPN tunnel to the on-premises network Deploy the CloudFormation template for each VPC Set up VPC peering between all the VPCs for VPC-to-VPC communication C. Set up a transit gateway in each Region Establish a redundant AWS Site-to-Site VPN connection between the on-premises firewalls and each transit gateway Route traffic between the different Regions through the company's on-premises firewalls Connect all the VPCs to the transit gateway in their Region D. Create an AWS CloudFormation template for a redundant AWS Site-to-Site VPN tunnel to the on-premises network Deploy the CloudFormation template for each VPC Route traffic between the different Regions through the company's on-premises firewalls
A. Set up a transit gateway in each Region Establish a redundant AWS Site-to-Site VPN connection between the on-premises firewalls and the transit gateway in the Region that is closest to the on-premises network Peer all the transit gateways with each other Connect all the VPCs to the transit gateway in their Region
Explanation
Question 480:
A company is migrating its on-premises file transfer solution to AWS Transfer Family. The on-premises host includes an SFTP server to receive files, an application that performs a transformation of the files, and a messaging server. The transformations run every 5 minutes. When a transformation is complete, the application sends a message to a queue on the messaging server. The company needs to simplify the solution and reduce the management of the components. What should the company do to meet these requirements with the LEAST operational overhead?
A. Configure Transfer Family to use Amazon EFS storage. Use a cron job on Amazon EFS to perform the transformations. Configure the cron job to publish a message to an Amazon SNS topic when a file has been transformed. B. Configure Transfer Family to use Amazon S3 storage. Use Amazon EMR to perform the transformations. Configure Amazon EMR to send a message to an Amazon SNS topic when a file has been transformed. C. Configure Transfer Family to use Amazon S3 storage. Use AWS Glue to perform the transformations after S3 event notifications. Configure AWS Glue to send a message to an Amazon SQS queue when a file has been transformed. D. Configure Transfer Family to use Amazon EFS storage. Create an AWS Glue time- based job to run every 5 minutes to initiate an AWS Glue transformation. Configure AWS Glue to send a message to an Amazon SQS queue when a file has been transformed.
C. Configure Transfer Family to use Amazon S3 storage. Use AWS Glue to perform the transformations after S3 event notifications. Configure AWS Glue to send a message to an Amazon SQS queue when a file has been transformed.
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