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Amazon SAP-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Continuous Improvement for Existing Solutions	25%	- Apply security best practices and compliance updates - Implement monitoring, logging, and observability - Refactor and modernize legacy applications - Optimize existing workloads for cost, performance, and security
Design for New Solutions	29%	- Design high-performing and scalable solutions - Design cost-optimized architectures - Design secure and resilient architectures - Design for reliability and fault tolerance
Design Solutions for Organizational Complexity	26%	- Design for compliance and governance requirements - Design for operational excellence and automation - Design multi-account and multi-region architectures - Design hybrid and multi-cloud networking
Accelerate Workload Migration and Modernization	20%	- Migrate applications, data, and infrastructure - Modernize applications and data platforms - Integrate AWS services with existing systems - Develop migration strategies and plans

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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q807-Q812):

NEW QUESTION # 807
A Solutions Architect is constructing a containerized.NET Core application for AWS Fargate. The application's backend needs a high-availability version of Microsoft SQL Server. All application levels must be extremely accessible. The credentials associated with the SQL Server connection string should not be saved to disk inside the.NET Core front-end containers.
Which tactics should the Solutions Architect use to achieve these objectives?

A. Create an Auto Scaling group to run SQL Server on Amazon EC2. Create a secret in AWS Secrets Manager for the credentials to SQL Server running on EC2. Create an Amazon ECS task execution role that allows the Fargate task definition to get the secret value for the credentials to SQL Server on EC2. Specify the ARN of the secret in Secrets Manager in the secrets section of the Fargate task definition so the sensitive data can be injected into the containers as environment variables on startup for reading into the application to construct the connection string. Set up the .NET Core service using Service Auto Scaling behind an Application Load Balancer in multiple Availability Zones.
B. Create a Multi-AZ deployment of SQL Server on Amazon RDS. Create a secret in AWS Secrets Manager for the credentials to the RDS database. Create non- persistent empty storage for the .NET Core containers in the Fargate task definition to store the sensitive information. Create an Amazon ECS task execution role that allows the Fargate task definition to get the secret value for the credentials to the RDS database in Secrets Manager. Specify the ARN of the secret in Secrets Manager in the secrets section of the Fargate task definition so the sensitive data can be written to the non-persistent empty storage on startup for reading into the application to construct the connection string. Set up the .NET Core service using Service Auto Scaling behind an Application Load Balancer in multiple Availability Zones.
C. Create a Multi-AZ deployment of SQL Server on Amazon RDS. Create a secret in AWS Secrets Manager for the credentials to the RDS database. Create an Amazon ECS task execution role that allows the Fargate task definition to get the secret value for the credentials to the RDS database in Secrets Manager. Specify the ARN of the secret in Secrets Manager in the secrets section of the Fargate task definition so the sensitive data can be injected into the containers as environment variables on startup for reading into the application to construct the connection string. Set up the .NET Core service in Fargate using Service Auto Scaling behind an Application Load Balancer in multiple Availability Zones.
D. Set up SQL Server to run in Fargate with Service Auto Scaling. Create an Amazon ECS task execution role that allows the Fargate task definition to get the secret value for the credentials to SQL Server running in Fargate. Specify the ARN of the secret in AWS Secrets Manager in the secrets section of the Fargate task definition so the sensitive data can be injected into the containers as environment variables on startup for reading into the application to construct the connection string. Set up the .NET Core service using Service Auto Scaling behind an Application Load Balancer in multiple Availability Zones.

Answer: C

Explanation:
Secrets Manager natively supports SQL Server on RDS. No real need to create additional 'ephemeral storage' to fetch credentials, as these can be injected to containers as environment variables. https://aws.amazon.com/premiumsupport/knowledge-center/ecs-data-security-container-task/

NEW QUESTION # 808
A video processing company uses an AWS Lambda function to handle image processing tasks.
An Amazon EventBridge rule that matches the event pattern when a new image is uploaded to an Amazon S3 bucket invokes the Lambda function. The processing task initially operated without errors.
The Lambda function now encounters frequent timeout errors. The Lambda function is configured with the maximum timeout value. A solutions architect must refactor the application's architecture to mitigate invocation failures.
Which combination of steps will meet these requirements with the LEAST operational overhead?
(Choose two.)

A. Build a Docker container image with the application code for deployment. Store the container image in Amazon ECR.
B. Create a new Amazon ECS deployment with the Fargate launch type. Configure the ECS task definition to use the new Docker container image. Configure EventBridge to invoke an ECS task by using the ECS task definition.
C. Create a new Amazon ECS deployment with the Amazon EC2 launch type. Configure the ECS task definition to use the new Docker container image. Configure the Lambda function to invoke an ECS task by using the ECS task definiti
D. Create a new AWS Step Functions state machine. Configure the state machine to use the new Docker container image. Configure the Lambda function to invoke the state machine when a new file arrives in Amazon S3.
E. Build a Docker container image with the application code for deployment. Store the container image in an S3 bucket with S3 Versioning enabled.

Answer: B,D

Explanation:
Moving the processing to Amazon ECS with the Fargate launch type helps by using containers without needing to manage EC2 instances. The Fargate option handles scaling automatically, reducing operational overhead. EventBridge can be configured to trigger ECS tasks when new files arrive in S3.
AWS Step Functions allows the orchestration of complex workflows. Refactoring the Lambda function to trigger a state machine can help offload the work from the Lambda function and allow for better handling of timeouts and retries. Step Functions can manage the image processing flow and integrate with other AWS services, offering a scalable solution.

NEW QUESTION # 809
A company wants to modernize a monolithic application in the company's data center and deploy the application on AWS. The monolithic application consists of an event broker in a central account and multiple microservices in individual AWS accounts. The event broker and the microservices are deployed on Amazon ECS clusters that use the Fargate launch type.
Multiple microservices need access to the same events from the event broker. The company wants to distribute events from the central event broker to each microservice across accounts.
Which solution will meet these requirements?

A. Create a data stream in Amazon Kinesis Data Streams in the central account. Create an IAM policy to grant the necessary permissions to access the data stream. Set each of the microservices as an event source on the Kinesis stream. Configure the stream to invoke each microservice.
B. Create a new Amazon EventBridge event bus in the central account with the required permissions. Add EventBridge rules filtered by service for each microservice. Invoke the rules to route events to other accounts.
C. Create an Amazon SNS topic in the central account. Add a topic policy to allow other accounts to subscribe to the topic. Create an Amazon SQS queue in each individual AWS account. Subscribe the SQS queue to the SNS topic. Configure the microservices to read events from their own SQS queue.
D. Create a new Amazon SQS queue as the event broker in the central account. Grant the required permissions. Configure each of the microservices to read messages from the central SQS queue.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
This explanation is based on AWS documentation and best practices but is paraphrased, not a literal extract.
The scenario describes a central event broker and multiple microservices running in separate AWS accounts that all need to consume the same events. The requirement is to distribute events from a central location to many microservices across accounts in a scalable and loosely coupled way, as part of modernizing to a microservices architecture.
Amazon EventBridge is a serverless event bus service designed for event-driven architectures. It supports centralized event buses, rich content-based filtering with rules, and cross-account event routing. With EventBridge, you can create an event bus in a central account and define rules that match specific event patterns (for example, by microservice or event type). Each rule can have one or more targets, including event buses in other AWS accounts. This supports the pattern of having a central event bus in one account and distributing relevant events to other accounts, where each microservice consumes events either directly from its own event bus or through additional rules and targets in its own account.
In this solution, you create a new EventBridge event bus in the central account and grant the appropriate permissions for cross-account access (option B). You then define EventBridge rules on the central event bus, filtered per microservice or per event category, and configure the rules to send events to the respective event buses or targets in the microservices' accounts. EventBridge handles the fan-out and delivery of events across accounts in a managed, scalable way, which aligns with the modernization goal and reduces the operational overhead of managing custom routing or polling logic.
Option A uses an SNS topic with SQS queues in each account. This is a valid fan-out pattern and supports cross-account subscriptions, but it is more suited to traditional pub/sub messaging and does not provide the event routing, filtering, and observability features that EventBridge offers for modern event-driven microservices. In scenarios that explicitly mention an event broker and modernization, EventBridge is the recommended service.
Option C is incorrect because Kinesis Data Streams is designed for high-throughput streaming data and requires building and managing consumer applications. The description in the option is also technically inaccurate; Kinesis does not "invoke" microservices directly as event targets in the same way as EventBridge or SNS does. Instead, applications must read from the stream.
Option D uses a single central SQS queue that all microservices read from. SQS provides at-least-once delivery to competing consumers, which means multiple consumers reading from the same queue will typically share messages rather than each getting all messages. This does not satisfy the requirement for multiple microservices to each receive the same events independently. It also reduces decoupling and observability compared to an event bus model.
Therefore, creating an Amazon EventBridge event bus in the central account with rules to distribute events across accounts (option B) best meets the requirements for distributing events from a central broker to multiple microservices across accounts in a modernized architecture.
References:AWS documentation on Amazon EventBridge event buses, cross-account event routing, and rule- based filtering and targeting.AWS guidance for event-driven microservices architectures and centralized event broker patterns.

NEW QUESTION # 810
A software as a service (SaaS) company uses AWS to host a service that is powered by AWS PrivateLink. The service consists of proprietary software that runs on three Amazon EC2 instances behind a Network Load Balancer (NLB). The instances are in private subnets in multiple Availability Zones in the eu-west-2 Region. All the company's customers are in eu-west-
2.
However, the company now acquires a new customer in the us-east-1 Region. The company creates a new VPC and new subnets in us-east-1. The company establishes inter-Region VPC peering between the VPCs in the two Regions.
The company wants to give the new customer access to the SaaS service, but the company does not want to immediately deploy new EC2 resources in us-east-1.
Which solution will meet these requirements?

A. Use AWS Resource Access Manager (AWS RAM) to share the EC2 instances that are in eu- west-2. In us-east-1, create an NLB and an instance target group that includes the shared EC2 instances from eu-west-2. Configure a PrivateLink endpoint service that uses the NLB that is in us-east-1. Grant specific AWS accounts access to connect to the SaaS service.
B. Create an NLB in us-east-1. Create an IP target group that uses the IP addresses of the company's instances in eu-west-2 that host the SaaS service. Configure a PrivateLink endpoint service that uses the NLB that is in us-east-1. Grant specific AWS accounts access to connect to the SaaS service.
C. Create an Application Load Balancer (ALB) in front of the EC2 instances in eu-west-2. Create an NLB in us-east-1. Associate the NLB that is in us-east-1 with an ALB target group that uses the ALB that is in eu-west-2. Configure a PrivateLink endpoint service that uses the NLB that is in us- east-1. Grant specific AWS accounts access to connect to the SaaS service.
D. Configure a PrivateLink endpoint service in us-east-1 to use the existing NLB that is in eu-west-2.
Grant specific AWS accounts access to connect to the SaaS service.

Answer: D

Explanation:
* Configuring a PrivateLink endpoint service in us-east-1 to use the existing NLB that is in eu- west-2 will allow the new customer to access the SaaS service without deploying new EC2 resources in us-east-1 1.
* Granting specific AWS accounts access to connect to the SaaS service will ensure that only authorized users can access the service 1.

NEW QUESTION # 811
A company's inventory application stores data in an Amazon Aurora PostgreSQL DB cluster in a single AWS Region. The company wants to improve resiliency by extending the database infrastructure to a secondary Region. The company wants an RTO of 15 minutes and an RPO of 5 minutes. The solution must not run Aurora DB instances in the secondary Region when the application is operational in the primary Region.
Which solution meets these requirements?

A. Create an AWS Backup job to back up the DB cluster and copy the DB cluster to the secondary Region every 5 minutes.
B. Configure AWS DMS to copy the Aurora DB cluster in the primary Region to the secondary Region.
Use AWS DMS to synchronize the primary DB cluster with the secondary DB cluster.
C. Create a headless Aurora DB cluster in the second Region that is part of the same global DB cluster as the primary Region's DB cluster.
D. Create a new Aurora PostgreSQL DB cluster in the secondary Region. Use AWS Backup to synchronize the primary DB cluster with the secondary DB cluster.

Answer: C

Explanation:
Creating a headless Aurora DB cluster in the secondary Region as part of an Aurora global database ensures continuous, low-latency replication without running active instances in the secondary Region.
This configuration meets the RTO and RPO requirements by allowing rapid promotion of the secondary cluster in a failover scenario.
It also reduces operational costs compared to continuously running standby instances in the secondary Region.
This aligns with AWS best practices for DR and cross-Region resiliency.

NEW QUESTION # 812
......

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