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The SAP-C02 exam is designed to test the knowledge and skills of professionals in designing and deploying AWS solutions using best practices and architectural principles. SAP-C02 exam consists of multiple-choice questions and takes approximately 180 minutes to complete. The questions are designed to test the candidate's ability to understand and apply AWS services and features in different scenarios.

Amazon SAP-C02 Exam is a professional-level certification offered by Amazon Web Services (AWS) for individuals who want to prove their expertise in designing and deploying AWS-based solutions. AWS Certified Solutions Architect - Professional (SAP-C02) certification is designed to test your knowledge and skills in various areas related to AWS architecture, including security, scalability, reliability, and cost optimization.

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The SAP-C02 exam tests candidates' skills in designing and deploying AWS solutions at scale, including designing and deploying multi-tier applications, designing and deploying highly available and fault-tolerant systems, and designing and deploying secure and compliant AWS solutions. SAP-C02 Exam also covers advanced topics such as designing and deploying AWS services for data management, designing and deploying AWS services for networking, and designing and deploying AWS services for security and compliance.

Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q221-Q226):

NEW QUESTION # 221
A publishing company's design team updates the icons and other static assets that an ecommerce web application uses. The company serves the icons and assets from an Amazon S3 bucket that is hosted in the company's production account. The company also uses a development account that members of the design team can access.
After the design team tests the static assets in the development account, the design team needs to load the assets into the S3 bucket in the production account. A solutions architect must provide the design team with access to the production account without exposing other parts of the web application to the risk of unwanted changes.
Which combination of steps will meet these requirements? (Select THREE.)

A. In the development account, create a group that contains all tfje IAM users of the design team. Attach a different IAM policy to the group to allow the sts;AssumeRole action on the role in the development account.
B. In the production account, create a role. Attach the new policy to the role. Define the development account as a trusted entity.
C. In the development account, create a new IAM policy that allows read and write access to the S3 bucket.
D. In the development account, create a group that contains all the IAM users of the design team. Attach a different IAM policy to the group to allow the sts:AssumeRole action on the role in the production account.
E. In the production account, create a new IAM policy that allows read and write access to the S3 bucket.
F. In the development account, create a role. Attach the new policy to the role. Define the production account as a trusted entity.

Answer: D,E,F

NEW QUESTION # 222
A company has applications in an AWS account that is named Source. The account is in an organization in AWS Organizations. One of the applications uses AWS Lambda functions and stores inventory data in an Amazon Aurora database. The application deploys the Lambda functions by using a deployment package. The company has configured automated backups for Aurora.
The company wants to migrate the Lambda functions and the Aurora database to a new AWS account that is named Target. The application processes critical data, so the company must minimize downtime.
Which solution will meet these requirements?

A. Download the Lambda function deployment package from the Source account. Use the deployment package and create new Lambda functions in the Target account. Share the automated Aurora DB cluster snapshot with the Target account.
B. Download the Lambda function deployment package from the Source account. Use the deployment package and create new Lambda functions in the Target account Share the Aurora DB cluster with the Target account by using AWS Resource Access Manager {AWS RAM). Grant the Target account permission to clone the Aurora DB cluster.
C. Use AWS Resource Access Manager (AWS RAM) to share the Lambda functions with the Target account. Share the automated Aurora DB cluster snapshot with the Target account.
D. Use AWS Resource Access Manager (AWS RAM) to share the Lambda functions and the Aurora DB cluster with the Target account. Grant the Target account permission to clone the Aurora DB cluster.

Answer: B

Explanation:
This solution uses a combination of AWS Resource Access Manager (RAM) and automated backups to migrate the Lambda functions and the Aurora database to the Target account while minimizing downtime. In this solution, the Lambda function deployment package is downloaded from the Source account and used to create new Lambda functions in the Target account. The Aurora DB cluster is shared with the Target account using AWS RAM and the Target account is granted permission to clone the Aurora DB cluster, allowing for a new copy of the Aurora database to be created in the Target account. This approach allows for the data to be migrated to the Target account while minimizing downtime, as the Target account can use the cloned Aurora database while the original Aurora database continues to be used in the Source account.

NEW QUESTION # 223
A company is using Amazon API Gateway to deploy a private REST API that will provide access to sensitive data. The API must be accessible only from an application that is deployed in a VPC. The company deploys the API successfully. However, the API is not accessible from an Amazon EC2 instance that is deployed in the VPC.
Which solution will provide connectivity between the EC2 instance and the API?

A. Create an Application Load Balancer (ALB) and a VPC Link. Configure private integration between API Gateway and the ALB. Use the ALB endpoint's DNS name to access the API.
B. Create an interface VPC endpoint for API Gateway. Attach an endpoint policy that allows the execute-api:lnvoke action. Enable private DNS naming for the VPC endpoint. Configure an API resource policy that allows access from the VPC endpoint. Use the API endpoint's DNS names to access the API. Most Voted
C. Create an interface VPC endpoint for API Gateway. Attach an endpoint policy that allows apigateway:* actions. Disable private DNS naming for the VPC endpoint. Configure an API resource policy that allows access from the VPC. Use the VPC endpoint's DNS name to access the API.
D. Create a Network Load Balancer (NLB) and a VPC link. Configure private integration between API Gateway and the NLB. Use the API endpoint's DNS names to access the API.

Answer: B

Explanation:
Explanation
According to the AWS documentation1, to access a private API from a VPC, you need to do the following:
Create an interface VPC endpoint for API Gateway in your VPC. This creates a private connection between your VPC and API Gateway.
Attach an endpoint policy to the VPC endpoint that allows the execute-api:lnvoke action for your private API. This grants permission to invoke your API from the VPC.
Enable private DNS naming for the VPC endpoint. This allows you to use the same DNS names for your private APIs as you would for public APIs.
Configure a resource policy for your private API that allows access from the VPC endpoint. This controls who can access your API and under what conditions.
Use the API endpoint's DNS names to access the API from your VPC. For example,
https://api-id.execute-api.region.amazonaws.com/stage.

NEW QUESTION # 224
A company has implemented a global multiplayer gaming platform The platform requires gaming clients to have reliable, low-latency access to the server infrastructure that is hosted on a fleet of Amazon EC2 instances in a single AWS Region The gaming clients use a custom TCP protocol to connect to the server infrastructure The application architecture requires client IP addresses to be available to the server software Which solution meets these requirements?

A. Use an AWS Direct Connect gateway to connect multiple Direct Connect locations in different Regions globally Configure Amazon Route 53 with geolocation routing to send traffic to the nearest Direct Connect location Associate the VPC that contains the EC2 instances with the Direct Connect gateway
B. Create an Application Load Balancer (ALB) and add the EC2 instances to a target group Create a set of Amazon Route 53 latency-based alias records that point to the DNS endpoint of the ALB Use X-Forwarded-For headers to preserve client IP addresses
C. Create an accelerator in AWS Global Accelerator and configure the listener to point to a single endpoint group Add each of the EC2 instances as endpoints to the endpoint group Configure the endpoint group weighting equally across all of the EC2 endpoints
D. Create a Network Load Balancer (NLB), and add the EC2 instances to a target group Create an Amazon CloudFront Real Time Messaging Protocol (RTMP) distribution and configure the origin to point to the DNS endpoint of the NLB Use proxy protocol version 2 headers to preserve client IP addresses

Answer: A

NEW QUESTION # 225
A company needs to run large batch-processing jobs on data that is stored in an Amazon S3 bucket. The jobs perform simulations. The results of the jobs are not time sensitive, and the process can withstand interruptions.
Each job must process 15-20 GB of data when the data is stored in the S3 bucket. The company will store the output from the jobs in a different Amazon S3 bucket for further analysis.
Which solution will meet these requirements MOST cost-effectively?

A. Create an AWS Batch compute environment that includes Amazon EC2 Spot Instances. Specify the SPOT_CAPACITY_OPTIMIZED allocation strategy.
B. Use Amazon EKS to run the processing jobs. Use managed node groups that contain a combination of Amazon EC2 On-Demand Instances and Spot Instances.
C. Create an AWS Batch compute environment that includes Amazon EC2 On-Demand Instances and Spot Instances. Specify the SPOT_CAPACITY_OPTIMIZED allocation strategy for the Spot Instances.
D. The workload consists of large batch-processing simulation jobs that read 15-20 GB per job from Amazon S3, write results back to S3, are not time sensitive, and can tolerate interruptions. These characteristics are ideal for using EC2 Spot Instances, which provide steep discounts compared to On- Demand pricing in exchange for potential interruptions.
AWS Batch is designed specifically for batch and simulation workloads. It can dynamically provision compute resources, manage job queues, retry failed jobs, and integrate tightly with EC2 Spot Instances.
Using an AWS Batch compute environment that is configured to use EC2 Spot Instances with the SPOT_CAPACITY_OPTIMIZED allocation strategy allows AWS Batch to choose the lowest interruption-risk Spot capacity pools automatically while still giving the largest cost savings.
E. Create a serverless data pipeline. Use AWS Step Functions for orchestration. Use AWS Lambda functions with provisioned capacity to process the data.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Option B leverages these capabilities. It creates an AWS Batch compute environment using only Spot Instances and uses the SPOT_CAPACITY_OPTIMIZED allocation strategy to select capacity across instance types with lower interruption rates. Since the simulations are not time sensitive and can withstand interruptions, the risk of Spot interruptions is acceptable, and AWS Batch will re-run interrupted jobs as needed. This combination provides the most cost-effective solution while minimizing operational overhead for job scheduling and capacity management.
Option A uses Lambda with Step Functions. Lambda has limits on memory, runtime, and payload size, making it a poor fit for processing 15-20 GB of data per job. In addition, the concurrency and invocation cost for large-scale, long-running simulation workloads would be higher and less cost- effective than EC2 Spot Instances.
Option C mixes On-Demand and Spot Instances. While this can provide reliability for more time- critical workloads, it is less cost-effective than a pure Spot configuration when the workload explicitly can tolerate interruptions and is not time sensitive.
Option D uses Amazon EKS with a mix of On-Demand and Spot Instances. While this can be made to work, it requires managing Kubernetes clusters, node groups, and job scheduling, which introduces more operational complexity than using AWS Batch, and the inclusion of On-Demand capacity reduces cost-effectiveness compared to pure Spot-based batch processing.Therefore, using AWS Batch with EC2 Spot Instances and the SPOT_CAPACITY_OPTIMIZED allocation strategy (option B) is the most cost-effective solution for this tolerant, batch-processing workload.
References:AWS documentation on AWS Batch for running batch and simulation jobs.AWS guidance on using EC2 Spot Instances and the SPOT_CAPACITY_OPTIMIZED allocation strategy for cost-effective, interruption-tolerant workloads.

NEW QUESTION # 226
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