Amazon Web Services SAP-C02 Study & Exam Dumps 2025

AWS Certified Solutions Architect - Professional Questions and Answers

Question 1

A research company conducts mathematical simulations in the AWS Cloud. The simulations run on several hundred Amazon EC2 Linux instances. If a simulation encounters an issue, an engineer establishes an SSH connection to the affected EC2 instance.

Company policy requires that each EC2 instance session is established with a unique SSH key and that all SSH connections are logged in AWS CloudTrail. CloudTrail is enabled for the company’s account and the AWS Regions that the company uses.

Which solution will meet these requirements?

Options:

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Answer:

Launch new EC2 instances. Generate an individual SSH key for each new EC2 instance. Store the SSH key in AWS Secrets Manager. Create a new IAM policy. Attach the IAM policy to the engineers ' IAM role with an Allow statement for the GetSecretValue action. Instruct the engineers to retrieve the SSH key from Secrets Manager when the engineers connect through any SSH client.

Answer:

Create an AWS Systems Manager document to run commands on EC2 instances to set a new unique SSH key. Create a new IAM policy. Attach the IAM policy to the engineers ' IAM role with an Allow statement to run Systems Manager documents. Instruct the engineers to run the document to set an SSH key and to connect through any SSH client.

Answer:

Launch new EC2 instances without setting up any SSH key for the new EC2 instances. Set up EC2 Instance Connect on each new EC2 instance. Create a new IAM policy. Attach the IAM policy to the engineers ' IAM role with an Allow statement for the SendSSHPublicKey action. Instruct the engineers to connect to the EC2 instances by using Instance Connect from the AWS CLI.

Answer:

Set up AWS Secrets Manager to store the EC2 SSH key. Create an AWS Lambda function to create a new SSH key and to call AWS Systems Manager Session Manager to set the SSH key on the EC2 instance. Configure Secrets Manager to use the Lambda function to automatically rotate the SSH key once daily. Instruct the engineers to retrieve the SSH key from Secrets Manager when the engineers connect through any SSH client.

Answer:

C is correct because EC2 Instance Connect pushes a temporary SSH public key to the instance for a short connection window instead of relying on long-lived shared key pairs. This satisfies the requirement that each SSH session use a unique key. AWS documentation states that the SendSSHPublicKey API pushes an SSH public key to the specified instance and that the key remains for 60 seconds. EC2 API calls, including SendSSHPublicKey, are recorded in CloudTrail, which gives the company auditable connection records. Secrets Manager key storage does not inherently log actual SSH connection attempts and still leaves operational complexity around key retrieval and rotation. Systems Manager documents also do not provide the clean session-specific SSH key behavior that EC2 Instance Connect provides.

Question 2

A company wants to use a third-party software-as-a-service (SaaS) application. The third-party SaaS application is consumed through several API calls. The third-party SaaS application also runs on AWS inside a VPC.

The company will consume the third-party SaaS application from inside a VPC. The company has internal security policies that mandate the use of private connectivity that does not traverse the internet. No resources that run in the company VPC are allowed to be accessed from outside the company’s VPC. All permissions must conform to the principles of least privilege.

Which solution meets these requirements?

Options:

Create an AWS PrivateLink interface VPC endpoint. Connect this endpoint to the endpoint service that the third-party SaaS application provides. Create a security group to limit the access to the endpoint. Associate the security group with the endpoint.

Create an AWS Site-to-Site VPN connection between the third-party SaaS application and thecompany VPC. Configure network ACLs to limit access across the VPN tunnels.

Create a VPC peering connection between the third-party SaaS application and the company VPUpdate route tables by adding the needed routes for the peering connection.

Create an AWS PrivateLink endpoint service. Ask the third-party SaaS provider to create an interface VPC endpoint for this endpoint service. Grant permissions for the endpoint service to the specific account of the third-party SaaS provider.

Question 3

A company that provisions job boards for a seasonal workforce is seeing an increase in traffic and usage. The backend services run on a pair of Amazon EC2 instances behind an Application Load Balancer with Amazon DynamoDB as the datastore. Application read and write traffic is slow during peak seasons.

Which option provides a scalable application architecture to handle peak seasons with the LEAST development effort?

Options:

Migrate the backend services to AWS Lambda. Increase the read and write capacity of DynamoDB.

Migrate the backend services to AWS Lambda. Configure DynamoDB to use global tables.

Use Auto Scaling groups for the backend services. Use DynamoDB auto scaling.

Use Auto Scaling groups for the backend services. Use Amazon Simple Queue Service (Amazon SQS) and an AWS Lambda function to write to DynamoDB.

Answer:

Explanation:

Option C is correct because using Auto Scaling groups for the backend services allows the company to scale up or down the number of EC2 instances based on the demand and traffic. This way, the backend services can handle more requests during peak seasons without compromising performance or availability. Using DynamoDB auto scaling allows the company to adjust the provisioned read and write capacity of the table or index automatically based on the actual traffic patterns. This way, the table or index can handle sudden increases or decreases in workload without throttling or overprovisioning1.

Option A is incorrect because migrating the backend services to AWS Lambda may require significant development effort to rewrite the code and test the functionality. Moreover, increasing the read and write capacity of DynamoDB manually may not be efficient or cost-effective, as it does not account for the variability of the workload. The company may end up paying for unused capacity or experiencing throttling if the workload exceeds the provisioned capacity1.

Option B is incorrect because migrating the backend services to AWS Lambda may require significant development effort to rewrite the code and test the functionality. Moreover, configuring DynamoDB to use global tables may not be necessary or beneficial for the company, as global tables are mainly used for replicating data across multiple AWS Regions for fast local access and disaster recovery. Global tables do not automatically scale the provisioned capacity of each replica table; they still require manual or auto scaling settings2.

Option D is incorrect because using Amazon Simple Queue Service (Amazon SQS) and an AWS Lambda function to write to DynamoDB may introduce additional complexity and latency to the application architecture. Amazon SQS is a message queue service that decouples and coordinates the components of a distributed system. AWS Lambda is a serverless compute service that runs code in response to events. Using these services may require significant development effort to integrate them with the backend services and DynamoDB. Moreover, they may not improve the read performance of DynamoDB, which may also be affected by high traffic3.

Auto Scaling groups

DynamoDB auto scaling

AWS Lambda

DynamoDB global tables

AWS Lambda vs EC2: Comparison of AWS Compute Resources - Simform

Managing throughput capacity automatically with DynamoDB auto scaling - Amazon DynamoDB

AWS Aurora Global Database vs. DynamoDB Global Tables

Amazon Simple Queue Service (SQS)

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