Amazon Web Services SAP-C02 Study & Exam Dumps 2025

AWS Certified Solutions Architect - Professional Questions and Answers

Question 1

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.

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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)

Question 2

A software as a service (SaaS) based company provides a case management solution to customers A3 part of the solution. The company uses a standalone Simple Mail Transfer Protocol (SMTP) server to send email messages from an application. The application also stores an email template for acknowledgement email messages that populate customer data before the application sends the email message to the customer.

The company plans to migrate this messaging functionality to the AWS Cloud and needs to minimize operational overhead.

Which solution will meet these requirements MOST cost-effectively?

Options:

Set up an SMTP server on Amazon EC2 instances by using an AMI from the AWS Marketplace. Store the email template in an Amazon S3 bucket. Create an AWS Lambda function to retrieve the template from the S3 bucket and to merge the customer data from the application with the template. Use an SDK in the Lambda function to send the email message.

Set up Amazon Simple Email Service (Amazon SES) to send email messages. Store the email template in an Amazon S3 bucket. Create an AWS Lambda function to retrieve the template from the S3 bucket and to merge the customer data from the application with the template. Use an SDK in the Lambda function to send the email message.

Set up an SMTP server on Amazon EC2 instances by using an AMI from the AWS Marketplace. Store the email template in Amazon Simple Email Service (Amazon SES) with parameters for the customer data.Create an AWS Lambda function to call the SES template and to pass customer data to replace the parameters. Use the AWS Marketplace SMTP server to send the email message.

Set up Amazon Simple Email Service (Amazon SES) to send email messages. Store the email template on Amazon SES with parameters for the customer data. Create an AWS Lambda function to call the SendTemplatedEmail API operation and to pass customer data to replace the parameters and the email destination.

Question 3

A company is using AWS to develop and manage its production web application. The application includes an Amazon API Gateway HTTP API that invokes an AWS Lambda function. The Lambda function processes and then stores data in a database.

The company wants to implement user authorization for the web application in an integrated way. The company already uses a third-party identity provider that issues OAuth tokens for the company ' s other applications.

Which solution will meet these requirements?

Options:

Integrate the company ' s third-party identity provider with API Gateway. Configure an API Gateway Lambda authorizer to validate tokens from the identity provider. Require the Lambda authorizer on all API routes. Update the web application to get tokens from the identity provider and include the tokens in the Authorization header when calling the API Gateway HTTP API.

Integrate the company ' s third-party identity provider with AWS Directory Service. Configure Directory Service as an API Gateway authorizer to validate tokens from the identity provider. Require the Directory Service authorizer on all API routes. Configure AWS IAM Identity Center as a SAML 2.0 identity provider. Configure the web application as a custom SAML 2.0 application.

Integrate the company ' s third-party identity provider with AWS IAM Identity Center. Configure API Gateway to use IAM Identity Center for zero-configuration authentication and authorization. Update the web application to retrieve AWS STS tokens from IAM Identity Center and include the tokens in the Authorization header when calling the API Gateway HTTP API.

Integrate the company ' s third-party identity provider with AWS IAM Identity Center. Configure IAM users with permissions to call the API Gateway HTTP API. Update the web application to extract request parameters from the IAM users and include the parameters in the Authorization header when calling the API Gateway HTTP API.

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