A company is designing an application to connect AWS Lambda functions to an Amazon RDS for MySQL DB instance. The DB instance manages many connections. The company needs to modify the application to improve connectivity and recovery.
Which solution will meet these requirements with the LEAST operational overhead?
A. Use Amazon RDS Proxy for connection pooling. Modify the application to use the RDS Proxy for connections to the DB instance. B. Create a new RDS instance for connection pooling. Modify the application to use the new RDS instance for connectivity. C. Create read replicas to distribute the load of the DB instance. Create a Network Load Balancer to distribute the load across the read replicas. D. Migrate the RDS for MySQL DB instance to Amazon Aurora MySQL to increase DB instance performance.
A. Use Amazon RDS Proxy for connection pooling. Modify the application to use the RDS Proxy for connections to the DB instance.
Explanation
Amazon RDS Proxy helps manage thousands of concurrent database connections by pooling and reusing them efficiently. It is especially useful for serverless applications like AWS Lambda that can open numerous connections quickly, potentially overwhelming the database. Using RDS Proxy reduces connection management overhead and improves fault tolerance.
Question 1442:
A company is using Amazon CloudFront with its website. The company has enabled logging on the CloudFront distribution, and logs are saved in one of the company's Amazon S3 buckets. The company needs to perform advanced analyses on the logs and build visualizations.
What should a solutions architect do to meet these requirements?
A. Use standard SQL queries in Amazon Athena to analyze the CloudFront logs in the S3 bucket. Visualize the results with AWS Glue. B. Use standard SQL queries in Amazon Athena to analyze the CloudFront logs in the S3 bucket. Visualize the results with Amazon QuickSight. C. Use standard SQL queries in Amazon DynamoDB to analyze the CloudFront logs in the S3 bucket. Visualize the results with AWS Glue. D. Use standard SQL queries in Amazon DynamoDB to analyze the CloudFront logs in the S3 bucket. Visualize the results with Amazon QuickSight.
B. Use standard SQL queries in Amazon Athena to analyze the CloudFront logs in the S3 bucket. Visualize the results with Amazon QuickSight.
Question 1443:
A company has 15 employees. The company stores employee start dates in an Amazon DynamoDB table.
The company wants to send an email message to each employee on the day of the employee's work anniversary.
Which solution will meet these requirements with the MOST operational efficiency?
A. Create a script that scans the DynamoDB table and uses Amazon Simple Notification Service (Amazon SNS) to send email messages to employees when necessary. Use a cron job to run this script every day on an Amazon EC2 instance. B. Create a script that scans the DynamoDB table and uses Amazon Simple Queue Service (Amazon SQS) to send email messages to employees when necessary. Use a cron job to run this script every day on an Amazon EC2 instance. C. Create an AWS Lambda function that scans the DynamoDB table and uses Amazon Simple Notification Service (Amazon SNS) to send email messages to employees when necessary. Schedule this Lambda function to run every day. D. Create an AWS Lambda function that scans the DynamoDB table and uses Amazon Simple Queue Service (Amazon SQS) to send email messages to employees when necessary. Schedule this Lambda function to run every day.
C. Create an AWS Lambda function that scans the DynamoDB table and uses Amazon Simple Notification Service (Amazon SNS) to send email messages to employees when necessary. Schedule this Lambda function to run every day.
Question 1444:
A company is building a mobile gaming app. The company wants to serve users from around the world with low latency. The company needs a scalable solution to host the application and to route user requests to the location that is nearest to each user.
Which solution will meet these requirements?
A. Use an Application Load Balancer to route requests to Amazon EC2 instances that are deployed across multiple Availability Zones. B. Use a Regional Amazon API Gateway REST API to route requests to AWS Lambda functions. C. Use an edge-optimized Amazon API Gateway REST API to route requests to AWS Lambda functions. D. Use an Application Load Balancer to route requests to containers in an Amazon ECS cluster.
C. Use an edge-optimized Amazon API Gateway REST API to route requests to AWS Lambda functions.
Explanation
Edge-optimized API Gateway endpoints utilize the Amazon CloudFront global network to decrease latency for clients globally. This setup ensures that the request is routed to the closest edge location, significantly reducing response time and improving performance for worldwide users.
References:
AWS Documentation?Amazon API Gateway Endpoint Types
Question 1445:
A company has 5 TB of datasets. The datasets consist of 1 million user profiles and 10 million connections.
The user profiles have connections as many-to-many relationships. The company needs a performance efficient way to find mutual connections up to five levels.
Which solution will meet these requirements?
A. Use an Amazon S3 bucket to store the datasets. Use Amazon Athena to perform SQL JOIN queries to find connections. B. Use Amazon Neptune to store the datasets with edges and vertices. Query the data to find connections. C. Use an Amazon S3 bucket to store the datasets. Use Amazon QuickSight to visualize connections. D. Use Amazon RDS to store the datasets with multiple tables. Perform SQL JOIN queries to find connections.
B. Use Amazon Neptune to store the datasets with edges and vertices. Query the data to find connections.
Question 1446:
A company hosts an application on AWS Lambda functions that are invoked by an Amazon API Gateway API. The Lambda functions save customer data to an Amazon Aurora MySQL database. Whenever the company upgrades the database, the Lambda functions fail to establish database connections until the upgrade is complete. The result is that customer data is not recorded for some of the event.
A solutions architect needs to design a solution that stores customer data that is created during database upgrades.
Which solution will meet these requirements?
A. Provision an Amazon RDS proxy to sit between the Lambda functions and the database. Configure the Lambda functions to connect to the RDS proxy. B. Increase the run time of the Lambda functions to the maximum. Create a retry mechanism in the code that stores the customer data in the database. C. Persist the customer data to Lambda local storage. Configure new Lambda functions to scan the local storage to save the customer data to the database. D. Store the customer data in an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Create a new Lambda function that polls the queue and stores the customer data in the database.
D. Store the customer data in an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Create a new Lambda function that polls the queue and stores the customer data in the database.
Question 1447:
A company needs to migrate its customer transactions database from on-premises to AWS. The database resides on an Oracle DB instance that runs on a Linux server. According to a new security requirement, the company must rotate the database password each year.
Which solution will meet these requirements with the LEAST operational overhead?
A. Convert the database to Amazon DynamoDB by using AWS Schema Conversion Tool (AWS SCT). Store the password in AWS Systems Manager Parameter Store. Create an Amazon CloudWatch alarm to invoke an AWS Lambda function for yearly password rotation. B. Migrate the database to Amazon RDS for Oracle. Store the password in AWS Secrets Manager. Turn on automatic rotation. Configure a yearly rotation schedule. C. Migrate the database to an Amazon EC2 instance. Use AWS Systems Manager Parameter Store to keep and rotate the connection string by using an AWS Lambda function on a yearly schedule. D. Migrate the database to Amazon Neptune by using AWS Schema Conversion Tool (AWS SCT). Create an Amazon CloudWatch alarm to invoke an AWS Lambda function for yearly password rotation.
B. Migrate the database to Amazon RDS for Oracle. Store the password in AWS Secrets Manager. Turn on automatic rotation. Configure a yearly rotation schedule.
Explanation
Amazon RDS for Oracle is a managed database service, which significantly reduces operational overhead compared to running Oracle on EC2 or on-premises. AWS Secrets Manager natively integrates with RDS and supports automatic, scheduled password rotation with minimal setup. You can configure the rotation schedule (including yearly), and Secrets Manager will handle the secure password storage and rotation workflow for you.
AWS Documentation Extract:
" AWS Secrets Manager helps you protect access to your applications, services, and IT resources without the upfront investment and on-going maintenance costs of operating your own infrastructure. You can configure automatic rotation for supported databases such as Amazon RDS for Oracle. " (Source: AWS Secrets Manager documentation)
Option A, Option C, Option D: These solutions require custom scripting, Lambda, and alarms, leading to more operational overhead.
References:
AWS Certified Solutions Architect?Official Study Guide, Secrets Manager and RDS.
Question 1448:
A company deploys an application on Amazon EC2 Spot Instances. The company observes frequent unavailability issues that affect the application's output. The application instances all use the same instance type in a single Availability Zone. The application architecture does not require the use of any specific instance family.
The company needs a solution to improve the availability of the application.
Which combination of steps will meet this requirement MOST cost-effectively? (Choose Three.)
A. Create an EC2 Auto Scaling group that includes a mix of Spot Instances and a base number of on-demand Instances. B. Create EC2 Capacity Reservations. C. Use the lowest price allocation strategy for Spot Instances. D. Specify similarly sized instance types and Availability Zones for the Spot Instances. E. Use a different instance type for the web application. F. Use the price capacity optimized strategy for Spot Instances.
A. Create an EC2 Auto Scaling group that includes a mix of Spot Instances and a base number of on-demand Instances. D. Specify similarly sized instance types and Availability Zones for the Spot Instances. F. Use the price capacity optimized strategy for Spot Instances.
Explanation
AWS Spot best practices recommend diversifying capacity across multiple instance types and Availability Zones and using the capacity-optimized (price-capacity-optimized) allocation strategy to choose pools with the deepest capacity for higher availability. Adding a small On-Demand base in the Auto Scaling group maintains steady, uninterrupted baseline processing while keeping costs low and absorbing Spot interruptions.
Option C (lowest price) increases interruption risk. Capacity Reservations (Option B) target On-Demand capacity guarantees and add cost, not needed for Spot-based elasticity.
Option E is redundant; diversification is already achieved with (Option D). This combination maximizes resiliency of Spot workloads while preserving strong cost efficiency and aligns with AWS guidance for fault-tolerant, stateless applications on Spot.
Question 1449:
A company is building a serverless web application with multiple interdependent workflows that millions of users worldwide will access. The application needs to handle bursts of traffic.
Which solution will meet these requirements MOST cost-effectively?
A. Deploy an Amazon API Gateway HTTP API with a usage plan and throttle settings. Use AWS Step Functions with a Standard Workflow. B. Deploy an Amazon API Gateway HTTP API with a usage plan and throttle settings. Use AWS Step Functions with an Express Workflow. C. Deploy an Amazon API Gateway HTTP API without a usage plan. Use AWS Step Functions with an Express Workflow. D. Deploy an Amazon API Gateway HTTP API without a usage plan. Use AWS Step Functions and multiple AWS Lambda functions with reserved concurrency.
B. Deploy an Amazon API Gateway HTTP API with a usage plan and throttle settings. Use AWS Step Functions with an Express Workflow.
Explanation
Express Workflows in AWS Step Functions are optimized for high-throughput, short-duration, and low-cost workflows. They are suitable for applications with large volumes of parallel and interdependent tasks.
When paired with HTTP APIs from API Gateway, which are more cost-efficient than REST APIs, this setup offers scalability and cost-effectiveness.
References:
AWS Documentation?Step Functions Express Workflows vs. Standard Workflows
Question 1450:
A company hosts a serverless application on AWS. The application uses Amazon API Gateway, AWS Lambda, and an Amazon RDS for PostgreSQL database. The company notices an increase in application errors that result from database connection timeouts during times of peak traffic or unpredictable traffic.
The company needs a solution that reduces the application failures with the least amount of change to the code.
What should a solutions architect do to meet these requirements?
A. Reduce the Lambda concurrency rate. B. Enable RDS Proxy on the RDS DB instance. C. Resize the RDS DB instance class to accept more connections. D. Migrate the database to Amazon DynamoDB with on-demand scaling.
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