SAA-C03 Exam Dumps - AWS Certified Solutions Architect - Associate (SAA-C03)

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Question # 9

Question:

An ecommerce company hosts an API that handles sales requests. The company hosts the API frontend on Amazon EC2 instances that run behind an Application Load Balancer (ALB). The company hosts the API backend on EC2 instances that perform the transactions. The backend tiers are loosely coupled by an Amazon Simple Queue Service (Amazon SQS) queue.

The company anticipates a significant increase in request volume during a new product launch event. The company wants to ensure that the API can handle increased loads successfully.

Options:

Double the number of frontend and backend EC2 instances to handle the increased traffic during the product launch event. Create a dead-letter queue to retain unprocessed sales requests when the demand exceeds the system capacity.

Place the frontend EC2 instances into an Auto Scaling group. Create an Auto Scaling policy to launch new instances to handle the incoming network traffic.

Place the frontend EC2 instances into an Auto Scaling group. Add an Amazon ElastiCache cluster in front of the ALB to reduce the amount of traffic the API needs to handle.

Place the frontend and backend EC2 instances into separate Auto Scaling groups. Create a policy for the frontend Auto Scaling group to launch instances based on incoming network traffic. Create a policy for the backend Auto Scaling group to launch instances based on the SQS queue backlog.

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Question # 10

A company has an application that collects data from loT sensors on automobiles. The data is streamed and stored in Amazon S3 through Amazon Kinesis Date Firehose The data produces trillions of S3 objects each year. Each morning, the company uses the data from the previous 30 days to retrain a suite of machine learning (ML) models.

Four times each year, the company uses the data from the previous 12 months to perform analysis and train other ML models The data must be available with minimal delay for up to 1 year. After 1 year, the data must be retained for archival purposes.

Which storage solution meets these requirements MOST cost-effectively?

Use the S3 Intelligent-Tiering storage class. Create an S3 Lifecycle policy to transition objects to S3 Glacier Deep Archive after 1 year

Use the S3 Intelligent-Tiering storage class. Configure S3 Intelligent-Tiering to automatically move objects to S3 Glacier Deep Archive after 1 year.

Use the S3 Standard-Infrequent Access (S3 Standard-IA) storage class. Create an S3 Lifecycle policy to transition objects to S3 Glacier Deep Archive after 1 year.

Use the S3 Standard storage class. Create an S3 Lifecycle policy to transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 30 days, and then to S3 Glacier Deep Archive after 1 year.

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Question # 11

A hospital wants to create digital copies for its large collection of historical written records. The hospital will continue to add hundreds of new documents each day. The hospital's data team will scan the documents and will upload the documents to the AWS Cloud.

A solutions architect must implement a solution to analyze the documents, extract the medical information, and store the documents so that an application can run SQL queries on the data. The solution must maximize scalability and operational efficiency.

Which combination of steps should the solutions architect take to meet these requirements? (Select TWO.)

Write the document information to an Amazon EC2 instance that runs a MySQL database.

Write the document information to an Amazon S3 bucket. Use Amazon Athena to query the data.

Create an Auto Scaling group of Amazon EC2 instances to run a custom application that processes the scanned files and extracts the medical information.

Create an AWS Lambda function that runs when new documents are uploaded. Use Amazon Rekognition to convert the documents to raw text. Use Amazon Transcribe Medical to detect and extract relevant medical information from the text.

Create an AWS Lambda function that runs when new documents are uploaded. Use Amazon Textract to convert the documents to raw text. Use Amazon Comprehend Medical to detect and extract relevant medical information from the text.

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Answer:

Explanation:

This solution meets the requirements of creating digital copies for a large collection of historical written records, analyzing the documents, extracting the medical information, and storing the documents so that an application can run SQL queries on the data. Writing the document information to an Amazon S3 bucket can provide scalable and durable storage for the scanned files. Using Amazon Athena to query the data can provide serverless and interactive SQL analysis on data stored in S3. Creating an AWS Lambda function that runs when new documents are uploaded can provide event-driven and serverless processing of the scanned files. Using Amazon Textract to convert the documents to raw text can provide accurate optical character recognition (OCR) and extraction of structured data such as tables and forms from documents using artificial intelligence (AI). Using Amazon Comprehend Medical to detect and extract relevant medical information from the text can provide natural language processing (NLP) service that uses machine learning that has been pre-trained to understand and extract health data from medical text.

Option A is incorrect because writing the document information to an Amazon EC2 instance that runs a MySQL database can increase the infrastructure overhead and complexity, and it may not be able to handle large volumes of data. Option C is incorrect because creating an Auto Scaling group of Amazon EC2 instances to run a custom application that processes the scanned files and extracts the medical information can increase the infrastructure overhead and complexity, and it may not be able to leverageexisting AI and NLP services such as Textract and Comprehend Medical. Option D is incorrect because using Amazon Rekognition to convert the documents to raw text can provide image and video analysis, but it does not support OCR or extraction of structured data from documents. Using Amazon Transcribe Medical to detect and extract relevant medical information from the text can provide speech-to-text transcription service for medical conversations, but it does not support text analysis or extraction of health data from medical text.

[References:, https://aws.amazon.com/s3/, https://aws.amazon.com/athena/, https://aws.amazon.com/lambda/, https://aws.amazon.com/textract/, https://aws.amazon.com/comprehend/medical/, , , , ]

Question # 12

A company has a web application with sporadic usage patterns There is heavy usage at the beginning of each month moderate usage at the start of each week and unpredictable usage during the week The application consists of a web server and a MySQL database server running inside the data center The company would like to move the application to the AWS Cloud and needs to select a cost-effective database platform that will not require database modifications

Which solution will meet these requirements?

Amazon DynamoDB

Amazon RDS for MySQL

MySQL-compatible Amazon Aurora Serverless

MySQL deployed on Amazon EC2 in an Auto Scaling group

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Question # 13

A meteorological startup company has a custom web application to sell weather data to its users online. The company uses Amazon DynamoDB to store is data and wants to bu4d a new service that sends an alert to the managers of four Internal teams every time a new weather event is recorded. The company does not want true new service to affect the performance of the current application

What should a solutions architect do to meet these requirement with the LEAST amount of operational overhead?

Use DynamoDB transactions to write new event data to the table Configure the transactions to notify internal teams.

Have the current application publish a message to four Amazon Simple Notification Service (Amazon SNS) topics. Have each team subscribe to one topic.

Enable Amazon DynamoDB Streams on the table. Use triggers to write to a mingle Amazon Simple Notification Service (Amazon SNS) topic to which the teams can subscribe.

Add a custom attribute to each record to flag new items. Write a cron job that scans the table every minute for items that are new and notifies an Amazon Simple Queue Service (Amazon SOS) queue to which the teams can subscribe.

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Question # 14

An ecommerce company needs to run a scheduled daily job to aggregate and filler sales records for analytics. The company stores the sales records in an Amazon S3 bucket. Each object can be up to 10 G6 in size Based on the number of sales events, the job can take up to an hour to complete. The CPU and memory usage of the fob are constant and are known in advance.

A solutions architect needs to minimize the amount of operational effort that is needed for the job to run. Which solution meets these requirements?

Create an AWS Lambda function that has an Amazon EventBridge notification Schedule the EventBridge event to run once a day

Create an AWS Lambda function Create an Amazon API Gateway HTTP API, and integrate the API with the function Create an Amazon EventBridge scheduled avert that calls the API and invokes the function.

Create an Amazon Elastic Container Service (Amazon ECS) duster with an AWS Fargate launch type. Create an Amazon EventBridge scheduled event that launches an ECS task on the cluster to run the job.

Create an Amazon Elastic Container Service (Amazon ECS) duster with an Amazon EC2 launch type and an Auto Scaling group with at least one EC2 instance. Create an Amazon EventBridge scheduled event that launches an ECS task on the duster to run the job.

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Question # 15

A company wants to run applications in containers in the AWS Cloud. These applications are stateless and can tolerate disruptions within the underlying infrastructure. The company needs a solution that minimizes cost and operational overhead.

What should a solutions architect do to meet these requirements?

Use Spot Instances in an Amazon EC2 Auto Scaling group to run the application containers.

Use Spot Instances in an Amazon Elastic Kubernetes Service (Amazon EKS) managed node group.

Use On-Demand Instances in an Amazon EC2 Auto Scaling group to run the application containers.

Use On-Demand Instances in an Amazon Elastic Kubernetes Service (Amazon EKS) managed node group.

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Question # 16

A company is building a new application that uses multiple serverless architecture components. The application architecture includes an Amazon API Gateway REST API and AWS Lambda functions to manage incoming requests.

The company needs a service to send messages that the REST API receives to multiple target Lambda functions for processing. The service must filter messages so each target Lambda function receives only the messages the function needs.

Which solution will meet these requirements with the LEAST operational overhead?

Send the requests from the REST API to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe multiple Amazon Simple Queue Service (Amazon SQS) queues to the SNS topic. Configure the target Lambda functions to poll the SQS queues.

Send the requests from the REST API to a set of Amazon EC2 instances that are configured to process messages. Configure the instances to filter messages and to invoke the target Lambda functions.

Send the requests from the REST API to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Configure Amazon MSK to publish the messages to the target Lambda functions.

Send the requests from the REST API to multiple Amazon Simple Queue Service (Amazon SQS) queues. Configure the target Lambda functions to poll the SQS queues.

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