Amazon Web Services exams4sure complete Saa-c03 Materials by Mara q120 vce pdf

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Exam Name:	AWS Certified Solutions Architect - Associate (SAA-C03)
Exam Code:	SAA-C03 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Associate
Questions:	1039 Q&A's	Shared By:	mara

Question 104

A company wants to run big data workloads on Amazon EMR. The workloads need to process terabytes of data in memory.

A solutions architect needs to identify the appropriate EMR cluster instance configuration for the workloads.

Which solution will meet these requirements?

Options:

Use a storage optimized instance for the primary node. Use compute optimized instances for core nodes and task nodes.

Use a memory optimized instance for the primary node. Use storage optimized instances for core nodes and task nodes.

Use a general purpose instance for the primary node. Use memory optimized instances for core nodes and task nodes.

Use general purpose instances for the primary, core, and task nodes.

Discussion

Question 105

A developer is creating an ecommerce workflow in an AWS Step Functions state machine that includes an HTTP Task state. The task passes shipping information and order details to an endpoint.

The developer needs to test the workflow to confirm that the HTTP headers and body are correct and that the responses meet expectations.

Which solution will meet these requirements?

Options:

Use the TestState API to invoke only the HTTP Task. Set the inspection level to TRACE.

Use the TestState API to invoke the state machine. Set the inspection level to DEBUG.

Use the data flow simulator to invoke only the HTTP Task. View the request and response data.

Change the log level of the state machine to ALL. Run the state machine.

Discussion

Question 106

A company is testing an application that runs on an Amazon EC2 Linux instance. A single 500 GB Amazon Elastic Block Store (Amazon EBS) General Purpose SSD (gp2) volume is attached to the EC2 instance.

The company will deploy the application on multiple EC2 instances in an Auto Scaling group. All instances require access to the data that is stored in the EBS volume. The company needs a highly available and resilient solution that does not introduce significant changes to the application's code.

Which solution will meet these requirements?

Options:

Provision an EC2 instance that uses NFS server software. Attach a single 500 GB gp2 EBS volume to the instance.

Provision an Amazon FSx for Windows File Server file system. Configure the file system as an SMB file store within a single Availability Zone.

Provision an EC2 instance with two 250 GB Provisioned IOPS SSD EBS volumes.

Provision an Amazon Elastic File System (Amazon EFS) file system. Configure the file system to use General Purpose performance mode.

Discussion

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Question 107

A company is developing a highly available natural language processing (NLP) application. The application handles large volumes of concurrent requests. The application performs NLP tasks such as entity recognition, sentiment analysis, and key phrase extraction on text data.

The company needs to store data that the application processes in a highly available and scalable database.

Options:

Options:

Create an Amazon API Gateway REST API endpoint to handle incoming requests. Configure the REST API to invoke an AWS Lambda function for each request. Configure the Lambda function to call Amazon Comprehend to perform NLP tasks on the text data. Store the processed data in Amazon DynamoDB.

Create an Amazon API Gateway HTTP API endpoint to handle incoming requests. Configure the HTTP API to invoke an AWS Lambda function for each request. Configure the Lambda function to call Amazon Translate to perform NLP tasks on the text data. Store the processed data in Amazon ElastiCache.

Create an Amazon SQS queue to buffer incoming requests. Deploy the NLP application on Amazon EC2 instances in an Auto Scaling group. Use Amazon Comprehend to perform NLP tasks. Store the processed data in an Amazon RDS database.

Create an Amazon API Gateway WebSocket API endpoint to handle incoming requests. Configure the WebSocket API to invoke an AWS Lambda function for each request. Configure the Lambda function to call Amazon Textract to perform NLP tasks on the text data. Store the processed data in Amazon ElastiCache.