AWS-Solutions-Architect-Associate 무료 덤프문제 온라인 액세스

Question:
A company uses Apache Hadoop and Spark on-prem. The infrastructure is complex and not scalable. They want to reduce operational complexity but keep data processing on-premises.
Options:

• A.Use AWS DataSync to connect to on-prem HDFS. Use Amazon EMR to process the data.
• B.Migrate to Amazon EMR on AWS Outposts.
• C.Use Site-to-Site VPN to access on-prem HDFS. Use Amazon EMR to process the data.
• D.Use AWS Snowball to migrate data to S3. Use EMR to process.

A company is using microservices to build an ecommerce application on AWS. The company wants to preserve customer transaction information after customers submit orders. The company wants to store transaction data in an Amazon Aurora database. The company expects sales volumes to vary throughout each year.

• A.Use Amazon Data Firehose to send transaction data to Amazon S3. Use AWS Database Migration Service (AWS DMS) to migrate the data from Amazon S3 to the Aurora database.
• B.Use an Amazon API Gateway HTTP API to send transaction data to an Application Load Balancer (ALB). Use the ALB to send the transaction data to Amazon Elastic Container Service (Amazon ECS) on Amazon EC2. Use ECS tasks to store the data in Aurora database.
• C.Use an Application Load Balancer (ALB) to route transaction data to Amazon Elastic Kubernetes Service (Amazon EKS). Use Amazon EKS to send the data to the Aurora database.
• D.Use an Amazon API Gateway REST API to invoke an AWS Lambda function to send transaction data to the Aurora database. Send transaction data to an Amazon Simple Queue Service (Amazon SQS) queue that has a dead-letter queue. Use a second Lambda function to read from the SQS queue and to update the Aurora database.

A company has built an application that uses an Amazon Simple Queue Service (Amazon SQS) standard queue and an AWS Lambda function. The Lambda function writes messages to the SQS queue. The company needs a solution to ensure that the consumer of the SQS queue never receives duplicate messages.
Which solution will meet this requirement with the FEWEST changes to the current architecture?

• A.Delete the SQS queue. Create an Amazon MQ message broker. Configure the broker to deduplicate messages.
• B.Modify the SQS queue to enable long polling for the queue.
• C.Modify the SQS queue to enable content-based deduplication for the queue.
• D.Delete the existing SQS queue. Recreate the queue as a FIFO queue. Enable content-based deduplication for the queue.

A company has a non-production application that runs on an Amazon EC2 instance. The EC2 instance has an instance profile and an associated IAM role.
The company wants to automate patching for the EC2 instance.
Which solution will meet this requirement?

• A.Attach the AmazonSSMManagedInstanceCore policy to an existing IAM user. Use EC2 Image Builder to patch the EC2 instance.
• B.Attach the AmazonSSMManagedInstanceCore policy to the existing IAM role. Use AWS Systems Manager to patch the EC2 instance.
• C.Create an IAM user. Attach the AmazonSSMManagedInstanceCore policy to the IAM user. Configure AWS Systems Manager to use the IAM user to patch the instance.
• D.Create a new IAM role. Attach the AmazonSSMManagedInstanceCore policy to the new IAM role.
  Attach the new IAM role to the EC2 instance profile. Use AWS Systems Manager to patch the instance.

The customers of a finance company request appointments with financial advisors by sending text messages.
A web application that runs on Amazon EC2 instances accepts the appointment requests. The text messages are published to an Amazon Simple Queue Service (Amazon SQS) queue through the web application.
Another application that runs on EC2 instances then sends meeting invitations and meeting confirmation email messages to the customers. After successful scheduling, this application stores the meeting information in an Amazon DynamoDB database.
As the company expands, customers report that their meeting invitations are taking longer to arrive.
What should a solutions architect recommend to resolve this issue?

• A.Add a DynamoDB Accelerator (DAX) cluster in front of the DynamoDB database.
• B.Add an Auto Scaling group for the application that sends meeting invitations. Configure the Auto Scaling group to scale based on the depth of the SQS queue.
• C.Add an Amazon CloudFront distribution. Set the origin as the web application that accepts the appointment requests.
• D.Add an Amazon API Gateway API in front of the web application that accepts the appointment requests.