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NEW QUESTION: 1
Which of the following are collection data types?
------
String Map List Date Set Number
A. Map, List, Set
B. For loops
C. FALSE
D. Primitive
Answer: A

NEW QUESTION: 2
A user has deployed an application on his private cloud. The user is using his own monitoring tool. He
wants to configure it so that whenever there is an error, the monitoring tool will notify him via SMS. Which
of the below mentioned AWS services will help in this scenario?
A. AWS SNS
B. AWS SMS
C. AWS SES
D. None because the user infrastructure is in the private cloud.
Answer: A
Explanation:
Amazon Simple Notification Service (Amazon SNS) is a fast, flexible, and fully managed push messaging
service. Amazon SNS can be used to make push notifications to mobile devices. Amazon SNS can
deliver notifications by SMS text message or email to the Amazon Simple Queue Service (SQS) queues
or to any HTTP endpoint. In this case user can use the SNS apis to send SMS.
Reference: http://aws.amazon.com/sns/

NEW QUESTION: 3
솔루션 아키텍트는 AWS에 배포되는 새로운 애플리케이션을 위한 클라우드 아키텍처를 설계하고 있습니다. 처리 할 작업 수에 따라 필요에 따라 애플리케이션 노드를 추가 및 제거하는 동안 프로세스가 병렬로 실행되어야 합니다. 프로세서 애플리케이션은 상태가 없습니다. 응용 프로그램이 느슨하게 결합되고 작업 항목이 내구성 있게 저장됩니다. 솔루션 설계자는 어떤 설계를 사용해야 합니까?
A. 처리해야하는 작업을 유지하기 위해 Amazon SQS 대기열 생성 프로세서 애플리케이션으로 구성된 Amazon 머신 이미지 (AMI) 생성 AMI를 사용하는 시작 구성 생성 시작 구성을 사용하여 Auto Scaling 그룹 생성 Auto Scaling 그룹이 네트워크 사용에 따라 노드를 추가 및 제거하기 위한 조정 정책
B. 처리해야 할 작업을 보내기 위해 Amazon SNS 주제 생성 프로세서 애플리케이션으로 구성된 Amazon 머신 이미지 (AMI) 생성 AMI를 사용하는 시작 구성 생성 시작 구성을 사용하여 Auto Scaling 그룹 생성 CPU 사용량을 기반으로 노드를 추가 및 제거하기 위한 Auto Scaling 그룹의 조정 정책
C. 처리해야 할 작업을 보내기 위해 Amazon SNS 주제 생성 프로세서 애플리케이션으로 구성된 Amazon 머신 이미지 (AMI) 생성 AMI를 사용하는 시작 템플릿 생성 시작 템플릿을 사용하여 Auto Scaling 그룹 생성 Auto Scaling 그룹이 SNS 주제에 게시 된 메시지 수에 따라 노드를 추가 및 제거하기 위한 조정 정책.
D. 처리해야 할 작업을 보유 할 Amazon SQS 대기열 생성 프로세서 애플리케이션으로 구성된 Amazon 머신 이미지 (AMI) 생성 AMI를 사용하는 시작 템플릿 생성 시작 템플릿을 사용하여 Auto Scaling 그룹 생성 Set Auto Scaling 그룹이 SQS 대기열의 항목 수에 따라 노드를 추가 및 제거하기위한 조정 정책
Answer: D
Explanation:
Amazon Simple Queue Service
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. SQS eliminates the complexity and overhead associated with managing and operating message oriented middleware, and empowers developers to focus on differentiating work. Using SQS, you can send, store, and receive messages between software components at any volume, without losing messages or requiring other services to be available. Get started with SQS in minutes using the AWS console, Command Line Interface or SDK of your choice, and three simple commands.
SQS offers two types of message queues. Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery. SQS FIFO queues are designed to guarantee that messages are processed exactly once, in the exact order that they are sent.
Scaling Based on Amazon SQS
There are some scenarios where you might think about scaling in response to activity in an Amazon SQS queue. For example, suppose that you have a web app that lets users upload images and use them online. In this scenario, each image requires resizing and encoding before it can be published. The app runs on EC2 instances in an Auto Scaling group, and it's configured to handle your typical upload rates. Unhealthy instances are terminated and replaced to maintain current instance levels at all times. The app places the raw bitmap data of the images in an SQS queue for processing. It processes the images and then publishes the processed images where they can be viewed by users. The architecture for this scenario works well if the number of image uploads doesn't vary over time. But if the number of uploads changes over time, you might consider using dynamic scaling to scale the capacity of your Auto Scaling group.
https://aws.amazon.com/sqs/#:~:text=Amazon%20SQS%20leverages%20the%20AWS,queues%20provide%20nearly%20unlimited%20throughput.
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-using-sqs-queue.html

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