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NEW QUESTION: 1
SDNはクラウド環境内で何を表していますか？
A. ソフトウェア依存のネットワーキング
B. ソフトウェア定義ネットワーキング
C. ソフトウェア動的ネットワーク
D. システム動的ノード
Answer: B
Explanation:
Software-defined networking separates the administration of network filtering and network forwarding to allow for distributed administration.

NEW QUESTION: 2
Service Busキューに含まれるメッセージの数に基づいてスケーリングするバックエンドAzure App Serviceを開発しています。
未処理の有効なキューメッセージの平均キュー長が1000を超える場合、App Serviceをスケールアップするルールが既に存在します。
スケールアップ条件が満たされない限り、App Serviceを継続的にスケールダウンする新しいルールを追加する必要があります。
スケールルールをどのように構成する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：各正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation
1]Service Bus Queue
2] Active Message Count
3] Average (Grain statistics) (You will not have COUNT)
4] Less than or equal to
5] Decrease count by
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/autoscale-best-practices#considerations-for-scalin

NEW QUESTION: 3
Cisco SD-Accessファブリックに基づくファブリックデータプレーンは、どのプロトコルまたはテクノロジーに基づいていますか。
A. Cisco TrustSec
B. IS-IS
C. LISP
D. VXLAN
Answer: D

NEW QUESTION: 4
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 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
D. 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.
Answer: C
Explanation:
In this case we need to find a durable and loosely coupled solution for storing jobs. Amazon SQS is ideal for this use case and can be configured to use dynamic scaling based on the number of jobs waiting in the queue.
To configure this scaling you can use the backlog per instance metric with the target value being the acceptable backlog per instance to maintain. You can calculate these numbers as follows:
Backlog per instance: To calculate your backlog per instance, start with the ApproximateNumberOfMessages queue attribute to determine the length of the SQS queue (number of messages available for retrieval from the queue). Divide that number by the fleet's running capacity, which for an Auto Scaling group is the number of instances in the InService state, to get the backlog per instance.
Acceptable backlog per instance: To calculate your target value, first determine what your application can accept in terms of latency. Then, take the acceptable latency value and divide it by the average time that an EC2 instance takes to process a message.
This solution will scale EC2 instances using Auto Scaling based on the number of jobs waiting in the SQS queue.
CORRECT: "Create an Amazon SQS queue to hold the jobs that needs to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue" is the correct answer.
INCORRECT: "Create an Amazon SQS queue to hold the jobs that need to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on network usage" is incorrect as scaling on network usage does not relate to the number of jobs waiting to be processed.
INCORRECT: "Create an Amazon SNS topic to send the jobs that need to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on CPU usage" is incorrect. Amazon SNS is a notification service so it delivers notifications to subscribers. It does store data durably but is less suitable than SQS for this use case. Scaling on CPU usage is not the best solution as it does not relate to the number of jobs waiting to be processed.
INCORRECT: "Create an Amazon SNS topic to send the jobs that need to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of messages published to the SNS topic" is incorrect. Amazon SNS is a notification service so it delivers notifications to subscribers. It does store data durably but is less suitable than SQS for this use case. Scaling on the number of notifications in SNS is not possible.
References:
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-using-sqs-queue.html