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NEW QUESTION: 1
귀하의 회사에서 대량의 공중 이미지 데이터를 S3에 업로드했습니다. 예전에는 사내 구축 환경에서 전용 데이터 그룹을 사용하여이 데이터를 처리하고 Rabbit MQ를 사용했습니다. - 오픈 소스 메시징 시스템을 통해 작업 정보를 얻었습니다 서버에. 일단 데이터가 처리되면 오프 사이트로 출고됩니다. 관리자는 현재 디자인을 유지하고 비용을 최소화하기 위해 AWS 보관 저장 및 메시징 서비스를 활용하라고 했습니다.
어느 것이 맞습니까?
A. S3 개체의 저장소 클래스를 Reduced Redundancy Storage로 변경합니다. 공간 인스턴스를 사용하여 SQS에서 메시지를 처리하는 대기열 깊이에 의해 트리거 된 자동 크기 조정 작업자 데이터가 처리 된 후 S3 개체의 저장소 클래스를 빙하로 변경합니다.
B. 작업 메시지 전달을 위해 SQS를 사용하면 클라우드 감시 알람을 사용하여 EC2 작업자 인스턴스가 유휴 상태가 될 때 종료합니다. 데이터가 처리되면 S3 개체의 저장소 클래스를 Redundancy Redundancy Storage로 변경합니다.
C. SNS를 사용하여 작업 메시지를 전달하면 클라우드 감시 알람을 사용하여 현장 작업자 인스턴스가 유휴 상태가 될 때 종료합니다. 데이터가 처리되면 S3 개체의 저장소 클래스를 Glacier로 변경합니다.
D. SOS에서 메시지를 처리하기 위해 스팟 인스턴스를 사용하는 대기열 깊이에 의해 트리거 된 자동 확장 작업자 설정 데이터가 처리되면,
Answer: C

NEW QUESTION: 2
Scenario: An organization has decided to implement a 'bring-your-own-device' (or 'BYOD') policy. To support the BYOD initiative, the organization is in search of a mobile device management solution. The primary business driver for the solution will be to provide IT with control of mobility resource provisioning and de-provisioning for terminated users, as well as the ability to perform a selective wipe on lost devices.
Which component should be included in the deployment to meet the needs of the solution?
A. Worx Home
B. XenMobile Device Manager
C. NetScaler Gateway
D. StoreFront
Answer: B

NEW QUESTION: 3
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You plan to create a predictive analytics solution for credit risk assessment and fraud prediction in Azure Machine Learning. The Machine Learning workspace for the solution will be shared with other users in your organization. You will add assets to projects and conduct experiments in the workspace.
The experiments will be used for training models that will be published to provide scoring from web services.
The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will predict probabilities in an Apache Hadoop ecosystem.
End of repeated scenario.
The users will use different data sources that follow a standard format. The users will receive results in a standard format by using the fraud prediction web service. The results will be saved to a location specified by the users.
You need to provide the users with the ability to get results for different risk tolerances without affecting the calculation of the model. Which three modules should be configured to use the Web Service Parameters? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Time Series Anomaly Detection
B. Evaluate Model
C. Export Data
D. Select Columns in Dataset
E. Import Data
Answer: B,C,E