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NEW QUESTION: 1
회사는 Amazon EC2 인스턴스에서 실행되는 2 계층 웹 사이트를 호스팅합니다. 이 웹 사이트에는 MySQL 용 Amazon RDS에서 실행되는 데이터베이스가 있습니다. 모든 사용자는 사용자 정의 페이지에 로그인 해야 합니다.
웹 사이트는 일반적으로 트래픽이 적습니다. 때때로 웹 사이트에서 트래픽이 갑작스럽게 증가하고 응답하지 않게 됩니다. 이러한 트래픽 증가 중에는 로드를 작성하십시오. 솔루션 아키텍트는 애플리케이션 코드를 변경하지 않고 웹 사이트의 가용성을 개선해야 합니다.
솔루션 아키텍트는 이러한 요구 사항을 충족하기 위해 무엇을 해야 합니까?
A. 데이터베이스를 Amazon Aurora Serverless 클러스터로 마이그레이션 합니다. 최대 Aurora 용량 단위 (ACU)를 Aurora 데이터베이스에 연결할 트래픽 증가. 인스턴스에 응답 할 수 있을 만큼 높은 값으로 설정합니다.
B. Redis 용 Amazon ElastiCache 클러스터를 생성합니다. ElastiCache 클러스터에서 일반 데이터베이스 쿼리를 캐시하도록 애플리케이션을 구성합니다.
C. EC2 인스턴스를 오리진으로 가리키는 Amazon CloudFront 배포를 생성합니다. 동적 콘텐츠의 캐싱을 활성화하고 데이터베이스에서 쓰기 제한을 구성합니다.
D. Auto Scaling 그룹을 생성합니다. 트래픽 중 사용중인 CPU 비율에 따라 EC2 인스턴스 수를 조정하도록 Amazon CloudWatch 경보를 구성합니다.
Answer: B

NEW QUESTION: 2
You need to recommend the appropriate technology to provide the predictive analytics for passenger pickup.
What should you do?
A. Use HDInsight to analyze the traffic data and write a .NET program to categorize the results.
B. Use Power BI to analyze the traffic data and PowerPivot to categorize the results.
C. Use Machine Learning Studio to create a predictive model and publish the results as a web service.
D. Use Hadoop on-premises to analyze the traffic and produce a report that shows high traffic zones.
Answer: C
Explanation:
Explanation
* Scenario: Predictive Routing:
/ An Azure solution must be used for prediction systems.
/ Predictive analytics must be published as a web service and accessible by using the REST API.
* Microsoft Azure Machine Learning Studio is a collaborative visual development environment that enables you to build, test, and deploy predictive analytics solutions that operate on your data. The Machine Learning service and development environment is cloud-based, provides compute resource and memory flexibility, and eliminates setup and installation concerns because you work through your web browser.
References: https://azure.microsoft.com/en-us/documentation/articles/machine-learning-what-is-ml-studio/
Topic 6, Lucerne PublishingBackground
Overview
Lucerne Publishing creates, stores, and delivers online media for advertising companies. This media is streamed to computers by using the web, and to mobile devices around the world by using native applications.
The company currently supports the iOS, Android, and Windows Phone 8.1 platform.
Lucerne Publishing uses proprietary software to manage its media workflow. This software has reached the end of its lifecycle. The company plans to move its media workflows to the cloud. Lucerne Publishing provides access to its customers, who are third-party companies, so that they can download, upload, search, and index media that is stored on Lucerne Publishing servers.
Apps and Applications
Lucerne Publishing develops the applications that customers use to deliver media. The company currently provides the following media delivery applications:
* Lucerne Media W - a web application that delivers media by using any browser
* Lucerne Media M - a mobile app that delivers media by using Windows Phone 8.1
* Lucerne Media A - a mobile app that delivers media by using an iOS device
* Lucerne Media N - a mobile app that delivers media by using an Android device
* Lucerne Media D - a desktop client application that customer's install on their local computer Business Requirements Lucerne Publishing's customers and their consumers have the following requirements:
* Access to media must be time-constricted once media is delivered to a consumer.
* The time required to download media to mobile devices must be minimized.
* Customers must have 24-hour access to media downloads regardless of their location or time zone.
* Lucerne Publishing must be able to monitor the performance and usage of its customer-facing app.
Lucerne Publishing wants to make its asset catalog searchable without requiring a database redesign.
* Customers must be able to access all data by using a web application. They must also be able to access data by using a mobile app that is provided by Lucerne Publishing.
* Customers must be able to search for media assets by key words and media type.
* Lucerne Publishing wants to move the asset catalog database to the cloud without formatting the source data.
Other Requirements
Development
Code and current development documents must be backed up at all times. All solutions must be automatically built and deployed to Azure when code is checked in to source control.
Network Optimization
Lucerne Publishing has a .NET web application that runs on Azure. The web application analyzes storage and the distribution of its media assets. It needs to monitor the utilization of the web application. Ultimately, Lucerne Publishing hopes to cut its costs by reducing data replication without sacrificing its quality of service to its customers. The solution has the following requirements:
* Optimize the storage location and amount of duplication of media.
* Vary several parameters including the number of data nodes and the distance from node to customers.
* Minimize network bandwidth.
* Lucerne Publishing wants be notified of exceptions in the web application.
Technical Requirements
Data Mining
Lucerne Publishing constantly mines its data to identify customer patterns. The company plans to replace the existing on-premises cluster with a cloud-based solution. Lucerne Publishing has the following requirements:
Virtual machines:
* The data mining solution must support the use of hundreds to thousands of processing cores.
* Minimize the number of virtual machines by using more powerful virtual machines. Each virtual machine must always have eight or more processor cores available.
* Allow the number of processor cores dedicated to an analysis to grow and shrink automatically based on the demand of the analysis.
* Virtual machines must use remote memory direct access to improve performance.
Task scheduling:
The solution must automatically schedule jobs. The scheduler must distribute the jobs based on the demand and available resources.
Data analysis results:
The solution must provide a web service that allows applications to access the results of analyses.
Other Requirements
Feature Support
* Ad copy data must be searchable in full text.
* Ad copy data must indexed to optimize search speed.
* Media metadata must be stored in Azure Table storage.
* Media files must be stored in Azure BLOB storage.
* The customer-facing website must have access to all ad copy and media.
* The customer-facing website must automatically scale and replicate to locations around the world.
* Media and data must be replicated around the world to decrease the latency of data transfers.
* Media uploads must have fast data transfer rates (low latency) without the need to upload the data offline.
Security
* Customer access must be managed by using Active Directory.
* Media files must be encrypted by using the PlayReady encryption method.
* Customers must be able to upload media quickly and securely over a private connection with no opportunity for internet snooping.

NEW QUESTION: 3
マーケティングチームは、毎週、聴衆にメールを送りたいと考えています。チームは毎週複数のファイルを受け取ります。これらのファイルはインポートして参加し、メールの対象ユーザーを作成する必要があります。このプロセスの実行に推奨されるツールはどれですか？
A. データ抽出アクティビティ
B. オートメーションスタジオ
C. ジャーニービルダー
D. アクティビティのフィルター
Answer: B

NEW QUESTION: 4
The help desk provided a security analyst with a screenshot of a user's desktop:

For which of the following is aircrack-ng being used?
A. Rainbow attack
B. Wireless access point discovery
C. Brute-force attack
D. PCAP data collection
Answer: A