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NEW QUESTION: 1
eu-west-1 지역에서 15 분마다 업데이트되는 뉴스 웹 사이트를 운영하고 있습니다.
웹 사이트에는 Elastic Load Balancer와 Amazon RDS 데이터베이스 뒤에 Auto Scaling 그룹을 사용하는 전 세계 사용자가 있습니다. 정적 컨텐츠는 Amazon S3에 있으며 Amazon CloudFront를 통해 배포됩니다. 자동 확장 그룹이 60 % CPU 사용률로 확장 이벤트를 트리거하도록 설정되어 있고 Amazon RDS 초대형 DB 인스턴스를
10.000 프로비저닝 된 IOPS CPU 사용률은 약 80 %입니다. 여유 메모리는 2GB 범위 안에 있습니다.
웹 분석 보고서는 웹 페이지의 평균로드 시간이 대략 1 ~ 5 시간
2 초,하지만 귀하의 SEO 컨설턴트가 평균 로딩 시간을 낮추고 싶어합니다.
0.5 초.
사용자의 페이지로드 시간을 어떻게 향상시킬 수 있습니까? (3 답변 선택)
A. 세션 및 빈번한 DB 쿼리를 저장하기 위해 Amazon ElastiCache 캐싱 레이어를 애플리케이션에 추가하십시오.
B. 다른 지역에 두 번째 설치를 설정하고 Amazon Route 53 대기 시간 기반 라우팅 기능을 사용하여 올바른 지역을 선택하십시오.
C. 사이트에서 재사용 가능한 콘텐츠를 캐싱 할 수 있도록 Amazon CloudFront 동적 콘텐츠 지원을 구성합니다.
D. Amazon RDS 데이터베이스를 대용량의 초대형 인스턴스 유형으로 전환합니다.
E. Auto Scaling 그룹의 스케일 업 트리거를 30 %로 낮춰서보다 적극적으로 스케일을 조정하십시오.
Answer: A,D,E

NEW QUESTION: 2
共有コード用のプロジェクトを作成する必要があります。
解決策：共有プロジェクトに共有コードを実装します。
これは目標を達成していますか？
A. はい
B. いいえ
Answer: A

NEW QUESTION: 3
不正データ使用検出システムを設計する必要があります。どのAzureサービスを設計に含める必要がありますか？
A. Azure Databricks
B. Azure Analysis Services
C. Azure SQL Data Warehouse
D. Azure Data Factory
Answer: C
Explanation:
Explanation
SQL Database and SQL Data Warehouse
SQL threat detection identifies anomalous activities indicating unusual and potentially harmful attempts to access or exploit databases.
Advanced Threat Protection for Azure SQL Database and SQL Data Warehouse detects anomalous activities indicating unusual and potentially harmful attempts to access or exploit databases.
Scenario:
Requirements. Security
The solution must meet the following security requirements:
Unauthorized usage of data must be detected in real time. Unauthorized usage is determined by looking for unusual usage patterns.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-threat-detection-overview
Topic 6, Litware Case
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the button to return to the question.
Overview
Litware, Inc. owns and operates 300 convenience stores across the US. The company sells a variety of packaged foods and drinks, as well as a variety of prepared foods, such as sandwiches and pizzas.
Litware has a loyalty club whereby members can get daily discounts on specific items by providing their membership number at checkout.
Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
Requirements. Business Goals
Litware wants to create a new analytics environment in Azure to meet the following requirements:
* See inventory levels across the stores. Data must be updated as close to real time as possible.
* Execute ad hoc analytical queries on historical data to identify whether the loyalty club discounts increase sales of the discounted products.
* Every four hours, notify store employees about how many prepared food items to produce based on historical demand from the sales data.
Requirements. Technical Requirements
Litware identifies the following technical requirements:
* Minimize the number of different Azure services needed to achieve the business goals
* Use platform as a service (PaaS) offerings whenever possible and avoid having to provision virtual machines that must be managed by Litware.
* Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.
* Use Azure Active Directory (Azure AD) authentication whenever possible.
* Use the principle of least privilege when designing security.
* Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use.
Files that have a modified date that is older than 14 days must be removed.
* Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
* Ensure that you can quickly restore a copy of the analytical data store within one hour in the event of corruption or accidental deletion.
Requirements. Planned Environment
Litware plans to implement the following environment:
* The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure.
* Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Daily inventory data comes from a Microsoft SQL server located on a private network.
* Litware currently has 5 TB of historical sales data and 100 GB of customer data. The company expects approximately 100 GB of new data per month for the next year.
* Litware will build a custom application named FoodPrep to provide store employees with the calculation results of how many prepared food items to produce every four hours.
* Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.

NEW QUESTION: 4

A. Option B
B. Option A
Answer: A