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NEW QUESTION: 1
HPE ProLiant Gen10サーバーに固有のセキュリティ機能はどれですか？
A. 永続メモリは仮想マシンをネットワークファブリックの侵害から保護します
B. 信頼のシリコンルートにより、Gen10サーバーは侵害されたファームウェアを検出できます
C. プロセッサーの高度な監査機能により、カーネルの疑わしい動作が検出されますか？
D. アプリケーション分離の強化により、仮想マシンへのネットワークトラフィックが制御されます
Answer: B

NEW QUESTION: 2
You use attributes to define a segmentation filter. You define a segmentation filter to create, or change a segment. To define a segmentation filter you perform the following main activities:
Response:
A. Select an attribute.
B. Choose a filter mode.
C. Define the filter parameters.
D. All of above
E. Specify one or more attribute values.
Answer: D

NEW QUESTION: 3
A company has a website running on Amazon EC2 instances across two Availability Zones. The company is expecting spikes in traffic on specific holidays, and wants to provide a consistent user experience. How can a solutions architect meet this requirement?
A. Use lifecycle hooks.
B. Use simple scaling.
C. Use step scaling.
D. Use scheduled scaling.
Answer: D

NEW QUESTION: 4
Overview:
Litware, Inc. is a company that manufactures personal devices to track physical activity and other health- related data.
Litware has a health tracking application that sends health-related data from a user's personal device to Microsoft Azure.
Litware has three development and commercial offices. The offices are located in the United States, Luxembourg, and India.
Litware products are sold worldwide. Litware has commercial representatives in more than 80 countries.
Existing Environment:
In addition to using desktop computers in all of the offices, Litware recently started using Microsoft Azure resources and services for both development and operations.
Litware has an Azure Machine Learning solution.
Litware recently extended its platform to provide third-party companies with the ability to upload data from devices to Azure. The data can be aggregated across multiple devices to provide users with a comprehensive view of their global health activity.
While the upload from each device is small, potentially more than 100 million devices will upload data daily by using an Azure event hub.
Each health activity has a small amount of data, such as activity type, start date/time, and end date/time.
Each activity is limited to a total of 3 KB and includes a customer identification key.
In addition to the Litware health tracking application, the users' activities can be reported to Azure by using an open API.
The developers at Litware perform Machine Learning experiments to recommend an appropriate health activity based on the past three activities of a user.
The Litware developers train a model to recommend the best activity for a user based on the hour of the day.
Requirements:
Litware plans to extend the existing dashboard features so that health activities can be compared between the users based on age, gender, and geographic region.
Minimize the costs associated with transferring data from the event hub to Azure Storage.
Litware identifies the following technical requirements:
Data from the devices must be stored for three years in a format that enables the fast processing of

date fields and filtering.
The third-party companies must be able to use the Litware Machine Learning models to generate

recommendations to their users by using a third-party application.
Any changes to the health tracking application must ensure that the Litware developers can run the

experiments without interrupting or degrading the performance of the production environment.
Activity tracking data must be available to all of the Litware developers for experimentation. The developers must be prevented from accessing the private information of the users.
When the Litware health tracking application asks users how they feel, their responses must be reported to Azure.
Users report that when they access data that is more than one year old from a dashboard, the response time is slow.
You need to resolve the issue that causes the slow response when visualizing older data.
What should you do?
A. Process the event hub data first, and then process the older data on demand.
B. Process the older data on demand first, and then process the event hub data.
C. Store all of the data from the event hub in a single partition.
D. Aggregate the older data by time, and then save the aggregated data to reference data streams.
Answer: D
Explanation:
Explanation/Reference:
Explanation: