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NEW QUESTION: 1
A company provides web app hosting services for customers.
You have a set of App Service Plans available to deploy resources for new projects. The available service tiers are shown in the Service Tiers exhibit. (Click the Service Tiers tab.)
You must provision resources for the projects as shown in the Projects exhibit. (Click the Projects tab.)
The Adventure Works a project requires the use of deployment slots as shown in the Deployment Slots exhibit. (Click the Deployment Slots tab.)
You need to determine where to deploy resources for each project.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION: 2
A client has a long term AEM project that they have extended with new components and extensive edit dialogs. The project is running with AEM version 5.6 and is using the Classic UI. Considering this information, the developer working on the project is wondering if it would be wise to recommend upgrading to AEM version 6.4. What is the recommended approach on a limited budget?
A. The Classic UI remains fully supported while being deprecated, providing all the necessary functionality to the project. Do not upgrade to 6.4
B. Upgrade to 6.4 and apply and configure the standard (Touch) UI and disable the Coral 3 formatting to avoid operational congruency issues
C. Upgrade to 6.4 and configure the Classic UI while starting a new project to migrate the components in a phased approach to Touch UI
D. The project would have to rebuilt. Given the extent of customization to the current project and the costs the client would incur, do not upgrade to 6.4
Answer: C
NEW QUESTION: 3
애플리케이션이 테라 바이트 규모의 데이터 처리를 지원해야 합니다. 어떤 큰 데이터 도구를 사용할 수 있습니까?
정답을 선택하십시오.
A. Amazon Redshift
B. 스파크가있는 Amazon EMR
C. Amazon Data Pipeline
D. Amazon Machine Learning
Answer: B
Explanation:
While Amazon ML can support up to 100 GB of data, terabyte-scale ingestion of data is not currently supported. Using Amazon EMR to run Spark's Machine Learning Library (MLlib) is a common tool for such a use case.
Reference:
https://d0.awsstatic.com/whitepapers/Big_Data_Analytics_Options_on_AWS.pdf