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NEW QUESTION: 1
In an application-centric infrastructure which four aspects of the solution must be configured to support an application? (Choose four)
A. The layer 2 through layer 7 network policies of the application.
B. Data center-specific configuration of the infrastructure.
C. The endpoints of the application.
D. A virtual machine or server
E. Establishes forwarding paths in the ACI fabric.
F. The relationship between endpoints and their policies.
Answer: A,B,E,F

NEW QUESTION: 2
Examine the initialization parameter that is set in the PFILE:
DB_CREATE_FILE_DEST ='/u01/app/oracle/oradata/'
You execute the following command to create theCDB1. container database (CDB):
SQL>CREATE DATABASE CDB1
DEFAULT TABLESPACE users
DEFAULT TEMPORARY TABLESPACE temp
UNDO TABLESPACE undotbsl
ENABLE PLUGGABLE DATABASE
SEED
SYSTEM DATAFILES SIZE125M AUTOEXTEND ON NEXT 10M MAXSIZE UNLIMITED
SYS AUX DATAFILES SIZE 100M;
Which three statements are true?
A. It sets the users tablespace as the default for both the root and seed databases.
B. It creates a multitenant container database with the root and seed databases opened and one PDB mounted.
C. undotbs1 is used as the undo tablespace for both the root and seed databases.
D. It creates a multitenant container database with the root database opened and the seed database mounted.
E. It creates a multitenant container database with a root and a seed pluggable database (PDB) that are opened in read-write and read-only modes, respectively.
F. The files created for both the root and seed databases use Oracle Managed Files (OMF).
Answer: C,E,F
Explanation:
Explanation
The seed actually doesn't use anything since it's read-only, but any PDB created from the seed will use the undotbs1 undo tablespace. Each PDB can have its own default tablespace, but cannot change the undo tablespace.

NEW QUESTION: 3
가상 머신이로드되는 동안 기다리십시오. 일단로드되면 랩 섹션으로 진행할 수 있습니다.
이 작업에는 몇 분이 걸릴 수 있으며 전체 테스트 시간에서 대기 시간이 차감되지 않습니다.
다음 버튼을 사용할수 있으면 클릭하여 실습 섹션에 액세스하십시오.
이 섹션에서는 실제 환경에서 일련의 작업을 수행합니다.
실제 환경에서와 같이 대부분의 기능을 사용할수 있지만 일부 기능 (예 : 복사 및 붙여 넣기, 외부 웹 사이트 탐색 기능)은 의도적으로 설계할수 없습니다.
채점은 실험실에 명시된 작업을 수행한 결과를 기반으로 합니다.
즉, 작업 수행 방법은 중요하지 않습니다. 작업을 성공적으로 수행하면 해당 작업에 대한 크레딧을 얻게 됩니다.
실습 시간은 별도로 정해져 있지 않으며 이 시험에는 두 개 이상의 실습 과정이 있어야 합니다.
각 실습을 완료하려는 시간만큼 사용할수 있습니다. 그러나 제공된 시간 내에 실험실 및 시험의 다른 모든 섹션을 완료할수 있도록 시간을 적절히 관리해야 합니다.
랩 내에서 다음 버튼을 클릭하여 작업을 제출하면 랩으로 돌아올수 없습니다.
이제 다음을 클릭하여 실습을 진행할 수 있습니다.
필요에 따라 다음 로그인 자격 증명을 사용하십시오.
Azure 사용자 이름 : XXXXXXX
Azure 비밀번호 : XXXXXXX
다음 정보는 기술 지원 목적으로만 사용됩니다.
랩 인스턴스 : 9172796

작업 2
미디어 파일을 rg1lod9172796 스토리지 계정에 저장하려고 합니다.
미디어 파일을 저장하려면 저장소 계정을 구성해야 합니다. 솔루션은 액세스 키가있는 사용자 만 미디어 파일을 다운로드 할 수 있고 HTTPS를 통해서만 파일에 액세스 할 수 있도록해야 합니다.
Azure Portal에서 무엇을 해야 합니까?
Answer:
Explanation:
아래 솔루션을 참조하십시오.
설명
Azure 파일 공유를 만들어야 합니다.
1 단계 : Azure Portal에서 모든 서비스를 선택합니다. 리소스 목록에서 스토리지 계정을 입력하십시오. 입력을 시작하면 입력에 따라 목록이 필터링됩니다. 저장소 계정을 선택하십시오.
스토리지 계정 창이 나타납니다.
2 단계 : rg1lod9172796 저장소 계정을 찾습니다.
3 단계 : 저장소 계정 페이지의 서비스 섹션에서 파일을 선택합니다.

4 단계 : 파일 서비스 페이지 상단의 메뉴에서 + 파일 공유를 클릭합니다. 새 파일 공유 페이지가 드롭 다운됩니다.
5 단계 : 이름에 myshare를 입력하십시오. 확인을 클릭하여 Azure 파일 공유를 만듭니다.
참고 문헌 :
https://docs.microsoft.com/en-us/azure/storage/files/storage-how-to-use-files-portal

NEW QUESTION: 4
You need to build an API pipeline that analyzes streaming data. The pipeline will perform the following:
* Visual text recognition
* Audio transcription
* Sentiment analysis
* Face detection
Which Azure Cognitive Services should you use in the pipeline?
A. Face API
B. Video Indexer
C. Custom Speech Service
D. Text Analytics
Answer: B
Explanation:
Explanation
Azure Video Indexer is a cloud application built on Azure Media Analytics, Azure Search, Cognitive Services (such as the Face API, Microsoft Translator, the Computer Vision API, and Custom Speech Service). It enables you to extract the insights from your videos using Video Indexer video and audio models described below:
Visual text recognition (OCR): Extracts text that is visually displayed in the video.
Audio transcription: Converts speech to text in 12 languages and allows extensions.
Sentiment analysis: Identifies positive, negative, and neutral sentiments from speech and visual text.
Face detection: Detects and groups faces appearing in the video.
References:
https://docs.microsoft.com/en-us/azure/media-services/video-indexer/video-indexer-overview
Topic 1, Contoso Case Study: 1
Overview
Contoso. Ltd. has an office in New York to serve its North American customers and an office in Paris to serve its European customers.
Existing Environment
Contoso. Ltd. has an office in New York to serve its North American customers and an office in Paris to serve its European customers.
Infrastructure
Each office has a small data center that hosts Active Directory services and a few off-the-shelf software solutions used by internal users.
The network contains a single Active Directory forest that contains a single domain named contoso.com.
Azure Active Directory (Azure AD) Connect is used to extend identity management to Azure.
The company has an Azure subscription. Each office has an Azure ExpressRoute connection to the subscription. The New York office connects to a virtual network hosted in the US East 2 Azure region. The Paris office connects to a virtual network hosted in the West Europe Azure region.
The New York office has an Azure Stack Development Kit (ASDK) deployment that is used for development and testing.
Current Business Model
Contoso has a web app named Bookings hosted in an App Service Environment (ASE). The ASE is in the virtual network in the East US 2 region. Contoso employees and customers use Bookings to reserve hotel rooms.
Data Environment
Bookings connects to a Microsoft SQL Server database named hotelDB in the New York office.
The database has a view named vwAvailability that consolidates columns from three tables named Hotels, Rooms, and RoomAvailability. The database contains data that was collected during the last 20 years.
Problem Statements
Contoso identifies the following issues with its current business model:
* European users report that access to Bookings is slow, and they lose customers who must wait on the phone while they search for available rooms.
* Users report that Bookings was unavailable during an outage in the New York data center for more than 24 hours.
Requirements
Contoso identifies the following issues with its current business model:
*European users report that access to Bookings is slow, and they lose customers who must wait on the phone while they search for available rooms.
Business Goals
*Users report that Bookings was unavailable during an outage in the New York data center for more than 24 hours.
Contoso wants to provide a new version of the Bookings app that will provide a highly available, reliable service for booking travel packages by interacting with a chatbot named Butler.
Contoso plans to move all production workloads to the cloud.
Technical Requirements
Contoso identifies the following technical requirements:
*Data scientists must test Butler by using ASDK.
*Whenever possible, solutions must minimize costs.
*Butler must greet users by name when they first connect.
*Butler must be able to handle up to 10.000 messages a day.
*Butler must recognize the users' intent based on basic utterances.
*All configurations to the Azure Bot Service must be logged centrally.
*Whenever possible, solutions must use the principle of least privilege.
*Internal users must be able to access Butler by using Microsoft Skype for Business.
*The new Bookings app must provide a user interface where users can interact with Butler.
*Users in an Azure AD group named KeyManagers must be able to manage keys for all Azure Cognitive Services.
*Butler must provide users with the ability to reserve a room, cancel a reservation, and view existing reservations.
*The new Bookings app must be available to users in North America and Europe if a single data center or Azure region fails.
*For continuous improvement, you must be able to test Butler by sending sample utterances and comparing the chatbot's responses to the actua intent.