DP-300 Korean 無料問題集「Microsoft Administering Relational Databases on Microsoft Azure (DP-300 Korean Version)」

Explanation:

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see the answer below in explanation.
Explanation:
Answer as in image below.

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/managed-instance/create-template-quickstart?tabs=azure- powershell

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Explanation:

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Explanation:

Box 1: The server, the elastic pool, and the database
Senario:
SalesSQLDb1 is in an elastic pool named SalesSQLDb1Pool.
Litware technical requirements include: all SQL Server and Azure SQL Database metrics related to CPU and storage usage and limits must be analyzed by using Azure built-in functionality.
Box 2: Azure Event hubs
Scenario: Migrate ManufacturingSQLDb1 to the Azure virtual machine platform.
Event hubs are able to handle custom metrics.
Topic 2, Contoso Ltd
Case study
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Overview
Existing Environment
Contoso, Ltd. is a financial data company that has 100 employees. The company delivers financial data to customers.
Active Directory
Contoso has a hybrid Azure Active Directory (Azure AD) deployment that syncs to on-premises Active Directory.
Database Environment
Contoso has SQL Server 2017 on Azure virtual machines shown in the following table.

SQL1 and SQL2 are in an Always On availability group and are actively queried. SQL3 runs jobs, provides historical data, and handles the delivery of data to customers.
The on-premises datacenter contains a PostgreSQL server that has a 50-TB database.
Current Business Model
Contoso uses Microsoft SQL Server Integration Services (SSIS) to create flat files for customers. The customers receive the files by using FTP.
Requirements
Planned Changes
Contoso plans to move to a model in which they deliver data to customer databases that run as platform as a service (PaaS) offerings. When a customer establishes a service agreement with Contoso, a separate resource group that contains an Azure SQL database will be provisioned for the customer. The database will have a complete copy of the financial data. The data to which each customer will have access will depend on the service agreement tier. The customers can change tiers by changing their service agreement.
The estimated size of each PaaS database is 1 TB.
Contoso plans to implement the following changes:
Move the PostgreSQL database to Azure Database for PostgreSQL during the next six months.
Upgrade SQL1, SQL2, and SQL3 to SQL Server 2019 during the next few months.
Start onboarding customers to the new PaaS solution within six months.
Business Goals
Contoso identifies the following business requirements:
Use built-in Azure features whenever possible.
Minimize development effort whenever possible.
Minimize the compute costs of the PaaS solutions.
Provide all the customers with their own copy of the database by using the PaaS solution.
Provide the customers with different table and row access based on the customer's service agreement.
In the event of an Azure regional outage, ensure that the customers can access the PaaS solution with minimal downtime. The solution must provide automatic failover.
Ensure that users of the PaaS solution can create their own database objects but he prevented from modifying any of the existing database objects supplied by Contoso.
Technical Requirements
Contoso identifies the following technical requirements:
Users of the PaaS solution must be able to sign in by using their own corporate Azure AD credentials or have Azure AD credentials supplied to them by Contoso. The solution must avoid using the internal Azure AD of Contoso to minimize guest users.
All customers must have their own resource group, Azure SQL server, and Azure SQL database. The deployment of resources for each customer must be done in a consistent fashion.
Users must be able to review the queries issued against the PaaS databases and identify any new objects created.
Downtime during the PostgreSQL database migration must be minimized.
Monitoring Requirements
Contoso identifies the following monitoring requirements:
Notify administrators when a PaaS database has a higher than average CPU usage.
Use a single dashboard to review security and audit data for all the PaaS databases.
Use a single dashboard to monitor query performance and bottlenecks across all the PaaS databases.
Monitor the PaaS databases to identify poorly performing queries and resolve query performance issues automatically whenever possible.
PaaS Prototype
During prototyping of the PaaS solution in Azure, you record the compute utilization of a customer's Azure SQL database as shown in the following exhibit.

Role Assignments
For each customer's Azure SQL Database server, you plan to assign the roles shown in the following exhibit.

See the explanation part for the complete Solution.
Explanation:
To generate an email alert to [email protected] when CPU percentage utilization for db1 is higher than average, you can use the Azure portal to create an alert rule based on the CPU percentage metric. Here are the steps to do that:
* Go to the Azure portal and select your Azure SQL Database server that hosts db1.
* Select Alerts in the Monitoring section and click on New alert rule.
* In the Condition section, click Add and select the CPU percentage metric.
* In the Configure signal logic page, set the threshold type to Dynamic. This will compare the current metric value to the historical average and trigger the alert when it deviates significantly1.
* Set the operator to Greater than, the aggregation type to Average, the aggregation granularity to 1 minute, and the frequency of evaluation to 5 minutes.
* Click Done to save the condition.
* In the Action group section, click Create and enter a name and a short name for the action group.
* In the Notifications section, click Add and select Email/SMS message/Push/Voice.
* Enter [email protected] in the Email field and click OK.
* Click OK to save the action group.
* In the Alert rule details section, enter a name and a description for the alert rule, choose a severity level, and make sure the rule is enabled.
* Click Create alert rule to create the alert rule.
This alert rule will send an email to [email protected] when the CPU percentage utilization for db1 is higher than average. You can also add other actions to the alert rule, such as calling a webhook or running an automation script

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Explanation:

Explanation:

Explanation:

Box 1: FactEvents
Fact tables store observations or events, and can be sales orders, stock balances, exchange rates, temperatures, etc.
Box 2: DimChannel
Dimension tables describe business entities - the things you model. Entities can include products, people, places, and concepts including time itself. The most consistent table you'll find in a star schema is a date dimension table. A dimension table contains a key column (or columns) that acts as a unique identifier, and descriptive columns.
Box 3: DimEvent
Reference:
https://docs.microsoft.com/en-us/power-bi/guidance/star-schema