Active geo-replication is an Azure SQL Database feature that allows you to create readable secondary databases of individual databases on a server in the same or different data center (region).
Incorrect Answers:
C: Availability Zones are unique physical locations within a region. Each zone is made up of one or more datacenters equipped with independent power, cooling, and networking.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/active-geo-replication-overview
Topic 1, Litware Existing Environment
Network Environment
The manufacturing and research datacenters connect to the primary datacenter by using a VPN.
The primary datacenter has an ExpressRoute connection that uses both Microsoft peering and private peering. The private peering connects to an Azure virtual network named HubVNet.
Identity Environment
Litware has a hybrid Azure Active Directory (Azure AD) deployment that uses a domain named litwareinc.com. All Azure subscriptions are associated to the litwareinc.com Azure AD tenant.
Database Environment
The sales department has the following database workload:
* An on-premises named SERVER1 hosts an instance of Microsoft SQL Server 2012 and two 1-TB databases.
* A logical server named SalesSrv01A contains a geo-replicated Azure SQL database named SalesSQLDb1. SalesSQLDb1 is in an elastic pool named SalesSQLDb1Pool. SalesSQLDb1 uses database firewall rules and contained database users.
* An application named SalesSQLDb1App1 uses SalesSQLDb1.
The manufacturing office contains two on-premises SQL Server 2016 servers named SERVER2 and SERVER3. The servers are nodes in the same Always On availability group. The availability group contains a database named ManufacturingSQLDb1 Database administrators have two Azure virtual machines in HubVnet named VM1 and VM2 that run Windows Server 2019 and are used to manage all the Azure databases.
Licensing Agreement
Litware is a Microsoft Volume Licensing customer that has License Mobility through Software Assurance.
Current Problems
SalesSQLDb1 experiences performance issues that are likely due to out-of-date statistics and frequent blocking queries.
Requirements
Planned Changes
Litware plans to implement the following changes:
* Implement 30 new databases in Azure, which will be used by time-sensitive manufacturing apps that have varying usage patterns. Each database will be approximately 20 GB.
* Create a new Azure SQL database named ResearchDB1 on a logical server named ResearchSrv01. ResearchDB1 will contain Personally Identifiable Information (PII) data.
* Develop an app named ResearchApp1 that will be used by the research department to populate and access ResearchDB1.
* Migrate ManufacturingSQLDb1 to the Azure virtual machine platform.
* Migrate the SERVER1 databases to the Azure SQL Database platform.
Technical Requirements
Litware identifies the following technical requirements:
* Maintenance tasks must be automated.
* The 30 new databases must scale automatically.
* The use of an on-premises infrastructure must be minimized.
* Azure Hybrid Use Benefits must be leveraged for Azure SQL Database deployments.
* 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.
Security and Compliance Requirements
Litware identifies the following security and compliance requirements:
* Store encryption keys in Azure Key Vault.
* Retain backups of the PII data for two months.
* Encrypt the PII data at rest, in transit, and in use.
* Use the principle of least privilege whenever possible.
* Authenticate database users by using Active Directory credentials.
* Protect Azure SQL Database instances by using database-level firewall rules.
* Ensure that all databases hosted in Azure are accessible from VM1 and VM2 without relying on public endpoints.
Business Requirements
Litware identifies the following business requirements:
* Meet an SLA of 99.99% availability for all Azure deployments.
* Minimize downtime during the migration of the SERVER1 databases.
* Use the Azure Hybrid Use Benefits when migrating workloads to Azure.
* Once all requirements are met, minimize costs whenever possible.

Scenario: Authenticate database users by using Active Directory credentials.
(Create a new Azure SQL database named ResearchDB1 on a logical server named ResearchSrv01.) Authenticate the user in SQL Database or SQL Data Warehouse based on an Azure Active Directory user:
CREATE USER [[email protected]] FROM EXTERNAL PROVIDER;
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-user-transact-sql Perform Administration by Using T-SQL Question Set 2

Section: [none]
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.
Incorrect Answers:
Azure Log Analytics
Azure metric and log data are sent to Azure Monitor Logs, previously known as Azure Log Analytics, directly by Azure. Azure SQL Analytics is a cloud only monitoring solution supporting streaming of diagnostics telemetry for all of your Azure SQL databases.
However, because Azure SQL Analytics does not use agents to connect to Azure Monitor, it does not support monitoring of SQL Server hosted on-premises or in virtual machines.
Testlet 2
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 Next 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 Question button to return to the question.
Overview
General Overview
Contoso, Ltd. is a financial data company that has 100 employees. The company delivers financial data to customers.
Physical Locations
Contoso has a datacenter in Los Angeles and an Azure subscription. All Azure resources are in the US West 2 Azure region. Contoso has a 10-Gb ExpressRoute connection to Azure.
The company has customers worldwide.
Existing Environment
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 be 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.

Section: [none]
Explanation:
The Max Size (MB) limit isn't strictly enforced. Storage size is checked only when Query Store writes data to disk. This interval is set by the Data Flush Interval (Minutes) option. If Query Store has breached the maximum size limit between storage size checks, it transitions to read-only mode.
Incorrect Answers:
C: Statistics Collection Interval: Defines the level of granularity for the collected runtime statistic, expressed in minutes. The default is 60 minutes. Consider using a lower value if you require finer granularity or less time to detect and mitigate issues. Keep in mind that the value directly affects the size of Query Store data.
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/performance/best-practice-with-the-query-store

The number of files depends on the number of (logical) processors on the machine. As a general rule, if the number of logical processors is less than or equal to eight, use the same number of data files as logical processors. If the number of logical processors is greater than eight, use eight data files and then if contention continues, increase the number of data files by multiples of 4 until the contention is reduced to acceptable levels or make changes to the workload/code.
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/databases/tempdb-database