DP-300 Administering Relational Databases on Microsoft Azure Questions and Answers

Scenario: SalesSQLDb1 uses database firewall rules and contained database users.

Scenario: Business Requirements

Litware identifies business requirements include: meet an SLA of 99.99% availability for all Azure deployments.

Box 1: Cloud witness

If you have a Failover Cluster deployment, where all nodes can reach the internet (by extension of Azure), it is recommended that you configure a Cloud Witness as your quorum witness resource.

Box 2: Azure Basic Load Balancer

Microsoft guarantees that a Load Balanced Endpoint using Azure Standard Load Balancer, serving two or more Healthy Virtual Machine Instances, will be available 99.99% of the time.

Note: There are two main options for setting up your listener: external (public) or internal. The external (public) listener uses an internet facing load balancer and is associated with a public Virtual IP (VIP) that is accessible over the internet. An internal listener uses an internal load balancer and only supports clients within the same Virtual Network.

Azure Database Migration service

Box 1: Premium 4-VCore

Scenario: Migrate the SERVER1 databases to the Azure SQL Database platform.

• Minimize downtime during the migration of the SERVER1 databases.

Premimum 4-vCore is for large or business critical workloads. It supports online migrations, offline migrations, and faster migration speeds.

Instead use a serverless SQL pool to create an external table with the extra column.

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 [Fritz@contoso.com] FROM EXTERNAL PROVIDER;

SalesSQLDb1 experiences performance issues that are likely due to out-of-date statistics and frequent blocking queries.

A: Use sys.dm_pdw_nodes_tran_locks instead of sys.dm_tran_locks from Azure Synapse Analytics (SQL Data Warehouse) or Parallel Data Warehouse.

E: Example:

The following query will show blocking information.

SELECT

t1.resource_type,

t1.resource_database_id,

t1.resource_associated_entity_id,

t1.request_mode,

t1.request_session_id,

t2.blocking_session_id

FROM sys.dm_tran_locks as t1

INNER JOIN sys.dm_os_waiting_tasks as t2

ON t1.lock_owner_address = t2.resource_address;

Note: Depending on the system you’re working with you can access these wait statistics from one of three locations:

sys.dm_os_wait_stats: for SQL Server

sys.dm_db_wait_stats: for Azure SQL Database

sys.dm_pdw_nodes_os_wait_stats: for Azure SQL Data Warehouse

Scenario: Authenticate database users by using Active Directory credentials.

The configuration steps include the following procedures to configure and use Azure Active Directory authentication.

• Create and populate Azure AD.

• Optional: Associate or change the active directory that is currently associated with your Azure Subscription.
• Create an Azure Active Directory administrator. (Step 1)
• Configure your client computers.
• Create contained database users in your database mapped to Azure AD identities. (Step 2)
• Connect to your database by using Azure AD identities. (Step 3)

Text Description automatically generated

By default, the cluster of nodes for the premium availability model is created in the same datacenter. With the introduction of Azure Availability Zones, SQL Database can place different replicas of the Business Critical database to different availability zones in the same region. To eliminate a single point of failure, the control ring is also duplicated across multiple zones as three gateway rings (GW). The routing to a specific gateway ring is controlled by Azure Traffic Manager (ATM). Because the zone redundant configuration in the Premium or Business Critical service tiers does not create additional database redundancy, you can enable it at no extra cost. By selecting a zone redundant configuration, you can make your Premium or Business Critical databases resilient to a much larger set of failures, including catastrophic datacenter outages, without any changes to the application logic. You can also convert any existing Premium or Business Critical databases or pools to the zone redundant configuration.

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.

To configure sq1370O6895 to support the creation of new database users from Azure AD identities, you need to do the following steps:

• Set up a Microsoft Entra tenant and associate it with your Azure subscription. You can use the Microsoft Entra portal or the Azure portal to create and manage your Microsoft Entra users and groups12.
• Configure a Microsoft Entra admin for sq1370O6895. You can use the Azure portal or the Azure CLI to set a Microsoft Entra user as the admin for the server34. The Microsoft Entra admin can create other database users from Microsoft Entra identities5.
• Connect to db1 using the Microsoft Entra admin account and run the following Transact-SQL statement to create a new database user from a Microsoft Entra identity: CREATE USER [Microsoft Entra user name] FROM EXTERNAL PROVIDER;6 You can replace the Microsoft Entra user name with the name of the user or group that you want to create in the database.
• Grant the appropriate permissions to the new database user by adding them to a database role or granting them specific privileges. For example, you can run the following Transact-SQL statement to add the new user to the db_datareader role: ALTER ROLE db_datareader ADD MEMBER [Microsoft Entra user name];

These are the steps to configure sq1370O6895 to support the creation of new database users from Azure AD identities.

To enable page compression on the PK_SalesOrderHeader_SalesOrderlD clustered index of the SalesLT.SalesOrderHeader table in db1, you can use the following Transact-SQL script:

-- Connect to the Azure SQL database named db1

USE db1;

GO

-- Enable page compression on the clustered index

ALTER INDEX PK_SalesOrderHeader_SalesOrderlD ON SalesLT.SalesOrderHeader

REBUILD WITH (DATA_COMPRESSION = PAGE);

GO

This script will rebuild the clustered index with page compression, which can reduce the storage space and improve the query performance

The script solution consists of three parts:

• The first part is USE db1; GO. This part connects to the Azure SQL database named db1, where the SalesLT.SalesOrderHeader table is located. The GO command separates the batches of Transact-SQL statements and sends them to the server.
• The second part is ALTER INDEX PK_SalesOrderHeader_SalesOrderlD ON SalesLT.SalesOrderHeader REBUILD WITH (DATA_COMPRESSION = PAGE); GO. This part enables page compression on the clustered index named PK_SalesOrderHeader_SalesOrderlD, which is defined on the SalesLT.SalesOrderHeader table. The ALTER INDEX statement modifies the properties of an existing index. The REBUILD option rebuilds the index from scratch, which is required to change the compression setting. The DATA_COMPRESSION = PAGE option specifies that page compression is applied to the index, which means that both row and prefix compression are used. Page compression can reduce the storage space and improve the query performance by compressing the data at the page level. The GO command ends the batch of statements.
• The third part is optional, but it can be useful to verify the compression status of the index. It is SELECT name, index_id, data_compression_desc FROM sys.indexes WHERE object_id = OBJECT_ID('SalesLT.SalesOrderHeader');. This part queries the sys.indexes catalog view, which contains information about the indexes in the database. The SELECT statement returns the name, index_id, and data_compression_desc columns for the indexes that belong to the SalesLT.SalesOrderHeader table. The OBJECT_ID function returns the object identification number for the table name. The data_compression_desc column shows the compression type of the index, which should be PAGE for the clustered index after the script is executed.

These are the steps of the script solution for enabling page compression on the clustered index of the SalesLT.SalesOrderHeader table in db1.

To configure a disaster recovery solution for db1, you can use the failover groups feature of Azure SQL Database. Failover groups allow you to manage the replication and failover of a group of databases across different regions with the same connection strings1. You can also use active geo-replication as an alternative, but you will need to update the connection strings manually after a failover2.

Here are the steps to create a failover group for db1 with the secondary server in the West US 3 region:

• Using the Azure portal:
• Using PowerShell commands:

These are the steps to create a failover group for db1 with the secondary server in the West US 3 region.

To generate an email alert to admin@contoso.com 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 admin@contoso.com 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 admin@contoso.com 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

To ensure that all queries executed against dbl are captured in the Query Store, you need to enable the Query Store feature for the database and set the query capture mode to ALL. The Query Store feature provides you with insight on query plan choice and performance for Azure SQL Database1. The query capture mode controls whether all queries or only a subset of queries are tracked2.

Here are the steps to enable the Query Store and set the query capture mode to ALL for the database dbl:

• Using the Azure portal:
• Using Transact-SQL statements:

These are the steps to ensure that all queries executed against dbl are captured in the Query Store.

Scenario: The sales data, including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytics process will perform aggregations that must be done continuously, without gaps, and without overlapping.

Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

Timeline Description automatically generated

Scenario: Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.

To monitor the performance of a database in Azure SQL Database and Azure SQL Managed Instance, start by monitoring the CPU and IO resources used by your workload relative to the level of database performance you chose in selecting a particular service tier and performance level.

Box 1: Yes

DBAGroup1 is member of the Contributor role.

The Contributor role grants full access to manage all resources, but does not allow you to assign roles in Azure RBAC, manage assignments in Azure Blueprints, or share image galleries.

Box 2: No

Box 3: Yes

DBAGroup2 is member of the SQL DB Contributor role.

The SQL DB Contributor role lets you manage SQL databases, but not access to them. Also, you can't manage their security-related policies or their parent SQL servers. As a member of this role you can create and manage SQL databases.

There are CPU and Data I/O spikes for the PaaS prototype. Business Critical 4-vCore is needed.

Scenario: 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.

The auto-failover groups feature allows you to manage the replication and failover of a group of databases on a server or all databases in a managed instance to another region. It is a declarative abstraction on top of the existing active geo-replication feature, designed to simplify deployment and management of geo-replicated databases at scale. You can initiate failover manually or you can delegate it to the Azure service based on a user-defined policy.

The latter option allows you to automatically recover multiple related databases in a secondary region after a catastrophic failure or other unplanned event that results in full or partial loss of the SQL Database or SQL Managed Instance availability in the primary region.

Scenario: Use a single dashboard to review security and audit data for all the PaaS databases.

With dashboards can bring together operational data that is most important to IT across all your Azure resources, including telemetry from Azure Log Analytics.

Note: Auditing for Azure SQL Database and Azure Synapse Analytics tracks database events and writes them to an audit log in your Azure storage account, Log Analytics workspace, or Event Hubs.

The lifecycle management policy lets you:

Delete blobs, blob versions, and blob snapshots at the end of their lifecycles

Scenario: Contoso requirements for the sales transaction dataset include:

Implement a surrogate key to account for changes to the retail store addresses.

A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the

table data. Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the IDENTITY property to achieve this goal simply and effectively without affecting load performance.

Graphical user interface, text, application Description automatically generated

Box 1: Hash

Scenario:

Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.

A hash distributed table can deliver the highest query performance for joins and aggregations on large tables.

Box 2: Round-robin

Scenario:

You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific product. The product will be identified by a product ID. The table will be approximately 5 GB.

A round-robin table is the most straightforward table to create and delivers fast performance when used as a staging table for loads. These are some scenarios where you should choose Round robin distribution:

• When you cannot identify a single key to distribute your data.
• If your data doesn’t frequently join with data from other tables.
• When there are no obvious keys to join.

DBCC SHRINKDATABASE shrinks the size of the data and log files in the specified database.

A: Auto-failover groups allow you to manage replication and failover of a group of databases on a server or all

databases in a managed instance to another region.

E: Because verification of the scale of the outage and how quickly it can be mitigated involves human actions

by the operations team, the grace period cannot be set below one hour. This limitation applies to all databases

in the failover group regardless of their data synchronization state.

Transparent data encryption (TDE) helps protect Azure SQL Database, Azure SQL Managed Instance, and Azure Synapse Analytics against the threat of malicious offline activity by encrypting data at rest.

You can use Databricks Pools to Speed up your Data Pipelines and Scale Clusters Quickly.

Databricks Pools, a managed cache of virtual machine instances that enables clusters to start and scale 4 times faster.

Text Description automatically generated

Box 1: No

Just one failure within the 5-minute interval.

Box 2: No

Just two failures within the 5-minute interval.

Box 3: No

Just two failures within the 5-minute interval.

Table Description automatically generated