DP-300 Administering Microsoft Azure SQL Solutions Question and Answers

SQL injection attacks are a type of cyberattack that exploit a vulnerability in the application code that interacts with the database. An attacker can inject malicious SQL statements into the user input, such as a form field or a URL parameter, and execute them on the database server, resulting in data theft, corruption, or unauthorized access1.

To protect all the databases on sql37006S95 from SQL injection attacks, you need to follow some best practices for securing your application and database layers. Here are some of the recommended steps:

• Use parameterized queries or stored procedures to separate the SQL code from the user input. This will prevent the user input from being interpreted as part of the SQL statement and avoid SQL injection23.
• Validate and sanitize the user input before passing it to the database. This will ensure that the input conforms to the expected format and type, and remove any potentially harmful characters or keywords4.
• Implement least privilege access for the database users and roles. This will limit the permissions and actions that the application can perform on the database, and reduce the impact of a successful SQL injection attack5.
• Enable Advanced Threat Protection for Azure SQL Database. This is a feature that detects and alerts you of anomalous activities and potential threats on your database, such as SQL injection, brute force attacks, or unusual access patterns. You can configure the alert settings and notifications using the Azure portal or PowerShell.

These are some of the steps to protect all the databases on sql37006S95 from SQL injection attacks.

To enable change data capture (CDC) for db1, you need to run the stored procedure sys.sp_cdc_enable_db in the database context. CDC is a feature that records activity on a database when tables and rows have been modified1. CDC can be used for various scenarios, such as data synchronization, auditing, or ETL processes2.

Here are the steps to enable CDC for db1:

• Connect to db1 using SQL Server Management Studio, Azure Data Studio, or any other tool that supports Transact-SQL statements.
• Open a new query window and run the following command: EXEC sys.sp_cdc_enable_db; GO
• This command will enable CDC for the database and create the cdc schema, cdc user, metadata tables, and other system objects for the database3.
• To verify that CDC is enabled for db1, you can query the is_cdc_enabled column in the sys.databases catalog view. The value should be 1 for db1.

These are the steps to enable CDC for db1

Azure Backup provides an Enterprise class backup capability for SQL Server on Azure VMs. All backups are stored and managed in a Recovery Services vault. There are several advantages that this solution provides, especially for Enterprises.

Azure SQL Database single database supports Data Sync.

To configure your user account as the Azure AD admin for the server named sql3700689S, you can use the Azure portal or the Azure CLI. Here are the steps for both methods:

• Using the Azure portal:
• Using the Azure CLI:

These are the steps to configure your user account as the Azure AD admin for the server named sql3700689S.

To configure high availability for dbl, 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 choose all, or a subset of, user databases in a logical server to be replicated to another logical server in a different region. You can also specify the failover policy, such as manual or automatic, and the grace period for data loss.

Here are the steps to create a failover group for dbl:

• Using the Azure portal:

• Using PowerShell commands:

These are the steps to create a failover group for dbl

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

There are resource types related to application code, compute infrastructure, networking, storage + databases.

You can deploy up to 800 instances of a resource type in each resource group.

Some resources can exist outside of a resource group. These resources are deployed to the subscription, management group, or tenant. Only specific resource types are supported at these scopes.

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

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.

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.

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.

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.

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.

The lifecycle management policy lets you:

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

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.

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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.

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.

To ensure that any enhancements made to the Query Optimizer through patches are available to dbl and db2 on sql37006895, you need to enable the query optimizer hotfixes option for each database. This option allows you to use the latest query optimization improvements that are not enabled by default1. You can enable this option by using the ALTER DATABASE SCOPED CONFIGURATION statement2.

Here are the steps to enable the query optimizer hotfixes option for dbl and db2 on sql37006895:

• Connect to sql37006895 using SQL Server Management Studio, Azure Data Studio, or any other tool that supports Transact-SQL statements.
• Open a new query window and run the following commands for each database:

-- Switch to the database context

USE dbl;

GO

-- Enable the query optimizer hotfixes option

ALTER DATABASE SCOPED CONFIGURATION SET QUERY_OPTIMIZER_HOTFIXES = ON;

GO

• Repeat the same commands for db2, replacing dbl with db2 in the USE statement.
• To verify that the query optimizer hotfixes option is enabled for each database, you can query the sys.database_scoped_configurations catalog view. The value of the query_optimizer_hotfixes column should be 1 for both databases.

These are the steps to enable the query optimizer hotfixes option for dbl and db2 on sql37006895.

To ensure that db1 is compatible with all the features and syntax of SQL Server 2012, you need to set the compatibility level of the database to 110, which is the compatibility level for SQL Server 20121. The compatibility level affects the behavior of certain Transact-SQL statements and features, and determines how the database engine interprets the SQL code2.

You can set the compatibility level of db1 by using the Azure portal or Transact-SQL statements. Here are the steps for both methods:

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

These are the steps to set the compatibility level of db1 to 110. 

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.

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

Graphical user interface, text, application Description automatically generated

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