To configure an Azure SQL Managed Instance to use the Business Critical service tier with PowerShell, you'll use the Set-AzSqlInstance cmdlet. This cmdlet allows you to modify various properties of an existing managed instance, including its service tier. You'll need to specify the resource group, instance name, and the desired service tier as "BusinessCritical".
Example:
$resourceGroupName = "YourResourceGroupName"
$managedInstanceName = "YourManagedInstanceName"
$serviceTier = "BusinessCritical"
Set-AzSqlInstance -ResourceGroupName $resourceGroupName -Name
$managedInstanceName -ServiceTier $serviceTier
Reference:
https://learn.microsoft.com/en-us/azure/azure-sql/managed-instance/scripts/create-configure-managed-instance-powershell

The fact that the classification engine has not run yet is the most likely reason why the column lacks a Confidential sensitivity label.
In Azure SQL Database, Dynamic Data Masking (DDM) and Data Discovery and Classification are two entirely independent features. Applying a mask to a column does not automatically assign a sensitivity label to it; the classification engine must scan the database schema to discover and recommend those labels.
Independent Features: Dynamic Data Masking obfuscates real-time data for non-privileged users.
Data Discovery and Classification tags data based on its business sensitivity. They do not automatically trigger each other.
Scan Requirement: The automated classification engine relies on regular schema scans to evaluate column names (like first_name) against built-in or custom information types. If it hasn't run, no recommendations will exist.
Manual Step Needed: Even after the engine runs, recommendations must be explicitly accepted and saved by an administrator before the labels are permanently applied to the columns.
Reference:
https://learn.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview

Explanation:
Box 1: 35591
Query 35591 has the longest duration.
Review top queries per duration
Two metrics in Query Performance Insight can help you find potential bottlenecks: duration and execution count. Long-running queries have the greatest potential for locking resources longer, blocking other users, and limiting scalability. They're also the best candidates for optimization.
Box 2: 35563
Query 35563 has the highest execution count.
Reference:
https://learn.microsoft.com/en-us/azure/azure-sql/database/query-performance-insight-use

Elastic jobs support two authentication methods to connect to target databases: Microsoft Entra ID (Azure AD) authentication using a user-assigned managed identity (UMI) or database-scoped credentials.
Microsoft recommends using user-assigned managed identity (UMI) for authentication because it integrates with Azure AD and supports Conditional Access policies, including location-based policies.

To create an email alert for high CPU percentage utilization in an Azure database within the Azure portal, you'll first need to navigate to your database resource, then to the "Alerts" section.
From there, you'll create a new alert rule, define the CPU percentage threshold, configure an action group for email notifications, and finally, create the alert rule.
Create alerts for Azure SQL Database and Azure Synapse Analytics using the Azure portal Step 1: In the Azure portal, locate the resource you are interested in monitoring and select it.
[Select db1]
Step 2: In the resource menu under Monitoring, select Alerts. The text and icon might vary slightly for different resources.
Step 3: Select the + Create button, then Alert rule.
Step 4: On the Create an alert rule page, the Scope is automatically configured to the individual resource.
Capture activity peaks or sustained resource stress with alerts on the Metrics signal category.
Step 5: On the Condition tab, select See all signals and Select a signal from the list of Metrics.
Step 6: Select the desired metric, for example CPU percentage. Select Apply. [Select CPU percentage] Step 7: After you select a signal, the Alert logic options appear. A preview of recent activity in this resource for that signal is also displayed.
Step 8: Configure a Threshold type to determine when the alert will take action. Choose Aggregation type, Operator, and Threshold value as desired. A typical threshold is: Static, Maximum, Greater than, 80%.
Threshold: [Select 50%]
Operator: [Select Greater than]
Aggregation granularity: [Select 5 minutes]
Select the interval that's used to group the data points by using the aggregation type function.
Choose an Aggregation granularity (period) that's greater than the Frequency of evaluation to reduce the likelihood of missing the first evaluation period of an added time series.
Frequency of evaluation: [Select one minute]
Select how often the alert rule is to be run. Select a frequency that's smaller than the aggregation granularity to generate a sliding window for the evaluation.
Step 9: Under When to evaluate, determine the desired frequency of evaluation. Use the Check every and Lookback period dropdown lists.
Step 10: Optionally, you can add multiple conditions for this alert, choose the Add condition alert if desired.
Step 11: Select Next: Actions >.
Create the new alert rule
Step 12: Use the Use quick actions feature to create a new action group and provide an email or Azure mobile app notification target.
Reference:
https://learn.microsoft.com/en-us/azure/azure-sql/database/alerts-create?