Azure Private Link enables you to access Azure PaaS Services (for example, Azure Storage and SQL Database) and Azure hosted customer-owned/partner services over a private endpoint in your virtual network.
Traffic between your virtual network and the service travels the Microsoft backbone network. Exposing your service to the public internet is no longer necessary.
Reference:
https://docs.microsoft.com/en-us/azure/private-link/private-link-overview

Explanation:
Box 1: DTU
Scenario:
The 30 new databases must scale automatically.
Once all requirements are met, minimize costs whenever possible.
You can configure resources for the pool based either on the DTU-based purchasing model or the vCore-based purchasing model.
In short, for simplicity, the DTU model has an advantage. Plus, if you're just getting started with Azure SQL Database, the DTU model offers more options at the lower end of performance, so you can get started at a lower price point than with vCore.
Box 2: An Azure SQL database elastic pool
Azure SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands. The databases in an elastic pool are on a single server and share a set number of resources at a set price. Elastic pools in Azure SQL Database enable SaaS developers to optimize the price performance for a group of databases within a prescribed budget while delivering performance elasticity for each database.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/elastic-pool-overview
https://docs.microsoft.com/en-us/azure/azure-sql/database/reserved-capacity-overview

Example:
Free space for the file in the below query result set will be returned by the FreeSpaceMB column.
SELECT DB_NAME() AS DbName,
name AS FileName,
type_desc,
size/128.0 AS CurrentSizeMB,
size/128.0 - CAST(FILEPROPERTY(name, 'SpaceUsed') AS INT)/128.0 AS FreeSpaceMB FROM sys.database_files WHERE type IN (0,1); Reference:
https://www.sqlshack.com/how-to-determine-free-space-and-file-size-for-sql-server-databases/

Answer as in image below.

B: Dynamic Thresholds continuously learns the data of the metric series and tries to model it using a set of algorithms and methods. It detects patterns in the data such as seasonality (Hourly / Daily / Weekly), and is able to handle noisy metrics (such as machine CPU or memory) as well as metrics with low dispersion (such as availability and error rate).
D: Alert threshold sensitivity is a high-level concept that controls the amount of deviation from metric behavior required to trigger an alert.
Low - The thresholds will be loose with more distance from metric series pattern. An alert rule will only trigger on large deviations, resulting in fewer alerts.
Incorrect Answers:
A: High - The thresholds will be tight and close to the metric series pattern. An alert rule will be triggered on the smallest deviation, resulting in more alerts.
Reference:
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/alerts-dynamic-thresholds