The answer is to configure server-level auditing with a Log Analytics workspace destination. This is correct because server-level auditing on Azure SQL Database captures all DDL statements—such as CREATE, ALTER, and DROP—executed by any user across all databases on that server, and it natively supports sending the audit logs directly to a Log Analytics workspace for querying and analysis. On the Microsoft Azure Database Administrator Associate DP-300 exam, this scenario tests your understanding of the difference between server-level and database-level auditing, as well as the supported destinations for audit logs. A common trap is choosing database-level auditing, which can also capture DDL but does not support Log Analytics as a destination; only server-level auditing offers that integration. Remember the memory tip: “Server for Logs”—if you need Log Analytics, always configure at the server level.
DP-300 Implement a secure environment Practice Question
This DP-300 practice question tests your understanding of implement a secure environment. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You need to audit schema changes on an Azure SQL Database. Specifically, you must capture details of any DDL statements executed by any user. The audit logs must be stored in a Log Analytics workspace for analysis. What should you configure?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure server-level auditing with a Log Analytics workspace destination
Option C is correct because Azure SQL Database server-level auditing with a Log Analytics workspace destination captures all DDL statements executed by any user and stores them in a Log Analytics workspace for analysis. This meets the requirement to audit schema changes and store logs in Log Analytics, as server-level auditing captures events for all databases on the server, including DDL operations, and supports Log Analytics as a destination.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Create DDL triggers that write to a table
Why it's wrong here
DDL triggers can be used but they can be disabled and are not as secure as auditing.
✗
Configure database-level auditing with blob storage destination
Why it's wrong here
This works but is not the best for analysis; Log Analytics is preferred.
✓
Configure server-level auditing with a Log Analytics workspace destination
Why this is correct
Server-level auditing captures all DDL changes and can stream to Log Analytics.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create an extended events session to capture DDL events
Why it's wrong here
Extended events are available in Azure SQL Database but auditing is the recommended method for compliance.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse database-level auditing with blob storage as sufficient, but the question explicitly requires Log Analytics workspace destination, which is only supported at the server-level auditing configuration in Azure SQL Database.
Detailed technical explanation
How to think about this question
Server-level auditing in Azure SQL Database uses the same auditing engine as Azure SQL Managed Instance, capturing events like DDL statements via the sys.fn_get_audit_file function when stored in blob storage, but when configured with a Log Analytics workspace destination, it streams audit logs directly to Azure Monitor. This enables real-time analysis using Kusto Query Language (KQL) and integration with Azure Sentinel for security monitoring. A subtle behavior is that server-level auditing captures events for all databases on the server, while database-level auditing only captures events for that specific database, making server-level auditing more comprehensive for cross-database schema changes.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-300 question in full detail.
Implement a secure environment — This question tests Implement a secure environment — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure server-level auditing with a Log Analytics workspace destination — Option C is correct because Azure SQL Database server-level auditing with a Log Analytics workspace destination captures all DDL statements executed by any user and stores them in a Log Analytics workspace for analysis. This meets the requirement to audit schema changes and store logs in Log Analytics, as server-level auditing captures events for all databases on the server, including DDL operations, and supports Log Analytics as a destination.
What should I do if I get this DP-300 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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