The answer is to increase the service tier to a higher performance level and to implement In-Memory OLTP. High WRITELOG waits signal that the transaction log is a bottleneck, typically caused by excessive log I/O where the log write rate cannot keep up with transaction throughput. In-Memory OLTP directly reduces this pressure by logging only the delta changes for memory-optimized tables instead of full row versions, which dramatically cuts the volume of log writes. On the DP-300 exam, this scenario tests your ability to diagnose performance metrics and apply targeted Azure SQL Database optimizations; a common trap is to focus on index tuning or query rewriting, but WRITELOG waits are fundamentally a log throughput issue. Remember the mnemonic: “Log lag? Boost the tier and delta the log.”
DP-300 Practice Question: Monitor, configure, and optimize database resources
This DP-300 practice question tests your understanding of monitor, configure, and optimize database resources. 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.
Which TWO configurations can help improve the performance of an Azure SQL Database experiencing high `WRITELOG` waits?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use in-memory OLTP to reduce log writes.
High WRITELOG waits indicate that the transaction log is a bottleneck, often due to excessive log I/O. In-memory OLTP reduces log writes by logging only the delta changes for memory-optimized tables, rather than full row versions, which directly alleviates log pressure. This makes option B correct.
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.
✗
Enable Transparent Data Encryption (TDE).
Why it's wrong here
TDE increases log writes due to encryption.
✓
Use in-memory OLTP to reduce log writes.
Why this is correct
In-memory OLTP reduces log generation.
Related concept
Read the scenario before looking for a memorised answer.
✓
Increase the service tier to a higher performance level.
Why this is correct
Higher tiers have higher log write throughput.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable Query Store.
Why it's wrong here
Query Store writes to the database, increasing log I/O.
✗
Increase the frequency of database backups.
Why it's wrong here
More backups increase log activity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse WRITELOG waits with general I/O bottlenecks and select backup frequency or TDE, not realizing that only reducing log write volume (via in-memory OLTP) or increasing log write speed (via higher service tier) directly resolves the wait type.
Detailed technical explanation
How to think about this question
WRITELOG waits occur when sessions wait for the log buffer to flush to disk, typically measured in milliseconds per write. In-memory OLTP uses native compilation and latch-free data structures, and its log records are smaller and written asynchronously in batches, reducing total log throughput. In a real-world scenario, a high-volume order entry system with frequent inserts can see WRITELOG waits drop by over 80% after migrating hot tables to memory-optimized tables.
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.
Monitor, configure, and optimize database resources — This question tests Monitor, configure, and optimize database resources — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use in-memory OLTP to reduce log writes. — High WRITELOG waits indicate that the transaction log is a bottleneck, often due to excessive log I/O. In-memory OLTP reduces log writes by logging only the delta changes for memory-optimized tables, rather than full row versions, which directly alleviates log pressure. This makes option B correct.
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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Question Discussion
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