Quick Answer
The answer is to increase the log write throughput by moving to a higher service tier and to add a nonclustered index to reduce the number of pages modified during write operations. These two actions directly address the root cause of PAGEIOLATCH_UP waits, which occur when a task holds an update latch while waiting for a page I/O request to complete—typically due to insufficient I/O capacity or excessive page modifications. On the DP-300 exam, this question tests your ability to diagnose and resolve I/O contention in Azure SQL Database, often appearing as a scenario where you must choose between scaling resources and optimizing index design. A common trap is confusing PAGEIOLATCH_UP with PAGEIOLATCH_SH (shared latch) waits; remember that UP waits are tied to update operations, so reducing the volume of modified pages or increasing log throughput is key. Memory tip: “UPdate needs UPgraded throughput or UPdated indexes.”
This DP-300 practice question tests your understanding of monitor, configure, and optimize database resources. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 actions can help reduce `PAGEIOLATCH_UP` waits on an Azure SQL Database?
Add a nonclustered index to reduce update I/O.
Index improvement reduces the I/O needed for updates.
Reduce MAXDOP to 1.
Why wrong: Reducing MAXDOP may increase serial I/O.
Increase the log write throughput by moving to a higher tier.
Log write throughput increase reduces log-related I/O waits.
Increase the buffer pool size by adding more memory.
Why wrong: Memory helps page reads, not log writes.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Add a nonclustered index to reduce update I/O.
A is correct because adding a nonclustered index can reduce the number of pages that need to be updated during write operations, thereby decreasing the I/O load that causes `PAGEIOLATCH_UP` waits. These waits occur when a task is waiting for a page I/O request to complete while holding an update latch. By optimizing the index structure, fewer pages are modified, reducing the I/O contention.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Add a nonclustered index to reduce update I/O.
Why this is correct
Index improvement reduces the I/O needed for updates.
Related concept
Read the scenario before looking for a memorised answer.
Reduce MAXDOP to 1.
Why it's wrong here
Reducing MAXDOP may increase serial I/O.
Increase the log write throughput by moving to a higher tier.
Why this is correct
Log write throughput increase reduces log-related I/O waits.
Related concept
Read the scenario before looking for a memorised answer.
Increase the buffer pool size by adding more memory.
Why it's wrong here
Memory helps page reads, not log writes.
Common exam traps
The trap here is that candidates often confuse `PAGEIOLATCH_UP` waits with general I/O bottlenecks and incorrectly assume that adding memory or reducing parallelism will resolve the issue, when in fact the wait is specifically tied to page-level latch contention during I/O, which is best addressed by reducing the I/O workload through indexing or increasing I/O throughput.
Detailed technical explanation
`PAGEIOLATCH_UP` waits indicate contention on page latches during I/O operations, specifically when a page is being read from or written to disk. In Azure SQL Database, the buffer pool is managed by the SQL Server engine, and increasing memory (e.g., by scaling up the service tier) can reduce the frequency of physical I/O but does not eliminate the need for latches during writes. A nonclustered index can reduce the number of pages modified by an update operation, especially if it covers the updated columns, thereby lowering the I/O demand and latch contention.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
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FAQ
Monitor, configure, and optimize database resources — This question tests Monitor, configure, and optimize database resources — Read the scenario before looking for a memorised answer..
The correct answer is: Add a nonclustered index to reduce update I/O. — A is correct because adding a nonclustered index can reduce the number of pages that need to be updated during write operations, thereby decreasing the I/O load that causes `PAGEIOLATCH_UP` waits. These waits occur when a task is waiting for a page I/O request to complete while holding an update latch. By optimizing the index structure, fewer pages are modified, reducing the I/O contention.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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