DP-300 Practice Question: Monitor, configure, and optimize database resources
You administer an Azure SQL Database that hosts an order-entry application. The database is in the General Purpose tier and uses the default configuration. Users complain that some inserts and updates occasionally wait for several seconds. You observe that the database's log write throughput is frequently near its tier limit, and that many small transactions are committed one row at a time. You need to reduce log write pressure without changing the service tier. What should you do?
⚠ Common exam trap
The trap here is assuming that the transaction log is a storage capacity problem that can be solved by increasing max size rather than a throughput problem caused by commit frequency.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Batch multiple row modifications into a single transaction to reduce the number of log flush operations.
Log write throughput is consumed per committed transaction because each commit forces a log flush. Many small single-row commits generate far more flushes than a few batched transactions containing the same rows. Batching reduces the number of flushes and lowers log write pressure, which addresses the bottleneck without changing the service tier.
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 read committed snapshot isolation so that readers do not block writers.
Why it's wrong here
Read committed snapshot isolation moves row versions to tempdb so readers do not block writers, but it does not reduce the log volume produced by the write workload itself. In fact, versioning can add overhead. The observed bottleneck is log write throughput driven by many small commits, so changing the isolation level for readers does not address the cause.
- ✓
Batch multiple row modifications into a single transaction to reduce the number of log flush operations.
Why this is correct
Each committed transaction requires a log flush, so committing one row at a time multiplies the number of flushes and inflates log write throughput. Grouping many row modifications into a single transaction reduces the number of commits and therefore the number of log flushes, lowering log write pressure while staying on the same tier. This directly targets the observed near-limit log throughput.
- ✗
Increase the database's max size to allow the transaction log to grow larger before truncation.
Why it's wrong here
The transaction log in Azure SQL Database is managed by the service, and max size governs data file size rather than log write throughput. Allowing more log space does not increase the rate at which log records can be written or flushed, so the log write limit would still be reached. The problem is the rate of log generation, not the available log space.
- ✗
Change the database to the Business Critical tier so that log writes use local SSD.
Why it's wrong here
Business Critical does provide lower-latency local storage for log writes, but the requirement explicitly states that the service tier must not change. Changing tiers would also increase cost and does not address the underlying pattern of many small single-row commits that generate disproportionate log volume. The goal is to reduce log write pressure within the existing tier.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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