DP-300 Practice Question: Monitor, configure, and optimize database resources
You are monitoring an Azure SQL Database using Intelligent Insights. You receive an alert indicating 'Degradation in performance due to increased log write wait time'. What is the most likely cause of this issue?
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
✓
The log rate limit has been reached due to high transaction throughput
High log write wait times typically indicate that the transaction log throughput is a bottleneck, often due to the log rate limit. Option A is wrong because high CPU utilization would cause other wait types like SOS_SCHEDULER_YIELD, not WRITELOG. Option B is wrong because long-running blocking transactions cause wait types like LCK_M_*, not increased log write wait time. Option D is wrong because insufficient storage space for data files causes different symptoms, such as write errors or data file growth issues, but not specifically log write wait.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
High CPU utilization on the database server
Why it's wrong here
High CPU utilisation surfaces as CPU-related waits and query timeouts, not increased log write wait time. It is tempting because CPU pressure degrades overall database performance, but Intelligent Insights isolates log write waits to transaction log throughput, usually caused by log-heavy write workloads or insufficient log throughput.
- ✗
Long-running blocking transactions
Why it's wrong here
Long-running blocking transactions manifest as lock waits (LCK_M_*) and deadlocks, not log write wait time. It is tempting because blocking also degrades performance, but Intelligent Insights ties log write waits to transaction log throughput, typically from excessive concurrent writes or log-intensive operations.
- ✓
The log rate limit has been reached due to high transaction throughput
Why this is correct
High transaction throughput saturates the transaction log write rate, hitting the Azure SQL Database log rate limit and producing increased log write wait time. Intelligent Insights attributes this specific wait category to log throughput throttling, not to CPU, memory, or storage IOPS pressure elsewhere.
- ✗
Insufficient storage space for data files
Why it's wrong here
Insufficient data-file storage produces errors such as 1105 or 9002 when files cannot grow, not elevated log write wait time. It is tempting because storage exhaustion degrades performance broadly, but Intelligent Insights attributes log write waits to transaction log throughput, typically from excessive concurrent writes or log-heavy operations.
Go deeper
Related to this question
Learn chapter
Monitoring Database Performance with Azure Tools
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
About these practice questions
Courseiva writes every DP-300 question from scratch — 574 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-300 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-300 exam.