DBS-C01 Monitoring and Troubleshooting Practice Question
A database engineer is monitoring an Amazon RDS for PostgreSQL instance and notices that the 'DiskQueueDepth' metric is consistently above 100. The instance uses gp2 storage with 1000 GB allocated. What is the most likely cause of the high disk queue depth?
⚠ Common exam trap
Candidates often confuse DiskQueueDepth with memory or network metrics, or assume that any high queue depth automatically indicates a hardware failure, rather than recognizing it as a symptom of IOPS exhaustion on gp2 storage.
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 instance has reached the IOPS limit of the gp2 volume
A consistently high DiskQueueDepth (above 100) on an Amazon RDS for PostgreSQL instance with gp2 storage indicates that the volume is saturating its IOPS limit. gp2 volumes provide a baseline of 3 IOPS per GB (up to 16,000 IOPS), so a 1000 GB gp2 volume has a baseline of 3000 IOPS. When the workload exceeds this baseline, the volume relies on burst credits, and once credits are exhausted, IOPS are throttled to the baseline, causing I/O requests to queue up and the DiskQueueDepth metric to rise.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Replication lag between the primary and standby instance
Why it's wrong here
Replication lag measures delay in data replication, not storage I/O.
- ✓
The instance has reached the IOPS limit of the gp2 volume
Why this is correct
For a 1000 GB gp2 volume, baseline IOPS is 3000; sustained I/O beyond that causes queuing.
- ✗
Insufficient memory allocated to the instance
Why it's wrong here
Memory issues cause swapping, not high disk queue depth.
- ✗
Network throughput limit is being exceeded
Why it's wrong here
Network limits would show in network metrics, not disk queue depth.
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Same concept, more angles
1 more way this is tested on DBS-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A database team is troubleshooting a performance issue on an Amazon RDS for PostgreSQL instance. They notice that the 'DiskQueueDepth' metric is consistently high. Which TWO actions should the team take to resolve this issue? (Choose TWO.)
easy- A.Increase the number of database connections.
- ✓ B.Enable storage auto scaling.
- ✓ C.Increase the provisioned IOPS for the instance.
- D.Enable query caching in PostgreSQL.
- E.Enable Multi-AZ deployment.
Why B: Options B and C are correct. A high disk queue depth indicates an I/O bottleneck on the RDS instance. Enabling storage auto scaling (B) allows the storage to automatically scale up when I/O demand increases, which can reduce queue depth. Increasing provisioned IOPS (C) directly improves the I/O performance by providing more throughput. Option A is incorrect because increasing connections can increase I/O contention, not reduce it. Option D is incorrect because PostgreSQL does not support query caching in the same way as MySQL, and it is not a solution to an I/O bottleneck. Option E is incorrect because Multi-AZ provides high availability but does not directly improve I/O performance.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services 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 DBS-C01 exam.