Quick Answer
The answer is CPU utilization and Disk IOPS. These two metrics are most important for detecting performance degradation in Cloud SQL for PostgreSQL because they directly reflect the two primary resource constraints that throttle database throughput. Sustained CPU utilization above 80% forces query queuing and increased latency, while hitting the Disk IOPS limit—such as the 3,000 IOPS ceiling on a pd-standard disk—causes I/O throttling that cripples WAL writes, checkpointing, and query execution. On the Google Professional Cloud Database Engineer exam, this question tests your understanding of how Cloud SQL’s shared resource model differs from standalone PostgreSQL, where memory or connection limits are often the first bottleneck. A common trap is choosing memory or connection count, but CPU and IOPS are the first to saturate under load. Memory tip: think “compute and storage”—CPU handles the compute, IOPS handles the storage path, and both must be balanced to avoid degradation.
This PCDE practice question tests your understanding of monitor and optimize database performance. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 metrics are most important to monitor for a Cloud SQL for PostgreSQL instance to detect performance degradation?
Memory usage
Why wrong: PostgreSQL manages memory inside the buffer cache; OS memory usage is not a primary indicator.
CPU utilization
High CPU indicates query processing load.
Query latency
Why wrong: Query latency is a symptom, not a resource metric.
Disk IOPS
High IOPS can indicate I/O contention.
Network throughput (bytes sent/received)
Why wrong: Rarely a bottleneck for typical database workloads.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
CPU utilization
CPU utilization (B) is a primary indicator of performance degradation because sustained high CPU usage (e.g., >80%) can lead to query queuing, reduced throughput, and increased latency. Disk IOPS (D) is equally critical because Cloud SQL for PostgreSQL relies on disk I/O for WAL writes, checkpointing, and query execution; hitting the IOPS limit of the underlying persistent disk (e.g., 3,000 IOPS for a pd-standard disk) causes throttling and severe performance drops.
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.
Memory usage
Why it's wrong here
PostgreSQL manages memory inside the buffer cache; OS memory usage is not a primary indicator.
CPU utilization
Why this is correct
High CPU indicates query processing load.
Related concept
Read the scenario before looking for a memorised answer.
Query latency
Why it's wrong here
Query latency is a symptom, not a resource metric.
Disk IOPS
Why this is correct
High IOPS can indicate I/O contention.
Related concept
Read the scenario before looking for a memorised answer.
Network throughput (bytes sent/received)
Why it's wrong here
Rarely a bottleneck for typical database workloads.
Common exam traps
Google Cloud often tests the misconception that query latency is a primary monitoring metric, but the trap here is that latency is a downstream effect—you must monitor the underlying resource metrics (CPU and IOPS) to detect degradation before users experience slow queries.
Detailed technical explanation
Cloud SQL for PostgreSQL uses Google Cloud's persistent disks (pd-standard, pd-balanced, pd-ssd) with specific IOPS limits per disk size; for example, a 10 GB pd-ssd disk provides 3,000 read IOPS and 1,500 write IOPS. When IOPS are exhausted, the database experiences I/O throttling, causing checkpoint writes and query execution to stall, which directly impacts CPU utilization as the database waits for I/O. CPU utilization above 70-80% often indicates that queries are competing for processing time, and in Cloud SQL, this can be exacerbated by autovacuum processes or inefficient query plans.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Monitor and optimize database performance — study guide chapter
Learn the concepts, then practise the questions
Monitor and optimize database performance practice questions
Targeted practice on this topic area only
All PCDE questions
503 questions across all exam domains
Google Professional Cloud Database Engineer study guide
Full concept coverage aligned to exam objectives
PCDE practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise PCDE questions linked to Plan and manage database infrastructure.
Practise PCDE questions linked to Define data structures and implement SQL for Business Intelligence.
Practise PCDE questions linked to Design and implement database schemas.
Practise PCDE questions linked to Monitor and optimize database performance.
Practise PCDE questions linked to PCDE fundamentals.
Practise PCDE questions linked to PCDE scenario.
Practise PCDE questions linked to PCDE troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..
The correct answer is: CPU utilization — CPU utilization (B) is a primary indicator of performance degradation because sustained high CPU usage (e.g., >80%) can lead to query queuing, reduced throughput, and increased latency. Disk IOPS (D) is equally critical because Cloud SQL for PostgreSQL relies on disk I/O for WAL writes, checkpointing, and query execution; hitting the IOPS limit of the underlying persistent disk (e.g., 3,000 IOPS for a pd-standard disk) causes throttling and severe performance drops.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 30, 2026
This PCDE practice question is part of Courseiva's free Google Cloud 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 PCDE exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.