Quick Answer
The answer is CPU utilization per node and commit latency. CPU utilization per node is the primary indicator of whether your Cloud Spanner instance is approaching its throughput limits, as excessive CPU usage directly degrades query and transaction performance. Commit latency, meanwhile, measures the time taken to finalize a write transaction; high commit latency often signals contention, hot spots, or suboptimal schema design, making it essential for evaluating write performance. On the Google Professional Cloud Database Engineer exam, this question tests your ability to distinguish between infrastructure-level metrics (like CPU) and transaction-level metrics (like commit latency) that together reveal the health of a Spanner instance. A common trap is choosing storage utilization or node count instead, but these do not directly reflect real-time performance bottlenecks. Memory tip: think “CPU for capacity, commit for speed” — if either is high, your database is struggling.
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 should you monitor in Cloud Monitoring to evaluate the performance of a Cloud Spanner instance? (Choose two.)
Row reads per second
Why wrong: Not a standard metric in Spanner.
Commit latency
Indicates write performance.
Connection count
Why wrong: Spanner can handle many connections.
Disk IOPS
Why wrong: Spanner is not disk-based.
CPU utilization per node
High CPU indicates overload.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Commit latency
Commit latency is a critical metric for Cloud Spanner because it directly measures the time taken to commit a transaction, which reflects the database's ability to handle write operations efficiently. High commit latency can indicate contention, node overload, or suboptimal schema design, making it essential for performance evaluation.
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.
Row reads per second
Why it's wrong here
Not a standard metric in Spanner.
Commit latency
Why this is correct
Indicates write performance.
Related concept
Read the scenario before looking for a memorised answer.
Connection count
Why it's wrong here
Spanner can handle many connections.
Disk IOPS
Why it's wrong here
Spanner is not disk-based.
CPU utilization per node
Why this is correct
High CPU indicates overload.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Google Cloud often tests the misconception that throughput metrics like row reads per second or disk-level metrics like IOPS are meaningful for evaluating performance in a fully managed, distributed database like Cloud Spanner, where internal optimizations and abstractions make such metrics irrelevant.
Detailed technical explanation
Commit latency in Cloud Spanner includes the time for Paxos consensus across replicas, which can be affected by transaction size, number of mutations, and geographic distribution. In real-world scenarios, a sudden spike in commit latency might indicate a hot spot due to monotonically increasing keys or excessive single-row transactions, requiring schema redesign or use of interleaved tables.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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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: Commit latency — Commit latency is a critical metric for Cloud Spanner because it directly measures the time taken to commit a transaction, which reflects the database's ability to handle write operations efficiently. High commit latency can indicate contention, node overload, or suboptimal schema design, making it essential for performance evaluation.
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 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.
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