The answer is adding more nodes to the instance and creating a secondary index on frequently queried columns. Adding nodes horizontally scales both compute and storage capacity, directly addressing high CPU utilization by distributing the read workload across more processing resources. Creating a secondary index allows Cloud Spanner to serve reads via index-only scans, bypassing full table scans and drastically reducing the number of rows processed per query—a critical optimization for read-heavy, high-CPU scenarios. On the Google Professional Cloud Database Engineer exam, this question tests your understanding of scaling strategies versus query optimization; a common trap is choosing read replicas, which improve regional read latency but do not reduce CPU on the primary instance. Memory tip: “Nodes for muscle, indexes for finesse”—scale out the hardware, then fine-tune the access path.
PCDE Plan and manage database infrastructure Practice Question
This PCDE practice question tests your understanding of plan and manage database infrastructure. 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.
A Cloud Spanner database is experiencing high CPU utilization and latency. The workload is read-heavy with occasional writes. Which TWO actions would most effectively improve performance?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a secondary index on frequently queried columns.
Creating a secondary index on frequently queried columns allows Cloud Spanner to serve read queries directly from the index without scanning the full base table, reducing CPU usage and latency. This is especially effective in read-heavy workloads because it minimizes the number of rows that must be processed per query.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Create a secondary index on frequently queried columns.
Why this is correct
Indexes reduce the need for full table scans, lowering CPU usage and query latency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use a smaller instance configuration to reduce cost.
Why it's wrong here
Reducing nodes would worsen performance; not recommended.
✓
Add more nodes to the instance.
Why this is correct
More nodes provide additional CPU and throughput capacity, reducing CPU utilization.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use a split point to distribute hot rows.
Why it's wrong here
Split points help with write hot spots, but the issue is read-heavy with high CPU; indexes and nodes are more effective.
✗
Enable interleaved tables to reduce joins.
Why it's wrong here
Interleaved tables optimize parent-child joins but are not a general performance tuning for high CPU.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that manual split points or interleaved tables are primary tools for read performance tuning, when in fact Spanner handles splits automatically and interleaving is mainly for write locality and join optimization.
Detailed technical explanation
How to think about this question
Cloud Spanner uses a distributed storage engine where secondary indexes are stored as separate tables that are automatically maintained and can be used for point lookups or range scans without touching the base table. Adding nodes increases the instance's compute and storage capacity, distributing the read load across more servers and reducing per-node CPU pressure. In practice, a read-heavy workload benefits most from index-only scans, while node scaling provides linear throughput improvement for both reads and writes.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Plan and manage database infrastructure — This question tests Plan and manage database infrastructure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a secondary index on frequently queried columns. — Creating a secondary index on frequently queried columns allows Cloud Spanner to serve read queries directly from the index without scanning the full base table, reducing CPU usage and latency. This is especially effective in read-heavy workloads because it minimizes the number of rows that must be processed per query.
What should I do if I get this PCDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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