- A
Increase the number of nodes in the Spanner instance.
Why wrong: Adding nodes increases overall throughput but does not reduce latency for individual writes. Write latency is bound by distributed commit overhead.
- B
Use interleaved tables to colocate related rows.
Interleaved tables store parent and child rows in the same split, reducing the number of participants in a transaction and decreasing write latency.
- C
Switch to eventual consistency mode for writes.
Why wrong: Cloud Spanner does not support eventual consistency for writes; it provides strong consistency. This option is not feasible.
- D
Split the table into multiple smaller tables.
Why wrong: Splitting tables can actually increase latency due to more cross-table transactions and does not address the root cause of distributed commit overhead.
Quick Answer
The answer is to use interleaved tables to colocate related rows. This design change most effectively reduces write latency in Cloud Spanner because interleaved tables physically store parent and child rows together on the same split, eliminating the need for cross-node round trips during single-row writes. For a globally distributed database handling high consistency requirements, this minimizes distributed transaction overhead, which is the primary cause of latency spikes during peak hours. On the Google Professional Cloud Developer exam, this concept tests your understanding of Cloud Spanner’s internal architecture and schema design—a common trap is to assume that adding more nodes or reducing consistency levels is the fix, but interleaving directly addresses the root cause of split-related latency. Remember the memory tip: “Interleave to interleave writes”—if your rows are related, keep them physically close to keep writes fast.
PCD Practice Question: Designing highly scalable, available, and reliable cloud-native applications
This PCD practice question tests your understanding of designing highly scalable, available, and reliable cloud-native applications. 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.
An online gaming platform uses Cloud Spanner as its globally distributed database. They notice that write latency increases significantly during peak hours. The application performs many single-row writes with high consistency requirements. Which design change would most effectively reduce write latency?
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
Use interleaved tables to colocate related rows.
Interleaved tables in Cloud Spanner physically colocate parent and child rows, reducing the number of splits and cross-node round trips for related single-row writes. This minimizes distributed transaction overhead and write latency, especially under high consistency requirements, without requiring additional nodes or sacrificing consistency.
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.
- ✗
Increase the number of nodes in the Spanner instance.
Why it's wrong here
Adding nodes increases overall throughput but does not reduce latency for individual writes. Write latency is bound by distributed commit overhead.
- ✓
Use interleaved tables to colocate related rows.
Why this is correct
Interleaved tables store parent and child rows in the same split, reducing the number of participants in a transaction and decreasing write latency.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Switch to eventual consistency mode for writes.
Why it's wrong here
Cloud Spanner does not support eventual consistency for writes; it provides strong consistency. This option is not feasible.
- ✗
Split the table into multiple smaller tables.
Why it's wrong here
Splitting tables can actually increase latency due to more cross-table transactions and does not address the root cause of distributed commit overhead.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume scaling nodes (Option A) is the universal fix for latency, but Cloud Spanner's write latency is dominated by distributed coordination, not node count, making interleaved tables a more targeted solution.
Detailed technical explanation
How to think about this question
Cloud Spanner uses a Paxos-based replication protocol with TrueTime to guarantee linearizability. Interleaved tables leverage the underlying key-value store's locality by storing child rows adjacent to their parent row in the same split, allowing single-row writes to commit within a single Paxos group. This avoids two-phase commit (2PC) overhead for related rows, which is critical for latency-sensitive workloads during peak hours.
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 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
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PCD question test?
Designing highly scalable, available, and reliable cloud-native applications — This question tests Designing highly scalable, available, and reliable cloud-native applications — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use interleaved tables to colocate related rows. — Interleaved tables in Cloud Spanner physically colocate parent and child rows, reducing the number of splits and cross-node round trips for related single-row writes. This minimizes distributed transaction overhead and write latency, especially under high consistency requirements, without requiring additional nodes or sacrificing consistency.
What should I do if I get this PCD 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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Last reviewed: Jun 25, 2026
This PCD 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 PCD exam.
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