The answer is that increased write latency as nodes scale is most likely caused by a high volume of cross-node transactions due to split rows. This happens because Cloud Spanner automatically partitions data into splits, distributing them across nodes; when a write transaction touches rows in multiple splits, it requires a two-phase commit (2PC) protocol to coordinate across nodes, introducing significant network overhead. As you add more nodes, the probability that any given transaction spans multiple splits rises, directly increasing the coordination cost and thus write latency. On the Google Professional Cloud DevOps Engineer exam, this scenario tests your understanding of Spanner’s distributed architecture and the trade-off between horizontal scaling and transaction locality. A common trap is assuming more nodes always improve write performance, but the key insight is that write-heavy workloads with poor row-key design force cross-split coordination. Memory tip: think “more splits, more trips” — if your rows aren’t designed for locality, adding nodes just adds more handshakes.
PCDOE Optimizing service performance Practice Question
This PCDOE practice question tests your understanding of optimizing service 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.
You are designing a globally distributed application using Cloud Spanner. The application has a write-heavy workload. You notice that write latency increases as the number of nodes increases. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The workload has many cross-node transactions due to split rows.
Option B is correct because in Cloud Spanner, write-heavy workloads with many cross-node transactions cause increased write latency as nodes are added. This occurs because Spanner splits rows across nodes, and transactions that span multiple splits require two-phase commit (2PC) coordination between nodes, which adds network overhead and latency. Adding more nodes increases the likelihood that a transaction touches multiple splits, exacerbating the coordination cost.
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.
✗
The instance is using a multi-region configuration with too many read-only replicas.
Why it's wrong here
Read-only replicas do not affect write latency.
✓
The workload has many cross-node transactions due to split rows.
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The application is using stale reads for write transactions.
Why it's wrong here
Stale reads are for read-only transactions.
✗
The number of splits is too low, causing hotspots.
Why it's wrong here
Low splits cause hotspots but not uniform latency increase.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume adding nodes always improves performance, but Cisco tests the counterintuitive behavior where cross-node coordination overhead in distributed databases like Spanner can degrade write latency with scale.
Detailed technical explanation
How to think about this question
Cloud Spanner uses a distributed storage layer where data is partitioned into splits, each managed by a set of servers. Cross-split transactions use the Percolator-style two-phase commit protocol, which involves a leader for each split and a transaction coordinator; as the number of nodes grows, the probability of a transaction spanning multiple splits increases, leading to more 2PC rounds and higher latency. In practice, this means write-heavy workloads should be designed with single-split transactions (e.g., using interleaved tables or row-level access patterns) to avoid the coordination penalty.
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.
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The workload has many cross-node transactions due to split rows. — Option B is correct because in Cloud Spanner, write-heavy workloads with many cross-node transactions cause increased write latency as nodes are added. This occurs because Spanner splits rows across nodes, and transactions that span multiple splits require two-phase commit (2PC) coordination between nodes, which adds network overhead and latency. Adding more nodes increases the likelihood that a transaction touches multiple splits, exacerbating the coordination cost.
What should I do if I get this PCDOE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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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