The answer is to optimize transactions to reduce lock contention. This is the correct first step because Cloud Spanner latency and transaction aborts during peak hours are almost always driven by lock contention, where overlapping read-write transactions compete for the same rows or key ranges, forcing aborts and retries that degrade performance. On the Google Professional Cloud Architect exam, this scenario tests your understanding of Spanner’s distributed transaction model and the principle that tuning application behavior—such as shortening transaction scopes, using read-only transactions for non-mutating work, and avoiding hot-spot writes—is the most cost-effective and schema-safe fix before considering scaling or schema redesign. A common trap is to immediately suggest increasing node count or switching to interleaved tables, but those address throughput or storage, not the root cause of contention. Memory tip: think “LCR” for Lock Contention Reduction—if your Spanner is slow and aborting, look at your locks first.
Google PCA Ensure solution and operations reliability Practice Question
This PCA practice question tests your understanding of ensure solution and operations reliability. 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 company uses Cloud Spanner for a global financial application. They experience increased latency and transaction aborts during peak hours. Which measure should they take first to improve reliability?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Optimize transactions to reduce lock contention.
Option C is correct because transaction aborts and latency in Cloud Spanner are most commonly caused by lock contention during peak hours. By optimizing transactions—such as reducing their scope, using read-only transactions where possible, and avoiding hot-spot writes—you directly address the root cause of contention without incurring additional cost or schema changes. This aligns with Google's best practices for Spanner reliability.
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 capacity but does not directly reduce contention-induced aborts.
✗
Reduce the number of indexes on frequently updated columns.
Why it's wrong here
Fewer indexes reduce write overhead but not transaction aborts due to contention.
✓
Optimize transactions to reduce lock contention.
Why this is correct
Short, single-partition transactions reduce the chance of conflicts and aborts.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use interleaved tables to co-locate related data.
Why it's wrong here
Interleaving improves join performance but does not directly reduce contention.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that scaling nodes (Option A) is the universal fix for performance issues, but the trap here is that Spanner's horizontal scaling does not resolve lock contention—it only increases parallelism, which can worsen contention if transactions are not optimized.
Detailed technical explanation
How to think about this question
Cloud Spanner uses TrueTime and pessimistic locking for read-write transactions; when two transactions contend for the same row, one must abort and retry, leading to latency spikes. Optimizing transactions can involve using stale reads (with a timestamp bound) for non-critical queries, splitting large transactions into smaller batches, or designing keys to avoid hot spots—such as using a hash prefix on monotonically increasing keys. In a global financial application, even a single hot row (e.g., a counter for a popular account) can cause cascading aborts across regions.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Ensure solution and operations reliability — This question tests Ensure solution and operations reliability — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Optimize transactions to reduce lock contention. — Option C is correct because transaction aborts and latency in Cloud Spanner are most commonly caused by lock contention during peak hours. By optimizing transactions—such as reducing their scope, using read-only transactions where possible, and avoiding hot-spot writes—you directly address the root cause of contention without incurring additional cost or schema changes. This aligns with Google's best practices for Spanner reliability.
What should I do if I get this PCA 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: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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