The answer is to enable Cloud Spanner interleaved tables and add secondary indexes for common query filters. This directly addresses query latency optimization under high load by improving data locality, which reduces the need for expensive cross-table joins, and by allowing the database to avoid full table scans through efficient index-based lookups. On the Google Professional Cloud Architect exam, this scenario tests your understanding of Spanner’s schema design principles, particularly how interleaved tables physically co-locate parent-child rows on the same split to minimize network round trips. A common trap is to focus on scaling nodes or adding read replicas, but the root cause here is inefficient query patterns, not raw capacity. Remember the mnemonic “Interleave for locality, index for selectivity” to recall that interleaving optimizes join performance while secondary indexes speed up filtered queries.
Google PCA Design and plan a cloud solution architecture Practice Question
This PCA practice question tests your understanding of design and plan a cloud solution architecture. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 global e-commerce platform is experiencing intermittent latency spikes during flash sales. The application is deployed on Google Kubernetes Engine (GKE) with a regional cluster. The architecture includes a frontend service, a product catalog service using Cloud Spanner, and an order processing service using Cloud Pub/Sub. During high load, the catalog service shows increased query latency, and some requests time out. What should the architect prioritize to address the issue?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable Cloud Spanner interleaved tables and add secondary indexes for common query filters.
The correct answer is C because the issue is specifically with Cloud Spanner query latency under high load. Enabling interleaved tables and adding secondary indexes optimizes data locality and query performance, reducing the need for expensive cross-table joins and full table scans. This directly addresses the root cause of increased latency and timeouts in the catalog service.
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.
✗
Use Cloud CDN to cache product catalog responses.
Why it's wrong here
Caching can reduce load but does not address the root cause of Spanner query latency; also product data may be dynamic.
✗
Increase the number of nodes in the GKE node pool.
Why it's wrong here
Scaling nodes may help overall throughput but does not directly fix query performance issues in Cloud Spanner.
✓
Enable Cloud Spanner interleaved tables and add secondary indexes for common query filters.
Read the scenario before looking for a memorised answer.
✗
Migrate the catalog service from Cloud Spanner to Cloud Bigtable for better read performance.
Why it's wrong here
Bigtable is optimized for time-series data, not transactional queries with complex filters.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse horizontal scaling (adding nodes) with database optimization, overlooking that Cloud Spanner performance issues require schema-level tuning rather than infrastructure scaling.
Detailed technical explanation
How to think about this question
Cloud Spanner interleaved tables physically co-locate parent and child rows on the same split, reducing cross-node round trips for joins. Secondary indexes in Spanner are global and strongly consistent, allowing efficient filtering without full table scans; however, they add write amplification. In a flash sale scenario, read-heavy workloads benefit from these optimizations, but architects must monitor index write overhead to avoid impacting write throughput.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Design and plan a cloud solution architecture — This question tests Design and plan a cloud solution architecture — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable Cloud Spanner interleaved tables and add secondary indexes for common query filters. — The correct answer is C because the issue is specifically with Cloud Spanner query latency under high load. Enabling interleaved tables and adding secondary indexes optimizes data locality and query performance, reducing the need for expensive cross-table joins and full table scans. This directly addresses the root cause of increased latency and timeouts in the catalog service.
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.
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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