- A
Use interleaved tables to colocate related data.
Interleaved tables store parent and child rows in the same split, reducing the number of participants in transactions and improving performance.
- B
Store large binary blobs directly in Spanner.
Why wrong: Large blobs are better stored in Cloud Storage; Spanner is optimized for structured data, not for large blobs.
- C
Define secondary indexes on every column.
Why wrong: Excessive secondary indexes increase write overhead and storage costs; they should be created only for frequently queried columns.
- D
Use monotonically increasing primary keys.
Why wrong: Monotonically increasing keys lead to hotspotting on a single split, causing poor write scalability.
- E
Choose primary keys that distribute write load evenly across nodes.
Evenly distributed primary keys ensure that writes are spread across splits, maximizing throughput.
Quick Answer
The answer is to use interleaved tables to colocate related data and design primary keys to avoid hotspots. Interleaved tables physically store parent and child rows together on the same Cloud Spanner split, which minimizes cross-node reads and dramatically improves join performance for globally distributed applications. This is critical because it reduces latency when related data must be accessed together across regions. On the Google Professional Cloud Developer exam, this concept tests your understanding of how schema design directly impacts distributed database scalability—a common trap is choosing secondary indexes or denormalization as primary solutions, but the exam emphasizes that interleaving is the foundational pattern for colocation. For primary key distribution, remember to use a monotonically increasing key with a hash prefix or a leading shard column to prevent write hot spots. A simple memory tip: “Interleave to weave, hash to heat-proof”—interleaving weaves related data together, while hashing your primary key prevents a single node from overheating with writes.
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.
A company uses Cloud Spanner for a globally distributed application. They need to design their table schema for maximum scalability and performance. Which two design considerations are critical? (Choose two.)
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 data.
Interleaved tables in Cloud Spanner physically colocate parent and child rows on the same split, reducing cross-node reads and improving join performance. This design is critical for globally distributed applications because it minimizes latency and ensures that related data is stored together for efficient access.
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 interleaved tables to colocate related data.
Why this is correct
Interleaved tables store parent and child rows in the same split, reducing the number of participants in transactions and improving performance.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Store large binary blobs directly in Spanner.
Why it's wrong here
Large blobs are better stored in Cloud Storage; Spanner is optimized for structured data, not for large blobs.
- ✗
Define secondary indexes on every column.
Why it's wrong here
Excessive secondary indexes increase write overhead and storage costs; they should be created only for frequently queried columns.
- ✗
Use monotonically increasing primary keys.
Why it's wrong here
Monotonically increasing keys lead to hotspotting on a single split, causing poor write scalability.
- ✓
Choose primary keys that distribute write load evenly across nodes.
Why this is correct
Evenly distributed primary keys ensure that writes are spread across splits, maximizing throughput.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that secondary indexes on every column improve query performance, but in Spanner they increase write latency and storage costs without benefiting all queries.
Detailed technical explanation
How to think about this question
Spanner uses a distributed, Paxos-based storage system where data is partitioned into splits based on primary key ranges. Interleaved tables ensure that child rows are stored within the same split as their parent, enabling atomic, consistent reads without cross-split coordination. For write distribution, using a primary key with a hash prefix (e.g., SHA256 of a unique identifier) spreads load across all nodes, avoiding the hot-spotting that occurs with sequential keys like timestamps or auto-increment IDs.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 data. — Interleaved tables in Cloud Spanner physically colocate parent and child rows on the same split, reducing cross-node reads and improving join performance. This design is critical for globally distributed applications because it minimizes latency and ensures that related data is stored together for efficient access.
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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