The answer is to review and create composite indexes for common query patterns. This is correct because as your Firestore database grows in size, queries that rely solely on automatic single-field indexes must scan more documents to return results, directly increasing read latency even when the number of document reads remains unchanged. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of Firestore’s indexing mechanics and the performance implications of data growth in Native mode. A common trap is to assume that unchanged read counts mean no indexing issue, but the real culprit is the expanding dataset forcing broader scans. The solution lies in creating composite indexes that match your query’s equality and range clauses, allowing Firestore to serve results from a targeted index without scanning irrelevant documents. Memory tip: “More data, same reads? Check your indexes for missing leads.”
PCDE Monitor and optimize database performance Practice Question
This PCDE practice question tests your understanding of monitor and optimize database 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.
Your application uses Firestore for real-time updates. You notice increasing read latency during peak hours. The database is in Native mode with a single-location (us-central1). After reviewing metrics, you see that the number of document reads has not changed significantly, but the database size has grown. What is the most likely cause and solution?
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
✓
Review and create composite indexes for common query patterns.
The correct answer is D because as the database size grows, Firestore's query performance can degrade if queries rely on automatic index scanning without composite indexes. Composite indexes allow Firestore to serve queries without scanning all documents, reducing read latency. The unchanged read count but increased latency indicates that queries are scanning more data due to missing indexes.
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.
✗
Enable multi-region replication to distribute read traffic.
Why it's wrong here
Multi-region may worsen read latency due to replication delays.
✗
The database needs to be defragmented periodically; run a compaction command.
Why it's wrong here
Firestore does not require manual compaction.
✗
Migrate the database to Datastore mode for better performance.
Why it's wrong here
Datastore mode is different but does not automatically solve read latency.
✓
Review and create composite indexes for common query patterns.
Why this is correct
Missing indexes cause full scans, increasing latency as data grows.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that database growth always requires scaling or replication, when in fact the root cause is often missing composite indexes that force full scans, especially in Firestore's automatic indexing model.
Detailed technical explanation
How to think about this question
Firestore uses automatic indexing for all fields, but queries with equality filters on one field and an order on another require a composite index to avoid scanning all documents. Without a composite index, Firestore performs a 'backfill' scan, reading every document that matches the equality filter, which becomes slower as the collection grows. In the Firestore query planner, missing composite indexes trigger a full collection scan, leading to increased latency proportional to database size.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Review and create composite indexes for common query patterns. — The correct answer is D because as the database size grows, Firestore's query performance can degrade if queries rely on automatic index scanning without composite indexes. Composite indexes allow Firestore to serve queries without scanning all documents, reducing read latency. The unchanged read count but increased latency indicates that queries are scanning more data due to missing indexes.
What should I do if I get this PCDE 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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