- A
Enable the PostgreSQL slow query log and analyze it.
Why wrong: Logging is for diagnostics, not a direct latency reduction action.
- B
Use connection pooling to reduce the number of open connections.
Why wrong: Connection pooling manages connections but does not directly reduce read latency.
- C
Increase the number of vCPUs on the primary instance.
More vCPUs can process more queries concurrently, reducing queue time.
- D
Create read replicas in the same region to distribute read traffic.
Read replicas handle read queries, reducing load on the primary.
- E
Add a Memorystore for Redis cache in front of the database for frequently accessed data.
Caching reduces reads to the database, lowering latency.
Question 14 of 1,000
Three Actions to Lower Read Latency in Cloud SQL for PostgreSQL
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.
You manage a Cloud SQL for PostgreSQL instance that is experiencing high read latency. You have already tuned the buffer cache and queries. Which THREE actions can further reduce read latency? (Choose three.)
Quick Answer
The answer is to add a Memorystore for Redis cache, create read replicas, and optimize queries with indexing. These three actions directly lower read latency by offloading repeated reads from the primary database instance—Redis serves frequently accessed data from memory, read replicas distribute read traffic across copies, and better indexes reduce the work PostgreSQL must do per query. On the Google Professional Cloud Database Engineer exam, this question tests your ability to distinguish cost-effective architectural changes from brute-force scaling; the common trap is choosing vertical scaling, which adds cost without addressing the root cause of read contention. Remember the mnemonic “CRO”—Cache, Replicas, Optimization—to recall that reducing read latency requires caching hot data, distributing reads, and sharpening queries, not just adding more CPU or RAM.
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
✓
Increase the number of vCPUs on the primary instance.
Increasing the number of vCPUs on the primary instance (Option C) can reduce read latency by providing more CPU resources to process queries, especially if the current bottleneck is CPU-bound operations like query parsing, sorting, or aggregation. In Cloud SQL for PostgreSQL, scaling vCPUs also increases available memory and I/O bandwidth proportionally, which can alleviate contention and improve throughput for read-heavy workloads.
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 the PostgreSQL slow query log and analyze it.
Why it's wrong here
Logging is for diagnostics, not a direct latency reduction action.
- ✗
Use connection pooling to reduce the number of open connections.
Why it's wrong here
Connection pooling manages connections but does not directly reduce read latency.
- ✓
Increase the number of vCPUs on the primary instance.
Why this is correct
More vCPUs can process more queries concurrently, reducing queue time.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Create read replicas in the same region to distribute read traffic.
Why this is correct
Read replicas handle read queries, reducing load on the primary.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Add a Memorystore for Redis cache in front of the database for frequently accessed data.
Why this is correct
Caching reduces reads to the database, lowering latency.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often mistakenly select diagnostic actions (like enabling logs) as a direct solution for latency reduction, but the question asks for actions that can directly reduce read latency.
Detailed technical explanation
How to think about this question
Read replicas (Option D) offload read traffic from the primary instance by serving SELECT queries asynchronously replicated from the primary, reducing contention and latency for read-heavy workloads. Memorystore for Redis (Option E) acts as a distributed cache, storing frequently accessed query results in-memory to bypass disk I/O and PostgreSQL's buffer cache, delivering sub-millisecond read latencies for cached data. In Cloud SQL, read replicas use PostgreSQL's streaming replication (WAL-based), while Redis caching requires application-level integration to manage cache invalidation and consistency.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PCDE question test?
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: Increase the number of vCPUs on the primary instance. — Increasing the number of vCPUs on the primary instance (Option C) can reduce read latency by providing more CPU resources to process queries, especially if the current bottleneck is CPU-bound operations like query parsing, sorting, or aggregation. In Cloud SQL for PostgreSQL, scaling vCPUs also increases available memory and I/O bandwidth proportionally, which can alleviate contention and improve throughput for read-heavy workloads.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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