The answer is application-level caching with Redis and connection pooling. These two actions reduce the number of read replicas needed for a Cloud SQL for PostgreSQL instance serving a read-heavy workload by offloading repetitive queries and minimizing connection overhead. Application-level caching stores frequent read results in memory, so the database isn’t hit for the same data repeatedly, directly lowering read demand. Connection pooling reuses established database connections, reducing CPU and memory consumption on the primary instance, which allows it to handle more concurrent reads without additional replicas. On the Google Professional Cloud Database Engineer exam, this tests your understanding of scaling strategies beyond simply adding replicas—a common trap is to overlook caching and pooling as cost-effective alternatives. Remember the mnemonic “Cache and Pool, Replicas Cool” to recall that these two techniques cool down the need for extra read replicas.
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.
Which TWO actions can help reduce the number of read replicas needed for a Cloud SQL for PostgreSQL instance that serves a read-heavy workload?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement connection pooling to reuse database connections.
Option A is correct because connection pooling reduces the overhead of establishing new database connections, which can consume significant CPU and memory resources on the primary instance. By reusing existing connections, the primary instance can handle more read requests without needing additional read replicas to offload the connection management load. This directly reduces the number of replicas required for a read-heavy workload.
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.
✓
Implement connection pooling to reuse database connections.
Why this is correct
Reduces connection overhead and improves replica efficiency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable synchronous replication on all read replicas.
Why it's wrong here
Synchronous replication increases write latency and does not help with read capacity.
✗
Use smaller machine types for read replicas.
Why it's wrong here
Smaller replicas have less capacity, potentially requiring more replicas.
✓
Use application-level caching (e.g., Redis) to cache frequent read results.
Why this is correct
Offloads read requests from the database, reducing replica load.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the max_connections parameter on the primary instance.
Why it's wrong here
Increasing max_connections may cause resource exhaustion and does not directly reduce the need for replicas.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that increasing database parameters like max_connections or using synchronous replication directly reduces read replica requirements, when in fact these actions either increase resource consumption or do not address read offloading.
Detailed technical explanation
How to think about this question
Connection pooling, such as with PgBouncer or built-in Cloud SQL connection pooling, maintains a pool of persistent connections to the database, reducing the overhead of frequent connection creation and teardown. This is especially beneficial in read-heavy workloads where many short-lived read queries are issued, as it lowers CPU usage on the primary instance and allows it to serve more read traffic directly. Application-level caching with Redis further reduces read load by serving frequently accessed data from memory, bypassing the database entirely and decreasing the need for replicas.
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: Implement connection pooling to reuse database connections. — Option A is correct because connection pooling reduces the overhead of establishing new database connections, which can consume significant CPU and memory resources on the primary instance. By reusing existing connections, the primary instance can handle more read requests without needing additional read replicas to offload the connection management load. This directly reduces the number of replicas required for a read-heavy workload.
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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Question Discussion
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