Cloud Digital Leader Google Cloud Products and Services Practice Question
An engineer is troubleshooting a Cloud SQL instance that is running out of memory. They want to reduce memory usage without changing the machine type. Which action would help?
⚠ Common exam trap
GCDL often tests whether candidates confuse storage scaling (disk) with memory scaling (RAM) — automatic storage increase sounds like it helps 'running out of memory' but only addresses disk space.
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
✓
Reduce the max_connections flag
In Cloud SQL, each database connection consumes memory for session state, buffers, and per-connection overhead. Reducing the max_connections flag lowers the maximum number of simultaneous connections, directly reducing the memory footprint of the database instance without changing the machine type. This is the most direct lever for memory reduction in this scenario.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Reduce the max_connections flag
Why this is correct
Lowering `max_connections` caps the number of concurrent client sessions, and each session reserves per-thread memory for sort buffers, join buffers, and temporary tables. Reducing this flag therefore directly bounds the aggregate connection-level memory consumption on the instance, preventing memory exhaustion and out-of-memory restarts. It is the correct remediation because the symptom is memory pressure, not disk capacity or query routing.
- ✗
Enable automatic storage increase
Why it's wrong here
Enabling automatic storage increase only expands the persistent disk volume when the instance approaches its capacity limit, which addresses disk space depletion but does nothing to reduce memory usage. RAM exhaustion is a separate resource constraint; the flag does not alter buffer pool sizing, connection overhead, or any memory allocation. Thus it would leave the troubleshooting unchanged.
- ✗
Add a read replica
Why it's wrong here
A read replica is used to redirect SELECT queries to a separate instance, reducing CPU and I/O load on the primary, but it does not remove the per-connection memory buffers already allocated on the primary. Writes still go to the source, and each existing session still holds memory; the replica itself also consumes its own RAM. This offloads read traffic, not memory pressure.
- ✗
Switch from InnoDB to MyISAM
Why it's wrong here
MyISAM does not support row-level locking or crash recovery, and Cloud SQL does not allow you to migrate tables to that engine as a supported configuration. More importantly, the memory problem is caused by connection thread buffers, not by the storage engine's access method, so changing engines would not reduce RAM usage. It also sacrifices transactional integrity without addressing the root cause.
Go deeper
Related to this question
Learn chapter
Machine Learning on Google Cloud
Key term
SQL
SQL is a standard programming language used to manage, query, and manipulate relational databases by issuing commands like SELECT, INSERT, UPDATE, and DELETE.
Key term
Machine type
A machine type defines the virtual hardware resources (vCPU, memory, and sometimes GPU) assigned to a virtual machine instance in a cloud computing environment.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This GCDL 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 GCDL exam.