- A
Switch to a Network Load Balancer for higher throughput.
Why wrong: Changing load balancer type is a significant architectural change and not an appropriate troubleshooting step.
- B
Increase the size of the instance group without investigation.
Why wrong: Scaling without understanding the cause may lead to unnecessary costs and may not solve the underlying problem.
- C
Enable HTTP health checks on the load balancer.
Why wrong: Health checks are important but are a preventive measure, not a diagnostic step for an ongoing issue.
- D
Check the CPU utilization of the instance group in Cloud Monitoring.
High CPU utilization may indicate that instances are overloaded, confirming the suspicion.
- E
Review the load balancer logs in Cloud Logging for error messages.
Load balancer logs can provide details about the errors, such as 5xx responses, helping to pinpoint the issue.
Cloud Digital Leader Scaling with Google Cloud operations Practice Question
This GCDL practice question tests your understanding of scaling with google cloud operations. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
An e-commerce platform uses Compute Engine instances in a managed instance group behind a Cloud Load Balancer. During a flash sale, the load balancer reports increased error rates. The operations team suspects the instances are overwhelmed. Which two steps should they take to troubleshoot the issue? (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
Check the CPU utilization of the instance group in Cloud Monitoring.
Option D is correct because checking CPU utilization in Cloud Monitoring directly reveals whether the instance group is resource-constrained. High CPU utilization indicates that the instances are overwhelmed, which aligns with the increased error rates reported by the load balancer. This metric is a primary indicator of compute capacity issues and helps validate the team's suspicion before taking corrective action.
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.
- ✗
Switch to a Network Load Balancer for higher throughput.
Why it's wrong here
Changing load balancer type is a significant architectural change and not an appropriate troubleshooting step.
- ✗
Increase the size of the instance group without investigation.
Why it's wrong here
Scaling without understanding the cause may lead to unnecessary costs and may not solve the underlying problem.
- ✗
Enable HTTP health checks on the load balancer.
Why it's wrong here
Health checks are important but are a preventive measure, not a diagnostic step for an ongoing issue.
- ✓
Check the CPU utilization of the instance group in Cloud Monitoring.
Why this is correct
High CPU utilization may indicate that instances are overloaded, confirming the suspicion.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Review the load balancer logs in Cloud Logging for error messages.
Why this is correct
Load balancer logs can provide details about the errors, such as 5xx responses, helping to pinpoint the issue.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse switching load balancer types (Option A) with a performance fix, when in fact the issue is backend capacity, not frontend protocol handling.
Detailed technical explanation
How to think about this question
Cloud Monitoring provides granular metrics like CPU utilization, memory usage, and request latency at the instance group level, which are essential for diagnosing capacity issues. The load balancer logs in Cloud Logging contain detailed error codes (e.g., 502 Bad Gateway, 503 Service Unavailable) and request timing data that can pinpoint whether errors stem from backend timeouts or instance failures. In practice, a sudden spike in 503 errors often correlates with CPU saturation above 80%, making these two steps a standard first-line troubleshooting approach.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this GCDL question test?
Scaling with Google Cloud operations — This question tests Scaling with Google Cloud operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Check the CPU utilization of the instance group in Cloud Monitoring. — Option D is correct because checking CPU utilization in Cloud Monitoring directly reveals whether the instance group is resource-constrained. High CPU utilization indicates that the instances are overwhelmed, which aligns with the increased error rates reported by the load balancer. This metric is a primary indicator of compute capacity issues and helps validate the team's suspicion before taking corrective action.
What should I do if I get this GCDL 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.
About these practice questions
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Last reviewed: Jun 25, 2026
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.
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