This GCDL practice question tests your understanding of scaling with google cloud operations. 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.
A company wants to automatically scale their Compute Engine managed instance group based on the number of requests per second. Which metric should they use?
CPU utilization
Why wrong: CPU utilization is an indirect measure and may not scale well with request volume.
HTTP load balancing serving capacity
Why wrong: This metric indicates utilization of load balancer capacity, not request rate.
Instance group size
Why wrong: Instance group size is the result of scaling, not a metric to scale on.
custom metric from Cloud Monitoring
Custom metrics allow you to export application-level request rates.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
custom metric from Cloud Monitoring
Option D is correct because the company needs to scale based on requests per second, which is a custom application-level metric. Cloud Monitoring allows you to create custom metrics from your application, and managed instance groups can use these custom metrics for autoscaling, enabling precise scaling based on actual request throughput rather than proxy indicators.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
CPU utilization
Why it's wrong here
CPU utilization is an indirect measure and may not scale well with request volume.
HTTP load balancing serving capacity
Why it's wrong here
This metric indicates utilization of load balancer capacity, not request rate.
Instance group size
Why it's wrong here
Instance group size is the result of scaling, not a metric to scale on.
custom metric from Cloud Monitoring
Why this is correct
Custom metrics allow you to export application-level request rates.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often confuse 'HTTP load balancing serving capacity' with request rate, but that metric measures the load balancer's backend capacity utilization (a ratio), not the raw number of requests per second, which requires a custom application metric.
Detailed technical explanation
Custom metrics in Cloud Monitoring are created via the Cloud Monitoring API or using the OpenCensus/OpenTelemetry libraries, and they can be published as either GAUGE, CUMULATIVE, or DELTA metric kinds. For autoscaling based on requests per second, you would typically use a CUMULATIVE metric and configure the autoscaler with a target value (e.g., 1000 requests per second per instance). Under the hood, the autoscaler polls the metric every 60 seconds and applies a moving average to smooth out spikes, preventing thrashing.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Scaling with Google Cloud operations — This question tests Scaling with Google Cloud operations — Read the scenario before looking for a memorised answer..
The correct answer is: custom metric from Cloud Monitoring — Option D is correct because the company needs to scale based on requests per second, which is a custom application-level metric. Cloud Monitoring allows you to create custom metrics from your application, and managed instance groups can use these custom metrics for autoscaling, enabling precise scaling based on actual request throughput rather than proxy indicators.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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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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