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.
A team deploys microservices on GKE with Horizontal Pod Autoscaler (HPA). They want to scale based on custom metrics from third-party monitoring. What must they do first?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Install the custom metrics API adapter.
B is correct because Horizontal Pod Autoscaler (HPA) in GKE relies on the custom.metrics.k8s.io API to retrieve custom metrics from external monitoring systems. To expose these metrics to the HPA, you must install a custom metrics API adapter (e.g., the Prometheus Adapter or Google Cloud's custom-metrics-stackdriver-adapter) that translates the third-party monitoring data into the format the Kubernetes API server expects. Without this adapter, the HPA cannot query the custom metrics and will fail to scale.
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.
✗
Use Cluster Autoscaler.
Why it's wrong here
Cluster Autoscaler adds nodes when pods are unschedulable, but does not enable custom metrics for HPA.
✓
Install the custom metrics API adapter.
Why this is correct
An adapter (e.g., Prometheus adapter, Stackdriver adapter) exposes custom metrics to the HPA via the custom.metrics.k8s.io API.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable Cloud Monitoring and configure custom metrics.
Why it's wrong here
Cloud Monitoring can collect custom metrics, but HPA needs a custom metrics API adapter to consume them.
✗
Use Vertical Pod Autoscaler.
Why it's wrong here
VPA adjusts resource requests/limits, not the number of replicas based on custom metrics.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that enabling a monitoring service (like Cloud Monitoring) alone is sufficient for HPA to use custom metrics, when in fact a dedicated API adapter is required to expose those metrics to the Kubernetes control plane.
Detailed technical explanation
How to think about this question
The custom metrics API adapter implements the custom.metrics.k8s.io API group, which the HPA queries via the Kubernetes API server using a specific endpoint (e.g., /apis/custom.metrics.k8s.io/v1beta1). The adapter must be configured with a metric collection pipeline (e.g., Prometheus scraping or Stackdriver monitoring) and a mapping rule to translate metric names and labels into the format the HPA understands. A subtle behavior is that the HPA requires the custom metric to be a 'gauge' type (instant value) and will fail if the metric is a 'counter' or 'histogram' without proper transformation.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this GCDL question in full detail.
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: Install the custom metrics API adapter. — B is correct because Horizontal Pod Autoscaler (HPA) in GKE relies on the custom.metrics.k8s.io API to retrieve custom metrics from external monitoring systems. To expose these metrics to the HPA, you must install a custom metrics API adapter (e.g., the Prometheus Adapter or Google Cloud's custom-metrics-stackdriver-adapter) that translates the third-party monitoring data into the format the Kubernetes API server expects. Without this adapter, the HPA cannot query the custom metrics and will fail to scale.
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.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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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