Google ACE Practice Question: Ensuring Successful Operation of a Cloud Solution
Your GKE cluster nodes are running low on resources. You need to enable node pool autoscaling so that the cluster automatically adds and removes nodes based on demand. The node pool is named 'default-pool'. Which command completes this task?
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
✓
gcloud container node-pools update default-pool --enable-autoscaling --min-nodes 1 --max-nodes 10
gcloud container node-pools update with --enable-autoscaling enables autoscaling, and --min-nodes/--max-nodes set boundaries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
gcloud container node-pools update default-pool --autoscaling enabled
Why it's wrong here
This command is syntactically invalid because `gcloud container node-pools update` does not accept a boolean flag named `--autoscaling`; the correct flag is `--enable-autoscaling`. The extra word `enabled` would be parsed as a positional argument or an unexpected value, causing the command to fail with a usage error. Even if the flag existed, you must also supply `--min-nodes` and `--max-nodes` for autoscaling to be configured.
- ✓
gcloud container node-pools update default-pool --enable-autoscaling --min-nodes 1 --max-nodes 10
Why this is correct
This is the correct gcloud command to enable cluster autoscaler on a specific node pool. The `--enable-autoscaling` switch turns on autoscaling for the `default-pool`, and the `--min-nodes 1` and `--max-nodes 10` flags define the minimum and maximum size of the node pool. With this configuration, GKE's cluster autoscaler will automatically add or remove nodes within that range based on pending pod resource requests, which directly relieves the low-resource condition on the cluster's nodes.
- ✗
kubectl autoscale node-pool default-pool --min 1 --max 10
Why it's wrong here
kubectl is a Kubernetes API client and cannot manage GCP infrastructure resources like node pools. The `kubectl autoscale` command is intended for creating HorizontalPodAutoscaler objects for Kubernetes workloads such as Deployments, and it does not recognize `node-pool` as a resource kind. Node pool autoscaling is a GCP-level operation that must be performed with `gcloud` commands, the GCP Console, or the Cloud API—not with kubectl.
- ✗
gcloud container clusters update my-cluster --enable-autoscaling --min-nodes 1 --max-nodes 10
Why it's wrong here
This command is invalid because `gcloud container clusters update` does not accept the flags `--enable-autoscaling`, `--min-nodes`, or `--max-nodes`; those flags are only valid with `gcloud container node-pools update`. Cluster autoscaling in GKE is configured per node pool, not at the cluster level, so you must target the specific node pool within the cluster. Additionally, the example uses `my-cluster` rather than the actual cluster name, but even correcting that would not make the command work because the flags are simply not supported on cluster update operations.
Go deeper
Related to this question
Learn chapter
GKE Node Pools and Cluster Autoscaler
Key term
Node pool
A node pool is a group of virtual machines (nodes) within a container orchestration cluster that share the same configuration, such as machine size, operating system, and scaling settings, allowing you to manage them as a single unit.
Key term
Container
A container is a lightweight, standalone software package that includes everything needed to run an application, such as code, runtime, system tools, and libraries.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This ACE 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 ACE exam.