easyMultiple ChoiceObjective-mapped
Google ACE Practice Question: A developer wants to deploy a containerized…
A developer wants to deploy a containerized application that can scale to zero when not in use and only pay for resources consumed during request processing. Which compute option should they choose?
⚠ Common exam trap
Google Cloud often tests the misconception that 'containerized' implies Kubernetes or Compute Engine, but the key differentiator here is the requirement to 'scale to zero' and 'pay only for request processing,' which is a serverless property unique to Cloud Run among the listed options.
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
✓
Cloud Run
Cloud Run is a fully managed serverless compute platform that automatically scales your containerized applications from zero instances up to handle traffic, and scales back down to zero when there are no requests. You only pay for the resources (CPU, memory, and networking) consumed during request processing, with no charges when the service is idle. This makes it the ideal choice for the described use case of scaling to zero and pay-per-request billing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
App Engine Flexible Environment
Why it's wrong here
The App Engine flexible environment is a PaaS that runs your containerized workload on managed Compute Engine VMs, but it is designed to maintain a baseline level of capacity: at least one instance per service must remain running to receive requests. This minimum instance count is enforced regardless of traffic, so the service can never scale down to zero. Consequently, you are always paying for at least one VM, making it unsuitable for a workload that is infrequently used and should incur no cost when idle.
- ✓
Cloud Run
Why this is correct
Cloud Run is Google's serverless container platform that executes containerized applications in a fully managed environment, with automatic scaling based on incoming HTTP requests. When there is no traffic, Cloud Run scales the number of instances to zero, completely shutting down the service and charging you nothing for idle resources. This makes it the only option among the four that truly supports scale-to-zero for a containerized app.
- ✗
Compute Engine with managed instance groups
Why it's wrong here
A managed instance group (MIG) manages a set of Compute Engine VMs, and its autoscaler can adjust the number of instances based on load metrics. However, the group's minimum size is always at least one instance, typically specified via `min_replicas` or the group's `autoscaling` policy, so it cannot scale down to zero. As a result, an idle MIG still runs a full VM, incurring compute costs even when there are no requests to serve.
- ✗
Google Kubernetes Engine
Why it's wrong here
Google Kubernetes Engine (GKE) requires a cluster to have at least one node in a node pool, as the node runs kubelet, kube-proxy, and other Kubernetes system daemons that are essential for cluster operation. Even with cluster autoscaler enabled, the minimum node count in a pool is one, and you cannot set it to zero without disrupting the control plane's ability to run workloads. Therefore, GKE cannot scale to zero nodes, meaning you always pay for at least one worker node.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
Learn chapter
Google Cloud Platform Overview
Key term
Serverless
Serverless is a cloud computing model where the cloud provider manages the servers, and you only pay for the actual compute time your code uses, without having to worry about provisioning or maintaining infrastructure.
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
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JA
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.