Google ACE Planning and Configuring a Cloud Solution Practice Question
A developer wants to deploy a containerized web application that receives HTTP requests and can scale to zero when not in use. The application is stateless and has a startup time of less than 2 seconds. Which Google Cloud compute option is the most cost-effective?
⚠ Common exam trap
ACE often tests the misconception that any autoscaling solution can scale to zero, but only serverless platforms like Cloud Run and App Engine Standard (with automatic scaling) truly scale to zero; managed instance groups and GKE Standard always maintain a minimum capacity.
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 platform that runs stateless containers and automatically scales to zero when there is no traffic, meaning you pay nothing when idle. It natively handles HTTP requests and supports rapid scaling based on incoming requests, making it ideal for a stateless web app with sub-2-second startup. The other options either do not scale to zero or require manual scaling configuration, leading to higher costs for sporadic workloads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Compute Engine with managed instance group and autoscaling
Why it's wrong here
Compute Engine managed instance groups scale the number of VM instances horizontally, but each instance is a full-fledged virtual machine billed per second while it runs. Autoscaling policies can lower the group to its `minimum` size, but that minimum must be at least 1 to serve traffic, and you also manage the OS, patches, and application runtime. For an intermittent workload this causes continuous baseline cost and more operational overhead than a serverless option.
- ✗
Google Kubernetes Engine (GKE) Standard
Why it's wrong here
In GKE Standard, the control plane is managed by Google but the worker nodes are Compute Engine VMs in your project, and those nodes are billed even when they sit idle. Cluster autoscaling can shed disposable node pools, but there must always be at least one node to host system pods such as kube-proxy and networking daemons, so the cluster can never scale to zero. You also own node image upgrades, taints, and pool autoscaling configuration, making it heavier than a zero-idle-cost serverless platform.
- ✗
App Engine Standard with manual scaling
Why it's wrong here
Manual scaling in App Engine Standard pins a fixed number of instances to a service version, and reducing that number to zero would effectively stop the version/stop serving traffic—the engine does not automatically re-create instances to handle spikes. Additionally, App Engine Standard runs within a sandbox with a whitelist of supported runtimes and libraries, so a custom containerized web app may not satisfy those environment restrictions unless ported to a compatible language. This violates the need for a flexible container deployment and fails to deliver cost-efficient scaling for intermittent HTTP traffic.
- ✓
Cloud Run
Why this is correct
Cloud Run executes stateless containers on a fully managed platform, where each instance only receives compute billing while actually processing a request and the service can scale down to zero when no traffic arrives. It automatically provisions instances based on concurrency and can start many instances to handle bursts, with optional min instances for latency-sensitive workloads. A containerized web application is an ideal fit because Cloud Run accepts any container image that listens on a port, and integrates directly with Cloud Build and Artifact Registry.
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
Billing Reports and Cost Tables
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
Cloud Run
Cloud Run is a fully managed compute platform from Google Cloud that lets you run containerized applications in a serverless environment, automatically scaling from zero to thousands of requests.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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.