Google ACE Deploying and Implementing a Cloud Solution Practice Question

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 groups

  Why it's wrong here

  Compute Engine with managed instance groups (MIGs) can autoscale based on CPU utilization, but the minimum allowed instance count is 1—it cannot scale to zero. You are still billed for the virtual machines whenever they run, even if they sit idle between requests. This makes it a poor fit for a sporadically used HTTP service where you want zero idle cost. A MIG also requires you to manage a custom instance template, health checks, and autoscaling policies, adding operational overhead compared to a fully managed serverless service.

• ✗

  Cloud Functions

  Why it's wrong here

  Cloud Functions is indeed serverless and scales to zero, but it is a Function-as-a-Service platform intended for event-driven, single-purpose functions, not for running arbitrary containerized applications. You cannot simply deploy a container image with your own runtime and dependencies in Cloud Functions; instead you write code in a supported language runtime or package a function in a limited wrapper. Since the developer specifically wants to deploy a containerized application, Cloud Run is a better fit because it directly executes the provided container image over HTTP.

• ✓

  Cloud Run

  Why this is correct

  Cloud Run is a fully managed serverless platform that runs stateless HTTP-triggered containers directly from a container image. It automatically scales down to zero when there are no incoming requests, so you incur no charges while idle, and bills only for request duration (CPU, memory, and concurrency metered during request handling). You can deploy any container that listens on HTTP, making it the ideal low-overhead choice for a containerized web application. Unlike GKE or Compute Engine, there is no infrastructure to manage or minimum charge for a running VM.

• ✗

  Google Kubernetes Engine (GKE) with cluster autoscaling

  Why it's wrong here

  Google Kubernetes Engine with cluster autoscaling can scale node pools down to zero nodes, but the cluster's control plane still exists and incurs costs (or, on Autopilot, a management fee remains). Moreover, running a full Kubernetes cluster to serve a simple stateless container is operationally overkill—you must manage Deployments, Services, Ingresses, and cluster-wide autoscaling configuration. While GKE is powerful for complex microservices, Cloud Run provides the same scale-to-zero benefit with far less operational burden and no residual control-plane cost for a single containerized app.

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