Google ACE Planning and Configuring 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.

• ✗

  Cloud Functions

  Why it's wrong here

  Cloud Functions is a Function-as-a-Service (FaaS) platform designed for single-purpose, event-driven code snippets that are triggered by specific events such as Pub/Sub messages, Cloud Storage changes, or HTTP calls. While it does offer an HTTP trigger, it does not allow you to run an arbitrary Docker container containing a full web server framework like Flask or Spring, nor does it support long-lived connections, custom runtimes, or persistent in-memory state between requests. Moreover, functions have strict timeout limits (up to 60 minutes for HTTP-triggered functions, but typically shorter in practice) and lack the streaming and request/response capabilities expected of a general-purpose HTTP application. Because the company wants to run a complete stateless HTTP web app, Cloud Functions is the wrong fit.

• ✓

  Cloud Run

  Why this is correct

  Cloud Run is Google Cloud's fully managed serverless container platform that executes stateless containers on a Knative-based infrastructure, making it ideal for an HTTP web application. It automatically scales to zero when there is no traffic, so you pay nothing during idle periods, and it scales up to thousands of concurrent instances based on incoming requests, with per-request billing that only charges from the moment a request starts to when it finishes. Cloud Run supports any OCI-container image, meaning you can package a web server (e.g., Nginx, Express, Django) and it will handle TLS certificates, domain mapping, and load balancing natively. For variable traffic patterns of a stateless HTTP app, Cloud Run offers the perfect balance of elasticity, cost-efficiency, and operational simplicity.

• ✗

  GKE Standard

  Why it's wrong here

  GKE Standard is a Google Kubernetes Engine cluster where you are responsible for managing the underlying node pool, including patching, upgrades, and node health. Even with cluster autoscaler enabled, GKE Standard cannot scale the node pool to zero because a Kubernetes cluster requires at least one node to run system components like kubelet, the Kubernetes control plane, and platform services like CoreDNS and metrics-server. As a result, you incur continuous VM costs while the cluster is running, and the operational burden of maintaining the cluster is significant for a simple stateless web application. This makes GKE Standard heavyweight and overkill compared to a serverless alternative.

• ✗

  Compute Engine with managed instance group

  Why it's wrong here

  A managed instance group (MIG) in Compute Engine is an IaaS-level solution that requires you to provision and maintain virtual machines running your web application. While MIGs offer autoscaling and health checking, the autoscaler cannot reduce the instance group below one instance, so you always pay for at least one VM, and you must handle OS patching, security hardening, and instance template updates yourself. The application also runs in fixed VMs, meaning you have to manage CPU/memory sizing and ensure the machine can handle peak load, which is less dynamic than serverless scaling. For a stateless HTTP app with variable traffic, this introduces unnecessary infrastructure management and baseline costs that Cloud Run avoids.

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