Cloud Digital Leader Practice Question: Google Cloud products, services, and solutions
A multinational retail company has an on-premises infrastructure with a mix of Windows and Linux servers. They are planning to migrate their e-commerce platform to Google Cloud to take advantage of scalability and reduce latency. The platform consists of a web frontend (Apache), a backend API (Node.js), and a MySQL database. They want to minimize downtime during the migration. They have a limited budget and need a solution that is cost-effective and quick to implement. The IT team has experience with containers but prefers to avoid managing Kubernetes. Which approach should they take?
⚠ Common exam trap
Candidates often assume containerization (GKE) is always the best path for modernizing applications, but the question explicitly states the team prefers to avoid managing Kubernetes, making serverless options like App Engine and Cloud Run the correct choice despite their perceived limitations.
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
✓
Migrate the frontend to App Engine Standard, the backend to Cloud Run, and the database to Cloud SQL with read replicas.
It combines fully managed, serverless services (App Engine Standard for the web frontend and Cloud Run for the backend API) with Cloud SQL for the database, which meets the requirements of minimizing downtime, being cost-effective, and avoiding Kubernetes management. App Engine Standard and Cloud Run automatically scale to zero when not in use, reducing costs, and Cloud SQL with read replicas provides high availability and low-latency reads without complex orchestration. This approach also allows for a gradual migration with minimal disruption, as the existing code can be adapted with minimal changes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Compute Engine for the web frontend, Cloud Functions for the backend API, and Cloud Spanner for the database.
Why it's wrong here
Migrating a MySQL database to Cloud Spanner introduces schema and transaction semantics changes that would require significant application refactoring, contradicting the requirement for a quick, cost-effective migration with minimal downtime. This option is tempting because Cloud Functions excels at event-driven, stateless workloads, and Cloud Spanner offers global strong consistency, making it ideal for a greenfield globally distributed application that can tolerate higher operational complexity.
- ✗
Lift and shift all components to Compute Engine with an autoscaling managed instance group, and migrate the database to Cloud SQL.
Why it's wrong here
While lift-and-shift to Compute Engine with an autoscaling managed instance group is quick to set up, it keeps the application as a monolith running on virtual machines, which still requires ongoing OS patching, infrastructure troubleshooting, and capacity planning. Autoscaling a monolithic web tier is less granular than scaling individual services, and you pay for idle VM capacity during low-traffic periods, making this option potentially more expensive than a serverless approach. Although Cloud SQL is managed, the compute layer itself does not reduce operational overhead to the degree the team seeks, so this does not fully satisfy the requirement for a quick, cost-effective, low-maintenance migration.
- ✗
Containerize all components using GKE, use Cloud SQL for the database, and deploy using a CI/CD pipeline.
Why it's wrong here
This option fails because the team explicitly wants to avoid managing Kubernetes, yet GKE still requires significant cluster administration, including node pool upgrades, version updates, autoscaling configuration, and system monitoring. While containerizing with GKE and using Cloud SQL provides scalability and a modern CI/CD pipeline, the infrastructure footprint is heavier than serverless alternatives—you pay for the entire node pool even when services are idle, and you must manage the control plane and worker nodes yourself. For a simple frontend/backend/database architecture, this adds unnecessary operational complexity and cost, directly contradicting the preference to avoid Kubernetes.
- ✓
Migrate the frontend to App Engine Standard, the backend to Cloud Run, and the database to Cloud SQL with read replicas.
Why this is correct
This correct option combines fully managed serverless services to eliminate infrastructure management: App Engine Standard serves the web frontend with automatic scaling, and Cloud Run hosts the backend API, which leverages the team's existing container experience without requiring them to manage any servers or clusters. Cloud SQL provides a fully managed MySQL database, and adding read replicas offloads read traffic from the primary instance, improving performance and reducing downtime risk during traffic spikes. This architecture minimizes application changes and operational overhead, scales to zero when idle to control costs, and avoids Kubernetes administration, exactly matching the team’s constraints for a quick, cost-effective migration.
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
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Cloud Digital Transformation
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.
Key term
Cloud SQL
Cloud SQL is a fully managed relational database service that lets you set up, maintain, and scale SQL databases (like MySQL, PostgreSQL, and SQL Server) in the cloud without managing the underlying infrastructure.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This GCDL 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 GCDL exam.