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Cloud Digital Leader Fundamental Cloud Concepts Practice Question

A company is migrating a legacy monolithic application to Google Cloud. The application has variable traffic and requires a relational database. They want to minimize operational overhead. Which TWO Google Cloud services should they choose? (Choose TWO.)

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 serverless container platform that minimizes operational overhead by automatically scaling. Cloud SQL is a fully managed relational database service, reducing database management tasks.

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 Run

    Why this is correct

    Cloud Run is a fully managed serverless platform that executes stateless containers and automatically scales from zero to handle each incoming request. For a legacy monolith, you can package it as a container and deploy without managing servers, with built-in request-driven autoscaling and pay-per-use billing. It supports any language and integrates with Cloud SQL for your persistent data, making it the lowest-operational-overhead option for a migrate-to-containers strategy.

  • Cloud SQL

    Why this is correct

    Cloud SQL is a fully managed relational database service compatible with MySQL, PostgreSQL, and SQL Server, which suits the transactional and relational data a legacy monolith relies on. It handles backups, patches, and high availability automatically, and supports vertical scaling without downtime. With Cloud Run as the compute layer and Cloud SQL for persistence, the monolith's data layer can be migrated as-is instead of rearchitecting.

  • Compute Engine

    Why it's wrong here

    Compute Engine gives you raw VMs, so you must handle operating system patching, security hardening, autoscaling configurations, and zone/host failure recovery yourself. Running a legacy monolith on VMs often means re-creating much of the same operational overhead you were trying to escape by moving to the cloud. While it offers maximum flexibility, it is the least 'managed' approach and requires significant ongoing administration.

  • Google Kubernetes Engine

    Why it's wrong here

    GKE provides managed Kubernetes, but you still need to manage the cluster lifecycle, node pools, version upgrades, and ensure your workloads are properly scheduled, serviced, and horizontally scaled. For a monolithic application that is not inherently microservices-based, this adds architectural and operational complexity with no clear benefit. Even GKE Autopilot requires you to define deployments, services, and autoscaling policies, so it is not a fully serverless abstraction like Cloud Run.

  • BigQuery

    Why it's wrong here

    BigQuery is a serverless, columnar data warehouse built for analytical queries on massive datasets, not for powering transactional applications. It does not support the full set of ACID guarantees, row-level UPDATE/DELETE semantics, and low-latency connection handling that a legacy relational monolith needs for day-to-day OLTP operations. Using BigQuery as the monolith's primary database would force a fundamental data model and query rewrite, making it an incorrect choice for this migration.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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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.