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.)
⚠ Common exam trap
GCDL often tests the misconception that managed services like GKE or Compute Engine minimize operational overhead, when in fact they still require significant management compared to serverless options like Cloud Run and fully managed databases like Cloud SQL.
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 (A) is correct because it is a fully managed serverless compute platform that automatically scales containerized workloads up and down based on traffic, which directly addresses the variable traffic requirement while minimizing operational overhead since Google manages the underlying infrastructure. Cloud SQL (B) is correct because it is a fully managed relational database service supporting MySQL, PostgreSQL, and SQL Server, satisfying the relational database requirement without the operational burden of self-managing database instances. Together, Cloud Run and Cloud SQL form a low-overhead, autoscaling stack suited to a migrated monolithic application with fluctuating demand. Compute Engine (C) is not ideal because it provides raw VMs that the customer must patch, scale, and manage, increasing operational overhead. Google Kubernetes Engine (D) is not chosen because managing clusters adds operational complexity compared to serverless Cloud Run. BigQuery (E) is a serverless analytics data warehouse, not a relational OLTP database, so it does not fit the transactional relational requirement.
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
| 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
Structured vs Unstructured Data Analytics
Key term
Relational database
A relational database organizes data into tables with rows and columns, where each table relates to others using unique keys, allowing efficient storage, retrieval, and manipulation of structured information.
Key term
SQL
SQL is a standard programming language used to manage, query, and manipulate relational databases by issuing commands like SELECT, INSERT, UPDATE, and DELETE.
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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 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.