Google Cloud · Free Practice Questions · Last reviewed May 2026
30real exam-style questions organised by domain, each with the correct answer highlighted and a plain-English explanation of why it's right — and why the others are wrong.
A traditional retailer currently maintains its own data centers, purchasing servers every 3–5 years and paying for facilities, power, and staff regardless of demand. When it migrates its workloads to the public cloud, which change in cost model does it experience?
From operational expenditure (OpEx) to capital expenditure (CapEx)
From capital expenditure (CapEx) to operational expenditure (OpEx)
Cloud eliminates large upfront hardware purchases (CapEx) and replaces them with pay-as-you-go usage fees (OpEx), aligning costs directly with actual business consumption.
From variable costs to fixed monthly costs
From consumption-based billing to annual depreciation cycles
A startup wants to launch a new product globally within 2 weeks. If it relied on traditional on-premises infrastructure, provisioning servers would take 6–8 weeks. By using the public cloud, the startup can launch on time. Which cloud benefit does this scenario illustrate?
Economies of scale — the cloud provider has more purchasing power than the startup.
Speed and agility — cloud resources are provisioned in minutes, enabling faster time-to-market.
Cloud's on-demand provisioning eliminates the 6–8 week hardware procurement cycle, allowing the startup to go from idea to global deployment in days.
Geographic reach — the cloud provider has data centers in more regions.
Reliability — cloud providers have better uptime SLAs than on-premises servers.
A traditional bank processes loan applications using manual paper-based workflows that take 2 weeks per application. The bank wants to use cloud technology to reduce this to under 24 hours. Which cloud-enabled capability primarily drives this transformation?
Lower storage costs for paper documents by digitizing them in Cloud Storage.
Cloud-based AI/ML services and workflow automation that process applications end-to-end without manual steps.
Managed AI services (document extraction, risk scoring) combined with automated cloud workflows remove manual bottlenecks, enabling loan decisions in hours instead of weeks.
Moving the bank's email system to a cloud-based provider.
Using Cloud SQL instead of on-premises Oracle database.
An e-commerce company plans its infrastructure for peak shopping events (e.g., Black Friday) which drive 50× normal traffic. On-premises, they must maintain 50× capacity year-round. In the cloud, they provision 50× capacity only during peak periods. Which cloud characteristic enables this cost optimization?
Measured service — metering and reporting resource consumption.
Elasticity — the ability to rapidly scale resources up during peak demand and release them when no longer needed.
Cloud elasticity lets the company provision 50× capacity for Black Friday (days) then scale back to 1× base capacity, paying only for what's used — eliminating year-round over-provisioning costs.
Broad network access — accessing resources from any internet-connected device.
Resource pooling — the provider's resources are shared among many customers.
A manufacturing company wants to improve product quality by analyzing sensor data from 10,000 factory machines in real-time to detect defects before they occur. Previously, this was impossible due to the massive compute requirements. Which cloud capability makes this feasible?
Cloud storage allowing all sensor data to be stored cheaply.
On-demand access to massive compute resources and AI/ML services for real-time data processing.
Cloud's elastic compute and managed ML services allow the company to process 10,000 machines' sensor streams simultaneously using resources that would be unaffordable to own, enabling real-time predictive quality control.
Cloud-based email and collaboration tools for factory staff.
Migration of the company's ERP system to the cloud.
A CEO asks why the company should invest in a cloud migration when the existing on-premises infrastructure 'still works fine.' Which business case arguments are MOST relevant to present? (Select the best answer.)
The cloud uses newer hardware and newer versions of Linux, which are technically superior.
Cloud enables faster innovation and time-to-market, reduces total cost of ownership, and provides access to advanced capabilities (AI, analytics) that improve competitive positioning.
These are the business outcomes that matter to a CEO: innovation speed (competitive advantage), TCO reduction (financial), and access to AI/ML (new capabilities). All three directly impact business results.
Cloud providers have more IT staff than the company, so IT headcount can be reduced immediately.
The current infrastructure will eventually fail, so proactive migration avoids future risk.
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Practice this domainA company wants to use computing resources over the internet without managing physical servers. The cloud provider manages the underlying hardware and virtualization, while the company manages the operating system, middleware, and applications. Which cloud service model does this describe?
Software as a Service (SaaS)
Infrastructure as a Service (IaaS)
IaaS provides virtualized compute, storage, and networking. The provider manages physical infrastructure; the customer manages OS, middleware, and applications. Compute Engine is Google's IaaS offering.
Platform as a Service (PaaS)
Function as a Service (FaaS)
A team uses Google Workspace (Gmail, Docs, Sheets) for their daily work. They do not manage any servers or software installation — Google maintains everything. Which cloud service model does Google Workspace represent?
Infrastructure as a Service (IaaS)
Platform as a Service (PaaS)
Software as a Service (SaaS)
Google Workspace delivers fully managed productivity applications over the internet. No infrastructure, OS, or application management by the user — just data and user configuration.
Database as a Service (DBaaS)
A hospital runs a patient records system that must remain on-premises due to strict regulatory data residency requirements. However, they also want to use cloud-based AI for diagnostic imaging analysis. Which cloud deployment model best describes their architecture?
Public cloud — all workloads run in a provider's infrastructure.
Private cloud — all workloads run in the hospital's own infrastructure.
Hybrid cloud — combining on-premises infrastructure with public cloud services.
Hybrid cloud connects on-premises (patient records, regulatory compliance) with public cloud (AI imaging analysis). This is the textbook hybrid cloud pattern for regulated industries.
Multi-cloud — using multiple public cloud providers simultaneously.
According to the NIST definition of cloud computing, which characteristic allows users to unilaterally provision computing resources such as server time and network storage without requiring human interaction with the service provider?
Broad network access
On-demand self-service
On-demand self-service allows users to provision resources (compute, storage) automatically through a portal or API without human interaction with the provider — core to the cloud experience.
Resource pooling
Measured service
An organization runs its entire infrastructure on a single public cloud provider (Google Cloud). All applications, data, and services live in Google Cloud's infrastructure. Which deployment model describes this?
Private cloud
Public cloud
Public cloud means all infrastructure is provided by and located in a third-party provider's (Google's) facilities, shared with other customers but logically isolated. Using only Google Cloud is a public cloud deployment.
Hybrid cloud
Community cloud
What is virtualization in the context of cloud computing, and why is it fundamental to how cloud providers deliver services?
Virtualization is the process of converting physical servers into digital images for backup purposes.
Virtualization abstracts physical hardware into multiple isolated virtual machines, enabling many customers to share physical infrastructure efficiently and securely.
A hypervisor divides physical hardware into isolated VMs. Cloud providers run thousands of customer VMs on shared physical servers — the foundation of cloud economics and multi-tenancy.
Virtualization is a networking technique that routes internet traffic more efficiently.
Virtualization is a backup strategy where data is stored in multiple geographic locations.
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Practice this domainA data analytics team needs to analyze petabytes of structured data using SQL queries without managing any database infrastructure. Query results must return within seconds for most queries. Which Google Cloud service is designed for this use case?
Cloud SQL
BigQuery
BigQuery is Google's serverless data warehouse, designed for petabyte-scale SQL analytics. It requires no infrastructure management and delivers fast query performance through massive parallelism.
Cloud Bigtable
Cloud Spanner
A developer wants to deploy a containerized web application without managing servers, clusters, or Kubernetes configuration. The application should automatically scale to zero when not in use and handle bursts of traffic. Which Google Cloud service is the best fit?
Google Kubernetes Engine (GKE)
Cloud Run
Cloud Run is fully managed serverless for containers. No Kubernetes, no cluster management — just deploy the container and Cloud Run handles scaling (including to zero), networking, and infrastructure.
Compute Engine
App Engine Standard
A retail company wants to build a recommendation engine that suggests products to customers based on their browsing history. The team has ML expertise but wants to use Google's pre-built ML infrastructure to train and deploy models at scale without managing compute resources. Which Google Cloud service should they use?
BigQuery ML
Vertex AI
Vertex AI is Google's unified ML platform with managed training (GPU/TPU clusters), AutoML, model registry, feature store, and serving endpoints. Teams bring ML expertise; Vertex AI handles infrastructure.
Cloud AI Platform Notebooks (now Vertex AI Workbench)
Cloud Dataflow
A company needs to store large volumes of unstructured data (images, videos, backups, documents) with high durability and global accessibility. Which Google Cloud service is designed for object storage at any scale?
Persistent Disk
Cloud Storage
Cloud Storage is Google's globally distributed object storage for unstructured data. It stores any type of file (images, videos, backups, datasets) at any scale with 11 nines durability.
Cloud Filestore
Cloud Spanner
A business intelligence team wants to create interactive dashboards and reports from their BigQuery data without writing code. They need to share reports with stakeholders who don't have GCP accounts. Which Google Cloud tool is most appropriate?
Vertex AI Workbench
Looker Studio (formerly Data Studio)
Looker Studio is Google's free BI dashboarding tool with native BigQuery integration. Reports can be shared via link with stakeholders who have no GCP accounts.
Cloud Dataprep by Trifacta
BigQuery Studio
A company wants to build an application that can understand and respond to natural language queries from customers (e.g., a customer support chatbot). Which Google Cloud capability should they use?
Cloud Vision API
Dialogflow CX or Vertex AI Conversation
Dialogflow CX is Google's advanced conversational AI platform for building NLU-powered chatbots and virtual agents. It understands customer intent and manages multi-turn conversations across channels.
BigQuery ML
Cloud Translation API
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Practice this domainA company's web service has a Service Level Objective (SLO) of 99.9% monthly availability. In a 30-day month, how many minutes of downtime are allowed before the SLO is violated?
~4.3 minutes
~43.2 minutes
99.9% availability = 0.1% downtime. In a 30-day month (43,200 minutes), 0.1% = 43.2 minutes of allowed downtime — the classic 'three nines' error budget.
~7.2 hours
~8.6 hours
A SRE team wants to alert when their service is consuming error budget faster than expected, rather than alerting only when the SLO threshold is crossed. Which Cloud Monitoring alerting strategy supports this approach?
Threshold alerting — alert when error rate exceeds 0.1%.
SLO burn rate alerting — alert when error budget is being consumed faster than the measurement window allows.
Burn rate alerting detects when errors are occurring at a rate that will exhaust the error budget before period end. This enables proactive response before the SLO is violated.
Uptime check alerting — alert when health checks fail.
Log-based alerting — alert when specific error messages appear in logs.
A company's on-premises IT team spends 70% of their time on routine maintenance tasks: patching servers, replacing failed hardware, and upgrading storage. After migrating to Google Cloud managed services, which operational outcome should they expect?
The IT team will need to hire more staff to manage additional cloud infrastructure.
The IT team can redirect time from maintenance to higher-value activities like innovation and feature development.
Google handles patching, hardware, and infrastructure management for managed services. The IT team's time shifts from undifferentiated maintenance to strategic, business-value work.
The IT team will still perform the same tasks but remotely via the Cloud Console.
The IT team will be fully automated out of their roles by Google's AI.
A company has deployed a critical application on Google Cloud and wants to understand what happens to their workloads during a Google Cloud data center maintenance event (e.g., host system upgrades). What Google Compute Engine feature handles this automatically for most VMs?
VMs are terminated and restarted automatically on new hardware, causing a few minutes of downtime.
Live migration transparently moves VMs to healthy hosts during maintenance with no VM downtime.
Compute Engine's live migration moves running VMs between physical hosts during maintenance events. The VM continues running — there's no stop/start cycle and no application downtime.
VMs are snapshotted, the snapshot is restored on new hardware, and the VM is restarted.
Customers must subscribe to Google Cloud support to receive advance notice and schedule their own maintenance windows.
A company's application experiences traffic spikes every weekday morning when employees log in at 9 AM. The team wants their infrastructure to automatically handle these spikes without manual intervention and without over-provisioning resources all day. Which Google Cloud capability addresses this?
Purchase reserved capacity for peak load and configure it to be active only on weekdays.
Configure autoscaling on the application's infrastructure to automatically scale up for load and scale down during off-peak hours.
Autoscaling monitors metrics (CPU, requests, custom) and automatically adds instances during the morning spike. Scheduled autoscaling can proactively scale before 9 AM. Resources scale down when load decreases.
Deploy additional VMs manually each weekday morning and terminate them at night.
Use Cloud Monitoring to send an email alert when CPU exceeds 80% so the team can manually scale.
A digital media company hosts video content globally. They want to reduce origin server load and deliver content faster to viewers worldwide. Their current architecture routes all viewer requests directly to the origin servers in `us-central1`, causing high latency for viewers in Asia and Europe. Which Google Cloud networking capability addresses this?
Deploy identical origin servers in every Google Cloud region globally.
Enable Cloud CDN to cache video content at Google's global edge PoPs, serving viewers from the nearest location.
Cloud CDN caches video content at edge PoPs globally. Asian viewers receive content from nearby PoPs (not us-central1), reducing latency significantly and offloading origin servers.
Use Cloud VPN to route viewer traffic through a direct tunnel to the origin servers.
Increase the origin servers' network bandwidth to handle more simultaneous viewer connections.
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Practice this domainGoogle Cloud encrypts all customer data at rest by default without any configuration required. A customer asks: 'Do we need to do anything special to encrypt our data stored in Cloud Storage?' What is the correct answer?
Yes, customers must enable encryption in the Cloud Storage bucket settings for each bucket.
No, Google Cloud encrypts all data at rest automatically using AES-256 — no configuration is needed.
All Google Cloud storage services encrypt data at rest by default with AES-256. Customers receive encryption without any setup, and can optionally use CMEK for key management control.
Only data in premium storage tiers is encrypted; Standard storage requires manual encryption.
Customers must purchase the Security Command Center Premium tier to enable data encryption.
A security architect wants to implement a 'never trust, always verify' security approach where no user or service is assumed to be trustworthy based on network location alone. Every access request must be authenticated and authorized regardless of whether it comes from inside or outside the corporate network. Which security model describes this approach?
Perimeter security model
Zero Trust security model
Zero Trust requires authentication and authorization for every request, regardless of network origin. 'Never trust, always verify' is the defining principle of Zero Trust.
Defense in depth model
Principle of least privilege
A company is concerned about which security responsibilities belong to Google versus which belong to them when using Google Cloud's managed database service (Cloud SQL). In the shared responsibility model, which security tasks does Google handle?
Google controls who can access the database and what data can be stored.
Google handles physical security, hardware maintenance, and OS and database software patching.
For managed services, Google manages the entire infrastructure layer: physical security, hardware, hypervisor, and service software updates. Customers manage their configuration and data.
Google is responsible for backing up customer data and ensuring data recovery.
Google determines which compliance certifications the customer's application must meet.
A healthcare company needs to store patient data in Google Cloud and must comply with HIPAA (Health Insurance Portability and Accountability Act). Which statement correctly describes how Google Cloud helps them achieve HIPAA compliance?
Storing data in Google Cloud automatically makes an application HIPAA-compliant.
Google offers HIPAA-eligible services and signs a Business Associate Agreement (BAA), but customers must implement their own technical safeguards and access controls.
Google provides HIPAA-eligible cloud infrastructure and signs BAAs. However, HIPAA compliance requires customer actions: access control, audit logging, workforce training, and breach procedures — all customer responsibilities.
HIPAA compliance is impossible on public cloud; healthcare data must stay on-premises.
Google Cloud's automatic data encryption fully satisfies all HIPAA technical safeguard requirements.
An organization uses Google Cloud Identity and Access Management (IAM). A new employee is a data engineer who needs to read BigQuery datasets and run queries but should NOT be able to create new datasets, delete tables, or modify IAM policies. Which IAM role should be assigned?
`roles/bigquery.admin`
`roles/bigquery.dataViewer` (with `roles/bigquery.jobUser` if needed to run queries)
dataViewer grants read-only access to datasets. jobUser allows creating and running query jobs. Together they provide read + query capability without write, delete, or admin access.
`roles/viewer` (project-level Viewer)
`roles/bigquery.dataEditor`
A company wants to ensure that sensitive data (credit card numbers, SSNs) stored in BigQuery is automatically identified and protected. They also want ongoing scanning to detect if any new data violates their data governance policies. Which Google Cloud service provides these capabilities?
Security Command Center — it scans BigQuery for sensitive data automatically.
Cloud Data Loss Prevention (Cloud DLP) with BigQuery inspection jobs.
Cloud DLP natively scans BigQuery tables to identify sensitive data using built-in and custom infoTypes. Scheduled jobs provide continuous governance monitoring; de-identification transforms protect identified data.
Cloud Monitoring custom dashboards with SQL queries that search for PII patterns.
Cloud Audit Logs — they record all BigQuery queries and can identify when sensitive columns are accessed.
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Practice this domainThe GCDL exam has 60 questions and must be completed in 90 minutes. The passing score is 700/1000.
Scenario-based questions covering exam objectives with detailed answer explanations.
The exam covers 5 domains: Why cloud technology is transforming business, Fundamental cloud concepts, Google Cloud products, services, and solutions, Scaling with Google Cloud operations, Trust and security with Google Cloud. Questions are weighted by domain — higher-weight domains appear more on your actual exam.
No. These are original exam-style practice questions written against the official Google Cloud GCDL exam objectives. They are not copied from the real exam. Courseiva focuses on genuine understanding, not memorisation of braindumps.
Courseiva tracks your accuracy per domain and routes you toward weak areas automatically. Free, no account required.