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Google Cloud Products and Services practice questions

Practise Google Cloud Digital Leader Google Cloud Products and Services practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security

20 questionsDomain: Google Cloud Products and Services

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What the exam tests

What to know about Google Cloud Products and Services

Cloud concepts questions usually test the service model (IaaS/PaaS/SaaS) and deployment model (public/private/hybrid/community) appropriate for a given scenario.

IaaS, PaaS and SaaS responsibilities and examples.

Public, private, hybrid and community cloud deployment models.

On-premises vs cloud trade-offs: cost, control, scalability.

How cloud connectivity options (VPN, Direct Connect, ExpressRoute) work.

Watch out for

Common Google Cloud Products and Services exam traps

▸IaaS gives you infrastructure control; SaaS gives you only the application.
▸Hybrid cloud combines on-premises and public cloud — not two public clouds.
▸Cloud does not automatically mean cheaper or more secure.
▸Management responsibility shifts with each service model (IaaS → PaaS → SaaS).

Practice set

Google Cloud Products and Services questions

20 questions · select your answer, then reveal the explanation

Question 1mediummultiple choice

Read the full Cloud Products and Services explanation →

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

Trap 1: Cloud Spanner

Spanner is a globally distributed relational database optimized for ACID transactions, not single-digit ms time-series reads at millions of QPS.

Trap 2: BigQuery

BigQuery is an analytics data warehouse with query latency measured in seconds. It is not designed for millisecond lookups at IoT scale.

Trap 3: Firestore

Firestore is a document database suited for mobile/web apps with hierarchical data. It does not scale to millions of QPS for time-series workloads.

Study all Google Cloud Products and Services common traps →

A
Cloud Spanner
Why wrong: Spanner is a globally distributed relational database optimized for ACID transactions, not single-digit ms time-series reads at millions of QPS.
B
Cloud Bigtable
Bigtable is the correct choice: wide-column NoSQL, designed for time-series and IoT workloads, single-digit ms latency, and scales to millions of QPS with additional nodes.
C
BigQuery
Why wrong: BigQuery is an analytics data warehouse with query latency measured in seconds. It is not designed for millisecond lookups at IoT scale.
D
Firestore
Why wrong: Firestore is a document database suited for mobile/web apps with hierarchical data. It does not scale to millions of QPS for time-series workloads.

Google Cloud Products and Services practice questions

What to know about Google Cloud Products and Services

Common Google Cloud Products and Services exam traps

Google Cloud Products and Services questions

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

A developer wants to deploy a containerized web application that can automatically scale to zero when there are no requests, and charges only for resources used during request processing. Which Google Cloud compute service should they use?

An organization needs to run a batch process every night that analyzes terabytes of data from Cloud Storage and writes results back to BigQuery. The job is not time-sensitive and can be preempted. Which compute approach is most cost-effective?

Which Google Cloud service provides a fully managed, scalable data warehouse for running SQL queries on petabyte-scale data and supports BI tools like Looker?

A company wants to migrate its on-premises PostgreSQL database to Google Cloud with minimal application changes. They need high availability and want to leverage AI-powered optimizations for performance. Which service should they choose?

A developer needs to run a small piece of Python code that processes a message from Pub/Sub and stores the result in Firestore. The code runs infrequently (a few hundred times per day) and takes less than a second to execute. Which compute service is most cost-effective and simple to manage?

What is the primary purpose of Google Cloud Armor?

A data engineer needs to process a continuous stream of clickstream events from a website, perform real-time aggregations (e.g., counts per page per minute), and write the results to BigQuery for dashboarding. Which combination of services should they use?

Which Google Cloud service provides a fully managed, scalable NoSQL document database suitable for mobile and web applications with real-time data synchronization?

A team is developing a machine learning model using TensorFlow. They want to train the model on a large dataset stored in Cloud Storage, using GPUs, and then deploy the trained model for online predictions with autoscaling. Which GCP service should they use for the entire workflow?

A company wants to set up a hybrid cloud connection between its on-premises data center and Google Cloud VPC with a dedicated, high-bandwidth, low-latency link. Which service should they use?

A company runs a critical application on Compute Engine. They need a backup and disaster recovery strategy that includes automated backups and the ability to restore in a different region. Which TWO services should they use together? (Select 2)

A developer wants to build a CI/CD pipeline that automatically builds a Docker container from a GitHub repository, stores the image securely, and deploys it to Cloud Run. Which THREE services should they integrate? (Select 3)

A company stores sensitive data in Cloud Storage. They want to restrict access to only users from the company's corporate network (IP range 203.0.113.0/24) and ensure data is encrypted at rest using a customer-managed key. Which TWO configurations are required? (Select 2)

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

A developer wants to deploy a containerized application that can scale down to zero when not in use and charges only for the resources consumed during request processing. Which Google Cloud compute service should they choose?

A large enterprise is migrating its on-premises data center to Google Cloud. They need a dedicated, low-latency, and highly available connection between their on-premises network and their VPC. Which networking service should they use?

A data engineering team wants to process continuous streams of real-time events from millions of devices, perform transformations, and load the results into BigQuery for analysis. They need a fully managed, serverless solution. Which service should they use?

A startup is building a mobile app and needs to store user profiles and preferences. The data is hierarchical and the app requires real-time synchronization across devices. Which Google Cloud database should they use?

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