Cloud Digital Leader Google Cloud products, services, and solutions Practice Test 1 — 15 Questions

Question 1

A 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?

Accepted Answer

BigQuery. BigQuery is a serverless, highly scalable data warehouse designed for analyzing petabytes of data using SQL without any infrastructure management. Its columnar storage and distributed query engine enable sub-second query performance on large datasets, making it ideal for this use case.

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Cloud SQL

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Cloud Bigtable

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Cloud Spanner

Question 2

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?

Accepted Answer

Cloud Run. Cloud Run is the best fit because it is a fully managed serverless container platform that automatically scales to zero when idle and scales up to handle traffic bursts, without requiring any server, cluster, or Kubernetes configuration. The developer simply deploys a container image, and Cloud Run handles all infrastructure management, including scaling and load balancing.

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Google Kubernetes Engine (GKE)

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Compute Engine

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App Engine Standard

Question 3

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?

Accepted Answer

Vertex AI. Vertex AI is the correct choice because it provides a fully managed, unified ML platform that handles the entire ML workflow—from data preparation and training to deployment and monitoring—without requiring the team to manage underlying compute infrastructure. It integrates with Google Cloud's pre-built ML infrastructure, including distributed training, AutoML, and custom model serving, making it ideal for building and scaling a recommendation engine.

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BigQuery ML

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Cloud AI Platform Notebooks (now Vertex AI Workbench)

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Cloud Dataflow

Question 4

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?

Accepted Answer

Cloud Storage. Cloud Storage is Google Cloud's fully managed, scalable object storage service designed for unstructured data such as images, videos, backups, and documents. It offers high durability (99.999999999% annual durability) and global accessibility via a unified namespace, making it the correct choice for storing large volumes of unstructured data at any scale.

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Persistent Disk

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Cloud Filestore

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Cloud Spanner

Question 5

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?

Accepted Answer

Looker Studio (formerly Data Studio). Looker Studio (formerly Data Studio) is the correct choice because it is a no-code, drag-and-drop business intelligence tool that connects directly to BigQuery, enabling the creation of interactive dashboards and reports. It also supports sharing reports via public links or embedded views, allowing stakeholders without GCP accounts to access them without needing IAM permissions.

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Vertex AI Workbench

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Cloud Dataprep by Trifacta

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BigQuery Studio

Question 6

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?

Accepted Answer

Dialogflow CX or Vertex AI Conversation. Dialogflow CX and Vertex AI Conversation are Google Cloud's purpose-built services for building conversational interfaces, including chatbots that understand natural language. They leverage natural language understanding (NLU) models to parse user intents and entities, enabling the application to respond appropriately to customer queries. This makes them the correct choice for a customer support chatbot.

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Cloud Vision API

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BigQuery ML

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Cloud Translation API

Question 7

A company needs to send messages between different microservices in a decoupled way. When one service publishes an event, multiple downstream services should receive and process it independently. Which Google Cloud service enables this publish-subscribe messaging pattern?

Accepted Answer

Cloud Pub/Sub. Cloud Pub/Sub is the correct choice because it is Google Cloud's fully managed, asynchronous messaging service designed specifically for the publish-subscribe pattern. It allows a publisher service to emit events to a topic, and multiple subscriber services can independently pull or push those messages from that topic, ensuring decoupled and reliable communication.

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Cloud Tasks

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Cloud Scheduler

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Eventarc

Question 8

A global fintech company needs a database that can handle financial transactions across 50+ countries with consistent, ACID-compliant operations, SQL queries, and automatic global replication with no downtime for maintenance. Which Google Cloud database service meets all these requirements?

Accepted Answer

Cloud Spanner. Cloud Spanner is the only Google Cloud database that provides ACID-compliant transactions, full SQL support, and automatic synchronous global replication with no downtime for maintenance. It is designed for horizontally scalable, globally distributed applications that require strong consistency across regions, making it the ideal choice for a fintech company operating in 50+ countries.

Answer

Cloud SQL (PostgreSQL)

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Cloud Bigtable

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Firestore

Question 9

A team needs to process and analyze streaming data in real-time as it arrives from IoT sensors. The pipeline must apply transformations, filter events, and write results to BigQuery. Which Google Cloud service is designed for this stream processing use case?

Accepted Answer

Cloud Dataflow. Cloud Dataflow is the correct choice because it is a fully managed, serverless service designed specifically for stream and batch data processing. It uses Apache Beam as its programming model, enabling you to apply transformations, filter events, and write results to BigQuery in real-time, exactly matching the described pipeline requirements.

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Cloud Dataproc

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Cloud Composer

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BigQuery Streaming Insert

Question 10

A company wants to use pre-trained Google AI models to add vision capabilities to their application — specifically to detect objects in images and extract text from scanned documents — without training their own models. Which Google Cloud APIs provide these capabilities?

Accepted Answer

Cloud Vision API for object detection and OCR; Cloud Document AI for structured document extraction.. Option A is correct because Cloud Vision API provides pre-trained models for object detection and OCR (Optical Character Recognition) to extract text from images, while Cloud Document AI specializes in extracting structured data (e.g., fields, tables) from scanned documents. Both services require no custom training, aligning with the company's requirement to use pre-trained Google AI models.

Answer

BigQuery ML for both use cases — it trains vision models on image data stored in BigQuery.

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Vertex AI AutoML Vision — train a custom model on your own images.

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Cloud Natural Language API for text extraction from images.

Question 11

A company runs many containerized microservices that need orchestration — automatic scheduling, scaling, self-healing, and rolling updates. They want a managed service so they don't maintain the control plane themselves. Which Google Cloud service is purpose-built for this?

Accepted Answer

Google Kubernetes Engine (GKE). Google Kubernetes Engine (GKE) is a managed Kubernetes service that provides automatic orchestration, scaling, self-healing, and rolling updates for containerized microservices. It fully manages the Kubernetes control plane, including the API server, etcd, and scheduler, so the customer does not have to maintain them. This makes GKE the purpose-built solution for the described requirements.

Answer

Cloud Run

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Cloud Composer

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Compute Engine with managed instance groups

Question 12

A development team builds a mobile app using Firebase. They need a real-time database that syncs data across all connected clients instantly (e.g., a collaborative to-do app where all users see updates in real-time). Which Firebase/Google Cloud service provides this?

Accepted Answer

Cloud Firestore or Firebase Realtime Database for real-time data sync across all connected clients.. Cloud Firestore and Firebase Realtime Database are the only Firebase/Google Cloud services that provide real-time data synchronization across all connected clients. They use persistent WebSocket connections or HTTP long-polling to push updates instantly to every subscribed client, making them ideal for collaborative apps like a shared to-do list.

Answer

Cloud SQL with read replicas to distribute updates to clients.

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BigQuery streaming inserts for real-time data delivery to mobile clients.

Answer

Cloud Pub/Sub subscriptions on the mobile clients.

Question 13

A company's web application faces DDoS attacks and SQL injection attempts from the internet. They need a service that sits in front of their load balancer to block malicious traffic before it reaches their application servers. Which Google Cloud service provides this protection?

Accepted Answer

Cloud Armor. Cloud Armor is Google Cloud's web application firewall (WAF) and DDoS mitigation service that operates at the edge of Google's network, in front of the load balancer. It can filter incoming traffic based on Layer 7 rules (e.g., SQL injection patterns, cross-site scripting) and Layer 3/4 conditions (e.g., IP reputation, rate limiting), blocking malicious requests before they reach the load balancer or application servers. This makes it the correct choice for protecting against both DDoS attacks and SQL injection attempts at the network perimeter.

Answer

Cloud Firewall (VPC firewall rules)

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Cloud VPN

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Cloud Identity-Aware Proxy (IAP)

Question 14

An enterprise wants employees to access internal web applications securely from any location (including remote work from home) without using a VPN. Employees should only access apps they're authorized for, based on their identity and device context. Which Google Cloud service enables this zero-trust access model?

Accepted Answer

Cloud Identity-Aware Proxy (IAP). Cloud Identity-Aware Proxy (IAP) is the correct service because it enforces zero-trust access by verifying a user's identity and device context before granting access to internal web applications, without requiring a VPN. It uses Google's BeyondCorp model to authenticate and authorize each request based on identity and context, allowing secure access from any location.

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Cloud VPN with split tunneling for internal application access.

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Cloud Armor IP allowlist to restrict access to corporate office IP ranges.

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Cloud Load Balancing with SSL termination.

Question 15

A company runs workloads across Google Cloud and on-premises environments. They want a single management plane to deploy and manage containerized applications consistently across both environments using the same tooling and policies. Which Google Cloud product provides this unified hybrid/multi-cloud management?

Accepted Answer

Anthos — Google's hybrid and multi-cloud application management platform.. Anthos is Google Cloud's hybrid and multi-cloud application management platform that provides a single control plane for deploying and managing containerized applications consistently across on-premises and cloud environments. It uses GKE on-prem and Anthos Config Management to enforce uniform policies, service mesh, and CI/CD pipelines, enabling the unified management described in the scenario.

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Cloud Interconnect — it connects on-premises to Google Cloud.

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Google Distributed Cloud — runs Google Cloud services inside the customer's data center.

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Cloud Deployment Manager — deploys resources via infrastructure-as-code templates.