Google Cloud Digital Leader Practice Test

Sample practice questions

A few real questions from this free bank, with full explanations. Use the practice tool above for the whole set.

1. 1. Digital Transformation with Google Cloud

   A company moves its workloads from an on-premises data center to Google Cloud and now pays only for the compute it consumes each month, with no upfront hardware purchase. Which financial shift best describes this change?

   • a.Shifting from operating expenses (OpEx) to capital expenses (CapEx)
   • b.Shifting from capital expenses (CapEx) to operating expenses (OpEx)
   • c.Eliminating both CapEx and OpEx entirely
   • d.Converting all costs into one-time depreciation charges

   Answer: b

   Explanation: On-premises hardware requires large upfront purchases, which are capital expenses (CapEx). Cloud usage is billed as you consume resources, turning spending into ongoing operating expenses (OpEx). This pay-as-you-go model is a core cloud benefit, so 'CapEx to OpEx' is correct. Cloud does not eliminate all cost, nor is it a one-time depreciation charge.

2. 2. Trust and Security with Google Cloud

   A security team wants a centralized service to gain visibility into misconfigurations, vulnerabilities, and active threats across all of their Google Cloud resources. Which service is designed for this?

   • a.Security Command Center
   • b.Cloud SQL
   • c.Pub/Sub
   • d.Compute Engine

   Answer: a

   Explanation: Security Command Center provides centralized visibility into an organization's Google Cloud resources, surfacing misconfigurations, vulnerabilities, and threats so teams can find and fix risks. Cloud SQL is a database, Pub/Sub is messaging, and Compute Engine provides virtual machines. Security Command Center is the security posture and threat-visibility tool described here.

3. 3. Data Transformation with Google Cloud

   A company needs a fully managed relational database that offers strong consistency and horizontal scalability across multiple regions for a global application. Which service best fits?

   • a.BigQuery
   • b.Pub/Sub
   • c.Cloud Storage
   • d.Cloud Spanner

   Answer: d

   Explanation: Cloud Spanner is a fully managed relational database that combines the structure of SQL with horizontal scalability and strong consistency across regions globally. BigQuery is an analytics warehouse, not an operational transactional database. Pub/Sub is a messaging service, and Cloud Storage is for objects. Spanner is the right choice for a globally scalable, consistent relational database.

4. 4. Data Transformation with Google Cloud

   A team wants to ingest a real-time stream of events from thousands of IoT sensors and reliably deliver those messages to multiple downstream processing systems. Which Google Cloud service is designed for this messaging pattern?

   • a.Cloud SQL
   • b.Looker
   • c.Pub/Sub
   • d.BigQuery BI Engine

   Answer: c

   Explanation: Pub/Sub is a scalable, asynchronous messaging service that decouples senders (publishers) from receivers (subscribers), making it ideal for ingesting real-time event streams and fanning them out to multiple consumers. Cloud SQL is a database, Looker is a BI platform, and BI Engine accelerates queries. Pub/Sub is the messaging backbone for streaming ingestion.

5. 5. Data Transformation with Google Cloud

   Which sequence best represents a typical data lifecycle in a cloud analytics pipeline?

   • a.Analyze, then ingest, then store, then delete
   • b.Store, then delete, then ingest, then process
   • c.Process, then ingest, then analyze, then store
   • d.Ingest, then store, then process, then analyze

   Answer: d

   Explanation: A common data lifecycle first ingests data from sources, stores it, processes or transforms it, and then analyzes it to generate insights. The other sequences put analysis or deletion before the data has even been collected or prepared, which is not workable. Understanding this ordered flow helps you match the right Google Cloud service to each stage.

6. 6. Innovating with Google Cloud AI

   How are artificial intelligence (AI) and machine learning (ML) best related?

   • a.AI and ML are completely unrelated fields
   • b.Machine learning is a subset of artificial intelligence
   • c.Artificial intelligence is a subset of machine learning
   • d.ML replaced AI as a newer, unrelated technology

   Answer: b

   Explanation: AI is the broad field of building systems that perform tasks requiring human-like intelligence, and machine learning is a subset of AI in which systems learn patterns from data rather than being explicitly programmed. ML is not the larger category, nor is it unrelated to or a replacement for AI. Knowing this hierarchy clarifies where tools like Vertex AI fit.

7. 7. Innovating with Google Cloud AI

   A global company needs to automatically translate user-generated reviews between dozens of languages in real time. Which pre-trained Google Cloud API is the best fit?

   • a.Cloud Vision API
   • b.Speech-to-Text API
   • c.Natural Language API
   • d.Cloud Translation API

   Answer: d

   Explanation: The Cloud Translation API uses pre-trained models to translate text between many languages, making it ideal for translating reviews on the fly. The Vision API handles images, Speech-to-Text converts audio to text, and the Natural Language API analyzes sentiment and entities. For language-to-language text translation, the Translation API is correct.

8. 8. Innovating with Google Cloud AI

   An organization is adopting AI and wants to reduce unfair bias, protect privacy, and keep humans accountable for outcomes. Which concept describes these commitments?

   • a.Serverless computing
   • b.The shared responsibility model
   • c.Responsible AI
   • d.Infrastructure as a Service

   Answer: c

   Explanation: Responsible AI refers to developing and using AI in ways that are fair, safe, privacy-preserving, transparent, and accountable, which matches reducing bias and keeping humans accountable. Serverless computing and IaaS are infrastructure concepts, and the shared responsibility model concerns security duties between provider and customer. Responsible AI is the governing principle for ethical AI use.

9. 9. Infrastructure and Application Modernization

   A startup wants to deploy a stateless containerized web service that automatically scales to zero when there is no traffic, with no server management. Which Google Cloud service best fits?

   • a.Compute Engine
   • b.Cloud SQL
   • c.Bare-metal servers
   • d.Cloud Run

   Answer: d

   Explanation: Cloud Run is a fully managed serverless platform for running stateless containers that scales automatically, including down to zero when idle, with no server management. Compute Engine requires managing VMs, Cloud SQL is a database, and bare-metal means managing physical hardware. Cloud Run matches serverless containers that scale to zero.

10. 10. Infrastructure and Application Modernization

    A company wants to run and manage containerized applications at scale with automated orchestration, scaling, and self-healing across clusters. Which Google Cloud service is designed for this?

    • a.App Engine
    • b.Cloud Functions
    • c.Google Kubernetes Engine (GKE)
    • d.Cloud Storage

    Answer: c

    Explanation: Google Kubernetes Engine (GKE) is a managed Kubernetes service that orchestrates containerized applications at scale, handling automated scaling, deployment, and self-healing across clusters. App Engine is a PaaS for apps without container orchestration control, Cloud Functions runs small event-driven code, and Cloud Storage holds objects. GKE fits managed container orchestration.