Cloud Digital Leader Practice Test 2 — 25 Questions

Question 1

A company wants to expose its internal backend services to external partners through a managed API layer that handles authentication, rate limiting, traffic management, and analytics — without modifying the underlying services. Which Google Cloud product is designed for this API management use case?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Apigee, Google Cloud's full-featured enterprise API management platform for authentication, rate limiting, analytics, and developer portal without modifying backend services. Apigee is Google Cloud's full-featured enterprise API management platform designed to expose backend services to external partners without requiring modifications to those services. It provides built-in authentication, rate limiting, traffic management, and analytics, along with a developer portal for partner onboarding. This makes it the correct choice for the described use case.

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Cloud Load Balancing, which distributes API requests across backend instances

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Cloud Endpoints, a lighter-weight API gateway for Google Cloud-hosted APIs

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Cloud Armor, Google Cloud's web application firewall and DDoS protection service

Question 2

A software team wants to host their container images securely within Google Cloud and integrate with Cloud Build for CI/CD pipelines and GKE for deployments. Which Google Cloud product serves as the managed repository for storing and managing container images?

Accepted Answer

Artifact Registry, Google Cloud's managed repository for container images and build artifacts with native CI/CD integration. Artifact Registry is Google Cloud's fully managed, next-generation repository for storing, managing, and securing container images and build artifacts. It natively integrates with Cloud Build for CI/CD pipelines and GKE for deployments, providing features like vulnerability scanning, access control via IAM, and support for multiple formats (Docker, Maven, npm, etc.). This makes it the correct choice for the team's requirements.

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Cloud Storage, by storing container images as objects in a bucket

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Container Registry (gcr.io), the legacy Google container image service

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Cloud Source Repositories, for storing source code and container build files

Question 3

An operations team wants to receive an automated alert when their web application's HTTP error rate exceeds 5% for more than 5 minutes. Which Google Cloud product is used to configure this type of metric-based alert?

Accepted Answer

Cloud Monitoring, by creating an alerting policy on the HTTP error rate metric with a 5-minute evaluation window and notification channel. Cloud Monitoring is the correct service because it is purpose-built for creating alerting policies based on metrics like HTTP error rates. You can define a condition that triggers when the error rate exceeds 5% for a specified evaluation window (e.g., 5 minutes) and route the alert through a notification channel (e.g., email, Slack). This directly matches the requirement for a metric-based alert with a time-based threshold.

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Cloud Logging, by configuring a log-based metric and email notification

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Cloud Trace, by setting a trace sampling threshold for error requests

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Security Command Center, by configuring a finding for high error rates

Question 4

A 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?

Accepted Answer

Infrastructure as a Service (IaaS). This scenario describes Infrastructure as a Service (IaaS) because the cloud provider manages the physical hardware and virtualization layer, while the customer retains control over the operating system, middleware, and applications. In IaaS, the provider offers virtualized computing resources (e.g., virtual machines, storage, networks) via APIs or dashboards, and the customer is responsible for OS patches, application configuration, and middleware management. This matches the given split of responsibilities exactly.

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Software as a Service (SaaS)

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Platform as a Service (PaaS)

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Function as a Service (FaaS)

Question 5

Google Cloud runs its own infrastructure operations using the Site Reliability Engineering (SRE) model, which Google invented. What is the core principle that distinguishes SRE from traditional IT operations?

Accepted Answer

SRE applies software engineering principles to operations — automating toil, using quantitative SLOs, and treating reliability as an engineered system property.. The core principle of SRE is applying software engineering practices to operations work. This means automating manual toil, defining quantitative Service Level Objectives (SLOs) to measure reliability, and treating reliability as an engineered property of the system — not as an afterthought. This contrasts with traditional IT operations, which often rely on manual processes and reactive troubleshooting.

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SRE teams never allow production deployments to ensure maximum stability.

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SRE relies entirely on external monitoring vendors to detect and respond to all incidents.

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SRE means development and operations teams are separate departments that communicate only via ticketing systems.

Question 6

What is the key difference between a virtual machine (VM) and a container in terms of how they package and run applications?

Accepted Answer

VMs include a full guest OS; containers share the host OS kernel and contain only the application and its dependencies.. The key difference is that a virtual machine (VM) includes a full guest operating system (OS) running on top of a hypervisor, which virtualizes the underlying hardware. In contrast, a container packages only the application and its dependencies (libraries, binaries, configuration files) and shares the host OS kernel via the container runtime (e.g., Docker, containerd). This makes containers lightweight and faster to start, as they avoid the overhead of a separate OS instance.

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VMs run on physical hardware; containers run in the cloud.

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Containers are less secure than VMs because they share hardware.

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VMs are only for Linux applications; containers support all operating systems.

Question 7

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?

Accepted Answer

Zero Trust security model. The Zero Trust security model (Option B) is correct because it explicitly enforces the 'never trust, always verify' principle, requiring authentication and authorization for every access request regardless of network location. In Google Cloud, this aligns with BeyondCorp, which uses identity-aware proxy (IAP) and context-aware access to verify each request based on user identity, device posture, and other attributes, rather than trusting based on IP address or network perimeter.

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Perimeter security model

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Defense in depth model

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Principle of least privilege

Question 8

A company wants to migrate its existing on-premises virtual machines (VMware VMs) to Google Cloud with minimal changes to the operating system and applications. Which Google Cloud product is specifically designed for migrating on-premises VMs to Google Cloud with minimal modification?

Accepted Answer

Migrate to Virtual Machines (formerly Velostrata), which migrates on-premises VMware VMs to Compute Engine with minimal modification and downtime. Migrate to Virtual Machines (formerly Velostrata) is the correct choice because it is specifically designed to migrate on-premises VMware VMs to Compute Engine with minimal modification to the OS and applications. It uses a streaming migration approach that moves the VM's disk state incrementally while keeping the VM running, resulting in minimal downtime and no need to re-architect the workloads.

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Cloud Dataflow, by streaming data from on-premises VMs to Google Cloud storage

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Anthos, by registering on-premises Kubernetes clusters with Google Cloud's management plane

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Cloud Storage Transfer Service, by copying VM disk images from on-premises storage to Cloud Storage

Question 9

A company has a requirement from their security auditor to demonstrate that all administrative actions performed in Google Cloud (such as creating VMs, modifying IAM policies, and deleting storage buckets) are logged and tamper-evident. Which Cloud Logging log type fulfills this requirement?

Accepted Answer

Admin Activity audit logs — always-on, tamper-resistant logs of all administrative API calls.. Admin Activity audit logs are always-on, tamper-resistant logs that record all administrative API calls, such as creating VMs, modifying IAM policies, and deleting storage buckets. They cannot be disabled or modified by users, ensuring tamper-evident logging for security auditor requirements.

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Data Access audit logs — they capture all read and write operations.

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System Event audit logs — they capture all Google Cloud operations.

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Cloud Monitoring logs — they track all changes to monitored resources.

Question 10

A company's production database is running on a Compute Engine VM with a 500 GB Persistent Disk. The operations team wants to create a backup they can restore from in case of data corruption or accidental deletion. Which Google Cloud capability provides point-in-time backup for Persistent Disks?

Accepted Answer

Persistent Disk Snapshots, which capture the disk state at a point in time and enable restoration or creation of new disks from that snapshot. Persistent Disk Snapshots are the correct Google Cloud feature for creating point-in-time backups of Persistent Disks. They capture the disk's data and configuration at a specific moment, allowing you to restore the disk or create new disks from that snapshot. This is the native, recommended method for backup and disaster recovery of Compute Engine VM disks.

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Cloud Storage bucket replication, by continuously copying the database files to a storage bucket

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Cloud SQL automated backups, which protect databases running on Compute Engine VMs

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VM live migration, which moves the running VM between physical hosts, automatically creating a backup in the process

Question 11

A startup is building a web application and wants to protect it from common web attacks like SQL injection and cross-site scripting. Which Google Cloud product provides web application firewall (WAF) capabilities?

Accepted Answer

Cloud Armor, which provides WAF rules to detect and block SQL injection, XSS, and other OWASP Top 10 attacks. Cloud Armor is Google Cloud's web application firewall (WAF) service that provides pre-configured rules to detect and block common web attacks, including SQL injection and cross-site scripting (XSS), as well as other OWASP Top 10 threats. It integrates with Cloud Load Balancing and allows you to create custom security policies with rate limiting, IP allow/deny lists, and managed rule sets. This makes it the correct choice for protecting a web application at the application layer.

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Cloud Firewall, which controls network-level traffic based on IP and port rules

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VPC Service Controls, which prevent data exfiltration from Google Cloud services

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Security Command Center, which detects security misconfigurations across Google Cloud resources

Question 12

A product team is discussing how to handle a planned 48-hour maintenance window for a critical customer-facing service. The SRE team argues the maintenance window is unnecessary with proper cloud architecture. Which cloud capability eliminates the need for planned downtime maintenance windows?

Accepted Answer

Zero-downtime deployment strategies like rolling updates and blue/green deployments, combined with cloud live migration for infrastructure maintenance. Cloud platforms like Google Cloud support zero-downtime deployment strategies (rolling updates, blue/green deployments) and live migration for infrastructure maintenance. Live migration transparently moves running VMs between hosts without interrupting the OS or applications, while blue/green deployments allow traffic to be switched to a fully updated environment before the old one is taken down. Together, these capabilities eliminate the need for planned downtime maintenance windows entirely.

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Longer maintenance windows scheduled during off-peak hours to minimize customer impact

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Notifying customers in advance of the maintenance window and offering service credits for the downtime

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Backing up all data before the maintenance window to ensure recovery if something goes wrong

Question 13

A Virtual Private Cloud (VPC) in Google Cloud provides network isolation. What does 'network isolation' mean in this context, and why is it important?

Accepted Answer

VPC provides a logically isolated private network where resources are separated from other customers' networks by default, preventing unauthorized cross-customer traffic.. A Google Cloud VPC provides a logically isolated private network within the shared Google Cloud infrastructure. This isolation ensures that resources in one customer's VPC cannot directly communicate with resources in another customer's VPC by default, preventing unauthorized cross-customer traffic. This is achieved through software-defined networking (SDN) constructs like virtual firewalls and routing tables, not through physical separation.

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Network isolation means the VPC blocks all internet access — resources cannot communicate with external services.

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Network isolation means all traffic within the VPC is automatically encrypted.

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A VPC requires dedicated physical hardware separate from other customers to ensure isolation.

Question 14

A data analyst at a media company needs to run complex SQL queries on petabytes of user engagement data to produce weekly reports. The dataset is stored in Google Cloud. Which Google Cloud product is purpose-built for this type of large-scale analytical SQL workload?

Accepted Answer

BigQuery, Google Cloud's serverless data warehouse for petabyte-scale analytical SQL. BigQuery is Google Cloud's serverless, highly scalable data warehouse specifically designed for petabyte-scale analytical SQL queries. It separates compute from storage and uses a columnar storage format and a distributed query engine to execute complex SQL on massive datasets without provisioning infrastructure, making it the ideal choice for the described workload.

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Cloud SQL, Google Cloud's managed relational database service

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Cloud Bigtable, Google's NoSQL wide-column database

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Firestore, Google Cloud's serverless NoSQL document database

Question 15

A company wants to enable its developers to write and run code in various programming languages (Python, Node.js, Go) without provisioning or managing any servers. The code should execute in response to HTTP requests. Which Google Cloud product is designed for this serverless, function-level execution model?

Accepted Answer

Cloud Functions, which executes code functions in response to events or HTTP requests with no server management required. Cloud Functions is the correct choice because it is Google Cloud's event-driven, serverless compute platform that allows developers to write and deploy single-purpose functions in languages like Python, Node.js, and Go. These functions automatically scale and execute in response to HTTP triggers (e.g., HTTP requests) without any server provisioning or management, directly matching the requirement for a function-level execution model.

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Compute Engine, which provides virtual machines for running code in any language

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Cloud SQL, which runs SQL queries in response to HTTP requests

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Persistent Disk, which stores code that can be executed on demand

Question 16

A company runs a customer-facing web application with a published SLA of 99.95% monthly availability. In the past month, the application experienced two outages: a 12-minute outage and a 7-minute outage. Did the company meet its SLA?

Accepted Answer

Yes — 99.95% availability in a 30-day month allows approximately 21.6 minutes of downtime; total outage of 19 minutes is within the budget, meaning the SLA was met. The SLA of 99.95% monthly availability permits a maximum downtime of approximately 21.6 minutes in a 30-day month (total minutes in month × (1 - 0.9995) = 43,200 × 0.0005 = 21.6 minutes). The combined outage of 19 minutes (12 + 7) is within this budget, so the SLA was met. This calculation assumes a 30-day month; if the month had 31 days, the allowable downtime would be about 22.3 minutes, still exceeding 19 minutes.

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No — the company missed the SLA because any outage automatically constitutes an SLA breach

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The answer cannot be determined without knowing the cause of the outages

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No — two separate outages in one month always constitute an SLA breach regardless of duration

Question 17

A multinational retail company has an on-premises infrastructure with a mix of Windows and Linux servers. They are planning to migrate their e-commerce platform to Google Cloud to take advantage of scalability and reduce latency. The platform consists of a web frontend (Apache), a backend API (Node.js), and a MySQL database. They want to minimize downtime during the migration. They have a limited budget and need a solution that is cost-effective and quick to implement. The IT team has experience with containers but prefers to avoid managing Kubernetes. Which approach should they take?

Accepted Answer

Migrate the frontend to App Engine Standard, the backend to Cloud Run, and the database to Cloud SQL with read replicas.. It combines fully managed, serverless services (App Engine Standard for the web frontend and Cloud Run for the backend API) with Cloud SQL for the database, which meets the requirements of minimizing downtime, being cost-effective, and avoiding Kubernetes management. App Engine Standard and Cloud Run automatically scale to zero when not in use, reducing costs, and Cloud SQL with read replicas provides high availability and low-latency reads without complex orchestration. This approach also allows for a gradual migration with minimal disruption, as the existing code can be adapted with minimal changes.

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Use Compute Engine for the web frontend, Cloud Functions for the backend API, and Cloud Spanner for the database.

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Lift and shift all components to Compute Engine with an autoscaling managed instance group, and migrate the database to Cloud SQL.

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Containerize all components using GKE, use Cloud SQL for the database, and deploy using a CI/CD pipeline.

Question 18

A company wants to allow a third-party security firm to conduct a penetration test against their Google Cloud environment to identify vulnerabilities. What is Google Cloud's policy on penetration testing?

Accepted Answer

Customers are authorized to penetration test their own GCP resources without prior Google approval, within the Acceptable Use Policy.. Google Cloud's policy explicitly authorizes customers to conduct penetration testing on their own GCP resources without prior approval from Google, as long as the testing complies with the Acceptable Use Policy. This is because Google treats the customer's environment as their own responsibility, and the shared responsibility model places security testing under the customer's control. Option B correctly reflects this policy, which is documented in Google Cloud's security testing guidelines.

Answer

Customers must submit a formal request to Google and wait for written approval before any penetration testing.

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Penetration testing is illegal in cloud environments and customers should use vulnerability scanners instead.

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Google automatically performs penetration testing on all customer resources monthly and shares the report.

Question 19

An architect is evaluating trade-offs between using Google Cloud's global network backbone for application traffic versus routing traffic over the public internet. She notes that Google's global network is one of the largest private networks in the world. What is the primary performance advantage of routing application traffic over Google's private backbone?

Accepted Answer

Traffic on Google's private backbone avoids public internet congestion and variable routing, providing consistently lower latency and higher throughput for traffic between regions and to users near Google PoPs. Google's private backbone is a dedicated, software-defined network that uses Google's own fiber infrastructure and BGP routing policies to keep traffic entirely within Google's controlled environment. This avoids the unpredictable congestion, packet loss, and variable routing paths of the public internet, resulting in consistently lower latency and higher throughput for traffic between Google Cloud regions and to users near Google Points of Presence (PoPs).

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Google's private backbone uses faster optical fiber than public internet service providers

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Google's private backbone is free for customers while public internet egress incurs data transfer charges

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Using Google's backbone eliminates the need for application-level TLS encryption because the network is inherently secure

Question 20

A company wants to create a customer-facing conversational AI assistant that understands natural language and can answer questions about its products, integrated into their website and mobile app. Which Google Cloud AI product is the most appropriate starting point?

Accepted Answer

Dialogflow CX, Google Cloud's managed conversational AI platform for building natural language understanding chatbots integrated into web and mobile apps. Dialogflow CX is the correct choice because it is Google Cloud's managed conversational AI platform specifically designed for building natural language understanding (NLU) chatbots that can be integrated into websites and mobile apps. It provides advanced state management, flow-based conversation design, and seamless integration with web and mobile channels, making it the most appropriate starting point for a customer-facing conversational AI assistant.

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BigQuery ML, for building machine learning models on customer data to predict product recommendations

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Cloud Vision API, for analyzing images to understand customer product photos

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Cloud Natural Language API, for analyzing the sentiment of customer product reviews