Cloud Digital Leader Practice Test 33 — 15 Questions

Question 1

A financial services firm must keep sensitive data on-premises due to regulatory requirements but wants to use Google Cloud's AI/ML services for analytics on that data. Which deployment model should they adopt?

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

Accepted Answer

Hybrid cloud (on-premises + Google Cloud). Hybrid cloud connects on-premises infrastructure to Google Cloud, allowing data to remain on-prem while leveraging cloud AI/ML services via secure connections. Public cloud would move data off-prem, private cloud is on-prem only, multi-cloud is about multiple public clouds.

Answer

Private cloud (on-premises only)

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Multi-cloud (AWS + Azure + Google Cloud)

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Public cloud (Google Cloud only)

Question 2

A gaming company uses Google Cloud to run a multiplayer game. They use Compute Engine VMs with GPUs for game servers. During peak hours, latency increases. They want to automatically add more game server instances based on the number of concurrent players. Which scaling approach should they use?

Accepted Answer

Create a managed instance group with autoscaling based on a custom metric representing concurrent players.. Utilizing a custom metric (number of concurrent players) with managed instance groups and autoscaling is the best approach. Cloud Load Balancing distributes traffic but does not scale based on custom metrics.

Answer

Use Cloud Load Balancing to distribute traffic and add more VM instances manually.

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Use Cloud Functions to spin up new game server VMs when player count exceeds a threshold.

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Pre-provision a fixed number of VMs with GPUs to handle peak load at all times.

Question 3

A company is running a stateful web application on Compute Engine with a SQL database. They want to use Cloud Load Balancing to distribute traffic across multiple instances in different zones. The application stores session state locally on each VM. Users report that after being directed to a different instance, their session is lost. What is the most suitable solution to maintain session persistence?

Accepted Answer

Enable session affinity (sticky sessions) on the load balancer. Cloud Load Balancing supports session affinity (sticky sessions) based on client IP or HTTP cookie, which directs a user to the same backend instance. Moving session state to a central database (Cloud SQL) or Memorystore also works but changes the application. Enabling HTTP cookies is a client-side solution not reliable. Using a header-based approach is less common.

Answer

Store session state in Cloud SQL and share across instances

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Configure Cloud CDN to cache session data

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Use a global load balancer with HTTP cookies to track sessions

Question 4

A startup wants to launch a new application and expects unpredictable traffic patterns. They want to avoid upfront hardware costs and only pay for resources they use. Which cloud deployment model best meets their needs?

Accepted Answer

Public cloud. Public cloud offers pay-as-you-go pricing, on-demand scaling, and no upfront hardware costs, ideal for unpredictable workloads. Private and hybrid models typically involve capital expenditure.

Answer

Private cloud

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Hybrid cloud

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Multi-cloud

Question 5

A company wants to run containerized applications on Google Cloud without managing the underlying VMs or orchestrator. Which compute service should they choose?

Accepted Answer

Cloud Run. Cloud Run is a fully managed serverless container platform that abstracts infrastructure. GKE requires cluster management. Compute Engine is VMs. App Engine supports containers but with more restrictions.

Answer

Google Kubernetes Engine (GKE)

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Compute Engine

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App Engine

Question 6

A data engineer needs to run a one-time complex data transformation job on a large dataset (10 TB) stored in Cloud Storage. The job will take approximately 8 hours and is not fault-tolerant. The engineer wants the cheapest possible compute option that can reliably complete the job. What should they use?

Accepted Answer

Standard VMs (on-demand) and delete them after the job. Preemptible VMs can be terminated at any time, so they are not reliable for a non-fault-tolerant job. Standard VMs are reliable and can be stopped after the job to save costs. Committed use discounts require long-term commitment. Dataflow is a fully managed service but may have a minimum cost; however, the question asks for the cheapest compute option, and standard VMs (with proper sizing) can be cheaper than Dataflow for a one-time job.

Answer

Preemptible VMs

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Committed use discount VMs for 1 year

Answer

Dataflow with preemptible workers

Question 7

A company wants to migrate its on-premises PostgreSQL database to Google Cloud with minimal downtime. They also need the ability to perform point-in-time recovery. Which TWO services or features should they use? (Choose two.)

Accepted Answer

Cloud SQL for PostgreSQL. Cloud SQL for PostgreSQL supports database migration and point-in-time recovery. Database Migration Service provides for minimal-downtime migrations.

Answer

Cloud Spanner

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Cloud SQL for MySQL

Answer

Cloud Dataflow

Question 8

A company wants to use Google Cloud for a workload that requires compliance with PCI DSS. Which of the following is a Google responsibility under the shared model?

Accepted Answer

Patching the hypervisor. Google is responsible for maintaining the security of the infrastructure, including the hypervisor, network, and physical security, which are part of PCI DSS compliance scope for the cloud provider.

Answer

Configuring firewall rules to protect cardholder data

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Managing access keys for cardholder data

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Encrypting cardholder data at rest

Question 9

A company stores sensitive healthcare data in Google Cloud and must comply with HIPAA. They are using Cloud Storage and BigQuery. Which of the following is the customer responsible for under the shared responsibility model?

Accepted Answer

Implementing IAM policies to restrict access to healthcare data. Under the shared responsibility model, the customer is responsible for access management (IAM), encryption of data at rest and in transit, and configuring firewall rules. Google is responsible for the physical security of data centers, hypervisor, and network infrastructure.

Answer

Physical security of data centers

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Hardware maintenance of storage servers

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Network infrastructure security

Question 10

A company is deploying a microservices architecture on Google Cloud and wants to ensure secure communication between services. Which THREE measures should they implement? (Choose THREE.)

Accepted Answer

Configure firewall rules to allow only necessary traffic. Using service mesh (e.g., Anthos Service Mesh) enables mTLS between services. Configuring firewall rules restricts network traffic. Enabling VPC Flow Logs helps monitor and audit traffic.

Answer

Assign public IP addresses to all services

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Use the same service account for all services

Question 11

A developer wants to trigger a serverless function whenever a new object is uploaded to a Cloud Storage bucket. Which Google Cloud service should they use?

Accepted Answer

Cloud Functions. Cloud Functions is an event-driven serverless compute service that can be triggered by Cloud Storage events such as object finalise/create. Cloud Run can also be triggered by events via Eventarc, but Cloud Functions is the simpler choice for small code snippets triggered by events. Dataflow and App Engine are not designed for event-triggered functions from Cloud Storage.

Answer

Cloud Run

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App Engine

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Dataflow

Question 12

A data engineering team is building a streaming pipeline that ingests clickstream events from a website, processes them in real-time (e.g., aggregations, filtering), and loads the results into BigQuery for analysis. They also need the ability to replay events in case of failures. Which combination of services is MOST appropriate for the streaming ingestion and processing?

Accepted Answer

Pub/Sub and Cloud Dataflow. Pub/Sub for ingestion allows event replay (by setting a subscription's retention), and Dataflow for stream processing handles real-time transformations and writes to BigQuery.

Answer

Cloud Storage and Cloud Functions

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Pub/Sub and Cloud Functions

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Apache Kafka on Compute Engine

Question 13

A company wants to enforce a policy that prevents all projects in the organization from enabling certain Google Cloud APIs. Where should the policy be applied to ensure it is inherited by all projects, including future ones?

Accepted Answer

On the organization node. Organization policies applied at the organization node are inherited by all folders and projects under it. This is the most efficient way to enforce a blanket restriction across the entire resource hierarchy.

Answer

On the billing account

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On each individual project

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On the folder containing the projects

Question 14

A startup wants to deploy a web application with minimal operational overhead. They want to focus only on writing code and not managing servers, containers, or runtimes. Which Google Cloud service is designed for this purpose?

Accepted Answer

App Engine. App Engine is a fully managed PaaS that abstracts the underlying infrastructure, allowing developers to focus solely on code. Cloud Run requires container images, Compute Engine requires full OS management, and GKE requires cluster management.

Answer

Cloud Run

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Google Kubernetes Engine (GKE)

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Compute Engine

Question 15

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?

Accepted Answer

Pub/Sub, Dataflow, BigQuery. Pub/Sub ingests the stream, Dataflow processes real-time aggregations using Apache Beam, and BigQuery stores results. Cloud Functions is not suitable for streaming aggregations. Cloud Storage is for batch, not real-time. Cloud SQL is not for streaming analytics.

Answer

Pub/Sub, Cloud Functions, Cloud SQL

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Cloud Storage, Dataflow, Cloud SQL

Answer

Pub/Sub, Cloud Functions, BigQuery