Cloud Digital Leader Practice Test 45 — 15 Questions

Question 1

A start-up wants to quickly build and deploy a web application using managed services to avoid operational overhead. They need a serverless compute platform that automatically scales and charges only for execution time. Which Google Cloud service should they use?

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

Accepted Answer

Cloud Run. Cloud Run is a serverless compute platform that runs containers, auto-scales, and charges per execution. Compute Engine is IaaS, Kubernetes Engine is container orchestration (not serverless), and Cloud Functions is also serverless but for event-driven functions, not full web apps with containers.

Answer

Cloud Functions

Answer

Compute Engine

Answer

Google Kubernetes Engine (GKE)

Question 2

An enterprise is planning to migrate its on-premises data center to Google Cloud to avoid a hardware refresh cycle. The migration must minimize application changes. Which migration strategy should they prioritize?

Accepted Answer

Lift and shift (rehost). Lift and shift (rehost) moves applications as-is to cloud VMs, minimizing changes while avoiding hardware refresh costs.

Answer

Re-architecting applications to use microservices

Answer

Replacing applications with SaaS

Answer

Refactoring to use managed services like Cloud SQL

Question 3

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?

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)

Answer

Multi-cloud (AWS + Azure + Google Cloud)

Answer

Public cloud (Google Cloud only)

Question 4

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.

Answer

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

Answer

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

Question 5

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

Answer

Configure Cloud CDN to cache session data

Answer

Use a global load balancer with HTTP cookies to track sessions

Question 6

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

Answer

Hybrid cloud

Answer

Multi-cloud

Question 7

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)

Answer

Compute Engine

Answer

App Engine

Question 8

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

Answer

Committed use discount VMs for 1 year

Answer

Dataflow with preemptible workers

Question 9

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

Answer

Cloud SQL for MySQL

Answer

Cloud Dataflow

Question 10

A company is migrating its on-premises data warehouse to Google Cloud. The data warehouse contains structured relational data (sales transactions, customer records) and is queried using standard SQL. The company wants to separate compute and storage costs and automatically scale compute resources up and down based on query load. Which Google Cloud service is most appropriate?

Accepted Answer

BigQuery. BigQuery is a serverless data warehouse that separates compute and storage, scales automatically, and supports standard SQL. Cloud SQL is for OLTP, not data warehousing. Spanner is globally distributed OLTP. Dataproc is for Hadoop/Spark workloads, not directly for SQL warehousing.

Answer

Cloud SQL

Answer

Dataproc

Answer

Cloud Spanner

Question 11

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

Answer

Encrypting cardholder data at rest

Question 12

A global gaming company needs to serve low-latency content to players worldwide. They want to cache static assets (images, videos) at edge locations closest to users. Which Google Cloud product should they use?

Accepted Answer

Cloud CDN. Cloud CDN uses Google's global edge network Points of Presence (PoPs) to cache content, reducing latency for users worldwide.

Answer

Cloud Storage

Answer

Compute Engine with global load balancer

Answer

Cloud Spanner

Question 13

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

Answer

Hardware maintenance of storage servers

Answer

Network infrastructure security

Question 14

An organization needs to comply with HIPAA for storing healthcare data in Google Cloud. Which of the following is a customer responsibility?

Accepted Answer

Implementing IAM policies to control access to PHI. Under the shared responsibility model, the customer is responsible for configuring access controls (IAM) and encrypting PHI appropriately.

Answer

Physical security of Google data centers

Answer

Patching the hypervisor

Answer

Obtaining SOC 2 certification for Google Cloud

Question 15

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

Answer

Use the same service account for all services