GCP Professional Cloud Architect Practice Questions

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Designing and planning a cloud solution architecture

Case study: KnightMotives Automotive is designing a new stateless customer portal. Traffic is unpredictable, developers want container deployment, and the team wants to support rapid growth. What architecture should you recommend?

A Cloud Storage static hosting for the API

B A zonal managed instance group without autoscaling

C Cloud Run behind a global external Application Load Balancer check_circle

D A single Compute Engine VM with startup scripts

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Explanation

Cloud Run is a managed, autoscaling container platform and the global external Application Load Balancer adds resilient edge entry. The best distractor fails because a single VM or non-autoscaled zonal group does not meet elasticity and availability goals.

Designing and planning a cloud solution architecture

KnightMotives Automotive needs a globally distributed relational database for the field service app. The workload requires strong consistency, horizontal scale, and multi-region availability. What should you choose?

A Cloud SQL for MySQL single zone

B Memorystore for Redis with persistence

C Cloud Spanner in a multi-region instance configuration check_circle

D BigQuery with streaming inserts as the OLTP database

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Explanation

Cloud Spanner is the Google Cloud relational database designed for strong consistency and global scale. The best distractor fails because Cloud SQL is excellent for managed relational workloads but does not provide the same horizontal global consistency pattern.

Designing and planning a cloud solution architecture

EHR Healthcare wants to migrate 400 applications from a data center. Dependencies are unclear and leadership wants a low-risk migration roadmap before selecting target services. What should the architect do first?

A Rewrite all applications before assessment

B Create one shared service account with Owner permissions

C Lift every server into one project using Migrate to Virtual Machines

D Run discovery and assessment with Migration Center and group workloads into migration waves check_circle

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Explanation

Migration Center and wave planning expose dependencies, cost, and suitability before committing to target designs. The best distractor fails because big-bang migration ignores dependency mapping and increases outage risk.

Designing and planning a cloud solution architecture

TravelVista is planning storage for archive records that are rarely read but must be retained for seven years. Access can tolerate retrieval latency and cost must be minimized. Which storage class is best?

A Cloud Storage Standard in one region

B Cloud SQL with compressed tables

C Cloud Storage Archive class with lifecycle management check_circle

D Persistent Disk snapshots kept forever

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Explanation

Archive storage plus lifecycle policies matches long-term, rare-access retention at low storage cost. The best distractor fails because Standard storage costs more for data that is almost never accessed.

Designing and planning a cloud solution architecture

StreamFlow needs to expose private services from a producer VPC to many consumer VPCs without peering all networks or using public IP addresses. What should you design?

A External load balancers with authorized networks

B Private Service Connect endpoints check_circle

C Cloud NAT for inbound producer access

D VPC Network Peering between every project

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Explanation

Private Service Connect provides private, scalable service access across VPC boundaries. The best distractor fails because mesh peering creates operational complexity and transitive routing limitations.

Designing and planning a cloud solution architecture

Case study: EHR Healthcare wants a lakehouse analytics platform for petabyte-scale SQL reporting and ML feature exploration. Analysts should not manage clusters. What is the best core service?

A BigQuery check_circle

B Cloud SQL read replicas

C Filestore Enterprise

D Self-managed PostgreSQL on Compute Engine

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Explanation

BigQuery is serverless, highly scalable, and optimized for analytical SQL workloads. The best distractor fails because Cloud SQL targets transactional databases and cannot serve petabyte analytics with the same managed scale.

Designing and planning a cloud solution architecture

Cymbal Retail runs a latency-sensitive online gaming backend. It needs custom Kubernetes controllers, service mesh integration, and fine-grained node configuration. Which compute platform fits best?

A App Engine standard only

B Cloud Run jobs

C Google Kubernetes Engine check_circle

D Cloud Functions only

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Explanation

GKE is appropriate when Kubernetes control, mesh, and node-level capabilities are required. The best distractor fails because Cloud Run reduces ops but does not provide full Kubernetes control-plane flexibility.

Designing and planning a cloud solution architecture

PharmaTrust has fault-tolerant image rendering jobs that can restart from checkpoints. Management wants the lowest compute cost. Which compute option should you use? Choose the option that best meets the requirement with the least operational overhead.

A Sole-tenant nodes for all workers

B Largest standard VMs running continuously

C Cloud SQL replicas for compute offload

D Spot VMs in a managed instance group with retry/checkpoint logic check_circle

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Explanation

Spot VMs are cost-effective for interruptible, retryable batch workloads. The best distractor fails because sole-tenant nodes solve isolation needs, not low-cost interruptible batch.

Designing and planning a cloud solution architecture

MetroHealth is creating a landing zone for several business units with different compliance needs. What resource design is most appropriate?

A Use an organization with folders for business units and separate projects for workloads check_circle

B Create a new Google Cloud organization for each app

C Place all workloads in one project

D Avoid folders and manage access manually

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Explanation

Organization, folder, and project hierarchy supports governance, isolation, and policy inheritance. The best distractor fails because one project reduces separation of duties and makes policy boundaries unclear.

Designing and planning a cloud solution architecture

EduNext wants an enterprise support assistant over internal documents using generative AI. The team wants managed search, grounding, and low operations. Which solution is best?

A Gemini Enterprise or Vertex AI Agent Builder with enterprise data connectors check_circle

B Use only Cloud CDN to cache documents

C Make all documents public and call a generic chatbot

D Train a foundation model from scratch on Compute Engine

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Explanation

Managed GenAI application services reduce custom ML work and support grounded enterprise use cases. The best distractor fails because training from scratch is expensive, slow, and unnecessary for a document assistant.

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