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Google Professional Cloud Architect - Domain 1

Designing and Planning a Cloud Solution Architecture

This is the architect's front door: translate business goals, technical constraints, migration realities, and future-state needs into a cloud architecture that can actually be built and operated.

Exam weight~25%
Core skillArchitecture trade-offs
Case-study roleHigh
Study priorityVery high

What This Domain Tests

Expect trade-off questions. The right answer usually balances business requirements, technical non-functional requirements, cost, risk, security, reliability, and future flexibility.

Exam Weight

Google lists this domain at ~25% of the standard Professional Cloud Architect exam.

How to Think

Read the scenario like an architect: identify constraints, rank trade-offs, and choose the answer that best satisfies the stated business and technical goals.

Study move: For this domain, do not only memorize product names. Practice explaining why the wrong answers are attractive but incomplete.
Ready to drill this domain?

Use the tabs above to move from official objectives to decision patterns, scenario practice, and a quick quiz.

Official Objective Map

Use this as your domain study outline.

1Design for business requirements

  • Identify business use cases, product strategy, KPIs, ROI, compliance obligations, observability needs, and business continuity expectations.
  • Map each requirement to architecture choices: service selection, integration pattern, data movement, cost model, and operating model.
  • Recognize build, buy, modify, and deprecate decisions when a case study has legacy systems or competing priorities.

2Design for technical requirements

  • Use the Google Cloud Well-Architected Framework to reason about availability, failover, scalability, latency, backup, recovery, flexibility, and performance.
  • Account for Gemini Cloud Assist and operational tooling when the scenario asks about maintainability or future improvements.
  • Choose designs that satisfy requirements with the least unnecessary complexity.

3Design network, storage, and compute resources

  • Connect on-premises, multicloud, and Google Cloud environments with clear boundaries and routing assumptions.
  • Choose storage, databases, data processing, compute, serverless, GKE, Cloud Run, and specialized workload options based on the workload shape.
  • Understand where AI and ML services, Gemini models, Model Garden, Agent Builder, and AI Hypercomputer belong in solution architecture.

4Create migration plans and future improvements

  • Use assessments, dependency planning, workload testing, network planning, and software license analysis to sequence migration work.
  • Include diagrams, proofs of concept, financial impact, and cutover planning when the case asks how to move safely.
  • Design with cloud-first evolution in mind, not just a one-time lift-and-shift.

Decision Patterns

These are the mental shortcuts that help under exam pressure.

Business continuityChoose regional or multi-regional patterns only when the RTO/RPO and business criticality justify the cost.
Compute platformUse Cloud Run for stateless containerized services, GKE for complex orchestration needs, and Compute Engine for VM-specific control.
Migration strategyStart with assessment and dependency mapping before proposing tool-specific migration steps.
Data placementLet latency, compliance, access pattern, durability, and analytics needs drive storage and database choices.
AI architecturePrefer managed AI services when the requirement is business capability; choose custom pipelines when the case demands model lifecycle control.

Mini Scenarios

Open each card, answer in your own words, then compare.

Prompt: A retailer wants to modernize a monolith, reduce operations overhead, and launch features faster without rebuilding every service at once.

Strong answer: Recommend a phased modernization plan: identify bounded contexts, containerize candidate services, use Cloud Run or GKE depending on orchestration needs, preserve stable integrations, and measure outcomes with deployment frequency and error-rate KPIs.

Prompt: A healthcare company needs analytics on regulated patient data across regions with strict auditability.

Strong answer: Prioritize data governance, access controls, encryption, audit logs, data residency, and approved processing locations before choosing analytics tools. The architecture should make compliance observable.

Prompt: A game studio has unpredictable global traffic spikes and wants low latency for players.

Strong answer: Use global load balancing, autoscaling compute, appropriate database/cache placement, CDN where applicable, and cost controls for burst capacity. Design for graceful degradation.

Readiness Checklist

Track what you can confidently explain without notes.

0 of 6 complete
Can explain each business requirement in architecture language
Can identify functional versus non-functional requirements
Can choose compute, storage, database, and network options by workload shape
Can map migration phases from assessment to cutover
Can apply Well-Architected pillars to case-study trade-offs
Can spot over-engineered designs when simpler managed services meet the need

Five-Question Quiz

Use this as a quick readiness pulse, not a score predictor.

Common Traps

These are the answer patterns to catch before exam day.

The exam often wants requirement-first thinking. Do not choose a product before identifying the constraint it solves.
KPIs, ROI, product strategy, and success measurements are architecture inputs, not side notes.
Multi-region can be correct, but only when the business continuity requirement justifies it.
Migration questions usually need dependency mapping, testing, network planning, and financial impact analysis.
AI services still need data flow, access control, cost, observability, and operating model decisions.

FAQ and Sources

Quick answers plus official references to verify details before exam registration.

It has the largest official weight at about 25%, and it also influences case-study reasoning across the whole exam.
No. Learn product selection logic: workload type, operational burden, scale, latency, compliance, and cost.
Enough to matter. Know assessment, dependency planning, network planning, testing, licensing, and financial impact.
Read the business goals first, then technical constraints, then decide which trade-offs the architecture must satisfy.
Practice explaining why one architecture option is better than two plausible alternatives.
Google Cloud Professional Cloud Architect certification pageOfficial Professional Cloud Architect exam guideProfessional Cloud Architect learning path