Google Cloud Professional Cloud Architect Designing and Planning a Cloud Solution Architecture Syllabus

Designing and Planning a Cloud Solution Architecture syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Designing and Planning a Cloud Solution Architecture in Google Cloud Professional Cloud Architect, not a summary of it.

1. 1

   Translating Business and Technical Requirements

   4 topics

   • Defining business use cases and success criteria
     • Mapping stakeholder goals to measurable KPIs
     • Cost optimization vs. performance trade-offs
     • Aligning solutions to business strategy
   • Capturing technical and functional requirements
     • Latency, throughput, and capacity targets
     • Integration with existing systems and data
   • Regulatory, compliance, and data sovereignty constraints
     • HIPAA, PCI-DSS, GDPR considerations
     • Data residency and regional placement
   • Managing customer success and decision frameworks
2. 2

   Designing for High Availability and Resilience

   4 topics

   • Availability tiers and SLA/SLO/SLI design
     • Computing composite SLAs across services
     • Error budgets and reliability targets
   • Multi-zone and multi-region architectures
   • Failover, redundancy, and graceful degradation
   • Disaster recovery patterns (RTO/RPO)
     • Backup and restore
     • Warm standby and hot multi-region
3. 3

   Network, Storage, and Compute Resource Design

   4 topics

   • Selecting compute platforms for workloads
     • Compute Engine vs. GKE vs. Cloud Run vs. App Engine
     • Spot/preemptible and committed use planning
   • Choosing storage and database services
     • Object, block, and file storage selection
     • Relational vs. NoSQL vs. analytical stores
   • Network topology and connectivity design
   • Capacity planning and quotas
4. 4

   Migration Planning

   4 topics

   • Workload assessment and discovery
     • Application dependency mapping
     • Total cost of ownership analysis
   • Migration strategies (rehost, replatform, refactor)
   • Data migration approaches
     • Storage Transfer Service and Transfer Appliance
     • Database Migration Service
   • Validation, cutover, and rollback planning
5. 5

   Cost Optimization and Future Improvement

   4 topics

   • Pricing models and cost estimation
     • Sustained and committed use discounts
     • Using the Pricing Calculator
   • Right-sizing and resource efficiency
   • Designing for elasticity and evolution
   • Advising on continuous improvement roadmaps

Designing and Planning a Cloud Solution Architecture flashcards for Google Cloud Professional Cloud Architect

19 of 54 cards from the Designing and Planning a Cloud Solution Architecture deck — real questions with worked answers.

1. In requirements gathering, what distinguishes a business use case from technical requirements?

   A business use case describes the desired business outcome and value (the 'why' and 'what'), while technical requirements specify the system capabilities needed to achieve it (the 'how'). Use cases drive prioritization; technical requirements drive design.

2. What makes a project's success criteria effective, and what framework is commonly used?

   Effective success criteria are specific, measurable, and tied to business outcomes (e.g., reduce checkout latency to <200ms). They are often expressed as SMART goals (Specific, Measurable, Achievable, Relevant, Time-bound) and mapped to KPIs.

3. What is the difference between functional and non-functional requirements?

   Functional requirements define what the system does (features, behaviors, inputs/outputs). Non-functional requirements define how the system performs (availability, latency, scalability, security, compliance, durability).

4. What is data sovereignty and how does it constrain cloud architecture?

   Data sovereignty is the principle that data is subject to the laws of the country where it is physically stored. It constrains architecture by requiring data residency in specific regions, dictating where compute and storage may be placed (e.g., EU data staying in EU regions).

5. Name three major regulatory/compliance regimes a cloud architect must design around and their domains.

   GDPR (EU personal data privacy), HIPAA (US healthcare PHI), and PCI DSS (payment card data). Others include SOX (financial reporting), FedRAMP (US government), and CCPA (California privacy).

6. In Google Cloud, what is the difference between data residency and data location controls like Org Policy resource location restriction?

   Data residency is the requirement that data stay in a jurisdiction. The Org Policy 'resource location restriction' constraint enforces it technically by limiting which regions/multi-regions resources can be created in, helping meet sovereignty obligations.

7. Define SLI, SLO, and SLA and how they relate.

   SLI (Service Level Indicator) is a measured metric (e.g., % of successful requests). SLO (Service Level Objective) is the internal target for that SLI (e.g., 99.9% success). SLA (Service Level Agreement) is the external contract with consequences (e.g., credits) if the objective is missed. Typically SLO is stricter than SLA.

8. How do you compute allowed downtime per month for a 99.9% availability SLO?

   Downtime = (1 - 0.999) x 30 days. (1 - 0.999) = 0.001; 0.001 x 30 x 24 x 60 min = 43.2 minutes per month (about 8.76 hours per year).

9. What is an error budget and how is it derived from an SLO?

   An error budget is the allowable amount of unreliability: 100% minus the SLO target. For a 99.9% SLO, the error budget is 0.1% of requests/time. Teams can 'spend' it on releases and risk; when exhausted, they freeze risky changes.

10. What annual downtime corresponds to availability of 99.99% (four nines)?

    About 52.6 minutes per year (0.0001 x 365 x 24 x 60 ≈ 52.56 minutes), or roughly 4.38 minutes per month.

11. In Google Cloud, what is the difference between a zone and a region?

    A region is a specific geographic location (e.g., us-central1) containing multiple isolated zones. A zone is an isolated deployment area within a region (e.g., us-central1-a) with its own power/network failure domain. Zones in a region have low-latency interconnects.

12. What availability benefit does a multi-zone (regional) deployment provide versus a single zone?

    Multi-zone deployment protects against zone-level failures (power, hardware, network in one zone) by distributing instances across zones in a region, raising availability. A single-zone deployment fails entirely if that zone goes down.

13. When should you choose a multi-region architecture over multi-zone?

    Choose multi-region when you need protection from region-wide outages, very high availability SLOs (e.g., >99.99%), disaster recovery across geographies, or low latency for globally distributed users. It costs more and adds cross-region latency/replication complexity.

14. What is graceful degradation in system design?

    Graceful degradation is designing a system to continue providing reduced but acceptable functionality when components fail, instead of failing completely (e.g., serving cached/read-only data, disabling non-critical features) to preserve core user experience.

15. Define redundancy and the principle of eliminating single points of failure (SPOF).

    Redundancy is duplicating critical components so a failure of one does not cause outage. Eliminating SPOFs means ensuring no single component's failure can bring down the system, achieved via N+1/N+2 redundancy across independent failure domains.

16. What is the difference between active-active and active-passive failover?

    Active-active runs multiple instances serving traffic simultaneously (load shared, instant failover, higher utilization). Active-passive keeps a standby that only takes over when the primary fails (simpler, but idle capacity and some failover delay).

17. Define RTO and RPO in disaster recovery.

    RTO (Recovery Time Objective) is the maximum acceptable time to restore service after a disaster. RPO (Recovery Point Objective) is the maximum acceptable amount of data loss measured in time (how far back the last usable backup must be).

18. Name the four common DR patterns ordered from cheapest/slowest to most expensive/fastest.

    1) Backup and restore (highest RTO/RPO, cheapest), 2) Pilot light, 3) Warm standby, 4) Hot standby / multi-site active-active (near-zero RTO/RPO, most expensive).

19. What does a 'pilot light' DR strategy involve?

    Pilot light keeps a minimal core of the system (e.g., replicated database, base configuration/images) always running in the recovery site. On disaster, the rest of the infrastructure is rapidly provisioned and scaled up around that core.

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