Use this cheat sheet for Google Cloud Professional Cloud Architect (PCA) when you already know the product names and need faster architecture decisions. PCA questions reward trade-off reasoning: meet the business requirement, satisfy the technical constraint, keep the design operable, and avoid unnecessary complexity.
Read every PCA question in this order
- Identify the primary constraint: reliability, latency, security, compliance, migration speed, cost, operations, or data residency.
- Choose the design lane: compute, storage, network, identity, data, integration, migration, or operations.
- Decide whether the workload needs regional, multi-regional, hybrid, batch, streaming, transactional, or analytical behavior.
- Add the missing operational control: monitoring, logging, backup, rollback, SLO, IAM, policy, or cost governance.
- Reject answers that choose a powerful service while ignoring the stated constraint.
PCA answer sequence
Use this when the stem mixes business constraints, service fit, operations, and resilience.
flowchart TD
S["Scenario"] --> C["Find the primary constraint"]
C --> L["Choose the design lane"]
L --> O["Add the missing operational control"]
O --> R["Check reliability, migration, or cost trade-offs"]
R --> E["Reject answers that miss the constraint"]
Architecture chooser
| Requirement |
Start with |
Watch for |
| portable container workload |
GKE or managed container pattern |
cluster operations, autoscaling, networking, and release process |
| event-driven lightweight app |
serverless compute |
cold starts, identity, observability, and integration path |
| steady VM-based workload |
Compute Engine or managed instance groups |
image management, autoscaling, load balancing, and patching |
| analytical queries |
BigQuery and governed data pipelines |
partitioning, access, query cost, and data freshness |
| globally consistent transactional need |
globally distributed database options |
latency, consistency, schema, and cost trade-offs |
| object storage |
Cloud Storage |
class, lifecycle, access, encryption, retention, and region |
Identity and security
| Scenario |
Strong answer pattern |
| service-to-service access |
service accounts, least privilege, and keyless patterns where possible |
| organization-wide guardrail |
resource hierarchy, organization policy, folders, projects, and policy inheritance |
| sensitive data |
classification, IAM, encryption, key management, audit logs, and retention |
| private workload |
private connectivity, firewall rules, load balancer design, and restricted egress |
| regulated environment |
control mapping, audit evidence, data residency, access review, and logging |
| emergency access |
break-glass process with approval, logging, expiry, and review |
Reliability and operations
| Requirement |
Better design instinct |
| high availability |
remove single points of failure across zones or regions according to RTO/RPO |
| disaster recovery |
backups, replication, tested restore, runbooks, and failover criteria |
| user-facing reliability |
SLOs, SLIs, error budgets, alerting, and incident response |
| safe deployment |
staged rollout, health checks, rollback, and artifact traceability |
| production support |
dashboards, logs, traces, ownership, and escalation path |
| dependency failure |
graceful degradation, retries with care, circuit breakers, and queues |
Migration and modernization
| Situation |
Better approach |
| many legacy apps |
assess dependencies, group waves, reduce risk, and avoid big-bang migration |
| minimal code change required |
rehost or replatform before deeper refactoring |
| business needs agility |
refactor selectively around high-value bottlenecks |
| hybrid period required |
reliable connectivity, identity federation, DNS, logging, and operational ownership |
| large data transfer |
choose transfer method based on volume, timeline, bandwidth, and downtime tolerance |
| cutover risk |
test, rehearse, monitor, and define rollback before production move |
| Symptom |
First checks |
| slow application |
latency path, load balancer, region, database query, cache, and dependency timing |
| expensive analytics |
partitioning, clustering, query shape, storage lifecycle, and user behavior |
| idle infrastructure |
autoscaling, schedules, rightsizing, and managed service fit |
| unexpected egress |
region placement, network path, CDN, replication, and data transfer pattern |
| overbuilt architecture |
simplify to meet the requirement with fewer moving parts |
Common traps
| Trap |
Better instinct |
| service catalog answer |
defend the design against the requirement |
| single-region default |
check availability, latency, DR, and data residency |
| broad IAM for speed |
use scoped roles, service accounts, and policy guardrails |
| migration without operations |
include monitoring, incident response, backup, and ownership |
| cost after design |
cost is a design constraint, not a final cleanup task |
| resilience without restore test |
backup exists only if recovery is validated |
Final 15-minute review
| If the stem says… |
Start here |
| architecture design |
requirement, constraint, service fit, failure domain, and operations |
| compliance |
IAM, encryption, logging, policy, residency, and evidence |
| migration |
dependency map, wave plan, data transfer, cutover, rollback |
| reliability |
SLO, HA, DR, backup, failover, incident process |
| performance |
bottleneck evidence, region, cache, query, autoscaling |
| cost |
rightsizing, managed fit, storage class, query cost, egress |
Practice fit
Use IT Mastery for the exact product route, practice status, spaced review when available, and close-answer explanation practice as coverage expands.
One-line decision rule
PCA answers should satisfy the business constraint with the smallest operable architecture that is secure, reliable, observable, recoverable, and cost-aware.