AWS Solution Architect

AWS Solution Architect

Design scalable, cost-effective AWS architectures for startups with infrastructure-as-code templates — recommend the right pattern, generate CloudFormation/CDK/Terraform, and optimize spend.

Core Capabilities

• Architecture design — recommend serverless, three-tier, microservices, data-pipeline, GraphQL, IoT, or multi-region patterns from app type, scale, budget, and compliance needs.
• IaC generation — produce production-ready CloudFormation (SAM), CDK (TypeScript), and Terraform (HCL) with API Gateway, Lambda, DynamoDB, Cognito, IAM least-privilege, and CloudWatch.
• Cost optimization — analyze inventory for idle resources, right-sizing, Savings Plans, storage tiering, and NAT Gateway alternatives with prioritized savings.
• Service selection — decision matrices for compute, database, storage, networking, and security.
• Operational excellence — monitoring, alarming, disaster recovery (RTO/RPO), and security hardening.

When to Use

• Designing serverless / three-tier / microservices / data-pipeline / multi-region AWS architecture.
• Writing or generating CloudFormation, CDK, or Terraform infrastructure-as-code.
• Reducing AWS costs, right-sizing, or evaluating Savings Plans / Reserved capacity.
• Selecting AWS services (Lambda, API Gateway, DynamoDB, Aurora, ECS/Fargate, EventBridge, AppSync).
• Setting up CI/CD (CodePipeline, CodeBuild) or migrating workloads to AWS.
• Hardening IAM, VPC, encryption, Cognito, WAF, or planning monitoring (CloudWatch, X-Ray).

Clarify First

Before designing the architecture, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• [ ] App type & scale — workload type and expected traffic (selects the pattern: serverless, three-tier, microservices, data-pipeline, or multi-region)
• [ ] IaC target — CloudFormation/SAM, CDK, or Terraform (sets the template format serverless_stack.py generates)
• [ ] Budget & compliance constraints — cost ceiling and any regulatory needs (drive service selection and the cost-optimization recommendations)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Tools

These are Python classes imported from scripts/ (no CLI). See references/tool-reference.md for full parameters, methods, and examples.

| Tool | Purpose | Usage |

|------|---------|-------|

| architecture_designer.py | Recommend a pattern + service stack + cost estimate from requirements | from scripts.architecture_designer import ArchitectureDesigner |

| serverless_stack.py | Generate CloudFormation / CDK / Terraform serverless templates | from scripts.serverless_stack import ServerlessStackGenerator |

| cost_optimizer.py | Analyze inventory + spend → prioritized savings recommendations | from scripts.cost_optimizer import CostOptimizer |

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

• references/workflow-and-usage.md — the 6-step design→deploy→validate workflow, quick-start scenarios (MVP, scaling, cost optimization, IaC), input-requirements JSON, and output formats. Read when running an end-to-end design.
• references/architecture_patterns.md — the 6 detailed patterns (serverless, microservices, three-tier, data processing, GraphQL, multi-region) with full service specs. Read when selecting and designing a pattern.
• references/service_selection.md — decision matrices for compute, database, storage, and messaging. Read when choosing between AWS services.
• references/best_practices.md — serverless design, cost optimization, security hardening, scalability, plus service limitations, troubleshooting, and success criteria. Read before shipping an architecture.
• references/tool-reference.md — full Python API (constructors, methods, requirement/resource dictionaries, examples) for the three tools. Read when invoking the tools programmatically.

Scope & Limitations

This skill covers:

• AWS architecture design for startups and growth-stage companies (serverless, three-tier, microservices, data pipelines, IoT, multi-region patterns)
• Infrastructure-as-code generation for CloudFormation (SAM), CDK (TypeScript), and Terraform (HCL)
• Cost analysis, right-sizing recommendations, and Savings Plans evaluation
• Service selection guidance for compute, database, storage, networking, and security

This skill does NOT cover:

• Multi-cloud or hybrid-cloud architectures (Azure, GCP) -- see engineering/cloud-migration-specialist/ for cross-cloud strategies
• Application-level code, business logic, or framework-specific implementation -- see engineering/senior-fullstack/ for fullstack development
• Compliance audit execution or regulatory evidence collection -- see ra-qm-team/ for SOC 2, HIPAA, GDPR, and ISO compliance skills
• AWS account management, organization policies, or billing disputes -- see AWS Support or engineering/ms365-tenant-manager/ for tenant administration patterns

Integration Points

| Skill | Integration | Data Flow |

|-------|-------------|-----------|

| engineering/senior-devops | CI/CD pipeline configuration for deploying generated IaC templates | Architecture templates flow into DevOps deployment pipelines and monitoring setup |

| engineering/senior-secops | Security hardening of generated architectures (IAM policies, WAF rules, GuardDuty) | Architecture design feeds into security review; SecOps findings feed back as architecture constraints |

| ra-qm-team/soc2-compliance | Compliance validation of AWS architectures against SOC 2 Trust Services Criteria | Architecture resource inventory feeds into compliance audit; audit findings drive architecture changes |

| engineering/senior-backend | Backend service implementation that runs on the designed AWS infrastructure | Architecture patterns define the runtime environment; backend requirements inform service selection |

| engineering/tech-stack-evaluator | Technology selection decisions that influence architecture pattern choice | Stack evaluation outputs (database, compute, messaging choices) feed into architecture requirements JSON |

| c-level-advisor/cto-advisor | Strategic infrastructure decisions, build-vs-buy, and cloud budget planning | Cost analysis from cost_optimizer.py informs CTO budget decisions; CTO constraints flow back as architecture requirements |