MCPInstall

aws-solution-architect

Expert AWS solution architecture for startups focusing on serverless, scalable, and cost-effective cloud infrastructure with modern DevOps practices and infrastructure-as-code

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/alirezarezvani/claude-code-skill-factory --skill aws-solution-architect
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads aws-solution-architect automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

AWS Solution Architect for Startups

This skill provides comprehensive AWS architecture design expertise for startup companies, emphasizing serverless technologies, scalability, cost optimization, and modern cloud-native patterns.

Capabilities

  • Serverless Architecture Design: Lambda, API Gateway, DynamoDB, EventBridge, Step Functions, AppSync
  • Infrastructure as Code: CloudFormation, CDK (Cloud Development Kit), Terraform templates
  • Scalable Application Architecture: Auto-scaling, load balancing, multi-region deployment
  • Data & Storage Solutions: S3, RDS Aurora Serverless, DynamoDB, ElastiCache, Neptune
  • Event-Driven Architecture: EventBridge, SNS, SQS, Kinesis, Lambda triggers
  • API Design: API Gateway (REST & WebSocket), AppSync (GraphQL), rate limiting, authentication
  • Authentication & Authorization: Cognito, IAM, fine-grained access control, federated identity
  • CI/CD Pipelines: CodePipeline, CodeBuild, CodeDeploy, GitHub Actions integration
  • Monitoring & Observability: CloudWatch, X-Ray, CloudTrail, alarms, dashboards
  • Cost Optimization: Reserved instances, Savings Plans, right-sizing, budget alerts
  • Security Best Practices: VPC design, security groups, WAF, Secrets Manager, encryption
  • Microservices Patterns: Service mesh, API composition, saga patterns, CQRS
  • Container Orchestration: ECS Fargate, EKS (Kubernetes), App Runner
  • Content Delivery: CloudFront, edge locations, origin shield, caching strategies
  • Database Migration: DMS, schema conversion, zero-downtime migrations

Input Requirements

Architecture design requires:

  • Application type: Web app, mobile backend, data pipeline, microservices, SaaS platform
  • Traffic expectations: Users/day, requests/second, geographic distribution
  • Data requirements: Storage needs, database type, backup/retention policies
  • Budget constraints: Monthly spend limits, cost optimization priorities
  • Team size & expertise: Developer count, AWS experience level, DevOps maturity
  • Compliance needs: GDPR, HIPAA, SOC 2, PCI-DSS, data residency
  • Availability requirements: SLA targets, uptime goals, disaster recovery RPO/RTO

Formats accepted:

  • Text description of application requirements
  • JSON with structured architecture specifications
  • Existing architecture diagrams or documentation
  • Current AWS resource inventory (for optimization)

Output Formats

Results include:

  • Architecture diagrams: Visual representations using draw.io or Lucidchart format
  • CloudFormation/CDK templates: Infrastructure as Code (IaC) ready to deploy
  • Terraform configurations: Multi-cloud compatible infrastructure definitions
  • Cost estimates: Detailed monthly cost breakdown with optimization suggestions
  • Security assessment: Best practices checklist, compliance validation
  • Deployment guides: Step-by-step implementation instructions
  • Runbooks: Operational procedures, troubleshooting guides, disaster recovery plans
  • Migration strategies: Phased migration plans, rollback procedures

How to Use

"Design a serverless API backend for a mobile app with 100k users using Lambda and DynamoDB" "Create a cost-optimized architecture for a SaaS platform with multi-tenancy" "Generate CloudFormation template for a three-tier web application with auto-scaling" "Design event-driven microservices architecture using EventBridge and Step Functions" "Optimize my current AWS setup to reduce costs by 30%"

Scripts

  • architecture_designer.py: Generates architecture patterns and service recommendations
  • serverless_stack.py: Creates serverless application stacks (Lambda, API Gateway, DynamoDB)
  • cost_optimizer.py: Analyzes AWS costs and provides optimization recommendations
  • iac_generator.py: Generates CloudFormation, CDK, or Terraform templates
  • security_auditor.py: AWS security best practices validation and compliance checks

Architecture Patterns

1. Serverless Web Application

Use Case: SaaS platforms, mobile backends, low-traffic websites

Stack:

  • Frontend: S3 + CloudFront (static hosting)
  • API: API Gateway + Lambda
  • Database: DynamoDB or Aurora Serverless
  • Auth: Cognito
  • CI/CD: Amplify or CodePipeline

Benefits: Zero server management, pay-per-use, auto-scaling, low operational overhead

Cost: $50-500/month for small to medium traffic

2. Event-Driven Microservices

Use Case: Complex business workflows, asynchronous processing, decoupled systems

Stack:

  • Events: EventBridge (event bus)
  • Processing: Lambda functions or ECS Fargate
  • Queue: SQS (dead letter queues for failures)
  • State Management: Step Functions
  • Storage: DynamoDB, S3

Benefits: Loose coupling, independent scaling, failure isolation, easy testing

Cost: $100-1000/month depending on event volume

3. Modern Three-Tier Application

Use Case: Traditional web apps with dynamic content, e-commerce, CMS

Stack:

  • Load Balancer: ALB (Application Load Balancer)
  • Compute: ECS Fargate or EC2 Auto Scaling
  • Database: RDS Aurora (MySQL/PostgreSQL)
  • Cache: ElastiCache (Redis)
  • CDN: CloudFront
  • Storage: S3

Benefits: Proven pattern, easy to understand, flexible scaling

Cost: $300-2000/month depending on traffic and instance sizes

4. Real-Time Data Processing

Use Case: Analytics, IoT data ingestion, log processing, streaming

Stack:

  • Ingestion: Kinesis Data Streams or Firehose
  • Processing: Lambda or Kinesis Analytics
  • Storage: S3 (data lake) + Athena (queries)
  • Visualization: QuickSight
  • Alerting: CloudWatch + SNS

Benefits: Handle millions of events, real-time insights, cost-effective storage

Cost: $200-1500/month depending on data volume

5. GraphQL API Backend

Use Case: Mobile apps, single-page applications, flexible data queries

Stack:

  • API: AppSync (managed GraphQL)
  • Resolvers: Lambda or direct DynamoDB integration
  • Database: DynamoDB
  • Real-time: AppSync subscriptions (WebSocket)
  • Auth: Cognito or API keys

Benefits: Single endpoint, reduce over/under-fetching, real-time subscriptions

Cost: $50-400/month for moderate usage

6. Multi-Region High Availability

Use Case: Global applications, disaster recovery, compliance requirements

Stack:

  • DNS: Route 53 (geolocation routing)
  • CDN: CloudFront with multiple origins
  • Compute: Multi-region Lambda or ECS
  • Database: DynamoDB Global Tables or Aurora Global Database
  • Replication: S3 cross-region replication

Benefits: Low latency globally, disaster recovery, data sovereignty

Cost: 1.5-2x single region costs

Best Practices

Serverless Design Principles

  1. Stateless functions - Store state in DynamoDB, S3, or ElastiCache
  2. Idempotency - Handle retries gracefully, use unique request IDs
  3. Cold start optimization - Use provisioned concurrency for critical paths, optimize package size
  4. Timeout management - Set appropriate timeouts, use Step Functions for long processes
  5. Error handling - Implement retry logic, dead letter queues, exponential backoff

Cost Optimization

  1. Right-sizing - Start small, monitor metrics, scale based on actual usage
  2. Reserved capacity - Use Savings Plans or Reserved Instances for predictable workloads
  3. S3 lifecycle policies - Transition to cheaper storage tiers (IA, Glacier)
  4. Lambda memory optimization - Test different memory settings for cost/performance balance
  5. CloudWatch log retention - Set appropriate retention periods (7-30 days for most)
  6. NAT Gateway alternatives - Use VPC endpoints, consider single NAT in dev environments

Security Hardening

  1. Principle of least privilege - IAM roles with minimal permissions
  2. Encryption everywhere - At rest (KMS) and in transit (TLS/SSL)
  3. Network isolation - Private subnets, security groups, NACLs
  4. Secrets management - Use Secrets Manager or Parameter Store, never hardcode
  5. API protection - WAF rules, rate limiting, API keys, OAuth2
  6. Audit logging - CloudTrail for API calls, VPC Flow Logs for network traffic

Scalability Design

  1. Horizontal over vertical - Scale out with more small instances vs. larger instances
  2. Database sharding - Partition data by tenant, geography, or time
  3. Read replicas - Offload read traffic from primary database
  4. Caching layers - CloudFront (edge), ElastiCache (application), DAX (DynamoDB)
  5. Async processing - Use queues (SQS) for non-critical operations
  6. Auto-scaling policies - Target tracking (CPU, requests) vs. step scaling

DevOps & Reliability

  1. Infrastructure as Code - Version control, peer review, automated testing
  2. Blue/Green deployments - Zero-downtime releases, instant rollback
  3. Canary releases - Test new versions with small traffic percentage
  4. Health checks - Application-level health endpoints, graceful degradation
  5. Chaos engineering - Test failure scenarios, validate recovery procedures
  6. Monitoring & alerting - Set up CloudWatch alarms for critical metrics

Service Selection Guide

Compute

  • Lambda: Event-driven, short-duration tasks (<15 min), variable traffic
  • Fargate: Containerized apps, long-running processes, predictable traffic
  • EC2: Custom configurations, GPU/FPGA needs, Windows apps
  • App Runner: Simple container deployment from source code

Database

  • DynamoDB: Key-value, document store, serverless, single-digit ms latency
  • Aurora Serverless: Relational DB, variable workloads, auto-scaling
  • Aurora Standard: High-performance relational, predictable traffic
  • RDS: Traditional databases (MySQL, PostgreSQL, MariaDB, SQL Server)
  • DocumentDB: MongoDB-compatible, document store
  • Neptune: Graph database for connected data
  • Timestream: Time-series data, IoT metrics

Storage

  • S3 Standard: Frequent access, low latency
  • S3 Intelligent-Tiering: Automatic cost optimization
  • S3 IA (Infrequent Access): Backups, archives (30-day minimum)
  • S3 Glacier: Long-term archives, compliance
  • EFS: Network file system, shared storage across instances
  • EBS: Block storage for EC2, high IOPS

Messaging & Events

  • EventBridge: Event bus, loosely coupled microservices
  • SNS: Pub/sub, fan-out notifications
  • SQS: Message queuing, decoupling, buffering
  • Kinesis: Real-time streaming data, analytics
  • MQ: Managed message brokers (RabbitMQ, ActiveMQ)

API & Integration

  • API Gateway: REST APIs, WebSocket, throttling, caching
  • AppSync: GraphQL APIs, real-time subscriptions
  • AppFlow: SaaS integration (Salesforce, Slack, etc.)
  • Step Functions: Workflow orchestration, state machines

Startup-Specific Considerations

MVP (Minimum Viable Product) Architecture

Goal: Launch fast, minimal infrastructure

Recommended:

  • Amplify (full-stack deployment)
  • Lambda + API Gateway + DynamoDB
  • Cognito for auth
  • CloudFront + S3 for frontend

Cost: $20-100/month Setup time: 1-3 days

Growth Stage (Scaling to 10k-100k users)

Goal: Handle growth, maintain cost efficiency

Add:

  • ElastiCache for caching
  • Aurora Serverless for complex queries
  • CloudWatch dashboards and alarms
  • CI/CD pipeline (CodePipeline)
  • Multi-AZ deployment

Cost: $500-2000/month Migration time: 1-2 weeks

Scale-Up (100k+ users, Series A+)

Goal: Reliability, observability, global reach

Add:

  • Multi-region deployment
  • DynamoDB Global Tables
  • Advanced monitoring (X-Ray, third-party APM)
  • WAF and Shield for DDoS protection
  • Dedicated support plan
  • Reserved instances/Savings Plans

Cost: $3000-10000/month Migration time: 1-3 months

Common Pitfalls to Avoid

Technical Debt

  • Over-engineering early - Don't build for 10M users when you have 100
  • Under-monitoring - Set up basic monitoring from day one
  • Ignoring costs - Enable Cost Explorer and billing alerts immediately
  • Single region dependency - Plan for multi-region from start

Security Mistakes

  • Public S3 buckets - Use bucket policies, block public access
  • Overly permissive IAM - Avoid "*" permissions, use specific resources
  • Hardcoded credentials - Use IAM roles, Secrets Manager
  • Unencrypted data - Enable encryption by default

Performance Issues

  • No caching - Add CloudFront, ElastiCache early
  • Inefficient queries - Use indexes, avoid scans in DynamoDB
  • Large Lambda packages - Use layers, minimize dependencies
  • N+1 queries - Implement DataLoader pattern, batch operations

Cost Surprises

  • Undeleted resources - Tag everything, review regularly
  • Data transfer costs - Keep traffic within same AZ/region when possible
  • NAT Gateway charges - Use VPC endpoints for AWS services
  • CloudWatch Logs accumulation - Set retention policies

Compliance & Governance

Data Residency

  • Use specific regions (eu-west-1 for GDPR)
  • Enable S3 bucket replication restrictions
  • Configure Route 53 geolocation routing

HIPAA Compliance

  • Use BAA-eligible services only
  • Enable encryption at rest and in transit
  • Implement audit logging (CloudTrail)
  • Configure VPC with private subnets

SOC 2 / ISO 27001

  • Enable AWS Config for compliance rules
  • Use AWS Audit Manager
  • Implement least privilege access
  • Regular security assessments

Limitations

  • Lambda limitations: 15-minute execution limit, 10GB memory max, cold start latency
  • API Gateway limits: 29-second timeout, 10MB payload size
  • DynamoDB limits: 400KB item size, eventually consistent reads by default
  • Regional availability: Not all services available in all regions
  • Vendor lock-in: Some serverless services are AWS-specific (consider abstraction layers)
  • Learning curve: Requires AWS expertise, DevOps knowledge
  • Debugging complexity: Distributed systems harder to troubleshoot than monoliths

Helpful Resources

FAQ

What does the aws-solution-architect skill do?

Expert AWS solution architecture for startups focusing on serverless, scalable, and cost-effective cloud infrastructure with modern DevOps practices and infrastructure-as-code

How do I install aws-solution-architect?

Run npx skills add https://github.com/alirezarezvani/claude-code-skill-factory --skill aws-solution-architect in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/aws-solution-architect/ (personal) or .claude/skills/aws-solution-architect/ (project).

Which AI agents can use aws-solution-architect?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is aws-solution-architect safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains aws-solution-architect?

It is published by alirezarezvani in alirezarezvani/claude-code-skill-factory. It has 91 recorded installs.

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