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aws-solution-architect

Design AWS infrastructure around application needs, traffic, budget, and team experience. Generate templates that define infrastructure as code, compare service choices and estimated costs, and guide deployment, monitoring, and cost reduction.

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Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization.

Works withAWSTerraform
See how to install

Good for

  • Designing a serverless backend for an MVP
  • Planning AWS infrastructure for a growing SaaS
  • Generating CloudFormation infrastructure templates
  • Reviewing AWS spending for savings opportunities

Files included (9)

  • SKILL.md9.8 KB
  • assets/expected_output.json1.5 KB
  • assets/sample_input.json426 B
  • references/architecture_patterns.md17.1 KB
  • references/best_practices.md14.2 KB
  • references/service_selection.md11.1 KB
  • scripts/architecture_designer.py34.8 KB
  • scripts/cost_optimizer.py15.3 KB
  • scripts/serverless_stack.py17.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

AWS Solution Architect

Design scalable, cost-effective AWS architectures for startups with infrastructure-as-code templates.


Workflow

Step 1: Gather Requirements

Collect application specifications:

- Application type (web app, mobile backend, data pipeline, SaaS)
- Expected users and requests per second
- Budget constraints (monthly spend limit)
- Team size and AWS experience level
- Compliance requirements (GDPR, HIPAA, SOC 2)
- Availability requirements (SLA, RPO/RTO)

Step 2: Design Architecture

Run the architecture designer to get pattern recommendations:

python scripts/architecture_designer.py --input requirements.json

Example output:

{
  "recommended_pattern": "serverless_web",
  "service_stack": ["S3", "CloudFront", "API Gateway", "Lambda", "DynamoDB", "Cognito"],
  "estimated_monthly_cost_usd": 35,
  "pros": ["Low ops overhead", "Pay-per-use", "Auto-scaling"],
  "cons": ["Cold starts", "15-min Lambda limit", "Eventual consistency"]
}

Select from recommended patterns:

  • Serverless Web: S3 + CloudFront + API Gateway + Lambda + DynamoDB
  • Event-Driven Microservices: EventBridge + Lambda + SQS + Step Functions
  • Three-Tier: ALB + ECS Fargate + Aurora + ElastiCache
  • GraphQL Backend: AppSync + Lambda + DynamoDB + Cognito

See references/architecture_patterns.md for detailed pattern specifications.

Validation checkpoint: Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding to Step 3.

Step 3: Generate IaC Templates

Create infrastructure-as-code for the selected pattern:

# Serverless stack (CloudFormation)
python scripts/serverless_stack.py --app-name my-app --region us-east-1

Example CloudFormation YAML output (core serverless resources):

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Parameters:
  AppName:
    Type: String
    Default: my-app

Resources:
  ApiFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: index.handler
      Runtime: nodejs20.x
      MemorySize: 512
      Timeout: 30
      Environment:
        Variables:
          TABLE_NAME: !Ref DataTable
      Policies:
        - DynamoDBCrudPolicy:
            TableName: !Ref DataTable
      Events:
        ApiEvent:
          Type: Api
          Properties:
            Path: /{proxy+}
            Method: ANY

  DataTable:
    Type: AWS::DynamoDB::Table
    Properties:
      BillingMode: PAY_PER_REQUEST
      AttributeDefinitions:
        - AttributeName: pk
          AttributeType: S
        - AttributeName: sk
          AttributeType: S
      KeySchema:
        - AttributeName: pk
          KeyType: HASH
        - AttributeName: sk
          KeyType: RANGE

Full templates including API Gateway, Cognito, IAM roles, and CloudWatch logging are generated by serverless_stack.py and also available in references/architecture_patterns.md.

Example CDK TypeScript snippet (three-tier pattern):

import * as ecs from 'aws-cdk-lib/aws-ecs';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as rds from 'aws-cdk-lib/aws-rds';

const vpc = new ec2.Vpc(this, 'AppVpc', { maxAzs: 2 });

const cluster = new ecs.Cluster(this, 'AppCluster', { vpc });

const db = new rds.ServerlessCluster(this, 'AppDb', {
  engine: rds.DatabaseClusterEngine.auroraPostgres({
    version: rds.AuroraPostgresEngineVersion.VER_15_2,
  }),
  vpc,
  scaling: { minCapacity: 0.5, maxCapacity: 4 },
});

Step 4: Review Costs

Analyze estimated costs and optimization opportunities:

python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000

Example output:

{
  "current_monthly_usd": 2000,
  "recommendations": [
    { "action": "Right-size RDS db.r5.2xlarge → db.r5.large", "savings_usd": 420, "priority": "high" },
    { "action": "Purchase 1-yr Compute Savings Plan at 40% utilization", "savings_usd": 310, "priority": "high" },
    { "action": "Move S3 objects >90 days to Glacier Instant Retrieval", "savings_usd": 85, "priority": "medium" }
  ],
  "total_potential_savings_usd": 815
}

Output includes:

  • Monthly cost breakdown by service
  • Right-sizing recommendations
  • Savings Plans opportunities
  • Potential monthly savings

Step 5: Deploy

Deploy the generated infrastructure:

# CloudFormation
aws cloudformation create-stack \
  --stack-name my-app-stack \
  --template-body file://template.yaml \
  --capabilities CAPABILITY_IAM

# CDK
cdk deploy

# Terraform
terraform init && terraform apply

Step 6: Validate and Handle Failures

Verify deployment and set up monitoring:

# Check stack status
aws cloudformation describe-stacks --stack-name my-app-stack

# Set up CloudWatch alarms
aws cloudwatch put-metric-alarm --alarm-name high-errors ...

If stack creation fails:

  1. Check the failure reason:
    aws cloudformation describe-stack-events \
      --stack-name my-app-stack \
      --query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]'
    
  2. Review CloudWatch Logs for Lambda or ECS errors.
  3. Fix the template or resource configuration.
  4. Delete the failed stack before retrying:
    aws cloudformation delete-stack --stack-name my-app-stack
    # Wait for deletion
    aws cloudformation wait stack-delete-complete --stack-name my-app-stack
    # Redeploy
    aws cloudformation create-stack ...
    

Common failure causes:

  • IAM permission errors → verify --capabilities CAPABILITY_IAM and role trust policies
  • Resource limit exceeded → request quota increase via Service Quotas console
  • Invalid template syntax → run aws cloudformation validate-template --template-body file://template.yaml before deploying

Tools

architecture_designer.py

Generates architecture patterns based on requirements.

python scripts/architecture_designer.py --input requirements.json --output design.json

Input: JSON with app type, scale, budget, compliance needs Output: Recommended pattern, service stack, cost estimate, pros/cons

serverless_stack.py

Creates serverless CloudFormation templates.

python scripts/serverless_stack.py --app-name my-app --region us-east-1

Output: Production-ready CloudFormation YAML with:

  • API Gateway + Lambda
  • DynamoDB table
  • Cognito user pool
  • IAM roles with least privilege
  • CloudWatch logging

cost_optimizer.py

Analyzes costs and recommends optimizations.

python scripts/cost_optimizer.py --resources inventory.json --monthly-spend 5000

Output: Recommendations for:

  • Idle resource removal
  • Instance right-sizing
  • Reserved capacity purchases
  • Storage tier transitions
  • NAT Gateway alternatives

Quick Start

MVP Architecture (< $100/month)

Ask: "Design a serverless MVP backend for a mobile app with 1000 users"

Result:
- Lambda + API Gateway for API
- DynamoDB pay-per-request for data
- Cognito for authentication
- S3 + CloudFront for static assets
- Estimated: $20-50/month

Scaling Architecture ($500-2000/month)

Ask: "Design a scalable architecture for a SaaS platform with 50k users"

Result:
- ECS Fargate for containerized API
- Aurora Serverless for relational data
- ElastiCache for session caching
- CloudFront for CDN
- CodePipeline for CI/CD
- Multi-AZ deployment

Cost Optimization

Ask: "Optimize my AWS setup to reduce costs by 30%. Current spend: $3000/month"

Provide: Current resource inventory (EC2, RDS, S3, etc.)

Result:
- Idle resource identification
- Right-sizing recommendations
- Savings Plans analysis
- Storage lifecycle policies
- Target savings: $900/month

IaC Generation

Ask: "Generate CloudFormation for a three-tier web app with auto-scaling"

Result:
- VPC with public/private subnets
- ALB with HTTPS
- ECS Fargate with auto-scaling
- Aurora with read replicas
- Security groups and IAM roles

Input Requirements

Provide these details for architecture design:

RequirementDescriptionExample
Application typeWhat you're buildingSaaS platform, mobile backend
Expected scaleUsers, requests/sec10k users, 100 RPS
BudgetMonthly AWS limit$500/month max
Team contextSize, AWS experience3 devs, intermediate
ComplianceRegulatory needsHIPAA, GDPR, SOC 2
AvailabilityUptime requirements99.9% SLA, 1hr RPO

JSON Format:

{
  "application_type": "saas_platform",
  "expected_users": 10000,
  "requests_per_second": 100,
  "budget_monthly_usd": 500,
  "team_size": 3,
  "aws_experience": "intermediate",
  "compliance": ["SOC2"],
  "availability_sla": "99.9%"
}

Output Formats

Architecture Design

  • Pattern recommendation with rationale
  • Service stack diagram (ASCII)
  • Monthly cost estimate and trade-offs

IaC Templates

  • CloudFormation YAML: Production-ready SAM/CFN templates
  • CDK TypeScript: Type-safe infrastructure code
  • Terraform HCL: Multi-cloud compatible configs

Cost Analysis

  • Current spend breakdown with optimization recommendations
  • Priority action list (high/medium/low) and implementation checklist

Reference Documentation

DocumentContents
references/architecture_patterns.md6 patterns: serverless, microservices, three-tier, data processing, GraphQL, multi-region
references/service_selection.mdDecision matrices for compute, database, storage, messaging
references/best_practices.mdServerless design, cost optimization, security hardening, scalability

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