
AWS Solution Architect
FreeDesign scalable AWS architectures with ease.
Free · Opens the source repo
What AWS Solution Architect does
The AWS Solution Architect skill is designed to assist developers and architects in creating efficient and cost-effective AWS architectures tailored for startups. By leveraging infrastructure-as-code (IaC) templates and serverless patterns, this skill simplifies the process of designing and deploying AWS solutions. It provides a structured workflow that guides users through gathering requirements, designing architectures, generating IaC templates, reviewing costs, and deploying the infrastructure.
At the core of this skill is the architecture designer script, which analyzes user requirements and recommends suitable architecture patterns. Users can choose from various patterns, such as serverless web applications, event-driven microservices, and more. Each recommended pattern includes a detailed service stack, estimated costs, and pros and cons, allowing users to make informed decisions based on their specific needs.
Once a pattern is selected, the skill generates IaC templates that can be deployed using CloudFormation, CDK, or Terraform. This automation not only speeds up the deployment process but also ensures consistency and reliability in the infrastructure setup. Additionally, the cost optimizer script helps users analyze their current AWS setup and provides actionable recommendations for cost savings, making it easier to manage budgets effectively.
This skill is ideal for startups and teams looking to implement AWS solutions without extensive cloud experience. It streamlines the architecture design process and helps users avoid common pitfalls associated with AWS deployments, ensuring a smoother transition to cloud-based infrastructure.
When to use it
Use this skill when you need to design serverless architectures, create CloudFormation templates, or optimize AWS costs.
When not to use it
It may not be suitable for large-scale enterprise architectures or users requiring highly customized solutions beyond standard patterns.
What you can build with it
Designing a Serverless Web Application
Use the skill to gather requirements and generate a serverless architecture for a new web app, streamlining the design process.
Cost Analysis for Existing AWS Setup
Run the cost optimizer to analyze your current AWS resources and receive actionable recommendations for cost savings.
Creating Infrastructure-as-Code Templates
Generate CloudFormation templates for your chosen architecture pattern, ensuring quick and consistent deployments.
How to install AWS Solution Architect
View source1. Install with the skills CLI
npx skills add alirezarezvani/claude-skills/aws-solution-architect --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by alirezarezvaniAWS 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.pyand also available inreferences/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:
- Check the failure reason:
aws cloudformation describe-stack-events \ --stack-name my-app-stack \ --query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]' - Review CloudWatch Logs for Lambda or ECS errors.
- Fix the template or resource configuration.
- 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_IAMand 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.yamlbefore 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:
| Requirement | Description | Example |
|---|---|---|
| Application type | What you're building | SaaS platform, mobile backend |
| Expected scale | Users, requests/sec | 10k users, 100 RPS |
| Budget | Monthly AWS limit | $500/month max |
| Team context | Size, AWS experience | 3 devs, intermediate |
| Compliance | Regulatory needs | HIPAA, GDPR, SOC 2 |
| Availability | Uptime requirements | 99.9% 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
| Document | Contents |
|---|---|
references/architecture_patterns.md | 6 patterns: serverless, microservices, three-tier, data processing, GraphQL, multi-region |
references/service_selection.md | Decision matrices for compute, database, storage, messaging |
references/best_practices.md | Serverless design, cost optimization, security hardening, scalability |
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