aws-solution-architect
alirezarezvani/claude-skills
Design serverless AWS architectures and generate IaC templates for startups with cost optimization.
What is aws-solution-architect?
This skill helps design scalable, cost-effective AWS architectures tailored to startup needs using serverless patterns and infrastructure-as-code. Use it when you need to architect serverless systems, create CloudFormation/CDK templates, optimize AWS costs, set up CI/CD pipelines, or plan AWS migrations.
- Generate architecture patterns (serverless web, event-driven microservices, three-tier, GraphQL) based on application requirements and scale
- Create production-ready CloudFormation YAML and CDK TypeScript templates with API Gateway, Lambda, DynamoDB, ECS, Aurora, and IAM roles
- Analyze current AWS infrastructure and recommend cost optimizations including right-sizing, Savings Plans, and storage tier transitions
- Estimate monthly AWS costs for proposed architectures and validate against budget constraints
- Provide deployment guidance and troubleshoot CloudFormation stack failures with specific remediation steps
How to install aws-solution-architect
npx skills add https://github.com/alirezarezvani/claude-skills --skill aws-solution-architect- AWS account with appropriate IAM permissions to create CloudFormation stacks, Lambda, DynamoDB, ECS, RDS, and related services
- AWS CLI configured with credentials and default region
- Python 3.8+ for running architecture_designer.py, serverless_stack.py, and cost_optimizer.py scripts
- Basic understanding of AWS services (Lambda, API Gateway, DynamoDB, RDS) or willingness to learn from generated templates
How to use aws-solution-architect
- 1.Gather application requirements: type, expected users, budget, team AWS experience, and compliance needs
- 2.Run architecture_designer.py with your requirements.json to get pattern recommendations and cost estimates
- 3.Review the recommended pattern (serverless web, microservices, three-tier, or GraphQL) and confirm it matches your operational maturity
- 4.Generate IaC templates using serverless_stack.py or CDK snippets for your chosen pattern
- 5.Run cost_optimizer.py on your current or proposed infrastructure to identify savings opportunities
- 6.Deploy the generated CloudFormation or CDK templates using AWS CLI or cdk deploy
- 7.Validate deployment status and set up CloudWatch alarms; troubleshoot failures using provided diagnostic commands
Use cases
- Design a serverless MVP backend for a mobile app with minimal operational overhead and <$100/month cost
- Create a scalable SaaS platform architecture supporting 50k+ users with ECS Fargate, Aurora, and multi-AZ deployment
- Optimize an existing $3000/month AWS bill by identifying idle resources and recommending right-sizing actions
- Generate CloudFormation templates for event-driven microservices using EventBridge, Lambda, SQS, and Step Functions
- Plan a migration from on-premises infrastructure to AWS with compliance requirements (GDPR, HIPAA, SOC 2)
- Startup founders and CTOs designing cloud infrastructure for the first time
- AWS Solutions Architects and DevOps engineers creating IaC templates and cost optimization plans
- Backend engineers building serverless APIs and microservices on AWS
- Technical leads evaluating AWS patterns and cost trade-offs for new projects
aws-solution-architect FAQ
Lambda, API Gateway, DynamoDB, ECS Fargate, Aurora (RDS), Cognito, S3, CloudFront, EventBridge, SQS, Step Functions, ElastiCache, CloudWatch, and IAM. It focuses on serverless and managed services suitable for startups.
The skill mentions Terraform as a deployment option (terraform init && terraform apply) but the primary IaC outputs are CloudFormation YAML and CDK TypeScript. Custom Terraform generation is not explicitly documented.
Estimates are based on service pricing and recommended resource configurations. Actual costs depend on traffic patterns, data storage, and data transfer. Use AWS Cost Explorer to validate estimates against real usage.
The skill provides diagnostic steps: check CloudFormation events, review CloudWatch logs, validate template syntax, verify IAM permissions, and request quota increases if needed. Delete failed stacks before retrying.
The skill covers multi-AZ deployment for high availability. Multi-region and disaster recovery patterns are not explicitly detailed in the provided documentation.
Full instructions (SKILL.md)
Source of truth, from alirezarezvani/claude-skills.
name: "aws-solution-architect" description: 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.
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.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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