aws-architect

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

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

• AWS Well-Architected Framework: https://aws.amazon.com/architecture/well-architected/
• AWS Architecture Center: https://aws.amazon.com/architecture/
• Serverless Land: https://serverlessland.com/
• AWS Pricing Calculator: https://calculator.aws/
• AWS Cost Explorer: Track and analyze spending
• AWS Trusted Advisor: Automated best practice checks
• CloudFormation Templates: https://github.com/awslabs/aws-cloudformation-templates
• AWS CDK Examples: https://github.com/aws-samples/aws-cdk-examples

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AWS Architect v1.1 - Enhanced

🔄 Workflow

Kaynak: AWS Well-Architected Framework

Aşama 1: Operational Excellence & Security

• Ops: Runbooks hazır mı? Hata durumunda (Rollback) süreç net mi?
• Security: IAM "Least Privilege" uygulandı mı? S3 Public Access kapalı mı?
• Encryption: Veri at-rest (KMS) ve in-transit (HTTPS) şifreli mi?

Aşama 2: Reliability & Performance

• Backup: Veritabanı PITR (Point-in-Time Recovery) açık mı?
• Scaling: Auto-scaling tetikleyicileri (CPU/RAM/Requests) test edildi mi?
• Caching: CloudFront/ElastiCache katmanları doğru yapılandırıldı mı?

Aşama 3: Cost Optimization

• Right-Sizing: Instance/Lambda boyutları CPU/RAM kullanımına uygun mu?
• Lifecycle: S3 verileri için Lifecycle kuralları (IA/Glacier) var mı?
• Alerts: Bütçe alarmları (AWS Budgets) kuruldu mu?

Kontrol Noktaları

Aşama	Doğrulama
1	Security Score > %90 (Trusted Advisor / Security Hub)
2	Yük testinde (Load Testing) %99.9 availability sağlandı
3	Tahmini maliyet bütçe sınırları içinde