vuralserhat86

aws_architect

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# Description

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

# SKILL.md


name: aws_architect
router_kit: DevOpsKit
description: Expert AWS solution architecture for startups focusing on serverless, scalable, and cost-effective cloud infrastructure with modern DevOps practices and infrastructure-as-code
metadata:
skillport:
category: auto-healed
tags: [automation, aws, aws architect, bash scripting, ci/cd, cloud computing, containerization, deployment strategies, devops, docker, gitops, infrastructure, infrastructure as code, kubernetes, linux, logging, microservices, monitoring, orchestration, pipelines, reliability, scalability, security, server management, terraform] - aws_architect


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

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

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