Cloud Infrastructure

Design and provision cloud infrastructure with AWS-primary patterns and cloud-agnostic naming for portability.

Decision Framework

New service/workload?
├── Stateless, event-driven, <15min → Serverless (Lambda + API GW)
├── Long-running, stateful, predictable → Containers (ECS Fargate)
├── Kubernetes-native, multi-cloud → Orchestration (EKS)
└── Static content, CDN → Storage (S3 + CloudFront)

Database needs?
├── Key-value, <1ms, scale-to-zero → DynamoDB
├── Relational, complex queries → RDS/Aurora
├── Document store, flexible schema → DocumentDB
└── Cache, sessions, pub/sub → ElastiCache (Redis)

IaC approach?
├── AWS-only, type-safe → CDK (TypeScript)
├── Multi-cloud, declarative → Terraform
└── Simple, YAML → CloudFormation

When NOT to Use

CI/CD pipelines: Use ci-cd skill for pipeline config (CodePipeline, GitHub Actions)
Database schema design: Use database-design skill for schema/migrations/queries
Application-level monitoring: Use observability skill for application metrics/logs/traces

References

File	Use When
`references/service-selection.md`	Choosing between AWS compute, database, or messaging services
`references/cdk-patterns.md`	Writing CDK constructs, organizing stacks, L1/L2/L3 patterns
`references/serverless-patterns.md`	Building Lambda functions, API Gateway, Step Functions, event-driven
`references/container-patterns.md`	ECS Fargate task definitions, service discovery, health checks
`references/iam-and-security.md`	IAM policies, security groups, VPC design, least privilege
`references/storage-and-cdn.md`	S3 configuration, CloudFront distributions, caching strategies
`references/database-selection.md`	DynamoDB patterns, RDS/Aurora configuration, managed DB comparison
`references/cost-optimization.md`	Right-sizing, reserved capacity, cost estimation, billing alerts

cloud-infrastructure

Cloud Infrastructure

Decision Framework

When NOT to Use

References