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cloud-infrastructure

@89jobrien/steve
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Cloud infrastructure design and deployment patterns for AWS, Azure, and

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SKILL.md

name cloud-infrastructure
description Cloud infrastructure design and deployment patterns for AWS, Azure, and GCP. Use when designing cloud architectures, implementing IaC with Terraform, optimizing costs, or setting up multi-region deployments.
author Joseph OBrien
status unpublished
updated 2025-12-23
version 1.0.1
tag skill
type skill

Cloud Infrastructure

Comprehensive cloud infrastructure skill covering multi-cloud architecture, Infrastructure as Code, cost optimization, and production deployment patterns.

When to Use This Skill

  • Designing cloud architecture for new applications
  • Implementing Infrastructure as Code (Terraform, CloudFormation, Pulumi)
  • Cost optimization and resource right-sizing
  • Multi-region and high-availability deployments
  • Cloud migration planning
  • Security and compliance implementation
  • Auto-scaling and performance optimization

Cloud Architecture Patterns

Compute Patterns

Pattern AWS Azure GCP Use Case
Serverless Lambda Functions Cloud Functions Event-driven, variable load
Containers ECS/EKS AKS GKE Microservices, consistent env
VMs EC2 Virtual Machines Compute Engine Legacy apps, full control
Batch Batch Batch Batch Large-scale processing

Storage Patterns

Type AWS Azure GCP Use Case
Object S3 Blob Storage Cloud Storage Static files, backups
Block EBS Managed Disks Persistent Disk Database storage
File EFS Azure Files Filestore Shared file systems
Archive Glacier Archive Coldline Long-term retention

Database Patterns

Type AWS Azure GCP Use Case
Relational RDS, Aurora SQL Database Cloud SQL ACID transactions
NoSQL DynamoDB Cosmos DB Firestore Flexible schema
Cache ElastiCache Cache for Redis Memorystore Session, caching
Data Warehouse Redshift Synapse BigQuery Analytics

Infrastructure as Code

Terraform Best Practices

Project Structure:

infrastructure/
├── modules/
│   ├── networking/
│   ├── compute/
│   └── database/
├── environments/
│   ├── dev/
│   ├── staging/
│   └── prod/
├── main.tf
├── variables.tf
├── outputs.tf
└── versions.tf

State Management:

  • Use remote state (S3, Azure Blob, GCS)
  • Enable state locking (DynamoDB, Blob lease)
  • Separate state per environment
  • Never commit state files

Module Design:

  • Single responsibility per module
  • Expose minimal required variables
  • Document inputs/outputs
  • Version modules with git tags

Cost Optimization

Compute Savings:

  • Reserved Instances (1-3 year commitment): 30-60% savings
  • Spot/Preemptible instances: 60-90% savings for interruptible workloads
  • Right-sizing: Match instance size to actual usage
  • Auto-scaling: Scale down during low usage

Storage Savings:

  • Lifecycle policies: Auto-transition to cheaper tiers
  • Compression: Reduce storage footprint
  • Deduplication: Eliminate redundant data
  • Delete unused resources: Orphaned volumes, snapshots

Network Savings:

  • Use CDN for static content
  • Optimize data transfer paths
  • Use private endpoints
  • Compress API responses

High Availability Patterns

Multi-AZ Deployment

  • Deploy across 2-3 availability zones
  • Use load balancers for distribution
  • Database replication across AZs
  • Automatic failover configuration

Multi-Region Deployment

  • Active-active or active-passive
  • DNS-based routing (Route53, Traffic Manager)
  • Data replication strategy
  • Disaster recovery procedures

Resilience Patterns

  • Circuit breakers for external dependencies
  • Retry with exponential backoff
  • Bulkhead isolation
  • Graceful degradation

Security Best Practices

Identity & Access

  • Principle of least privilege
  • Use IAM roles, not long-term credentials
  • Enable MFA for privileged accounts
  • Regular access reviews

Network Security

  • VPC/VNet isolation
  • Security groups as firewalls
  • Private subnets for backend services
  • VPN/Direct Connect for hybrid

Data Protection

  • Encryption at rest (KMS)
  • Encryption in transit (TLS)
  • Key rotation policies
  • Backup and recovery testing

Monitoring & Observability

Key Metrics

  • CPU, Memory, Disk utilization
  • Network throughput and latency
  • Error rates and types
  • Cost per service/team

Alerting Strategy

  • Set thresholds based on baselines
  • Alert on symptoms, not causes
  • Runbooks for each alert
  • Escalation paths defined

Reference Files

  • references/terraform_patterns.md - IaC patterns and examples
  • references/cost_optimization.md - Detailed cost reduction strategies

Integration with Other Skills

  • security-engineering - For security architecture
  • network-engineering - For network design
  • performance - For optimization strategies
  • devops-runbooks - For operational procedures