Claude-skill-registry cloud-architect
Senior Cloud Architect specializing in AWS, Azure, and GCP multi-cloud strategies with expertise in cost optimization, infrastructure design, and enterprise cloud migration. Use when designing cloud architecture, planning migrations, optimizing cloud costs, or implementing multi-cloud strategies.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/cloud-architect-skill" ~/.claude/skills/majiayu000-claude-skill-registry-cloud-architect-249af6 && rm -rf "$T"
manifest:
skills/data/cloud-architect-skill/SKILL.mdsource content
Cloud Architect
Purpose
Provides expertise in designing scalable, secure, and cost-effective cloud architectures across major providers. Handles infrastructure design, cloud migration planning, multi-cloud strategies, and cloud cost optimization.
When to Use
- Designing cloud-native architectures
- Planning cloud migration strategies
- Implementing multi-cloud or hybrid solutions
- Optimizing cloud costs and resource utilization
- Selecting cloud services and regions
- Designing disaster recovery solutions
- Setting up cloud governance and security
Quick Start
Invoke this skill when:
- Designing cloud-native architectures
- Planning cloud migration strategies
- Implementing multi-cloud or hybrid solutions
- Optimizing cloud costs and resource utilization
- Setting up cloud governance and security
Do NOT invoke when:
- Writing Terraform/IaC code (use terraform-engineer)
- Managing Kubernetes clusters (use kubernetes-specialist)
- Implementing CI/CD pipelines (use devops-engineer)
- Azure-specific infrastructure (use azure-infra-engineer)
Decision Framework
Cloud Provider Selection: ├── Enterprise with Microsoft stack → Azure ├── Startup/Web-native → AWS or GCP ├── ML/AI workloads → GCP or AWS ├── Data analytics focus → GCP BigQuery or AWS Redshift ├── Vendor lock-in concerns → Multi-cloud with K8s └── Regulated industry → Private cloud or hybrid Service Type Selection: ├── Stateless workloads → Serverless (Lambda, Functions) ├── Container workloads → Managed K8s (EKS, AKS, GKE) ├── Legacy applications → VMs (EC2, Compute Engine) └── Event-driven → Event services (EventBridge, Pub/Sub)
Core Workflows
1. Cloud Architecture Design
- Gather requirements and constraints
- Define availability and DR requirements
- Select appropriate services per tier
- Design network topology and security
- Plan for scalability and elasticity
- Document architecture decisions
- Estimate costs and optimize
2. Cloud Migration Planning
- Assess current infrastructure (6 Rs)
- Prioritize workloads for migration
- Design landing zone architecture
- Plan data migration strategy
- Define migration waves
- Create rollback procedures
- Plan cutover and validation
3. Cost Optimization
- Analyze current spending patterns
- Identify idle or underutilized resources
- Implement rightsizing recommendations
- Apply reserved/spot instances
- Set up cost monitoring and alerts
- Implement auto-scaling policies
Best Practices
- Design for failure with multi-AZ deployments
- Use managed services over self-managed when possible
- Implement least-privilege access controls
- Tag all resources for cost allocation
- Automate infrastructure with IaC
- Plan for 10x scale from day one
Anti-Patterns
| Anti-Pattern | Problem | Correct Approach |
|---|---|---|
| Lift-and-shift only | Misses cloud benefits | Refactor for cloud-native |
| Single AZ deployment | No fault tolerance | Multi-AZ or multi-region |
| No cost controls | Budget overruns | Set budgets and alerts |
| Hardcoded configs | Brittle infrastructure | Use parameter stores, IaC |
| Over-engineering | Unnecessary complexity | Start simple, evolve |