wshobson/multi-cloud-architecture
plugins/cloud-infrastructure/skills/multi-cloud-architecture/SKILL.md
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, GCP, and OCI. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
$ install --global
skillsauthnpx skillsauth add wshobson/agents multi-cloud-architectureInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 25, 2026, 11:49 AM6.1s3 files scanned
SKILL.md
- name:
- multi-cloud-architecture
- description:
- Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, GCP, and OCI. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
Multi-Cloud Architecture
Decision framework and patterns for architecting applications across AWS, Azure, GCP, and OCI.
Purpose
Design cloud-agnostic architectures and make informed decisions about service selection across cloud providers.
When to Use
- Design multi-cloud strategies
- Migrate between cloud providers
- Select cloud services for specific workloads
- Implement cloud-agnostic architectures
- Optimize costs across providers
Cloud Service Comparison
Compute Services
| AWS | Azure | GCP | OCI | Use Case | | ------- | ------------------- | --------------- | ------------------- | ------------------ | | EC2 | Virtual Machines | Compute Engine | Compute | IaaS VMs | | ECS | Container Instances | Cloud Run | Container Instances | Containers | | EKS | AKS | GKE | OKE | Kubernetes | | Lambda | Functions | Cloud Functions | Functions | Serverless | | Fargate | Container Apps | Cloud Run | Container Instances | Managed containers |
Storage Services
| AWS | Azure | GCP | OCI | Use Case | | ------- | --------------- | --------------- | -------------- | -------------- | | S3 | Blob Storage | Cloud Storage | Object Storage | Object storage | | EBS | Managed Disks | Persistent Disk | Block Volumes | Block storage | | EFS | Azure Files | Filestore | File Storage | File storage | | Glacier | Archive Storage | Archive Storage | Archive Storage | Cold storage |
Database Services
| AWS | Azure | GCP | OCI | Use Case | | ----------- | ---------------- | ------------- | ------------------- | --------------- | | RDS | SQL Database | Cloud SQL | MySQL HeatWave | Managed SQL | | DynamoDB | Cosmos DB | Firestore | NoSQL Database | NoSQL | | Aurora | PostgreSQL/MySQL | Cloud Spanner | Autonomous Database | Distributed SQL | | ElastiCache | Cache for Redis | Memorystore | OCI Cache | Caching |
Reference: See references/service-comparison.md for complete comparison
Multi-Cloud Patterns
Pattern 1: Single Provider with DR
- Primary workload in one cloud
- Disaster recovery in another
- Database replication across clouds
- Automated failover
Pattern 2: Best-of-Breed
- Use best service from each provider
- AI/ML on GCP
- Enterprise apps on Azure
- Regulated data platforms on OCI
- General compute on AWS
Pattern 3: Geographic Distribution
- Serve users from nearest cloud region
- Data sovereignty compliance
- Global load balancing
- Regional failover
Pattern 4: Cloud-Agnostic Abstraction
- Kubernetes for compute
- PostgreSQL for database
- S3-compatible storage (MinIO)
- Open source tools
Cloud-Agnostic Architecture
Use Cloud-Native Alternatives
- Compute: Kubernetes (EKS/AKS/GKE/OKE)
- Database: PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL/MySQL HeatWave)
- Message Queue: Apache Kafka or managed streaming (MSK/Event Hubs/Confluent/OCI Streaming)
- Cache: Redis (ElastiCache/Azure Cache/Memorystore/OCI Cache)
- Object Storage: S3-compatible API
- Monitoring: Prometheus/Grafana
- Service Mesh: Istio/Linkerd
Abstraction Layers
Application Layer
↓
Infrastructure Abstraction (Terraform)
↓
Cloud Provider APIs
↓
AWS / Azure / GCP / OCI
Cost Comparison
Compute Pricing Factors
- AWS: On-demand, Reserved, Spot, Savings Plans
- Azure: Pay-as-you-go, Reserved, Spot
- GCP: On-demand, Committed use, Preemptible
- OCI: Pay-as-you-go, annual commitments, burstable/flexible shapes, preemptible instances
Cost Optimization Strategies
- Use reserved/committed capacity (30-70% savings)
- Leverage spot/preemptible instances
- Right-size resources
- Use serverless for variable workloads
- Optimize data transfer costs
- Implement lifecycle policies
- Use cost allocation tags
- Monitor with cloud cost tools
Reference: See references/multi-cloud-patterns.md
Migration Strategy
Phase 1: Assessment
- Inventory current infrastructure
- Identify dependencies
- Assess cloud compatibility
- Estimate costs
Phase 2: Pilot
- Select pilot workload
- Implement in target cloud
- Test thoroughly
- Document learnings
Phase 3: Migration
- Migrate workloads incrementally
- Maintain dual-run period
- Monitor performance
- Validate functionality
Phase 4: Optimization
- Right-size resources
- Implement cloud-native services
- Optimize costs
- Enhance security
Best Practices
- Use infrastructure as code (Terraform/OpenTofu)
- Implement CI/CD pipelines for deployments
- Design for failure across clouds
- Use managed services when possible
- Implement comprehensive monitoring
- Automate cost optimization
- Follow security best practices
- Document cloud-specific configurations
- Test disaster recovery procedures
- Train teams on multiple clouds
Related Skills
terraform-module-library- For IaC implementationcost-optimization- For cost managementhybrid-cloud-networking- For connectivity
Related Skills
wshobson/hermes-tweet
tools
VerifiedTrustedCommunity
Install and operate Hermes Tweet, a Hermes Agent plugin for X/Twitter research, timeline reading, tweet analysis, and approval-gated private or state-changing operations. Use this skill when installing Hermes Tweet, researching X/Twitter accounts, monitoring launch signals, investigating mentions, auditing giveaways, or preparing gated X operations. Use proactively when a Hermes Agent workflow needs current X/Twitter context. Requires XQUIK_API_KEY for read and action tools.
39,228SKILL.mdUpdated Jul 9, 2026
wshobson/avoid-ai-writing
testing
VerifiedTrustedCommunity
Audit and rewrite prose so it stops reading as machine-generated. Use this skill when asked to remove AI-isms, clean up AI writing, edit a draft for AI tells, audit a README, changelog, release note, PR description, or blog post for machine-sounding prose, or make text sound less like AI. Supports a detect-only mode, a rewrite mode, and an edit-in-place mode, with optional voice and context profiles.
38,906SKILL.mdUpdated Aug 19, 2026
wshobson/python-design-patterns
development
VerifiedTrustedCommunity
Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance. Use this skill when designing a new service or component from scratch and choosing how to layer responsibilities, when refactoring a God class or monolithic function that has grown too large, when deciding whether to add a new abstraction or live with duplication, when evaluating a pull request for structural issues like tight coupling or leaking internal types, when choosing between inheritance and composition for a new class hierarchy, or when a codebase is becoming hard to test because of entangled I/O and business logic.
38,906SKILL.mdUpdated Apr 25, 2026
wshobson/prompt-engineering-patterns
development
VerifiedTrustedCommunity
This skill should be used when the user asks to "optimize a prompt", "improve prompt performance", "design a prompt template", "write better prompts", "debug prompt issues", "use chain-of-thought", "structured prompting", "few-shot prompting", or wants to apply advanced prompt engineering patterns for production LLM applications.
38,906SKILL.mdUpdated Apr 25, 2026