Multi cloud architecture

Skill Ghosteken/agent-harness/skills/multi-cloud-architecture

Decision framework and patterns for architecting applications across AWS, Azure, and GCP.From its SKILL.md

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npx -y skills add Ghosteken/agent-harness --skill multi-cloud-architecture

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SKILL.md

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Multi-Cloud Architecture

Decision framework and patterns for architecting applications across AWS, Azure, and GCP.

Do not use this skill when

The task is unrelated to multi-cloud architecture
You need a different domain or tool outside this scope

Instructions

Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.

Purpose

Design cloud-agnostic architectures and make informed decisions about service selection across cloud providers.

Use this skill when

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	Use Case
EC2	Virtual Machines	Compute Engine	IaaS VMs
ECS	Container Instances	Cloud Run	Containers
EKS	AKS	GKE	Kubernetes
Lambda	Functions	Cloud Functions	Serverless
Fargate	Container Apps	Cloud Run	Managed containers

Storage Services

AWS	Azure	GCP	Use Case
S3	Blob Storage	Cloud Storage	Object storage
EBS	Managed Disks	Persistent Disk	Block storage
EFS	Azure Files	Filestore	File storage
Glacier	Archive Storage	Archive Storage	Cold storage

Database Services

AWS	Azure	GCP	Use Case
RDS	SQL Database	Cloud SQL	Managed SQL
DynamoDB	Cosmos DB	Firestore	NoSQL
Aurora	PostgreSQL/MySQL	Cloud Spanner	Distributed SQL
ElastiCache	Cache for Redis	Memorystore	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
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)
Database: PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL)
Message Queue: Apache Kafka (MSK/Event Hubs/Confluent)
Cache: Redis (ElastiCache/Azure Cache/Memorystore)
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

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

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

Reference Files

references/service-comparison.md - Complete service comparison
references/multi-cloud-patterns.md - Architecture patterns

Related Skills

hybrid-cloud-networking - For connectivity

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most architecture codebase skills give in ~1.2k tokens

Counted across 858 of the 1,304 authors here whose files we hold, read 2026-09-06

Apply the deletion test to identify shallow modulesin 32 of 858, across 31 files
Read domain glossary and ADRs before exploringin 22 of 858, across 19 files
Use Tailwind and Mermaid via CDN for reportsin 21 of 858, across 18 files
Document architecture decision recordsin 20 of 858, across 12 files
Offer to record ADRs for rejected candidatesin 17 of 858, across 14 files
Limit primary navigation to four to seven itemsin 17 of 858, across 7 files
Write HTML report to the system temp directoryin 17 of 858, across 14 files
Read product marketing context before asking questionsin 16 of 858, across 6 files
Use Mermaid graph TD for visual sitemapsin 15 of 858, across 5 files
Ensure every page has at least one internal linkin 15 of 858, across 5 files
Use ASCII tree format for page hierarchy draftsin 15 of 858, across 5 files
Enforce lowercase URLs with hyphensin 15 of 858, across 5 files

Said here and by no other author read

Implement CI/CD pipelines
Design for failure across clouds
Implement comprehensive monitoring
Automate cost optimization
Document cloud-specific configurations
Test disaster recovery procedures

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.