Design multi-cloud architectures using a decision framework

Multi cloud architecture

by wshobson · MIT license · ★ 39,857 on GitHub · updated Sep 21

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…

---
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

Overview

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

Manual install (npx, ZIP)

Claude Codenpx skills add wshobson/agents --skill multi-cloud-architecture -g -a claude-code

Claude Code (manual)

mkdir -p ~/.claude/skills && curl -sL https://codeload.github.com/wshobson/agents/tar.gz/4236bb91f839 \
  | tar -xz -C ~/.claude/skills --strip-components=4 agents-4236bb91f839/plugins/cloud-infrastructure/skills/multi-cloud-architecture

Windows (PowerShell)

New-Item -ItemType Directory -Force "$HOME\.claude\skills" | Out-Null; Invoke-WebRequest "https://m.agentalley.io/zip/fcc6516e079abdb5abdd/multi-cloud-architecture.zip" -OutFile "$env:TEMP\multi-cloud-architecture.zip"; Expand-Archive "$env:TEMP\multi-cloud-architecture.zip" -DestinationPath "$HOME\.claude\skills" -Force

Claude.ai / desktopDownload the ZIP and upload it under Settings → Capabilities → Skills.

Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

SKILL.md5.6 KB
references/2 files · 2.7 KB

Read the files here

wshobson/4236bb93 files

SKILL.md5.6 KB

SKILL.md

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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

terraform-module-library - For IaC implementation
cost-optimization - For cost management
hybrid-cloud-networking - For connectivity

1	---
2	name: multi-cloud-architecture
3	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.
4	---
5
6	# Multi-Cloud Architecture
7
8	Decision framework and patterns for architecting applications across AWS, Azure, GCP, and OCI.
9
10	## Purpose
11
12	Design cloud-agnostic architectures and make informed decisions about service selection across cloud providers.
13
14	## When to Use
15
16	- Design multi-cloud strategies
17	- Migrate between cloud providers
18	- Select cloud services for specific workloads
19	- Implement cloud-agnostic architectures
20	- Optimize costs across providers
21
22	## Cloud Service Comparison
23
24	### Compute Services
25
26	\| AWS \| Azure \| GCP \| OCI \| Use Case \|
27	\| ------- \| ------------------- \| --------------- \| ------------------- \| ------------------ \|
28	\| EC2 \| Virtual Machines \| Compute Engine \| Compute \| IaaS VMs \|
29	\| ECS \| Container Instances \| Cloud Run \| Container Instances \| Containers \|
30	\| EKS \| AKS \| GKE \| OKE \| Kubernetes \|
31	\| Lambda \| Functions \| Cloud Functions \| Functions \| Serverless \|
32	\| Fargate \| Container Apps \| Cloud Run \| Container Instances \| Managed containers \|
33
34	### Storage Services
35
36	\| AWS \| Azure \| GCP \| OCI \| Use Case \|
37	\| ------- \| --------------- \| --------------- \| -------------- \| -------------- \|
38	\| S3 \| Blob Storage \| Cloud Storage \| Object Storage \| Object storage \|
39	\| EBS \| Managed Disks \| Persistent Disk \| Block Volumes \| Block storage \|
40	\| EFS \| Azure Files \| Filestore \| File Storage \| File storage \|
41	\| Glacier \| Archive Storage \| Archive Storage \| Archive Storage \| Cold storage \|
42
43	### Database Services
44
45	\| AWS \| Azure \| GCP \| OCI \| Use Case \|
46	\| ----------- \| ---------------- \| ------------- \| ------------------- \| --------------- \|
47	\| RDS \| SQL Database \| Cloud SQL \| MySQL HeatWave \| Managed SQL \|
48	\| DynamoDB \| Cosmos DB \| Firestore \| NoSQL Database \| NoSQL \|
49	\| Aurora \| PostgreSQL/MySQL \| Cloud Spanner \| Autonomous Database \| Distributed SQL \|
50	\| ElastiCache \| Cache for Redis \| Memorystore \| OCI Cache \| Caching \|
51
52	Reference: See `references/service-comparison.md` for complete comparison
53
54	## Multi-Cloud Patterns
55
56	### Pattern 1: Single Provider with DR
57
58	- Primary workload in one cloud
59	- Disaster recovery in another
60	- Database replication across clouds
61	- Automated failover
62
63	### Pattern 2: Best-of-Breed
64
65	- Use best service from each provider
66	- AI/ML on GCP
67	- Enterprise apps on Azure
68	- Regulated data platforms on OCI
69	- General compute on AWS
70
71	### Pattern 3: Geographic Distribution
72
73	- Serve users from nearest cloud region
74	- Data sovereignty compliance
75	- Global load balancing
76	- Regional failover
77
78	### Pattern 4: Cloud-Agnostic Abstraction
79
80	- Kubernetes for compute
81	- PostgreSQL for database
82	- S3-compatible storage (MinIO)
83	- Open source tools
84
85	## Cloud-Agnostic Architecture
86
87	### Use Cloud-Native Alternatives
88
89	- Compute: Kubernetes (EKS/AKS/GKE/OKE)
90	- Database: PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL/MySQL HeatWave)
91	- Message Queue: Apache Kafka or managed streaming (MSK/Event Hubs/Confluent/OCI Streaming)
92	- Cache: Redis (ElastiCache/Azure Cache/Memorystore/OCI Cache)
93	- Object Storage: S3-compatible API
94	- Monitoring: Prometheus/Grafana
95	- Service Mesh: Istio/Linkerd
96
97	### Abstraction Layers
98
99	```
100	Application Layer
101	↓
102	Infrastructure Abstraction (Terraform)
103	↓
104	Cloud Provider APIs
105	↓
106	AWS / Azure / GCP / OCI
107	```
108
109	## Cost Comparison
110
111	### Compute Pricing Factors
112
113	- AWS: On-demand, Reserved, Spot, Savings Plans
114	- Azure: Pay-as-you-go, Reserved, Spot
115	- GCP: On-demand, Committed use, Preemptible
116	- OCI: Pay-as-you-go, annual commitments, burstable/flexible shapes, preemptible instances
117
118	### Cost Optimization Strategies
119
120	1. Use reserved/committed capacity (30-70% savings)
121	2. Leverage spot/preemptible instances
122	3. Right-size resources
123	4. Use serverless for variable workloads
124	5. Optimize data transfer costs
125	6. Implement lifecycle policies
126	7. Use cost allocation tags
127	8. Monitor with cloud cost tools
128
129	Reference: See `references/multi-cloud-patterns.md`
130
131	## Migration Strategy
132
133	### Phase 1: Assessment
134
135	- Inventory current infrastructure
136	- Identify dependencies
137	- Assess cloud compatibility
138	- Estimate costs
139
140	### Phase 2: Pilot
141
142	- Select pilot workload
143	- Implement in target cloud
144	- Test thoroughly
145	- Document learnings
146
147	### Phase 3: Migration
148
149	- Migrate workloads incrementally
150	- Maintain dual-run period
151	- Monitor performance
152	- Validate functionality
153
154	### Phase 4: Optimization
155
156	- Right-size resources
157	- Implement cloud-native services
158	- Optimize costs
159	- Enhance security
160
161	## Best Practices
162
163	1. Use infrastructure as code (Terraform/OpenTofu)
164	2. Implement CI/CD pipelines for deployments
165	3. Design for failure across clouds
166	4. Use managed services when possible
167	5. Implement comprehensive monitoring
168	6. Automate cost optimization
169	7. Follow security best practices
170	8. Document cloud-specific configurations
171	9. Test disaster recovery procedures
172	10. Train teams on multiple clouds
173
174
175	## Related Skills
176
177	- `terraform-module-library` - For IaC implementation
178	- `cost-optimization` - For cost management
179	- `hybrid-cloud-networking` - For connectivity
180