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@24df162
by Seth Hobsonwshobson/agents40k stars
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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.

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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

  1. Use reserved/committed capacity (30-70% savings)
  2. Leverage spot/preemptible instances
  3. Right-size resources
  4. Use serverless for variable workloads
  5. Optimize data transfer costs
  6. Implement lifecycle policies
  7. Use cost allocation tags
  8. 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

  1. Use infrastructure as code (Terraform/OpenTofu)
  2. Implement CI/CD pipelines for deployments
  3. Design for failure across clouds
  4. Use managed services when possible
  5. Implement comprehensive monitoring
  6. Automate cost optimization
  7. Follow security best practices
  8. Document cloud-specific configurations
  9. Test disaster recovery procedures
  10. Train teams on multiple clouds

Related Skills

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

Source: SKILL.md on GitHub

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    The multi-cloud-architecture skill provides architectural guidance and service comparisons for major cloud providers. It contains no executable code, network operations, or security risks.

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Provenance

Signed by skilld at 24df162. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 days ago.

Activeupdated 7 months ago

Topics

  • multi-cloud
  • aws
  • azure
  • gcp
  • oci
  • architecture
  • infrastructure-as-code
  • kubernetes
  • cost-optimization
  • disaster-recovery

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What it does

Provides a decision framework and service comparison tables for architecting applications across AWS, Azure, GCP, and OCI. Covers compute, storage, and database service equivalents; multi-cloud patterns (best-of-breed, geographic distribution, disaster recovery); and cost optimization strategies for avoiding vendor lock-in.

Generated from the current SKILL.md.

Frequently asked

Does this skill cover all four cloud providers equally?
Yes. The skill provides service comparison tables and patterns for AWS, Azure, GCP, and OCI, with equivalent services mapped across each provider.
What's the primary output of using this skill?
A decision framework and architectural patterns for selecting cloud services, choosing between multi-cloud strategies (single provider with DR, best-of-breed, geographic distribution, or cloud-agnostic), and migrating workloads across providers.
Does this skill include infrastructure-as-code templates?
No. The skill documents patterns and best practices but references a separate terraform-module-library skill for IaC implementation.
Can this help me avoid vendor lock-in?
Yes. The skill describes a cloud-agnostic abstraction pattern using Kubernetes, PostgreSQL, S3-compatible storage, and open source tools to minimize provider-specific dependencies.
Does this address cost comparison between clouds?
Yes. The skill includes pricing factors for each provider, cost optimization strategies, and references a cost-optimization skill for deeper cost management.

Generated from the current SKILL.md. These answers refresh after source changes.