Agent skill · product strategy · aiskillstore
multi-cloud-architecture
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
Why this skill is useful
Provides specific decision frameworks and patterns for architecting multi-cloud systems that the AI wouldn't reliably generate on its own.
What it needs
About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Multi-Cloud Architecture Decision framework and patterns for architecting applications across AWS, Azure, and GCP. 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 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 D …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/multi-cloud-architecture--118247