# Design Resilient Multi-Cloud Architectures

Choosing services and operating models across cloud providers creates portability, resilience, and cost tradeoffs. This skill provides structured comparisons, architecture patterns, and migration guidance.

## Install

```bash
npx skillstore add sickn33/multi-cloud-architecture
```

## Metadata

- Status: approved
- Slug: sickn33-multi-cloud-architecture
- Skillstore revision: r2
- Version status: missing
- Tree hash: 744eabc5e026ffbf932e5ba736ab79424a645fac09411f722f6f3e5bb1ab6ac4
- Author: sickn33
- GitHub username: sickn33
- License: MIT
- Repository: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/multi-cloud-architecture
- Ref: 81e05e636292629114b76cbb3922fbe57672fc02
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands
- Quality score: 78
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/sickn33-multi-cloud-architecture
- Manifest: https://skillstore.pages.dev/api/skills/sickn33-multi-cloud-architecture/manifest

## Capabilities

- Compares common compute, storage, database, cache, and container services across AWS, Azure, and GCP.
- Explains four multi-cloud patterns for disaster recovery, service selection, geographic distribution, and provider abstraction.
- Recommends portable technologies such as Kubernetes, PostgreSQL, Kafka, Redis, Prometheus, and Terraform.
- Organizes cloud migration into assessment, pilot, migration, and optimization phases.
- Identifies pricing factors and cost optimization practices across the three providers.

## Use Cases

- Plan a Cloud Migration: Create phased migration options and compare equivalent target services for an existing application.
- Design Cross-Cloud Recovery: Define a secondary-cloud recovery approach with replication, failover, monitoring, and testing considerations.
- Evaluate Provider Portability: Identify managed-service dependencies and select practical abstraction layers for a new product.

## Prompt Templates

### Compare Cloud Services

```
Compare AWS, Azure, and GCP services for [workload]. Include compute, storage, database, and operational tradeoffs.
```

### Choose a Multi-Cloud Pattern

```
Recommend a multi-cloud pattern for [business goal]. Consider availability, portability, team skills, compliance, and cost.
```

### Build a Migration Roadmap

```
Create a phased migration roadmap from [current provider] to [target model]. Include dependencies, pilot scope, validation, rollback, and optimization.
```

### Review an Architecture

```
Review this architecture: [description]. Identify provider coupling, failure modes, data transfer risks, recovery gaps, cost drivers, and validation steps.
```

## Limitations

- It provides architecture guidance, not deployable infrastructure or provider-specific configuration.
- Service mappings and pricing require validation against current provider documentation.
- It does not assess an environment without workload, compliance, latency, budget, and recovery requirements.
- The packaged skill includes only overview guidance; its referenced detail files are not included.

## Best Practices

- Define recovery, compliance, latency, portability, and cost requirements before selecting providers.
- Test failover, data consistency, observability, and rollback under realistic conditions.
- Validate service capabilities, regional availability, quotas, and pricing with current provider documentation.

## Anti Patterns

- Do not adopt multiple providers without a measurable availability, regulatory, geographic, or commercial requirement.
- Do not assume similarly named services have equivalent behavior, limits, security controls, or pricing.
- Do not hide provider differences behind abstractions that prevent access to required managed capabilities.

## Security Audit

- Audited at: 2026-08-04T15:13:18.67\+00:00
- Summary: All nine static findings are false positives caused by Markdown inline-code markers or fenced architecture diagrams. No executable commands, prompt injection, data exfiltration, or other semantic security risks were found.

## Stats

- Views: 113
- Downloads: 11
- Favorites: 0
- Popularity score: 0