AWS vs. GCP vs. Azure
The Multi-Billion-Dollar Cloud Decision
AWS leads in breadth. GCP leads in AI/ML. Azure leads in enterprise integration. Your stack determines your cloud.
📊 Scoring Matrix
31% (dominant leader)
GCP 12% / Azure 25%
SageMaker + Bedrock
Vertex AI (GCP leads)
Strong but complex
Azure: M365 integration
EKS (solid)
GKE (best-in-class)
Complex, negotiable
GCP sustained discounts
Largest certified base
Smaller but growing
📋 Executive Summary
AWS for breadth and talent. GCP for AI/ML and Kubernetes. Azure for Microsoft shops. Multi-cloud adds complexity.
Cloud costs typically 20-40% of engineering budget. Wrong cloud can add 15-30% overhead in migration costs.
🎯 Decision Framework
- ✓ Broadest service catalog needed
- ✓ Largest talent pool required
- ✓ Startup-friendly free tier
- ✓ Most mature ecosystem
- ✓ AI/ML-first workloads (GCP)
- ✓ Microsoft enterprise ecosystem (Azure)
- ✓ Best Kubernetes experience (GCP)
- ✓ Sustained-use discount model
Already on Microsoft? Azure. Heavy AI/ML? GCP. Everything else? AWS. Multi-cloud only if regulatory requires it.
🌐 Market Context
Cloud infrastructure market reached 270B in 2024. AWS, Azure, and GCP control 67% combined.
Multi-cloud adoption at 89% but intentional multi-cloud (vs accidental) only 35%. GCP gaining in AI-first companies.
🛠️ Related Tools
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