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Technical Research

Multi-Cloud Architecturefor AI-Powered Platforms

Independent analysis of AWS, Google Cloud, Azure, and Oracle Cloud for building AI-powered creator platforms. Real cost comparisons, architecture patterns, and decision frameworks from an Oracle AI Architect.

Cost Comparison
Architecture Patterns
Real-World Analysis

Cloud Provider Comparison

Think of cloud providers like mixing consoles. Each has different strengths, but they all help you produce great work. Here's how they stack up.

AWS

Pricing Tier: Premium

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Strengths

  • Mature ecosystem
  • Most AI services
  • Best documentation
  • Largest community

Best For

Enterprise scale, mature ecosystem, maximum service selection

Weaknesses

  • • Complex pricing
  • • Steep learning curve
  • • Vendor lock-in patterns

AI Services

  • • SageMaker
  • • Bedrock (Claude/LLMs)
  • • Comprehend
  • • Rekognition

Compute

Serverless: Lambda

Containers: ECS/EKS

GPU: P4d/P5 instances

Database

Relational: RDS, Aurora

NoSQL: DynamoDB

Vector: OpenSearch, pgvector

Cache: ElastiCache

Networking

CDN: CloudFront

Load Balancer: ALB/NLB

DNS: Route 53

Estimated Monthly Costs

For a mid-sized AI creator platform (10K-50K monthly users)

Compute

$300-600

Storage

$100-200

Database

$400-800

AI Services

$400-900

Total Monthly Estimate$1,200 - $2,500

* Estimates based on moderate usage patterns. Actual costs vary with traffic, AI model usage, and storage needs.

Ideal Use Cases

Enterprise-scale SaaS platforms
ML pipelines with SageMaker
Global content delivery
Serverless microservices

Decision Framework

Like choosing gear for your studio, pick the cloud that serves your workflow best. Here's how to decide.

Cost-Focused

Bootstrap, indie hacker, or cost-sensitive startup

→ OCI for best price-performance

→ GCP for generous free tier

Ecosystem-Focused

Need maximum integrations and community support

→ AWS for largest ecosystem

→ GCP for AI/ML leadership

Enterprise-Focused

Corporate environment, compliance requirements

→ Azure for Microsoft integration

→ OCI for Oracle workloads

Innovation-Focused

Cutting-edge AI, rapid experimentation

→ GCP for latest AI models

→ AWS for SageMaker + Bedrock

Need help choosing? Every architecture decision is like mixing a track—balance the elements that serve your vision.

Get Architecture Consultation

This is independent technical research by Frank, Oracle AI Architect. Not endorsed by or representing Oracle, AWS, Google, or Microsoft.