Phase 5: Cloud 3.0 Concepts
Cloud 1.0 was about virtual machines. Cloud 2.0 was about microservices and DevOps. Cloud 3.0 is about AI-native infrastructure — distributed intelligence, edge computing, data sovereignty, and sustainable scale. This phase explores the emerging paradigms that are reshaping how we think about cloud architecture in the AI era.
What is Cloud 3.0?
The evolution from centralized data centers to intelligent, distributed, AI-native infrastructure — what changed, why it matters, and what comes next.
Start here →Edge AI & Federated Learning
Running AI at the network edge — on phones, sensors, and local servers — and federated learning, the technique that trains models without centralizing data.
Explore edge AI →Sovereign Cloud & AI Governance
Data residency requirements, national cloud initiatives, and the regulatory frameworks (GDPR, AI Act) shaping where and how AI can be built and deployed.
Learn governance →FinOps: Cloud Cost Optimization for AI
AI workloads are expensive. FinOps is the practice of making every cloud dollar count — spot instances, reserved capacity, autoscaling, and cost attribution for ML teams.
Optimize costs →Frequently Asked Questions
What will I learn here?
This page covers the core concepts and techniques you need to understand the topic and progress confidently to the next lesson.
How should I use this page?
Start with the overview, then follow the section links to deepen your understanding. Use the table of contents on the right to jump to specific sections.
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