%%{init: {'theme': 'base', 'themeVariables': { 'primaryColor': '#2C3E50', 'primaryTextColor': '#fff', 'primaryBorderColor': '#16A085', 'lineColor': '#16A085', 'secondaryColor': '#E67E22', 'tertiaryColor': '#7F8C8D', 'fontSize': '14px'}}}%%
flowchart LR
A[Fundamentals] --> B[Service Models]
B --> C[Deployment Models]
C --> D[Security]
D --> E[Production]
E --> F[Platforms]
style A fill:#2C3E50,stroke:#16A085,color:#fff
style B fill:#16A085,stroke:#2C3E50,color:#fff
style C fill:#E67E22,stroke:#16A085,color:#fff
style D fill:#2C3E50,stroke:#16A085,color:#fff
style E fill:#16A085,stroke:#2C3E50,color:#fff
style F fill:#E67E22,stroke:#16A085,color:#fff
269 Cloud Computing for IoT
269.1 Overview
Cloud Computing has become a fundamental enabler for Internet of Things (IoT) systems, providing the scalable infrastructure needed to store, process, and analyze massive volumes of sensor data. The combination of IoT’s distributed sensing capabilities with cloud computing’s centralized processing power creates powerful applications across domains.
This chapter series explores cloud computing fundamentals, service models, deployment strategies, security considerations, and their specific application to IoT architectures.
NoteIn One Sentence
Cloud computing provides virtually unlimited scale and powerful analytics for IoT, but introduces latency and connectivity dependencies that make it unsuitable for real-time control.
Remember this rule: Use cloud for storage, analytics, and management; use edge for real-time decisions and offline operation.
269.2 Chapter Series
This comprehensive topic has been organized into six focused chapters:
269.2.1 1. Cloud Computing Fundamentals
What you’ll learn:
- NIST definition and five essential characteristics
- Evolution from grid computing to modern cloud
- Why IoT systems benefit from cloud infrastructure
Key topics: On-demand self-service, rapid elasticity, measured service, resource pooling
269.2.2 2. Cloud Service Models
What you’ll learn:
- Compare IaaS, PaaS, and SaaS for IoT applications
- Choose the right service model for your team and requirements
- Understand serverless vs. container-based architectures
Key topics: Infrastructure as a Service, Platform as a Service, Software as a Service, microservices
269.2.3 3. Cloud Deployment Models
What you’ll learn:
- Evaluate public, private, hybrid, and community clouds
- Design hybrid architectures for compliance and scalability
- Decide where to process data based on latency, cost, and security
Key topics: Public cloud, private cloud, hybrid cloud, edge-cloud integration
269.2.4 4. Cloud Security for IoT
What you’ll learn:
- Implement identity and access management (IAM)
- Apply shared responsibility model across service types
- Secure device credentials with per-device certificates
Key topics: Authentication, authorization, X.509 certificates, multi-region security
269.2.5 5. Production Cloud Deployment
What you’ll learn:
- Transition from development to production-grade infrastructure
- Optimize costs for cloud IoT at scale
- Handle cloud platform rate limits and throttling
Key topics: Cost optimization, throttling, auto-scaling, production readiness
269.2.6 6. Cloud Platforms and Message Queues
What you’ll learn:
- Compare AWS IoT Core, Azure IoT Hub, and alternatives
- Select appropriate message queue technologies
- Calculate capacity requirements for IoT deployments
Key topics: AWS IoT, Azure IoT, MQTT brokers, Kafka, capacity planning
269.3 Learning Path
269.4 Quick Reference
| Topic | Best Chapter |
|---|---|
| “What is cloud computing?” | Fundamentals |
| “Should I use AWS or Azure?” | Platforms |
| “IaaS vs PaaS vs SaaS?” | Service Models |
| “Public vs private cloud?” | Deployment Models |
| “How do I secure IoT devices?” | Security |
| “How do I handle 100K devices?” | Production |
| “Which message broker should I use?” | Platforms |