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Computer Science
Cloud Computing
Cloud Architecture and Services
1. Introduction to Cloud Computing
2. Core Architectural Components
3. Cloud Service Models
4. Cloud Architecture Design Principles
5. Modern Cloud Architecture Patterns
6. Cloud Governance and Management
Modern Cloud Architecture Patterns
Microservices Architecture
Microservices Principles
Service Decomposition
Decentralized Data Management
Independent Deployment
Fault Isolation
Service Communication
Synchronous Communication
Asynchronous Messaging
Event-Driven Patterns
Service Discovery
Service Registry
Dynamic Discovery Mechanisms
Load Balancing Integration
API Management
API Gateways
Request Routing
Rate Limiting
Security and Authentication
Data Management
Database per Service
Distributed Transactions
Event Sourcing
CQRS Pattern
Serverless Architecture
Function as a Service
Event Sources
Function Triggers
Stateless Function Design
Cold Start Optimization
Backend as a Service
Managed Authentication
Database as a Service
File Storage Services
Event-Driven Architecture
Event Sources
Event Processing Patterns
Event Streaming
Choreography vs. Orchestration
Cloud-Native Design
Twelve-Factor App Methodology
Codebase
Dependencies
Configuration
Backing Services
Build Release Run
Processes
Port Binding
Concurrency
Disposability
Dev/Prod Parity
Logs
Admin Processes
Container Orchestration
Container Lifecycle Management
Service Mesh
Auto-scaling
Self-healing Systems
DevOps Integration
Continuous Integration
Continuous Delivery
Continuous Deployment
Automated Testing
Infrastructure as Code
Data Architecture Patterns
Data Lakes
Raw Data Storage
Schema-on-Read
Data Cataloging
Data Governance
Data Warehouses
Structured Data Storage
ETL Processes
Analytical Querying
Data Modeling
Data Processing
Batch Processing
Stream Processing
Real-time Analytics
Lambda Architecture
Kappa Architecture
Business Intelligence
Data Visualization
Reporting Tools
Self-Service Analytics
AI and Machine Learning Architectures
ML Platform Services
Managed ML Services
Model Training Infrastructure
Model Hosting
Feature Stores
MLOps
Model Versioning
Automated Pipelines
Model Monitoring
A/B Testing
Model Retraining
AI/ML Workload Patterns
Training Workloads
Inference Workloads
Distributed Training
Edge AI Deployment
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4. Cloud Architecture Design Principles
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6. Cloud Governance and Management