Cloud Computing Course Outline
I. Introduction to Cloud Computing
Overview of Cloud Computing
Definition and characteristics of cloud computing
Evolution and adoption of cloud technologies
Benefits and challenges of cloud computing
Cloud Service Models
Infrastructure as a Service (IaaS)
Platform as a Service (PaaS)
Software as a Service (SaaS)
Comparison of service models
Cloud Deployment Models
Public cloud, private cloud, hybrid cloud
Community cloud and multi-cloud strategies
Choosing the right deployment model for businesses
II. Cloud Infrastructure
Virtualization Technologies
Virtual machines (VMs) vs. containers (Docker, Kubernetes)
Hypervisors and virtualization management
Serverless computing and Function as a Service (FaaS)
Cloud Storage
Object storage vs. block storage
Cloud storage providers (Amazon S3, Google Cloud Storage, Azure Blob Storage)
Data durability, availability, and scalability
Networking in the Cloud
Virtual Private Cloud (VPC) and network isolation
Load balancing and auto-scaling
Content Delivery Networks (CDNs) for performance optimization
III. Cloud Security and Compliance
Cloud Security Fundamentals
Shared responsibility model
Identity and Access Management (IAM)
Data encryption and key management
Securing Cloud Applications
Secure coding practices
Web application firewall (WAF) and API security
Incident response and cloud forensics
Compliance and Governance
Regulatory compliance (GDPR, HIPAA, PCI DSS)
Auditing and monitoring in the cloud
Legal and ethical considerations
IV. Cloud Computing Platforms
Amazon Web Services (AWS)
Core services (EC2, S3, RDS, Lambda)
AWS Global Infrastructure
Cost management and pricing models
Microsoft Azure
Azure services (VMs, Blob Storage, Azure SQL Database)
Azure regions and availability zones
Integration with Microsoft ecosystem (Office 365, Active Directory)
Google Cloud Platform (GCP)
GCP core services (Compute Engine, Cloud Storage, BigQuery)
Google Cloud regions and network infrastructure
Machine learning and data analytics capabilities
V. Cloud Migration and Adoption Strategies
Cloud Migration Planning
Assessment of on-premises workloads
Lift-and-shift vs. re-architecting strategies
Risk assessment and mitigation
DevOps and Continuous Integration/Continuous Deployment (CI/CD)
Automating deployment pipelines in the cloud
Infrastructure as Code (IaC) with tools like Terraform or CloudFormation
Monitoring and logging for cloud-native applications
Optimizing Performance and Cost
Resource optimization and right-sizing
Cloud billing and cost management tools
Performance monitoring and scaling strategies
VI. Managing Cloud Services
Service Level Agreements (SLAs)
Understanding SLA terms and commitments
Monitoring and meeting SLA requirements
Negotiating SLAs with cloud service providers
Cloud Service Management
Cloud management platforms (CMPs)
Orchestration and automation tools (Ansible, Chef, Puppet)
Incident management and service desk integration
VII. Emerging Trends in Cloud Computing
Serverless Computing and Edge Computing
Functions as a Service (FaaS) and serverless architectures
Edge computing and IoT integration
Use cases and benefits in modern applications
Artificial Intelligence and Machine Learning in the Cloud
AI/ML services provided by cloud platforms
Training and deploying models in the cloud
Data analytics and predictive insights
VIII. Case Studies and Real-World Applications
Industry Use Cases
Case studies of cloud adoption in various industries (finance, healthcare, e-commerce)
Success stories and lessons learned
Challenges and solutions in implementing cloud solutions
IX. Ethical and Legal Considerations
Ethics in Cloud Computing
Data privacy and consumer rights
Ethical use of AI and machine learning
Transparency and accountability in cloud services
X. Practical Applications and Projects
Hands-On Labs and Exercises
Setting up cloud environments (AWS, Azure, GCP)
Deploying applications to the cloud
Implementing security controls and best practices
Capstone Project
Designing and deploying a scalable cloud application
Integrating multiple cloud services and APIs
Project presentation and evaluation