1. Project Review
1.1. Summary of Project
1.2. Timeline:
1.3. Budget:
1.4. Resources:
2. IaaS
2.1. on-demand access to computing ressources
2.1.1. AWS EC2
2.1.1.1. AWS Services
2.1.1.1.1. Networking and Security
2.1.1.1.2. Backup and Disaster Recovery
2.1.1.1.3. Scaling and Performance Optimization
2.1.1.1.4. Security and Compliance
2.1.1.2. Features
2.1.1.2.1. Instance Types
2.1.1.2.2. Networking Options
2.1.1.2.3. Storage Options
2.1.1.2.4. Operating Systems
2.1.2. Azure VMs
2.1.2.1. Custom images for deploying specialized workloads
2.1.2.2. Auto-scaling VM clusters based on demand
2.1.3. Google Compute Engine
2.1.3.1. Customizable VM instances
2.1.3.2. Automatic discounts based on usage without upfront payments
2.1.3.3. Automatically scale VM i
2.1.3.4. High-performance local disks for compute-heavy workloads
2.2. Scalability
2.3. Suitable for developers and IT professionals
2.4. Pay - as - you - go
2.5. Provides virtual resources
3. SaaS
3.1. Integration as a service
3.1.1. Amazon SQS
3.1.2. Oracle Service Bus (OSB)
3.2. Fully functional over the internet service provider manages all
3.2.1. Google Workspace
3.3. Features
3.3.1. Accessibility
3.3.1.1. Ease of access (Access from anywhere )
3.3.2. Subscription Model
3.3.2.1. Subscription-based pricing
3.3.2.1.1. Pay-per-use, subscription-based pricing
3.3.3. Multi-tenancy
3.3.3.1. Single application instance serving multiple customers
3.3.3.2. Data isolation and security for each tenant
3.4. Suitable for End users and businesses
3.5. Delivers software online, no installation needed
4. PaaS
4.1. Developers don't have to worry about hardware
4.2. Development flexibility
4.3. Usage-based pricing
4.4. Suitable for App developers and businesses
4.5. Offers a platform to engineer app.
4.6. Features
4.6.1. Application Deployment
4.6.1.1. Pre-built environments for quick startup
4.6.1.2. One-click app deployment
4.6.1.3. Automated scaling of applications
4.6.2. Development Frameworks
4.6.2.1. Built-in frameworks (Spring, Django)
4.6.2.2. Support for microservices and serverless architectures
4.6.3. Database Management
4.6.3.1. NoSQL databases
4.6.3.2. Fully managed relational databases ( MySQL, PostgreSQL)
4.7. Popular PaaS Providers
4.7.1. AWS Elastic Beanstalk
4.7.1.1. Automatic environment management
4.7.1.1.1. load balancing
4.7.1.1.2. scaling
4.7.1.1.3. monitoring
4.7.1.2. Integration with AWS services like S3, and CloudWatch
4.7.2. Google App Engine
4.7.2.1. Automatic scaling and load balancing
4.7.2.2. Integrated with Google Cloud services (BigQuery, Datastore)
4.7.3. Microsoft Azure App Service
4.7.3.1. Build, deploy, and scale web apps
4.7.3.2. Built-in support for CI/CD
4.7.3.3. Integration with Azure DevOps and GitHub