- What is Cloud Computing
- Basic Concepts
- Deployment Models
- Service Models
- Pros & Cons of Cloud Computing
- Amazon Global Infrastructure
- AWS History & Application Areas
Cloud Computing is the on-demand delivery of IT resources via the internet with a pay-as-you-go pricing model. Instead of maintaining physical data centers, users can access resources (computing power, storage, databases) through cloud service providers.
- Providers (like AWS, Google) install servers with CPU, memory, storage disks, and network equipment.
- Service buyers deploy applications on the cloud, accessible either publicly or privately.
- Example: Google Colab for Jupyter Notebooks.
💡 Cloud Computing is for:
- Organizations of various sizes across industries for use cases like:
- Data Backup
- Disaster Recovery
- Email Solutions
- Software Development & Testing
- Big Data Analytics
Key components behind cloud computing:
- Deployment Models
- Service Models
Cloud deployment is defined by ownership, access, and purpose:
- Public Cloud 🌍: Accessible to everyone (e.g., AWS, Google).
- Private Cloud 🔐: Not internet-accessible, used by sectors like defense or banking.
- Hybrid Cloud 🌐: Combination of public and private; e.g., public application with a private database.
- Community Cloud 👥: Shared among multiple organizations (e.g., HEC cloud for universities).
- Multi-cloud 🖥️: Utilizes multiple cloud providers simultaneously.
Defines levels of control, management, and flexibility:
- Infrastructure as a Service (IaaS) 🏗️: Provides basic setup for cloud, with the highest flexibility and control.
- Platform as a Service (PaaS) 🛠️: Manages infrastructure, allowing users to focus on app deployment.
- Software as a Service (SaaS) 📲: Complete product managed by the provider (e.g., Google Workspace).
- Agility 🚀: Innovate quickly with various services.
- Elasticity 📈: Scale resources up/down as needed.
- Cost Savings 💰: Pay only for what you use.
- Global Deployment 🌐: Launch in new regions swiftly.
- Disaster Recovery 🔄: Enhanced security and multi-location backup.
- Limited Control 🛑: Providers manage the infrastructure.
- Slower Backups 🐢: Over-the-internet backups may lag.
- Internet Dependency 📶: Requires a stable internet connection.
- Bandwidth Constraints 📉: Heavy internet use can affect performance.
AWS provides cloud computing platforms via a network of server farms, delivering 200+ services globally. AWS offers multiple regions and availability zones to enhance resilience and performance.
- Regions 📍: Physical clusters of data centers (e.g., us-east-1, eu-west-3).
- Availability Zones (AZs) 🗂️: Isolated data centers for failover.
- Data Centers 🏢: Physical setups of AWS cloud.
- Edge Locations 🛰️: Temporary caching areas to reduce latency.
Factors:
- Compliance ✅: Data governance.
- Proximity 📏: Nearer to customers.
- Available Resources 🛠️: Services may vary by region.
- Pricing 💲: Varies by region.
- Compute (EC2, Lambda, etc.)
- Database (Aurora, DynamoDB)
- Machine Learning (SageMaker, DeepComposer)
- IoT (FreeRTOS, IoT Analytics)
- Prediction 📈: 65.9% of app software spending to go cloud-based by 2025.
- Recognition 🌟: AWS named leader in 2022 Magic Quadrant for Cloud Infrastructure and Platform Services.
- Define cloud computing and its importance.
- List and explain the cloud deployment models.
- What are the service models in cloud computing, and what levels of control do they offer?
- Discuss the benefits of cloud computing for modern businesses.
- What are the main disadvantages of cloud storage?
- Explain the infrastructure of Amazon Web Services (AWS).
- How does AWS ensure data redundancy and reliability across regions?
- Discuss the factors to consider when choosing an AWS region.
- What predictions has Gartner made about cloud spending in the future?