Week11
Week 11: Introduction to Cloud Computing
Instructor: D. Marwa Chendeb El Rai
Course: Fall 2024 COMP101 IT and Innovation in Today's World
Overview of Cloud Computing
Definition: Cloud computing involves convenient, on-demand access to a shared pool of configurable computing resources (e.g., networks, servers, storage).
Characteristics: Discusses essential traits of cloud computing.
Cloud Service Models: Outlines the different service models available.
Deployment Models: Overview of deployment methods used in cloud computing.
Relation to Big Data: Examines the connection between big data and cloud computing.
Difference Between Big Data and Cloud Computing
Big Data: Focuses on managing large volumes of data.
Cloud Computing: Provides IT infrastructure as services.
What is Cloud Computing?
Description: A model that allows network access to shared computing resources, provisioned and released quickly with minimal management.
NIST Definition: Specifies the five characteristics, three service models, and four deployment models crucial to cloud computing.
Enabling Technology: Virtualization
Traditional Stack vs. Virtualized Stack:
Traditional involves Hardware > OS > Apps.
Virtualization introduces a hypervisor layer that enables the creation of virtual servers.
Characteristics of Cloud Computing
On-Demand Self-Service: Users can access resources as needed without human intervention.
Example: Businesses scaling server capacity during high traffic.
Broad Network Access: Resources are reachable from any internet device.
Example: Accessing company applications remotely.
Resource Pooling: Providers pool resources for multiple customers, optimizing efficiency.
Example: Dynamic resource allocation in cloud environments.
Rapid Elasticity: Services can scale quickly based on demand.
Example: E-commerce site scaling for Black Friday sales.
Measured Service: Resource usage is monitored and controlled.
Example: Users billed based on their resource usage.
Security: Advanced measures are in place to safeguard data and applications.
Example: Use of encryption and firewalls.
Cloud Service Models - Comparison
Service Model Identification: Differentiate between IaaS, PaaS, SaaS regarding who manages specific components (applications, runtime, middleware, OS, etc.).
Cloud Service Models
1. Infrastructure as a Service (IaaS)
Provides virtual hardware resources over the internet.
Example: AWS EC2 for renting virtual servers.
Benefits:
Cost Savings
Scalability
Flexibility
Scenario: Renting servers vs. managing physical ones.
2. Platform as a Service (PaaS)
Enables development and management of applications without infrastructure overhead.
Examples: Google App Engine, Wix.
Comparison: Using PaaS simplifies application deployment versus building everything from scratch.
3. Software as a Service (SaaS)
Offers ready-to-use software via the internet on a subscription model.
Examples: Salesforce, Microsoft 365, YouTube.
Advantages for Businesses: Ideal for immediate software solutions without setup.
Cloud Service Delivery Models - Examples
SaaS: Office 365, YouTube.
PaaS: Google App Engine.
IaaS: AWS, Azure, Google Compute Engine.
Types of Cloud Computing Models
1. Public Cloud
Services offered over the internet to anyone paying for them.
Examples: Google Drive, Microsoft OneDrive.
2. Private Cloud
Dedicated to a single organization for better control.
Examples: Financial institutions managing sensitive data.
3. Hybrid Cloud
Combines public and private cloud capabilities.
Examples: Businesses using public clouds for non-sensitive operations but private clouds for critical data.
Main Cloud Providers
Market Share: AWS (32%), Microsoft Azure (23%), Google Cloud (10%).
AWS - Regions and Availability Zones
AWS has extensive global infrastructure with 108 Availability Zones.
Notable Regions: Middle East (Bahrain) and UAE, launched in 2019 and 2022 respectively.
Impact of Cloud Computing
Business Continuity: Ensures secure data backup.
Example: Operational continuity during disasters.
Collaboration: Enables real-time project collaboration from various locations.
Example: Tools like Google Workspace.
Cost Efficiency: Reduces need for physical hardware and IT staff.
Example: Startups utilizing cloud resources.
Flexibility and Scalability: Adapts resources to meet business needs.
Example: E-commerce scaling for seasonal traffic.
Cloud Computing in Different Fields
Psychology: Facilitates data storage and analysis for research.
Example: Behavioral data analysis.
Business: Uses for CRM and financial tools.
Example: Salesforce for customer interactions.
Biology: Supports genomic research.
Example: Computational power for genomic sequencing.
International Studies: Analyzes global data trends.
Example: Social media analysis for public opinion.
Arts and Media: Offers tools for digital content creation.
Example: Adobe Creative Cloud for artists.
Architecture: Assists in design and simulations.
Example: Autodesk for building simulations.