History of Computing Milestones
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Questions and Answers

Which decade saw the introduction of time-sharing on mainframes?

  • 1980s
  • 1990s
  • 1970s
  • 1960s (correct)

The rise of the Internet and Application Service Providers (ASPs) occurred in the 1980s.

False (B)

What is a precursor to Software as a Service (SaaS)?

Application Service Providers (ASPs)

The era in which the Dot-Com Boom and Bust occurred is referred to as the __________.

<p>Late 1990s to Early 2000s</p> Signup and view all the answers

Match the following milestones with their decades:

<p>Time-sharing on Mainframes = 1960s Rise of the Internet and ASPs = 1990s Dot-Com Boom and Bust = Late 1990s - Early 2000s Virtual Machines = 1970s</p> Signup and view all the answers

Which company launched AWS in 2006, marking the start of modern cloud computing?

<p>Amazon (D)</p> Signup and view all the answers

The cloud computing era began in the 2010s with the launch of significant platforms.

<p>False (B)</p> Signup and view all the answers

What capabilities have driven the further acceleration of cloud adoption during the 2010s?

<p>Scalability, cost-effectiveness, and data processing capabilities.</p> Signup and view all the answers

Companies like Amazon, Alibaba, and Shopify leverage the cloud to manage millions of online __________.

<p>transactions</p> Signup and view all the answers

Match each industry with its corresponding use case:

<p>E-commerce = Website and platform hosting Education = Management Systems (LMS)</p> Signup and view all the answers

Flashcards

Cloud Computing

Using internet-based remote resources instead of local servers.

Time-sharing on Mainframes

Early shared computing on expensive mainframe computers.

Virtual Machines (VMs)

Software that creates the illusion of multiple isolated computing environments on one physical machine.

Application Service Providers (ASPs)

Early providers of hosted software apps over the web.

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SaaS

Software as a Service (cloud-based software applications)

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Dot-com Boom/Bust

Period of rapid growth and subsequent collapse of many internet-based businesses in late 1990s - early 2000s

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Modern Cloud Computing

Cloud computing that began with Amazon Web Services (AWS) in 2006 and evolved through phases including mobile and big data explosion, AI, ML, and edge computing, impacting numerous industries.

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Amazon Web Services (AWS)

A pioneering company that launched cloud computing services, marking the start of the modern cloud era by offering on-demand services for storage and processing.

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Cloud Era (2008-2010)

The period where other major players like Google App Engine and Microsoft Azure entered the cloud market, intensifying competition and innovation.

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Mobile & Big Data Explosion (2010s)

A period of significant cloud adoption due to growing needs for scalability, cost-effectiveness, and handling increased data volume.

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AI/ML & Edge Computing

The cloud's next wave of technological developments, focusing on Artificial Intelligence (AI), Machine Learning (ML) and computing at the edge using the cloud.

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E-commerce Use Case

E-commerce companies (like Amazon, Alibaba, and Shopify) use cloud services for website hosting to handle high transaction volumes by dynamically scaling resources.

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Education LMS Use Case

Learning Management Systems (LMS) like Moodle, Canvas, and Blackboard utilize cloud services for online learning platforms to provide anytime-anywhere access for students and educators.

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Use Cases

Applications or instances where cloud computing improves efficiency and accessibility, like e-commerce platforms and learning management systems.

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Study Notes

Cloud Computing & IoT

  • Course 1: Introduction to Cloud Computing
  • Instructor: Pr Meriem Belguidoum
  • Semester: 2024/2025, Semester 3
  • Topic: Cloud Computing
  • Subtopics: History, Definition, Why use cloud computing, Cloud Deployment Models, Cloud Service Models, Comparison between Cloud Providers, Cloud Computing & IoT
  • Course Outline:
    • Some History
    • What is Cloud Computing?
    • Why using cloud computing?
    • The features of Cloud Computing
    • Cloud deployment models
    • Cloud service models
    • Comparison between some Cloud providers
    • Cloud computing & IoT
  • History
    • 1960s: Time-sharing on mainframes: Early shared computing, maximizing expensive resource use.
    • 1970s: Virtual Machines (VMs): Foundation for multiple isolated environments on a single physical machine.
    • 1990s: Rise of the Internet & ASPs (Application Service Providers): Hosted software applications offered over the web, a precursor to SaaS.
    • Late 1990s - Early 2000s: Dot-Com Boom & Bust: Highlighted the limitations of traditional IT and the need for flexible, scalable solutions.
    • 2006: Amazon launches AWS: Marks the beginning of modern cloud computing with on-demand services for storage and computing power.
    • 2008-2010: Google App Engine & Microsoft Azure Launch: Major players enter the market, increasing competition and driving innovation.
    • 2010s: Mobile & Big Data Explosion: Further accelerates cloud adoption due to the need for scalability, cost-effectiveness, and data processing capabilities.
    • Present: Serverless, AI/ML, Edge computing emerge: The cloud continues to evolve, enabling new possibilities and transforming industries.

Real-world Use Cases

  • E-commerce: Website and platform hosting, handling millions of online transactions with dynamic resource scaling to accommodate traffic surges.
  • Education: Learning Management Systems (LMS) like Moodle, Canvas, Blackboard, utilizing the cloud for online learning platforms. Students receive anytime, anywhere access.
  • Entertainment: Video and music streaming services like Netflix, Spotify, Disney+ relying on the cloud to stream multimedia content globally to ensure quality and minimal buffering.
  • Healthcare: Medical data storage and analysis, enabling secure storage and analysis of large volumes of medical data, facilitating personalized medicine, and research.
  • Finance: Online banking and algorithm trading, financial institutions leveraging the cloud to power secure and reliable online banking platforms.

What is Cloud Computing?

  • Definition (NIST): Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

Why Using Cloud Computing?

  • Traditional Approach Limitations: High costs, significant upfront investments in hardware, software, maintenance, high complexity requiring specialized technical skills, lack of flexibility to adapt to changing needs and peak demands, underutilized resources (servers often idle, wasting energy).
  • Real-world use case challenges: Handling website traffic surges during peak seasons, enabling seamless collaboration for remote teams across different locations and time zones.
  • Cloud Solutions: Elasticity, cloud resources scale up or down automatically, adjusting to changing traffic patterns. Cloud-based collaboration Platforms offer tools like Google Workspace and Microsoft 365.
  • Benefits: Cost-efficiency, improved performance, enhanced productivity, streamlined workflows, access to work anywhere, anytime.

Cloud Deployment Models

  • Public Cloud: Massive available space, easy scalability, recommended for software development and collaborative projects (e.g., AWS, Azure, Google Cloud).
  • Private Cloud: Resides behind a firewall, used by a single organization, recommended for businesses with stringent regulatory requirements.
  • Hybrid Cloud: Combines public and private clouds for seamless interaction; balancing big data analytics with strict data privacy regulations.
  • Community Cloud: Collaborative, multi-tenant platform shared by organizations with common interests, like research institutions, government agencies, or industry groups.

Cloud Service Models

  • IaaS (Infrastructure as a Service): The user has complete control over the physical and virtual environment, manages operating systems, applications, and data. (Examples: Amazon Web Services (AWS) - EC2, Microsoft Azure - Virtual Machines)
  • PaaS (Platform as a Service): Provides a complete platform for developing, testing, deploying, and managing applications without worrying about the underlying infrastructure. (Examples: Amazon Web Services (AWS) - Elastic Beanstalk, Microsoft Azure - App Service)
  • SaaS (Software as a Service): Software applications delivered over the internet. The user doesn't manage the underlying infrastructure, applications, or operating systems. (Examples: Google Workspace, Microsoft 365)

Comparison between Cloud Providers

  • AWS, Azure, GCP: Strengths, weaknesses, market position, strengths of each service for compute, networking, database, data analytics, machine learning, and other services.

Cloud Computing & IoT

  • Cloud as Engine for IoT: Stores and analyzes IoT devices' data safely and securely to offer insights in real-time.
  • Cloud Platforms for IoT Solutions: Offers tools and platforms for IoT solutions, such as connecting, monitoring, managing, and analyzing (e.g., AWS IoT, Google Cloud IoT Core, Azure IoT Hub).
  • IoT Data Analysis and Prediction: Utilizing machine learning services and APIs to find patterns in IoT data; automating actions for predictive, more efficient processes, especially related to equipment failures

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Description

Test your knowledge on the key milestones in computing history. This quiz covers significant developments from mainframe time-sharing to the Dot-Com Boom of the late 20th century. Match important events with their respective decades for a deeper understanding.

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