Cloud computing14 02 .pptx

What is Cloud?
The term Cloud refers to a Network or Internet. In other words, we can say that Cloud is something,
which is present at remote location. Cloud can provide services over public and private networks, i.e.,
LAN, WAN or VPN.
Applications such as e-mail, Web Conferencing, Customer Relationship Management execute on cloud.
Computing
Computing is any goal-oriented activity requiring, benefiting from, or creating computing
machinery. It includes the study and experimentation of algorithmic processes, and the
development of both hardware and software. Computing has scientific, engineering,
mathematical, technological, and social aspects.

Cloud Computing refers to Manipulating, Configuring, and Accessing the hardware and
software resources remotely. It offers online data storage, infrastructure, and application.
What is Cloud Computing?

More Definitions
Cloud Computing refers to the accessing and storing of data and providing services related to
computing over the internet. It is simply referred to as remote services on the internet managing and
accessing data online rather than any local drives. The data can be anything like images, videos,
audio, documents, files, etc.
Cloud Computing Service Providers:
Cloud computing is in huge demand so, big organizations providing services like Amazon
AWS, Microsoft Azure, Google Cloud, Alibaba Cloud, etc. are some Cloud Computing Service
Providers.

Pros and cons
PROS :
• It is easier to get back up in the cloud.
• It allows us easy and quick access to stored information anywhere and anytime.
• It allows us to access data via mobile.
• It reduces both hardware and Software costs, and it is easily maintainable.
• One of the biggest advantages of Cloud Computing is Database Security.
CONS :
• It requires a good internet connection.
• Users have limited control over the data.

Advantages of Cloud Computing
• Cost Saving
• Data Redundancy and Replication
• Ransomware/Malware Protection
• Flexibility
• Reliability
• High Accessibility
• Scalable
Disadvantages of Cloud Computing
• Internet Dependency
• Issues in Security and Privacy
• Data Breaches
• Limitations on Control

Centralized and distributed computing are two fundamental approaches to computing
system architecture. Each has its advantages and use cases.
Centralized Computing
In centralized computing, all computing resources (processing power, storage, and control)
are concentrated in a single system or data center.
Characteristics:
 Single Control Point: One main server or system manages all tasks.
 High Dependency: Users depend on a central server for computing and data access.
 Easier Management: Centralized updates, security, and maintenance.
 Limited Scalability: Performance bottlenecks may occur as demand increases.
 Potential Single Point of Failure: If the central system fails, the entire network can go
down.
Centralized vs. Distributed Computing

Examples of Centralized Computing:
Mainframe Computers: Large enterprises use centralized mainframes for transaction
processing.
Traditional Client-Server Architecture: Corporate databases and ERP systems hosted on
a single server.
Cloud Computing (Partially): Some cloud services operate on centralized data centers.
Centralized vs. Distributed Computing…

Distributed Computing
In distributed computing, multiple independent computers work together as a unified
system. Tasks and resources are spread across multiple machines or locations.
Characteristics:
 Decentralized Processing: Work is divided among multiple nodes.
 Fault Tolerance: If one node fails, others can continue operating.
 Scalability: Easily add more resources as demand grows.
 High Performance: Parallel processing speeds up computation.
 Complex Management: Requires efficient coordination between distributed nodes.

Examples of Distributed Computing:
Cloud Computing & Edge Computing: Workloads distributed across global data centers.
Blockchain Networks: Decentralized ledger systems (e.g., Bitcoin, Ethereum).
Content Delivery Networks (CDNs): Websites use distributed servers to optimize content
delivery.
Internet of Things (IoT): Smart devices process data at the edge rather than relying on a
central server.
Grid Computing: Scientific research projects use distributed computing to analyze big
data (e.g., SETI@home).

Which One to Choose?
Use centralized computing when security, control, and simplicity are priorities (e.g.,
enterprise systems, financial institutions).
Use distributed computing when scalability, fault tolerance, and performance are critical
(e.g., cloud services, IoT, AI, and big data applications).

During 1961, John MacCharty delivered his speech at MIT that “Computing Can be sold as a
Utility, like Water and Electricity.” According to John MacCharty, it was a brilliant idea.
 This is implemented by Salesforce.com in 1999.
 In 2002, Amazon started Amazon Web Services (AWS), Amazon provide storage, and
computation over the Internet.
 In 2006 Amazon launched Elastic Compute Cloud Commercial Service which was/is open
for Everybody to use.
 After that in 2009, Google Play also started providing Cloud Computing Enterprise
Applications as other companies will see the emergence of Cloud Computing they also started
providing their cloud services.
History of Cloud Computing

Client/Server Computing:
Before the advent of cloud computing, Client/Server
computing was the dominant approach. The server
side of this architecture served as the central location
for all software programs, data, and controls.
History of Cloud Computing…
Users connected to the server and obtained the necessary access permissions to access
specific data or run programs.
Networked computing was built on top of client/server computing, but it had drawbacks in
terms of resource efficiency and scalability.

Evolution of Distributed Computing:
The idea of distributed computing evolved as
computers grew increasingly networked. Multiple
computers could cooperate and share resources and
processing power thanks to distributed computing.
This model allowed for parallel processing and increased efficiency by dividing tasks
across various processors. The centralized approach underwent a dramatic change with the
advent of distributed computing, opening the door for more scalable and adaptable
computer structures.

The Concept of Cloud Computing:
Client/server and distributed computing paradigms served as the cornerstones for the
paradigm that eventually developed as cloud computing. The objective was to offer
network-based, primarily the Internet, on-demand access to shared computer resources
and services. The goal of cloud computing was to offer consumers flexible, scalable, and
economical access to computing resources, storage, and applications. It shifted the
emphasis to distant services and pay-as-you-go business models from local infrastructure
and ownership.

• First introduced in the 1950s to describe internet-related services
• It evolved from distributed computing to the modern technology
• Cloud computing allows users to access a wide range of services stored in the
cloud or on the Internet
Evolution of Cloud Computing…

Distributed Systems
• Composition of multiple independent systems but all of them are depicted as a single
entity to the users to share resources and also use them effectively and efficiently
• Distributed systems having characteristics such as scalability, concurrency, continuous
availability, heterogeneity, and independence in failures.
Main problem with this system was that all the systems were required to be present at the
same geographical location. To overcome this type of problem: Mainframe computing,
cluster computing, and grid computing

Mainframe Computing
• First came into existence in 1951
are highly powerful and reliable
computing machines
• Handling large data such as
massive input-output operations
• these increased the processing
capabilities of the system
But these were very expensive. To
reduce this cost, cluster computing
came as an alternative to
mainframe technology.

Cluster Computing
• In 1980s, cluster computing came as an
alternative to mainframe computing
• Each machine in the cluster was
connected to each other by a network with
high bandwidth.
• These were way cheaper than those
mainframe systems
• Equally capable of high computations
• New nodes could easily be added to the
cluster if it was required.
But the problem related to geographical
restrictions still pertained. To solve this, the
concept of grid computing was introduced.

Grid Computing
• In 1990s, the concept of grid computing
was introduced
• Different systems were placed at entirely
different geographical locations and these
all were connected via the internet
• These systems belonged to different
organizations and thus the grid consisted
of heterogeneous nodes
• But new problems emerged as the
distance between the nodes increased
The main problem which was encountered
was the low availability of high bandwidth
connectivity and with it other network
associated issues. Thus. cloud computing is
often referred to as “Successor of grid
computing”.

Cloud Computing
 Cloud Computing means storing and accessing the data and programs on remote
servers that are hosted on the internet instead of the computer’s hard drive or local
server.
 Cloud computing is also referred to as Internet-based computing, it is a technology
where the resource is provided as a service through the Internet to the user.
 The data that is stored can be files, images, documents, or any other storable
document.

Characteristics of Cloud Computing

Characteristics of Cloud Computing
 On-Demand Self-Services: Cloud computing services do not require any human
administrators, users themselves are able to provision, monitor and manage
computing resources as needed.
 Broad Network Access: The Computing services are generally provided over
standard networks and heterogeneous devices.
 Rapid Elasticity: The Computing services should have IT resources that can scale
out quickly and on a needed basis. Whenever the user requires services, it is
provided to him and scales out as soon as their requirement gets over.

 Resource pooling: The IT resources (e.g., networks, servers, storage, applications,
and services) are shared across multiple applications and occupants in an
uncommitted manner. Multiple clients are provided service from the same physical
resource.
 Measured service: The resource utilization is tracked for each application, it will
provide both the user and the resource provider with an account of what has been
used. This is done for various reasons like monitoring billing and effective use of
resources.
Characteristics of Cloud Computing…

 Multi-Tenancy: Cloud computing providers can support multiple tenants (users or
organizations) on a single set of shared resources.
 Virtualization: Cloud computing providers use virtualization technology to abstract
underlying hardware resources and present them as logical resources to users.
 Flexible Pricing Models: Cloud providers offer a variety of pricing models, including
pay-per-use, subscription-based, and spot pricing, allowing users to choose the option
that best suits their needs.
 Security: Cloud providers invest heavily in security measures to protect their users’
data and ensure the privacy of sensitive information.
Characteristics of Cloud Computing…

Difference between Cloud Computing and Traditional Computing
Aspect Cloud Computing Traditional Computing
Definition
Cloud Computing refers to delivery of different
services such as data and programs through
internet on different servers.
Traditional Computing refers to delivery of
different services on local server.
Infrastructure Location
Cloud Computing takes place on third-party
servers that is hosted by third-party hosting
companies.
Traditional Computing takes place on physical
hard drives and website servers.
Data Accessibility
Cloud Computing is ability to access data
anywhere at any time by user.
User can access data only on system in which data
is stored.
Cost Effectiveness
Cloud Computing is more cost effective as
compared to tradition computing as operation and
maintenance of server is shared among several
parties that in turn reduce cost of public services.
Traditional Computing is less cost effective as
compared to cloud computing because one has to
buy expensive equipment’s to operate and maintain
server.
User-Friendliness
Cloud Computing is more user-friendly as
compared to traditional computing because user
can have access to data anytime anywhere using
internet.
Traditional Computing is less user-friendly as
compared to cloud computing because data cannot
be accessed anywhere and if user has to access data
in another system, then he need to save it in
external storage medium.

Internet Dependency
Cloud Computing requires fast, reliable and
stable internet connection to access information
anywhere at any time.
Traditional Computing does not require any
internet connection to access data or
information.
Storage and Computing
Power
Cloud Computing provides more storage space
and servers as well as more computing power
so that applications and software run must
faster and effectively.
Traditional Computing provides less storage as
compared to cloud computing.
Scalability and Elasticity
Cloud Computing also provides scalability and
elasticity i.e., one can increase or decrease
storage capacity, server resources, etc.,
according to business needs.
Traditional Computing does not provide any
scalability and elasticity.
Maintenance and
Support
Cloud service is served by provider’s support
team.
Traditional Computing requires own team to
maintain and monitor system that will need a
lot of time and efforts.
Software Delivery Model
Software is offered as an on-demand service
(SaaS) that can be accessed through
subscription service.
Software in purchased individually for every
user and requires to be updated periodically.

Importance of Cloud Computing
The cloud delivers more flexibility and reliability, increased performance and efficiency,
and helps to lower IT costs. It also improves innovation, allowing organizations to achieve
faster time to market and incorporate AI and machine learning use cases into their strategies.
Cloud is Inexpensive :
Cloud computing helps in reducing a considerable amount of CAPEX (Capital
Expenditure) & OPEX (Operational Expenditures) an organization does not need to invest
in expensive hardware’s, storage devices, & software’s etc. and you only have to pay for the
resources you utilize.

• Cloud computing enables you to reduce and increase your resources
demands as per your requirements, e.g., if you have heavy traffic on your
site you can increase your resources and vice versa.
• Cloud computing gives you the flexibility to work from wherever you
want and whenever you want all you require is an internet connection.
Elasticity & flexibility

• Software updates and upgrades can be a painful thing cloud computing
simplifies it for you as all the software maintenance and upgrades are
looked after and regulated by your cloud service provider.
Auto Updating

Driving Factors Towards Cloud
Scalability and Flexibility: Cloud services offer scalability to easily adjust resources
based on demand, which is crucial for businesses needing to scale up or down rapidly.
Cost Efficiency: Cloud computing often reduces upfront infrastructure costs by shifting to
a pay-as-you-go model, minimizing the need for large capital expenditures on hardware.
Accessibility and Collaboration: Cloud enables easy access to data and applications from
anywhere with an internet connection, promoting collaboration and remote work
capabilities.
Security and Reliability: Major cloud providers invest heavily in security measures and
redundancies, often providing better security than many organizations can afford on their
own.

Driving Factors Towards Cloud…
Disaster Recovery and Business Continuity: Cloud services offer robust backup and
disaster recovery solutions, ensuring business continuity in case of unforeseen events.
Speed and Time-to-Market: Cloud infrastructure allows businesses to deploy
applications and services much faster compared to traditional on-premise setups.
Automatic Updates and Maintenance: Cloud providers handle software and security
updates automatically, reducing IT overhead and ensuring the latest features and
protections.
Global Reach and Performance Optimization: Cloud services have data centers across
multiple regions, allowing businesses to serve users worldwide with lower latency.

Internet of Things (IoT) Enablement: Cloud computing supports IoT ecosystems by
providing scalable storage, real-time analytics, and connectivity for smart devices.
Competitive Advantage: Businesses that leverage cloud technologies can innovate faster,
respond to market changes more efficiently, and gain an edge over competitors.
Green IT and Sustainability: Cloud data centers are often more energy-efficient than
traditional IT infrastructures, helping organizations reduce their carbon footprint.
Hybrid and Multi-Cloud Strategies: Organizations can use hybrid or multi-cloud setups to
optimize workloads, improve redundancy, and avoid vendor lock-in.

Innovation and Agility: Cloud platforms provide access to advanced technologies like AI,
machine learning, and big data analytics, enabling businesses to innovate faster and stay
competitive.
Regulatory Compliance and Governance: Many cloud providers offer compliance
certifications (e.g., GDPR, HIPAA, ISO 27001) to help businesses meet industry and
government regulations.
Workforce Mobility: With cloud solutions, employees can securely access applications and
data from anywhere, enhancing remote work productivity.

Edge Computing Support: Cloud providers enable edge computing, processing data
closer to the source for faster decision-making in applications like autonomous vehicles and
smart cities.
More storage:
Employees Better Work Life Balance:
These factors collectively drive organizations to adopt cloud computing as a strategic
advantage in today's digital landscape.

Workload patterns in the cloud refer to different ways applications consume cloud
resources based on demand, usage, and performance needs. Here are the main types of
cloud workload patterns:
Static Workload
• Predictable and consistent usage over time.
• Resources are provisioned once and do not change significantly, e.g., Corporate
websites, internal business applications.
Dynamic (Variable) Workload
• Demand fluctuates but follows a somewhat predictable pattern.
• Requires scaling up or down based on usage trends.
• Example: E-commerce websites with seasonal traffic spikes.
Types of Workload Patterns for the Cloud

Periodic Workload
• Workload usage follows a recurring pattern (e.g., daily, weekly, monthly).
• Can be scaled based on expected peaks and lows, e.g., Payroll processing, batch job
executions, financial report generation.
Spiky (Burst) Workload
• Unpredictable traffic spikes requiring rapid resource scaling.
• Needs an elastic cloud environment to handle demand surges, e.g., Ticket booking
systems, viral social media apps.

Predictable Bursting Workload
• Generally stable but experiences temporary bursts at known intervals.
• Can use auto-scaling to handle short-term demand increases, e.g., Online gaming
events, streaming services during primetime.
Unpredictable (On-Demand) Workload
• Sudden, unexpected spikes in demand with no clear pattern.
• Requires real-time scaling and efficient resource management, e.g., Breaking news
websites, emergency response systems.

Compute-Intensive Workload
• Requires high-performance computing (HPC) and large processing power.
• Typically uses GPU/CPU clusters for intensive calculations , e.g., Machine learning, AI
model training, scientific simulations.
Memory-Intensive Workload
• Needs large RAM allocations for in-memory processing.
• Often used for high-speed data analytics and caching , e.g., Real-time financial trading,
database caching.

Storage-Intensive Workload
• Focuses on large data storage, retrieval, and processing.
• Requires scalable storage solutions like object storage or file systems, e.g., Big data
analytics, media streaming, backup and archival systems.
Latency-Sensitive Workload
• Requires low latency and high availability.
• Often uses edge computing or geographically distributed cloud resources, e.g., Online
gaming, IoT applications, autonomous vehicles.

Hybrid Workload
• A mix of multiple workload patterns running in hybrid cloud environments.
• Requires intelligent workload distribution between on-premises and cloud , e.g.,
Enterprise applications with both real-time and batch processing.
Event-Driven (Server less) Workload
• Executes functions only when triggered by an event.
• Optimized for cost efficiency and scalability , e.g., Chatbots, IoT event processing,
automated workflows.
Each workload pattern requires different cloud architecture strategies to optimize
performance, cost, and scalability.

IT as a Service (ITaaS) is a model where IT services are delivered to businesses on a
consumption-based, on-demand basis, similar to cloud computing. Instead of managing IT
infrastructure and services in-house, organizations consume IT resources as a managed
service from external providers or internal IT departments operating in a service-provider
role.
Key Characteristics of ITaaS:
Service-Oriented Approach – IT resources (such as infrastructure, applications, and support) are
offered as services rather than owned assets.
Pay-as-You-Go Model – Organizations pay only for the IT services they use, reducing upfront capital
expenditures.
Scalability & Flexibility – IT services can scale up or down based on business needs.
Automation & Self-Service – Users can provision IT resources via self-service portals without
needing manual intervention.
IT as a Service (ITaaS)

Benefits of ITaaS:
Cost Efficiency: Reduces capital expenses (CapEx) and shifts costs to operational expenses
(OpEx).
Enhanced Agility: Allows businesses to adopt new technologies quickly without long-term
investments.
Focus on Core Business: Enables organizations to focus on strategic goals rather than IT
management.
Improved Security & Compliance: Ensures up-to-date security measures and regulatory
compliance.
Better Performance & Reliability: Offers high availability, backup, and disaster recovery
solutions.
IT as a Service (ITaaS)…

Cloud computing is widely used across various industries and applications. Here are some
of its key applications:
Data Storage and Backup
Cloud Storage: Services like Google Drive, Dropbox, and OneDrive allow users to store
and access files from anywhere.
Backup & Disaster Recovery: Cloud-based backups ensure data protection in case of
failures or cyberattacks (e.g., AWS Backup, Veeam).
Cloud Hosting and Web Applications
Website Hosting: Websites and applications are hosted on cloud platforms (e.g., AWS,
Azure, Google Cloud).
E-commerce Platforms: Online businesses use cloud-based infrastructure to handle traffic
and transactions (e.g., Shopify, Magento).
Applications of Cloud Computing

SaaS (Software as a Service) Applications
Office Productivity: Microsoft 365, Google Workspace for collaboration and document
management.
CRM & ERP Systems: Salesforce, SAP, and Oracle Cloud for business management.
Accounting & Finance: QuickBooks Online, Xero for cloud-based financial management.
Cloud Computing in Healthcare
Electronic Health Records (EHR): Cloud solutions store and manage patient data (e.g., Epic,
Cerner).
Telemedicine: Video consultations and remote patient monitoring using cloud-based platforms.
Medical Research: Cloud computing enables big data analytics in genomics and drug discovery.
Artificial Intelligence and Machine Learning
AI & ML Services: Cloud providers offer AI-powered services like AWS SageMaker, Google AI,
and Azure AI.
Chatbots & Virtual Assistants: AI-driven cloud-based applications like ChatGPT, Google
Assistant, and Siri. Image & Speech Recognition:
Applications of Cloud Computing…

Big Data and Analytics
Real-Time Data Processing: Cloud platforms analyze massive datasets for business intelligence
(e.g., Apache Hadoop, Google BigQuery).
Predictive Analytics: Industries use AI-driven analytics for forecasting trends (e.g., IBM Watson,
Tableau).
IoT Data Processing: Cloud-based solutions analyze sensor data from IoT devices.
Cloud Computing in Banking and Finance
Digital Banking: Cloud enables mobile banking apps and secure transactions.
Fraud Detection: AI-driven cloud solutions analyze transactions for fraudulent activities.
Algorithmic Trading: Financial institutions use cloud-based high-speed computing for trading.
Cloud-Based Gaming
Cloud Gaming Platforms: Services like Google Stadia, NVIDIA GeForce Now, and Xbox Cloud
Gaming allow users to stream games without expensive hardware.
Multiplayer & Online Gaming: Cloud infrastructure powers real-time online gaming experiences.

Cloud Computing in Education
E-Learning Platforms: Cloud-based LMS (Learning Management Systems) like Moodle, Google
Classroom, and Coursera provide remote learning.
Virtual Labs: Cloud computing enables students to access lab environments remotely.
Collaboration Tools: Cloud-based tools like Zoom, Microsoft Teams, and Slack enhance virtual
learning.
Cloud-Based Internet of Things (IoT)
Smart Homes & Cities: Cloud computing powers IoT devices like smart thermostats, security
cameras, and connected cars.
Industrial IoT: Manufacturing uses cloud IoT for predictive maintenance and real-time monitoring.
Healthcare IoT: Wearable devices sync data to the cloud for health tracking.
Content Delivery & Media Streaming
Video Streaming: Netflix, YouTube, and Disney+ use cloud CDNs for high-quality streaming.
Music Streaming: Services like Spotify and Apple Music store and deliver content from the cloud.
CDN (Content Delivery Network): Cloud-based CDNs (e.g., Cloudflare, Akamai) optimize
website performance and reduce latency.

Cloud Computing in Government & Defence
Smart Governance: Governments use cloud platforms for citizen services, identity management,
and taxation.
Cybersecurity & Surveillance: Cloud-based security solutions protect national data.
Disaster Response & Relief: Cloud computing aids emergency response with real-time
coordination.
Hybrid & Multi-Cloud Deployments
Enterprise IT Management: Businesses use hybrid cloud for balancing workloads between on-
premises and cloud solutions.
Multi-Cloud Strategies: Organizations use multiple cloud providers to avoid vendor lock-in.
BlockChain and Cryptocurrency
Decentralized Applications (DApps): Blockchain-based apps use cloud platforms for hosting.
Cryptocurrency Mining: Cloud computing enables scalable mining operations and blockchain
node hosting.

Cloud-Based Automation & DevOps
Continuous Integration & Deployment (CI/CD): Cloud platforms enable automated software
testing and deployment (e.g., Jenkins, GitHub Actions).
Infrastructure as Code (IaC): Tools like Terraform and AWS CloudFormation automate cloud
infrastructure management.
Cloud computing is revolutionizing multiple industries by providing scalable, cost-
efficient, and high-performance solutions. From data storage and AI to healthcare and
IoT, cloud technology continues to drive digital transformation.

Virtualization is the process of creating a virtual version of computing resources, such as
servers, storage, networks, or operating systems, instead of relying on physical hardware. It
enables efficient resource utilization, scalability, and flexibility by running multiple virtual
instances on a single physical machine.
 Virtualization was introduced nearly (1970) 55 years back.
 It refers to the process of creating a virtual layer over the hardware which allows the user
to run multiple instances simultaneously on the hardware.
 It is a key technology used in cloud computing.
 It is the base on which major cloud computing services such as Amazon EC2, VMware
vCloud, etc work on.
 Hardware virtualization is still one of the most common types of virtualization.
Virtualization

Virtualization…
A hardware virtualized server hosting three virtual machines, each one running distinct
operating system and user level software stack.

How Hardware Virtualization Works
Hardware virtualization in cloud computing is typically implemented through a technology
called hypervisor or virtual machine monitor (VMM).
Hypervisor: This software layer allows multiple virtual machines (VMs) to run on a single
physical machine (host). There are two types of hypervisors:
o Type 1 (bare-metal): Runs directly on the host's hardware, like VMware ESXi or
Microsoft Hyper-V.
o Type 2 (hosted): Runs as an application on the host's operating system, like
VirtualBox or VMware Workstation.
Virtualization…

Virtualization Process:
Resource Allocation: The hypervisor manages and allocates physical resources (CPU,
memory, storage) among the virtual machines.
Isolation: Each VM operates independently, unaware of other VMs running on the
same host. This isolation prevents one VM from affecting others.
Benefits:
o Resource Efficiency: Allows better utilization of physical hardware by running
multiple VMs simultaneously.
o Flexibility: VMs can be created, modified, and deleted dynamically, offering
scalability and flexibility in cloud environments.
o Security: Isolation between VMs enhances security, as compromising one VM does
not necessarily affect others.
Virtualization…

Types of Virtualization Techniques
1. Server Virtualization
Divides a physical server into multiple virtual servers, each running its own operating
system and applications.
Benefits: Improved resource utilization, cost savings, and isolation of workloads.
Examples: VMware vSphere, Microsoft Hyper-V, KVM (Kernel-based Virtual Machine).
2. Network Virtualization
Abstracts physical networking hardware to create multiple virtual networks.
Enables network segmentation, software-defined networking (SDN), and network function
virtualization (NFV).
Examples: Cisco ACI, VMware NSX, OpenFlow.
Virtualization…

3. Storage Virtualization
Combines multiple physical storage devices into a single logical storage pool.
Enhances data management, scalability, and redundancy.
Examples: Storage Area Networks (SAN), Network Attached Storage (NAS), IBM
Spectrum Virtualize.
4. Desktop Virtualization (VDI - Virtual Desktop Infrastructure)
Hosts desktop environments on a central server, allowing remote access from any device.
Benefits: Centralized management, enhanced security, and remote work enablement.
Examples: Citrix Virtual Apps & Desktops, VMware Horizon, Microsoft Azure Virtual
Desktop.
5. Application Virtualization
Runs applications in a virtualized environment without installing them on the local device.
Benefits: Software compatibility, security, and ease of deployment.
Examples: Microsoft App-V, VMware ThinApp, Citrix XenApp.
Types of Virtualization Techniques…

6. Operating System (OS) Virtualization (Containerization)
Uses containers to run multiple isolated applications on a shared OS kernel.
Benefits: Lightweight, faster deployment, and scalability.
Examples: Docker, Kubernetes, LXC (Linux Containers).
7. Memory Virtualization
Combines physical memory from multiple systems into a single shared resource.
Improves system performance by optimizing memory usage.
Examples: RAM disk, virtual memory paging.
8. Data Virtualization
Abstracts data from multiple sources into a unified, real-time view.
Enables seamless data integration and analytics.
Examples: Denodo, IBM Cloud Pak for Data.
Types of Virtualization Techniques…

 Cost Reduction: Lowers hardware and operational costs.
 Efficient Resource Utilization: Maximizes hardware capacity.
 Scalability & Flexibility: Easily scales workloads and applications.
 Improved Security & Isolation: Virtual machines (VMs) and containers provide
sandboxed environments.
 Disaster Recovery & Backup: Simplifies backups and failover mechanisms.
 Supports Cloud Computing: Virtualization is the backbone of cloud services.
Virtualization is a key technology in modern IT, enabling businesses to optimize
resources, improve scalability, and enhance security and Understanding different
virtualization techniques helps to choose the right solutions for their needs.
Benefits of Virtualization

Web 2.0
 Web 2.0 is the interface through which the cloud computing services interact
with the clients.
 It is because of Web 2.0 that we have interactive and dynamic web pages.
 It also increases flexibility among web pages.
 Popular examples of web 2.0 include Google Maps, Facebook, Twitter, etc.
Needless to say, social media is possible because of this technology only.
 It gained major popularity in 2004.

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