Cloud Computing — Complete Exam Notes

CSE-468 · Units 1, 2 & 3 · Prof. Saurav Tripathi · Exam Preparation

UNIT 1: Introduction to Cloud Computing

1.1 What is Cloud Computing? — All Key Definitions

Cloud computing is a term with many authoritative definitions. Know all of them — exams ask you to compare.

NIST Definition (Most Important)

Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.

Berkeley Definition

Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the datacenters that provide those services. When a Cloud is made available in a pay-as-you-go manner to the public, the service being sold is called Utility Computing.

Buyya's Definition

A Cloud is a type of parallel and distributed system consisting of a collection of interconnected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources based on service-level agreements (SLAs) established through negotiation between the service provider and consumers.

Wikipedia Definition

Cloud computing is Internet-based computing, whereby shared resources, software, and information are provided to computers and other devices on demand, like the electricity grid.

Simple Working Definition

Cloud Computing is a service model that provides on-demand services to the user with minimal management efforts, regulated by Quality of Service (QoS) and Service Level Agreement (SLA). It is well known for the Pay-as-you-go model (renting rather than owning).

1.2 The NIST 5-4-3 Model

This is the cornerstone of cloud computing theory. Always remember:

1.3 Essential Characteristics (Learn Each One)

1. On-Demand Self-Service

A consumer can unilaterally provision computing resources — such as server time, network storage, and applications — as needed, automatically without human interaction from the cloud provider. Once configured, usage can be automated, requiring no further human involvement.

2. Broad Network Access

Computing resources are available over the network and can be accessed using heterogeneous client platforms — mobiles, laptops, desktops, PDAs, tablets. Establishing ubiquitous access may require support for a range of devices, transport protocols, interfaces, and security technologies.

3. Resource Pooling

The provider's computing resources are pooled to serve multiple consumers using a multi-tenant model. Different physical and virtual resources are dynamically assigned and reassigned according to consumer demand. The customer usually has no knowledge of the exact physical location of the provided resources (location transparency), though at a higher level of abstraction, the region can be specified.

4. Rapid Elasticity

Resources can be elastically provisioned and released (automatically or manually) to scale rapidly outward and inward according to demand. To the consumer, available resources often appear to be unlimited and can be purchased in any quantity at any time.

5. Measured Service

Cloud systems automatically control and optimize resource use by leveraging a metering capability. Resource usage can be monitored, controlled, and reported, providing transparency for both provider and consumer. Users pay only for what they actually use (pay-as-you-go). Measured usage is not limited to billing — it also encompasses general monitoring and usage reporting.

1.4 Deployment Models

1. Private Cloud

Deployed for the exclusive use of a single organization. The organization may own and manage it, assign it to a third party, or both. Infrastructure can be on-premise or off-premise. Also called internal cloud. Limits access to service consumers belonging to the same organization.

2. Public Cloud

Infrastructure is made available to the general public. Owned by an organization selling cloud services, a government organization, or both. Typically deployed at the cloud vendor's premises. Also called external cloud or multitenant cloud.

3. Community Cloud

Infrastructure is shared by multiple organizations that form a community with shared concerns (mission, security requirements, policy, compliance). Owned, managed, and operated by the organizations or a third party. Can be on-premise or off-premise.

4. Hybrid Cloud

Infrastructure is a composition of two or more distinct cloud models (private, public, or community) that remain unique entities but are bound together by standardized or proprietary technology enabling data and application portability (e.g., cloud bursting for load-balancing between clouds).

1.5 Service Models

1. Software as a Service (SaaS)

The provider offers use of applications running on cloud infrastructure accessible via web browser (thin client). The consumer does NOT manage or control the underlying cloud infrastructure — not the network, servers, OS, storage, or individual application capabilities (except possibly limited user-specific settings).

What provider manages: Everything — servers, storage, networks, virtualization, OS, runtime, software, maintenance, updates.

Examples: Google Apps (Gmail, Google Docs), Salesforce.com, Microsoft OneDrive, Dropbox, Slack, EyeOS.

2. Platform as a Service (PaaS)

Provider gives consumers a runtime environment / development platform to deploy consumer-created or acquired applications (using programming languages and tools supported by the provider). The consumer does NOT manage or control the underlying cloud infrastructure (network, servers, OS, storage) but has control over deployed applications and possibly application hosting environment configurations.

What provider manages: Infrastructure, OS, runtime, middleware.

Examples: Google App Engine, Microsoft Windows Azure, Heroku, Hadoop.

3. Infrastructure as a Service (IaaS)

Provider offers processing, storage, networks, and other fundamental computing resources where the consumer can deploy and run arbitrary software (including OS and applications) via virtualization. The consumer does NOT manage the underlying cloud infrastructure but has control over OS, storage, deployed applications, and possibly limited networking components.

What provider manages: Physical hardware, network, storage hardware, virtualization.

Examples: Amazon EC2, Amazon Web Services (AWS), Google Compute Engine, Rackspace, Eucalyptus, OpenStack.

1.6 XaaS and DaaS

Everything-as-a-Service (XaaS)

Also known as Anything-as-a-Service, XaaS provides flexibility for users and companies to customize computing environments on demand. XaaS is evolving from technology-as-a-service to business-as-a-service.

Data as a Service (DaaS)

A data management strategy that uses the cloud to deliver data storage, integration, processing, and/or analytics services via a network connection. Similar to SaaS, DaaS removes the need to install and manage data infrastructure locally — it outsources data storage, integration, and processing operations to the cloud. Used in data integration, business intelligence, and cloud computing.

1.7 Evolution & History of Cloud Computing

1.8 Pre-existing Technologies (Technology Influences)

Clustering

A cluster is a group of independent IT resources interconnected to work as a single system (usually via LAN). Key features: redundancy, failover, high-speed communication links between nodes, reduced failure rates, increased availability. The concept of built-in redundancy and failover is core to cloud platforms.

Grid Computing

A computing grid provides a platform where computing resources are organized into one or more logical pools, collectively coordinated to provide a high-performance distributed grid — sometimes called a "super virtual computer."

Grid computing differs from clustering: grid systems are much more loosely coupled and distributed. Grid is based on a middleware layer deployed on computing resources that implements workload distribution, load balancing, failover controls, and autonomic configuration management.

1.9 Key Terminology

Cloud

A distinct IT environment designed for the purpose of remotely provisioning scalable and measured IT resources. The term originated as a metaphor for the Internet. A cloud is typically privately owned and offers metered access to IT resources.

IT Resource

A physical or virtual IT-related artifact — either software-based (virtual server, custom software) or hardware-based (physical server, network device).

On-Premise

An IT resource hosted in a conventional IT enterprise within an organizational boundary that does NOT specifically represent a cloud. An on-premise IT resource cannot be cloud-based and vice versa. However: on-premise resources can interact with cloud-based resources; on-premise resources can be migrated to the cloud.

Cloud Provider vs Cloud Consumer

• Cloud Provider: The party that provides cloud-based IT resources.
• Cloud Consumer: The party that uses cloud-based IT resources.
• Cloud Service Consumer: A temporary runtime role assumed by a software program when it accesses a cloud service.

Scaling

• Horizontal Scaling: Scaling out (adding more machines) and scaling in (removing machines).
• Vertical Scaling: Scaling up (adding more resources to a machine) and scaling down (removing resources).

Cloud Service

Any IT resource made remotely accessible via a cloud. The driving motivation is to provide IT resources as services that encapsulate other IT resources while offering functions for clients to use remotely. Most cloud services are labeled with the "as-a-service" suffix.

1.10 Cloud Properties in Detail

Dynamic Provisioning

A strategy that manages server resources by activating only what is needed, aiming to reduce power consumption by adjusting resource availability based on demand.

Traditional problems: (1) Under-provision → loss of users/revenue because demand exceeds capacity. (2) Over-provision → wasted resources because capacity far exceeds demand.

Cloud solution: Dynamically provision resources to track demand — meet seasonal variations, burst demand for extraordinary events, and variations between industries.

Availability & Reliability

• Availability: The degree to which a system is in a specified operable and committable state at the start of a mission. Cloud requires high availability — e.g., "Five Nines" = 99.999% availability.
• Reliability: The ability of a system to perform its required functions under stated conditions for a specified time period.

How to achieve: Fault-tolerant systems, system resilience, reliable system security.

Fault Tolerance

The property that enables a system to continue operating properly in the event of failure of some of its components. Four basic characteristics:

1. No Single Point of Failure (SPOF): No single component whose failure stops the entire system. If a failure occurs, the system must continue to operate without interruption during repair.
2. Fault Detection and Isolation (FDI): Monitoring the system, identifying when a fault has occurred, and pinpointing the type and location of the fault.
3. Fault Containment: Isolating the failing component to prevent propagation of failure to the rest of the system.
4. Availability of Reversion Modes: System must maintain checkpoints to manage state changes and revert if needed.

System Resilience

The ability to provide and maintain an acceptable level of service in the face of faults. A resilient system returns to its original state after encountering trouble as quickly as possible.

Disaster Recovery strategies: Data backup (off-site at regular intervals), data replication, system replication, local mirror systems, UPS (Uninterruptible Power Supply), surge protectors.

Autonomic Computing (Self-Management)

Develops computer systems capable of self-management. Four functional areas:

• Self-Configuration: Automatic configuration of components.
• Self-Healing: Automatic discovery and correction of faults.
• Self-Optimization: Automatic monitoring and control of resources for optimal functioning.
• Self-Protection: Proactive identification and protection from arbitrary attacks.

Load Balancing

A technique to distribute workload evenly across two or more computers, network links, CPUs, hard drives, or other resources to: optimize resource utilization, maximize throughput, minimize response time, and avoid overload.

Benefits: Improved resource utilization, improved system performance, improved energy efficiency.

Job Scheduling

A software application that manages unattended background executions (batch processing). In cloud: manages computation-intensive tasks, dynamically growing/shrinking tasks, and tasks with complex processing dependencies. Approaches: pre-defined workflow, system automatic configuration.

1.11 Issues, Risks & Challenges

Major Research Challenges in Cloud Computing

1. Portability: Ability to move an application and its data from one cloud to another irrespective of provider, platform, or OS (e.g., moving from a Windows cloud to a Linux cloud without changing the application).
2. New Architecture Development: Most clouds use centralized old-style data centers. Research into voluntary resources, hybrid dedicated/voluntary architectures for scientific computing.
3. Limited Scalability: Providers promise infinite scalability but struggle as millions of users migrate to cloud.
4. Lack of Standards: Each CSP has their own standards with no comparative performance measurement facility for users to compare clouds.
5. Security & Privacy: Main obstacle to fast adoption — applications and architectures must be private; security mechanisms must be evolving and adaptive. Trust and Privacy are key research areas.
6. Reliability: Reliability of the connection to cloud services; secure data movement at required speed.
7. Governance: Governments providing cloud services via own data centers; government, organizations, and users must work together.
8. Metering: Services must be metered and monitored using standard parameters.
9. Energy Management: Resources "on all the time" is energy-inefficient; need energy-efficient equipment and data centers.
10. Denial of Service (DoS): What happens when cloud is under heavy DoS attack? Should DoS protection be built into cloud or handled at internet level?

1.12 Principles to Scale Up Cloud Computing

1. Federation: Each cloud has limited capacity; federation of service providers enables collaboration and resource sharing. A federated cloud must allow virtual applications to be deployed on federated sites and migrate easily between sites.
2. Freedom: End-users should be completely free to use cloud services without depending on a specific CSP. CSPs should be able to manage services without sharing internal details.
3. Isolation: A CSP provides resources to multiple end-users; each user's data must be isolated and cannot be accessed by others sharing the cloud.
4. Elasticity: Resources should be elastic — users can freely attach and release computing resources on demand.
5. Business Orientation: CSPs must understand exact business requirements of customers and customize service parameters accordingly, guaranteeing QoS for mission-critical applications.
6. Trust: Most important factor driving customers to the cloud. Trust must be maintained among cloud customer, vendor, and providers to create successful federations.

Advantages of Cloud Computing

• Pay-per-use (no huge upfront investment)
• No server space required; no maintenance team needed
• Automatic software updates
• More flexible; data accessible remotely from anywhere
• Rapid implementation; better data security
• High scalability and elasticity
• Better collaboration and disaster recovery

Disadvantages of Cloud Computing

1. Internet Connectivity: Requires constant, stable internet — downtime disrupts everything.
2. Vendor Lock-in: Hard to switch providers; data and applications may not be portable.
3. Limited Control: Users have reduced visibility and control over their data and infrastructure.
4. Security: Data transmitted over internet raises security and privacy concerns.

UNIT 2: Virtualization

2.1 What is Virtualization?

Virtualization is the "creation of a virtual (rather than actual) version of something" — such as a server, desktop, storage device, operating system, or network resources.

More precisely: Virtualization represents a technology platform used for the creation of virtual instances of IT resources. A layer of virtualization software allows physical IT resources to provide multiple virtual images of themselves so that their underlying processing capabilities can be shared by multiple users.

Key facts:

• Prior to virtualization, software was limited to residing on and being coupled with static hardware environments.
• Hardware requirements can be simulated by emulation software running in virtualized environments.
• Virtual Machine (VM) is the basic unit to execute a service request.
• The Virtualization layer is the middleware between the underlying hardware and the VMs — also known as VMM or Hypervisor.

Types of Virtualization (4 types from Unit 1)

1. Hardware Virtualization: VMM/hypervisor installed directly on hardware. Main job: control/monitor processor, memory, and hardware. Used mainly for server platforms.
2. Operating System Virtualization: VMM installed on the host OS (not directly on hardware). Used mainly for testing applications on different OS platforms.
3. Server Virtualization: VMM installed directly on the server system. One physical server divided into multiple virtual servers on demand — enables load balancing.
4. Storage Virtualization: Process of grouping physical storage from multiple network storage devices so it looks like a single storage device. Done mainly for backup and recovery purposes.

VMM/Hypervisor Functions

• Enables creation and management of VMs
• Manages allocation of system resources for VMs
• Allows several OS to run concurrently on a single hardware platform
• Examples: Xen, VMware, UML, Denali

2.2 Implementation Levels of Virtualization

2.3 Hypervisor — Type 1 vs Type 2

A hypervisor is a hardware virtualization technique allowing multiple operating systems (guests) to run on a host machine. Also called Virtual Machine Monitor (VMM).

Type 1: Bare Metal Hypervisor

• Sits directly on the bare metal computer hardware (CPU, memory, etc.)
• All guest OSes are a layer above the hypervisor
• The original CP/CMS hypervisor developed by IBM was of this kind
• Examples: VMware ESXi, Microsoft Hyper-V, Xen
• Advantage: Better performance — no host OS overhead

Type 2: Hosted Hypervisor

• Runs on top of a host operating system
• Hypervisor is the second layer over hardware (OS → Hypervisor → Guest OS)
• The host OS is usually unaware of the virtualization
• Examples: VMware Workstation, VirtualBox, QEMU
• Advantage: Easier to install and manage

2.4 Full Virtualization vs Para-Virtualization

Full Virtualization

• Does NOT need to modify the guest OS
• Critical instructions are emulated by software using binary translation — automatically modifying x86 software on-the-fly to replace critical instructions
• A guest OS can run unchanged under the VMM as if running directly on hardware
• Requires a virtualizable architecture
• Examples: VMware Workstation
• Advantage: No need to modify OS (use any guest OS)
• Disadvantage: Binary translation slows down performance

Para-Virtualization

• Must modify the guest OS — non-virtualizable instructions are replaced by hypercalls that communicate directly with the hypervisor/VMM
• Guest OS is modified to use only instructions that can be virtualized
• Reduces overhead but cost of maintaining a paravirtualized OS is high
• Examples: Xen, Denali, VMware (also supports it)
• Reasons to use: Some hardware aspects cannot be virtualized; improved performance; simpler interface

2.5 CPU, Memory, and I/O Virtualization

CPU Virtualization

Modern OS and processors support multiple processes running simultaneously. Processors have at least two modes:

• User Mode: For unprivileged instructions
• Supervisor Mode: For privileged instructions (run at higher privilege)

Three categories of critical instructions:

1. Privileged instructions: Execute in privileged mode; trapped if executed outside this mode
2. Control-sensitive instructions: Attempt to change the configuration of resources used
3. Behavior-sensitive instructions: Have different behaviors depending on resource configuration (e.g., load/store over virtual memory)

A CPU architecture is virtualizable if it supports running the VM's privileged and unprivileged instructions in the CPU's user mode while the VMM runs in supervisor mode.

RISC CPU architectures can be naturally virtualized. x86 architectures are NOT primarily designed for virtualization (10 sensitive instructions are not privileged).

Hardware-Assisted CPU Virtualization (Intel VT/AMD-V): Intel and AMD add an additional mode called privilege mode level (Ring -1) to x86 processors, so OSes still run at Ring 0 and the hypervisor runs at Ring -1. All privileged and sensitive instructions are automatically trapped in the hypervisor — removing the need for binary translation in full virtualization.

Memory Virtualization

Similar to virtual memory supported by modern OS. Modern x86 CPUs include a Memory Management Unit (MMU) and a Translation Lookaside Buffer (TLB) to optimize virtual memory performance.

Two-stage mapping:

1. Guest OS maps: Virtual Memory → Physical Memory (Guest Physical)
2. VMM maps: Physical Memory (Guest Physical) → Machine Memory (Real Physical)

Each page table of the guest OS has a corresponding shadow page table in the VMM. VMware uses shadow page tables to perform virtual-memory-to-machine-memory translation. Intel's Extended Page Table (EPT) hardware performs this in hardware, avoiding performance overhead.

I/O Virtualization

Involves managing the routing of I/O requests between virtual devices and shared physical hardware. Three approaches:

1. Full Device Emulation: All functions of a device (enumeration, identification, interrupts, DMA) are replicated in software. Simple but slowest.
2. Para-virtualization (Frontend/Backend):
   • Frontend driver runs in Domain U (guest) — manages I/O requests of all guest OS
   • Backend driver runs in Domain 0 (privileged) — manages real I/O devices and multiplexes I/O data
   • Better device performance than full emulation
3. Direct I/O Virtualization: VM devices access hardware directly; close-to-native performance without high CPU costs. Uses Self-Virtualized I/O (SV-IO) — provides Virtual Interface (VIF) for every virtualized I/O device.

2.6 Data, Hardware, and Software Virtualization

Data Virtualization

Process of retrieving data from various resources without knowing its type and physical location. Collects heterogeneous data from different resources and allows access according to work requirements. Accessible using web portals, web services, SaaS, mobile applications.

Used in: Data integration, business intelligence, cloud computing.

Industries: Communication & Technology (real-time ODS for marketing), Finance (trade reconciliation), Government (environmental protection), Healthcare (patient care), Manufacturing (supply chain optimization).

Advantages: Access data without worrying about location; better security; reduces costs by removing data replication; real-time data access; user-friendly interface.

Disadvantages: Availability issues (maintained by third-party providers); high implementation cost; scalability issues.

Hardware Virtualization

Accomplished by abstracting the physical hardware layer using a hypervisor/VMM installed directly on hardware. Main job: control and monitor processor, memory, and other hardware resources.

Advantages:

• Efficient Resource Utilization: Unused resources allocated to other VMs
• Lower Costs via Server Consolidation: Multiple OS on one physical server — fewer servers, less rack space, less power consumption
• Increased Uptime: Advanced features like live migration allow running VMs to move between hosts dynamically; maintain a running copy of VM on another host in case primary fails
• IT Flexibility: Quick deployment of server resources in a managed, consistent way

Software Virtualization

Abstracts the software installation procedure and creates virtual software installations. Virtualized software is an application installed into its own self-contained unit. Examples: VMware, VirtualBox.

Advantages:

• Easier Deployments: Simply copy or link a file to install virtual software on a workstation
• Easy Management: Update at one place and deploy to all clients
• Simpler Migration: Moving from one software platform to another is much easier with virtualized environments

2.7 VM Migration

Why Migrate VMs?

• Upgrading hardware without downtime
• Balancing resource usage (load balancing)
• Recovering from VM failures
• Meeting Service Level Agreements (SLAs)

Types of VM Migration

1. Live / Hot Migration (VM is powered ON):

Process of moving a running VM from one physical host to another without disrupting normal operations or causing downtime. Memory, storage, and network connectivity are transferred from the original host to the destination. The end-user experiences no service interruption.

Requirements for Live Migration (Hyper-V):

• Two or more servers running Hyper-V that support hardware virtualization
• Use processors from the same manufacturer (e.g., all AMD or all Intel)
• Belong to the same Active Directory domain or mutually trusting domains
• VMs must use virtual hard disks or virtual Fibre Channel disks (no physical disks)
• Isolated network (physically or via VLANs) recommended for migration traffic

2. Regular / Cold Migration (VM is powered OFF):

VM is shut down before moving. Simpler but causes downtime.

2.8 Virtual Clusters

Virtual cluster nodes can be either physical or virtual machines. Multiple VMs running different OSes can be deployed on the same physical node.

Purpose: Consolidate multiple functionalities on the same server → greatly enhance server utilization and application flexibility.

Key characteristics:

• VMs can be colonized (replicated) across multiple servers for distributed parallelism, fault tolerance, and disaster recovery
• Failure of a physical node may disable VMs on the failing node
• Virtual cluster nodes are independent of the underlying hardware

Virtual Cores vs Physical Cores:

2.9 Cloud OS: Eucalyptus

Eucalyptus (Elastic Utility Computing Architecture) is a paid and open-source software for building AWS-compatible private and hybrid cloud environments. Originally developed by Eucalyptus Systems.

• Hypervisors supported: KVM, Xen, VMware
• OS: Linux; can host Linux and Windows VMs
• Languages: Java, C
• Compatible with Amazon AWS APIs

UNIT 3: Service Models and Deployment Models (Deep Dive)

3.1 Infrastructure as a Service (IaaS) — Deep Dive

The capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications.

The consumer does NOT manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., firewalls).

Examples of IaaS

• Amazon EC2 (Elastic Compute Cloud)
• Eucalyptus
• OpenStack
• Google Compute Engine
• Rackspace

Enabling Technique: Virtualization

Virtualization is the key enabling technique for IaaS. It is an abstraction of logical resources away from underlying physical resources.

• Virtualization shifts OS onto hypervisor
• Multiple OS share physical hardware and provide different services
• Improves utilization, availability, security, and convenience

IaaS uses: Server Virtualization + Storage Virtualization + Network Virtualization

IaaS Provided Services

• Resource Management Interface: Consumer manages VMs, storage, networking
• System Monitoring Interface: Track resource usage, performance, billing

3.2 Platform as a Service (PaaS) — Deep Dive

The capability provided is to deploy onto cloud infrastructure consumer-created or acquired applications using programming languages and tools supported by the provider.

The consumer does NOT manage the underlying infrastructure (network, servers, OS, storage) but has control over deployed applications and possibly application hosting environment configurations.

Examples of PaaS

• Heroku
• Google App Engine
• Hadoop
• Microsoft Windows Azure

Enabling Technique: Runtime Environment Design

A runtime environment refers to a collection of software services available — usually implemented as a collection of program libraries. Common properties in runtime environment:

• Manageability and Interoperability
• Performance and Optimization
• Availability and Reliability
• Scalability and Elasticity

PaaS Provided Services

1. Programming IDE:

• Integrates full functionalities supported from underlying runtime environment
• Provides development tools: profiler, debugger, testing environment
• Supports computation, storage, and communication resource operations

2. System Control Interface:

• Policy-Based Control: Described as a principle or rule to guide decisions and achieve rational outcomes; makes decisions according to requirements
• Workflow Control: Describes the flow of installation and configuration of resources; workflow processing daemon delivers speedy construction and management of cloud resources

3.3 Software as a Service (SaaS) — Deep Dive

The capability provided is for the consumer to use the provider's applications running on cloud infrastructure, accessible from various client devices through a thin client interface such as a web browser.

The consumer does NOT manage or control the underlying infrastructure (network, servers, OS, storage) or even individual application capabilities — only limited user-specific application configuration settings.

Examples of SaaS

• Google Apps (Gmail, Google Docs, Google Sites)
• Salesforce.com
• EyeOS
• Microsoft Office 365
• Dropbox, Slack

Enabling Technique: Web Service (Web 2.0)

Web 2.0 is the trend of using the full potential of the web:

• Viewing the Internet as a computing platform
• Running interactive applications through a web browser
• Leveraging interconnectivity and mobility of devices
• Enhanced effectiveness with greater human participation
• Key cloud properties enabled: Accessibility and Portability

SaaS Provided Services

Web Portal:

• Apart from standard search, offers email, news, stock prices, information, databases, entertainment
• Provides consistent look and feel with access control across multiple applications and databases
• Examples: iGoogle, MSNBC, Netvibes, Yahoo!

Web-based Application Categories:

• General applications
• Business applications
• Scientific applications
• Government applications

3.4 Deployment Models — Full Advantages & Disadvantages

Public Cloud

Cloud infrastructure made available to the general public or large industry group. Also known as external cloud or multitenant cloud.

Basic characteristics: Homogeneous infrastructure, common policies, shared resources, multi-tenant, leased/rented infrastructure, economies of scale.

Advantages:

• Minimal Investment: Pay-per-use — no substantial upfront fee
• No Setup Cost: Entire infrastructure subsidized by CSP
• Cost Effective: Same resources shared by many users
• No Infrastructure Management: CSP handles everything
• No Maintenance: Maintenance done by service provider
• Dynamic Scalability: On-demand resources always accessible
• Reliable, Flexible, Location-independent

Disadvantages:

• Data Security and Privacy Concerns: Open to public — not complete protection; may expose weaknesses to cyber-attacks
• Limitation on Service/License: While resources are shared, there is a limit on how much you can use

Private Cloud

Cloud infrastructure operated solely for one organization. May be managed by the organization or a third party; on-premise or off-premise. Also called internal cloud or on-premise cloud.

Basic characteristics: Heterogeneous infrastructure, customized and tailored policies, dedicated resources, in-house infrastructure, end-to-end control.

Advantages:

• Better Control: Complete command over service integration, IT operations, policies, and user behavior
• Data Security and Privacy: Suitable for corporate information; improved access and security through resource segmentation
• Supports Legacy Systems: Works with legacy systems that cannot access public cloud
• Customization: Tailor solutions to specific needs
• Cost and Energy Efficiency

Disadvantages:

• Restricted Scalability: Scaled only within confines of internally hosted resources; hardware choice impacts scalability
• Higher Cost: Must pay for software, hardware, staffing — higher investment than public cloud

Hybrid Cloud

Composition of two or more clouds (private or public) that remain unique entities but are bound together by standardized or proprietary technology enabling data and application portability.

Usage pattern: Non-critical activities → public cloud; Critical activities → private cloud (or vice versa). Cloud bursting is used for load-balancing between clouds.

Advantages:

• Flexibility and Control: Design personalized solutions to meet particular needs
• Cost: Public cloud provides scalability — only pay for extra capacity when needed
• Security: Data is properly separated, reducing chances of theft

Disadvantages:

• Maintenance: Hybrid strategy may necessitate additional maintenance → higher operational expense
• Difficult Integration: Combining two or more infrastructures involves significant upfront cost; data and application integration is complex

Community Cloud

Cloud infrastructure shared by several organizations that have shared concerns (mission, security requirements, policy, compliance). May be managed by the organizations, a third party, or both.

Advantages:

• Cost Effective: Cost shared by multiple organizations/communities
• Security: Better security than public cloud
• Shared Resources: Share resources, infrastructure among multiple organizations
• Collaboration and Data Sharing: Suitable for both collaboration and data sharing

3.5 Multi-Cloud

Multi-Cloud refers to the distributed, heterogeneous world of applications and users across public clouds, data centers, and edge.

In this model, organizations use a combination of on-premises, private cloud, public cloud, and edge to build, operate, access, and secure their applications consistently across clouds.

Key benefits:

• Flexibility to run workloads on any cloud the business requires
• Migrate, manage, and secure applications consistently regardless of deployment location
• Move fast, spend less, and reduce risk across a distributed IT landscape

PYQ Analysis & Important Questions

How to Answer Common Exam Questions

Q: What is cloud computing? Explain its essential characteristics.

Start with the NIST definition (most important). Then explain the 5-4-3 model. Write all 5 characteristics with 3–4 lines each. Mention examples where possible. Always mention the Pay-as-you-go model.

Q: Explain the service models of cloud computing with examples.

Draw the layered diagram (IaaS → PaaS → SaaS). For each model: define it, state what the consumer controls, what the provider controls, and give examples. Use the house analogy if needed.

Q: Differentiate full virtualization and para-virtualization.

Use a 5-column comparison table. Key points: Guest OS modification, Binary Translation, Hypercalls, Performance, Examples.

Quick-Revision: Everything in One Place

Cloud Computing Notes · CSE-468 · Units 1–3 · Saurav Tripathi · SRM University AP