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CLOUD COMPUTING
Unit Structure
1.0 Objectives
1.1 Introduction to Cloud Computing
1.2 Characteristics and benefits of Cloud Computing
1.3 Basic concepts of Distributed Systems
1.4 Web 2.0
1.5 Service -Oriented Computing
1.6 Utility -Oriented Computing
1.7 Let us Sum Up
1.8 List of References
1.9 Unit End Exercises
1.0 OBJECTIVE
 To understand the concept of cloud computing.
 To study the characteristics and benefits of cloud computing.
 To Understand the basic concepts of distributed computing.
 To learn about Service Oriented and Utility Oriented Computing.
1.1 INTRODUCTION TO CLOUD COMPUTING
Cloud computing technologies are:
 Virtualization
 Service -Oriented Architecture (SOA)
 Grid Computing
 Utility Computing
Virtualization
“Virtualization means the process of c reating a virtual environment to run
multiple applications and operating systems on the same server”.
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2 Types of Virtualization
1. Hardware virtualization
2. Server virtualization
3. Storage virtualization
4. Operating system virtualization
5. Data Virtualization
Service -Oriented Architecture (SOA)
Service -Oriented Architecture enables organizations to access on -demand
cloud -based computing solutions on the report of the change of business
requirement.
Applications of Service -Oriented Architecture
1. It is used in the healthc are industry.
2. It is used to create different mobile applications and games using SOA.
3. In the air force, SOA infrastructure is used to establish situational
awareness systems.

Fig. 1. SOA
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3 Grid computing
Grid computing is also known as distributed computi ng. It is a type of
processor architecture that merges various different computing resources
from multiple locations to achieve a common goal.
Types of machines used in computing:
1. Control Node: It is a group of servers which administers the whole
network.
2. Provider: It is a computer which contributes its resources in the
network resource pool.
3. User: It uses the resources on the network.

Fig.2 Grid Computing
Utility Computing
Utility computing is the bulk trending IT service model. It supply on -
demand comp uting resources (i.e. computation, storage, and programming
services via API) and infrastructure based on the pay per use method.

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4 ● Cloud computing gives guarantee to transform computing into a utility
delivered over the internet.
● Enterprise architecture is a function within IT departments that has
developed over time, playing a high value role in managing transitions
to new technologies, such as cloud computing.
1.2 CHARACTERISTICS AND BENEFITS OF CLOUD
COMPUTING
● Cloud computing refers to different technologies, services, and
concepts.
● It is associated with virtualized infrastructure or hardware on demand,
utility computing, IT outsourcing, platform and software as a service,
and many other things that now are the heart of the I T industry.
● Figure 4 shows too many different ideas included in current definitions
of cloud computing systems.
● The term cloud has an abstraction of the network in system diagrams.
This meaning is also put into cloud computing, which refers to an
Internet -centric way of computing.
● The Internet plays a fundamental role in cloud computing, it shows the
medium or the platform through which many cloud computing
services are delivered and made accessible.
Definition of cloud computing:
“Cloud computing introd uces both the applications delivered as services
over the Internet and the hardware and system software in the data
centers that provide those services.”
● Cloud computing as aoccurance touching on the entire stack: from the
underlying hardware to the high -level software services and its
applications.
● Here is the concept of everything as a service, like XaaS, the different
components of a system IT infrastructure, development platforms,
databases, and so on can be delivered, measured, and consequently
cost a s a service.
● Cloud computing is a model for defining ubiquitous, convenient, on -
demand network access to a shared pool of configurable computing
resources (e.g., like networks, servers, storage, applications, and
services) that can be instantly provisione d and free with less
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Fig. 4 Cloud computing environment
● Utility -oriented approach is an important aspect of cloud computing .
● Cloud computing concentrates on delivering services with a given
pricing mode l, in most cases a pay -per-use method.
● It is also possible to access online storage, rent the virtual hardware, or
use development platforms and pay only for their effective usage, with
no or minimal up -front costs.
● All these operations can be executed a nd billed simply by entering the
credit card details and accessing the exposed services through a Web
browser.
● The criteria to disfavor whether a service is delivered in the cloud
computing style:
○ The service is accessible through a Web browser or a Web s ervices
application programming interface.
○ Zero capital expenditure
○ pay only for what you use
● Characteristics
○ Resources Pooling
Cloud providers pulled the computing resources to give services to
multiple customers with the help of a multi -tenant model.

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6 ○ On-Demand Self -Service
It is one of the key and valuable features of Cloud Computing as the user
can regularly monitor the server uptime, capabilities, and allotted network
storage.
○ Easy Maintenance
The servers are easy to maintain and the downtime is requi red very less
and even in some situations, there is no downtime.
○ Large Network Access
The user can access the data of the cloud or upload the data to the cloud
from anywhere just with the help of a device and an internet connection.
○ Availability
The pote ntial of the Cloud can be altered as per the use and can be
extended a lot. It studies storage usage and allows the user to purchase
extra Cloud storage if needed for a very small amount.
○ Automatic System
Cloud computing automatically analyzes the data nee ded and supports a
metering capability at some level of services.
○ Economical
It is a one -time investment as the company has to buy the storage and a
small part of it can be provided to the many companies which save the
host from monthly or yearly costs.
○ Security
Security creates a snapshot of the data stored so that the data may not get
lost even if one of the single servers gets damaged.
○ Pay as you used
In cloud computing, the user has to pay only for the service they have
utilized and used.
○ Measured Ser vice
Cloud Computing resources used to handle and the company uses it for
recording.
1.3 BASIC CONCEPTS OF DISTRIBUTED SYSTEMS
● In Cloud Computing whenever a need and demand from thirds party,
that make its available their service to party which is essenti ally large
DS.
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7 ● The characterization of a distributed system is define using definition:
“A distributed system is a collection of independent computers that
appears to its users as a single coherent system.”
● This includes a variety of computer systems, but it affirms two most
important elements that distinguish a distributed system.
● DS is composed of multiple independent components and that these
components are recognized as a single entity by users.
● This is true for the case of cloud computing, in which cl ouds hide the
complex architecture they depend on and provide a single interface to
users.
● The primary use of distributed systems is to share resources and utilize
them in a better way.
● The infrastructure, runtime environments, and services are rented to
users.
● In fact, one of the navigational factors of cloud computing has been
the availability of the large computing facilities or services of IT such
as Amazon, Google.
● This offers their computing capabilities as a service provided
opportunities for best utilization of their infrastructure.
● Distributed systems often show other properties such as heterogeneity,
openness, scalability, transparency, concurrency, continuous
availability, and independent failures.
● To some areas these also distinguish clouds , especially in the factors of
scalability, concurrency, and continuous availability.
● There are three major milestones that have led to cloud computing
facilities:
1. Mainframe Computing
● Mainframes controlling the large computational facilities with multiple
processing units.
● Mainframes are powerful, highly reliable computers functional for
large data movement and massive input and output operations.
● The Mainframe computing is used by large organizations for huge data
processing tasks like online transactio ns, enterprise resource planning,
and other operations that require the processing of significant amounts
of data.
● One of the most highlighted features of mainframes computing was the
ability to be highly reliable computers that were “always on” and be up
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8 ● System shutdown process was needed to replace failed components,
and the system worked properly without any interruption.
● Batch processing is the main application of mainframes computing.
Not only are their populari ty and deployments reduced, but also
extended versions of such systems are presently in use for transaction
processing.
● Examples, such as online banking, airline ticket booking, supermarket
and telcos, and government services.
2. Cluster computing
● Cluster co mputing started using a low -cost another method to the use
of mainframes and supercomputers.
● The technology advancement that makes faster and more powerful
mainframes and supercomputers in time generated an increased
availability of cheap product machines as a side effect.
● These machines are connected by a high -bandwidth network and
controlled by certain software tools that handle them as an individual
system.
● Cluster technology contributed to the natural selection of tools and
frameworks for distributed computing, example including Condor,
Parallel Virtual Machine (PVM), and Message Passing Interface (MPI)
● One of the engaging features of clusters was that the computational
power of commodity machines could be advantages to solve problems
that were previo usly manageable only on expensive supercomputers.
● Besides, the clusters could be easily extended if more computational
power was needed.
3. Grid computing
● Grid computing is a description of the power grid, grid computing
suggests a new approach to access lar ge computational power, large
storage facilities, and a different variety of services.
● Users can consume resources in the same manner as they use other
utilities such as power, gas, and water.
● Grids initially developed as aggregations of geographically s catter
clusters by means of Internet connections.
● These types of clusters belonged to different organizations, and
arrangements were made among them to share the computational
power.
● This is different from a large cluster, a computing grid was a dynamic
collection of heterogeneous computing nodes, and its scale was
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9 ● Several developments made possible the spreading of computing grids:
a. Clusters is a quite common resources
b. they were frequently underutilized
c. New problems were re quiring computational power that move beyond
the capability of single clusters
d. The improvements in networking and the spreading of the Internet
made possible long -distance, high -bandwidth connectivity. All these
elements guide the development of grids.
● Cloud computing is frequently examined as the successor of grid
computing.
● In actuality, it related aspects of all these three major technologies.
Computing clouds are deployed in large data centers provided by a
single organization that provides services to others.
● In the case of mainframes clouds are distinguished by the fact of
having virtually unbounded capacity, being liberal to failures, and
being always on..
● In the case of clusters, The computing nodes that shape the
infrastructure of computing clouds are commodity machines.
● The services made available by a cloud vendor are consumed on a pay -
per-use basis, and clouds fully implement the utility vision established
by grid computing.
1.4 WEB 2.0
● Cloud computing delivers its services through the Web whic h is the
primary interface.
● The Web encloses a set of technologies and services that ease
interactive information sharing, collaboration, user -centered design,
and application composition.
● This transforms the Web into a rich platform for developing
applic ations, known as Web 2.0.
● This term captures a new way in which developers design applications
and deliver these services with the Internet and gives new experiences
for users of these applications and services.
● Web 2.0 provides interactivity and flexibil ity to Web pages, providing
added user experience by gaining Web -based access to all the
functions that are normally present in desktop applications.
● This potential is obtained by integrating a collection of standards and
technologies such as XML, Asynchr onous JavaScript and XML
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10 ● These technologies allow us to build applications advantageous to the
contribution of users, who presently become providers of content.
● The Internet opens new opportunities and markets for the Web, the
servic es of which can now be accessed from a variety of devices such
as mobile phones, car dashboards, TV sets, etc.
● Web 2.0 applications are especially dynamic, they upgrade
continuously, and new updates and features are integrated at a constant
rate.
● Web 2.0 applications aim to strengthen the “long tail” of Internet users
by making it available to everyone in terms of either media
accessibility.
● Examples of Web 2.0 applications are Google Documents, Google
Maps, Flickr, Facebook, Twitter, YouTube, Blogger..
● Social Websites take the biggest advantage of Web 2.0 applications.
The level of interaction in Websites such as Facebook or Flickr would
not have been possible without the support of AJAX technology.
● Facebook is a social networking site that leverages user activity to
enable content, and Blogger, like any other blogging website, provides
an online diary that is fed by users.
● Web 2.0. Applications and frameworks for implementing rich Internet
applications (RIAs) are fundamental for building cloud services
approachable to the extensive public.
● Web 2.0 applications definitely contributed to making people more
accustomed to the use of the Internet in their everyday lives and
● Web 2.0 which opened the path to the acceptance of cloud computing
as a standard.
● The I T infrastructure is offered through a Web interface.
1.5 SERVICE ORIENTED COMPUTING
● In this Service orientation computing defines the core reference model
for cloud computing systems.
● This approach acquires the concept of services as the main element of
application and system development.
● Service -oriented computing helps to develop rapid, low -cost, flexible,
interoperable, and evolvable applications and systems.
● A service is an abstraction act for a self -describing and platform
challenger component that ca n execute any function, any from a
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11 ● Virtually any segment of code that performs a task can be changed into
a service and expose its functionalities through a network -accessible
protocol.
● A service needs to be loosely coupled, reusable, programming
language independent, and location transparent. Loose coupling
enables services to obey different frameworks more easily and makes
them reusable.
● Independence from a specific platform increases services accessibility .
● Accordingly, a wider range of clients, which can improve services in
global registries and consume them in a location transparent manner,
can be served.
● Services are controlled and accumulated into a service -oriented
architecture, which is a logical way to arrange software systems to
provide end users or other entities distributed over the network with
services through published and discoverable interfaces.
● Service oriented computing establishes and broadcasts two important
concepts, which are also fundam ental to cloud computing:
1. quality of service (QoS)
2. Software -as-a-Service (SaaS)
○ Quality of service :
■ recognize a set of functional and nonfunctional attributes that can be
used to estimate the behavior of a service from different Viewpoints.
■ QoS could be p erformance metrics such as response time, or security
attributes, transactional integrity, reliability, scalability, and
availability.
■ QoS requirements are formed between the client and the provider
through an SLA that recognizes the least values for the QoS attributes
that are required to be satisfied upon the service call.
○ Software -as-a-Service
■ The idea of Software -as-a-Service introduces a new delivery model for
applications.
■ The word has been inherited from the application service providers
(ASPs), wh ich bring software services -based solutions over the wide
area network from a central datacenter and make them available on a
rental basis.
■ “The ASP is responsible for maintaining the infrastructure and making
available the application, and the client is discharged from
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12 ■ This SD model is possible because economies of scale are reached by
means of timeshare.
■ The SaaS approach achieves its full development with service -oriented
computing.
■ Loosely coupled software co mponents allow the delivery of complex
business processes and transactions as a service while allowing
applications to be composed on the fly and services to be reused from
everywhere and by anyone.
1.6 UTILITY -ORIENTED COMPUTING
● Utility computing is an o bservation of computing that defines a service
provisioning model for calculating services in which resources such as
storage, compute power, applications, and infrastructure are packaged
and offered on a pay/use basis.
● The concept of providing computing a s a utility like natural gas, water,
power, and telephone connection has a long past but has become a
reality with the advent of cloud computing.
● This vision can be observed as a “If computers of the kind I have
advocated become the computers of the futur e, then computing may
someday be organized as a public utility, just as the telephone system
is a public utility. The computer utility could become the pillar of a
new and important industry.”
● Utility -Oriented Computing is the first trace of this service -
provisioning model that began in the mainframe era.
● IBM and other mainframe providers offered mainframe power to
organizations like banks and government agencies throughout their
data centers.
● The business model initiated with utility computing brings new
requirements and conduct to improvements in mainframe technology.
● Alo provide additional features such as operating systems, process
control, and user -metering facilities.
● The idea of computing as utility abided and extended from the
business domain to t he educational sector with the advent of cluster
computing.
● Not only businesses but also research institutes became acquainted
with the idea of exploiting an external IT infrastructure on request.
● Computational science is one of the major operating facto rs for
building computing clusters, still requiring large computing power for
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13 ● The capillary scattering of the Internet and the Web enables the
technological means to notice utility computing on a worldwide scale
and through simple interfaces.
● Computing grids provided a planet scale distributed computing
infrastructure that was approachable on demand. Computing grids
bring the concept of utility computing to a new level.
● With the help of utility computing accessible on a wider scale, it is
easier to provide a trading infrastructure where grid products storage,
computation, and services are offered for or sold.
● Here E -commerce technology provided the infrastructure support for
utility computing. Example, significant interest in buying any kind of
good online spreads to the wider public: food, clothes, multimedia
products, and online services such as storage space and Web hosting.
● Applications were not only dispenses, they started to be composed as a
network of services provided by different entities.
● These services, accessible through the Internet, were made available
by charging on the report to usage.
● SOC widened the concept of what could have been retrieved as a
utility in a computer system, not only measuring power and storage but
also services and application components could be employed and
integrated on demand.
1.7 LET US SUM UP
● The vision and opportunities of cloud computing along with it s
characteristics and challenges.
● The cloud computing paradigm emerged as a result of the maturity and
convergence of several of its supporting models and technologies,
namely distributed computing, virtualization, Web 2.0, service
orientation, and utilit y computing.
● The only element that is shared among all the different views of cloud
computing is that cloud systems support dynamic provisioning of IT
services and adopt a utility -based cost model to price these services.
● This concept is applied across t he entire computing stack and enables
the dynamic provisioning of IT infrastructure and runtime
environments in the form of cloud -hosted platforms for the
development of scal - able applications and their services. This vision
is what inspires the Cloud Com puting Reference Model.
● This model identifies three major market segments for cloud
computing: Infrastructure -as-a-Service (IaaS), Platform -as-a-Service
(PaaS), and Software -as-a-Service (SaaS).
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14 1.8 LIST OF REFERENCES
● Mastering Cloud Computing, Rajkumar Buyya, Christian Vecchiola, S
ThamaraiSelvi, Tata McGraw Hill Education Private Limited, 2013.
1.9 UNIT END EXERCISES
1. What is the innovative characteristic of cloud computing?
2. Which are the technologies on which cloud computing relies?
3. Provide a brief cha racterization of a distributed system.
4. Define cloud computing and identify its core features.
5. What is the major revolution introduced by Web 2.0?
6. Describe the main characteristics of a service orientation.
7. What is utility computing?
8. Explain the Cloud Compu ting Reference Model.



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15 2
ELEMENTS OF PARALLEL COMPUTING
Unit Structure
2.0 Objectives
2.1 Introduction
2.2 Elements of Parallel Computing
2.3 Elements of Distributed Computing
2.4 Technologies for Distributed Computing
2.5 Summary
2.6 Reference for further reading
2.7 Unit End Exercises
2.0 OBJECTIVES
● To understand the concept of Parallel & Distributed computing.
● To study the elements of Parallel Distributed computings.
● To study the different types of technologies for Distributed
Computing.
2.1 INTRODUCTION
● The analogous/ simul taneous development in availability of big data
and in the number of simultaneous users on the Internet places
particular pressure on the need to take out computing tasks in parallel,
or simultaneously.
● Parallel and distributed computing occurs around man y different topic
areas in computer science, including algorithms, computer
architecture, networks, operating systems, and software engineering.
● During the early 21st century there was volatile growth in
multiprocessor design and other strategies for comp lex applications to
run rapidly.
● Parallel and distributed computing assemble on fundamental systems
concepts, such as concurrency, mutual exclusion, consistency in state
or memory manipulation, message -passing, and shared -memory
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16 ● The first steps in this conduct direction to the development of parallel
computing, which encloses techniques, architectures, and systems for
performing multiple activities in parallel.
● The term parallel computing has indistinct edges with the term
distributed computing and is often used in place of the latter term.
● In this chapter, we associate it with its proper characterization, which
involves the introduction of parallelism within a single computer by
coordinating the activity of multiple processors together.
2.2 ELEMEN TS OF PARALLEL COMPUTING
Parallel processing
● “Processing of multiple tasks simultaneously on multiple processors is
called parallel processing.”
● The parallel program consists of multiple active processes or tasks
simultaneously solving a particular problem .
● A given task is divided into multiple subtasks using a divide and
conquer technique (data structure), and each subtask is processed on a
different central processing unit (CPU).
● Programming on a multiprocessor system with the divide and conquer
techniq ue is called parallel programming.
● Many applications this day require more computing power than a
traditional sequential computer can offer.
● Parallel processing provides a cost effective solution to this problem
by increasing the number of CPUs in a compu ter and by computing an
efficient communication system between them.
● The workload can then be shared between different processors. This
arrangement results in higher computing power and performance than
a single processor system supply.
● The development of parallel processing is being determined by many
factors. The noticeable among them consist the following:
○ Computational requirements are regularly increasing in the areas of
both scientific and business computing. The technical computing
problems, which ne ed high speed estimation power, are associated
with life sciences, aerospace, geographical information systems,
mechanical design and analysis..
○ Sequential architectures are achieving physical limitations as they are
compulsion by the speed of light and th ermodynamics laws. The speed
at which sequential CPUs can handle is reaching saturation point, and
hence a substitute way to get high computational speed is to connect
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17 ○ Hardware refinement in pipelining, superscalar, and the like are non
scalable and require sophisticated compiler technology. Evolving like
compiler technology is a hard task.
Hardware architectures for parallel processing
● The basic elements of parallel processing are CPUs. The number of
instruction and data streams that can be processed at the same time,
computing systems are categorize into the following:
1. Single -instruction, single -data (SISD)
2. Single -instruction, multiple -data (SIMD)
3. Multiple -instruction, single -data (MISD)
4. Multiple -instruction, multiple -data (MIMD)
1. Single -instruction, single -data (SISD) systems
● An SISD computing system is a uniprocessor machine capable of
executing a single instruction,which operates on a single data stream
shown in figure. 1.
● In SISD, machine instructions are processed linearly, therefore
computers that acquire this model are popularly called sequential
computers.
● Most conventional computers are developed using the SISD model.
All the instructions and data to be handled have to be stored in primary
memory.
● The rate of the processing element in the SISD model is restricted by
the rate at which the computer can transfer information internally.
● Presiding representative SISD systems are IBM PC, Macintosh, and
workstations.

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18 2. Single -instruction, multiple -data (SIMD) systems
● SIMD computing system is a multiprocessor machine that executes the
same instruction on all the CPUs but utilizes different data streams
which is shown in figure 2.
● Machines based on an SIMD model are well matched to scientific
computing since they imply lots of vector and matrix operations.
● For example, statements such as
Ci = Ai * Bi
can be passed to all the processing elements, arranged data elements of
vectors A and B can be divided into multiple sets, and each processing
element can process one data set. presiding representative SIMD systems
are Cray’s vector processing machine and Thinking Machines’ cm
.Multiple -instruction, single -data (MISD) systems
● MISD computing system is a multiprocessor machine efficient of
executing different instructions on different processing elements but all of
them operating on the same data set shown in figure 3. For example,
statements such as
y = sin(x) + cos(x) + tan(x)
Which carry out different operations on the same data set. Machines built
using the MISD model are not beneficial in most of the applications; a few
machines are assembled, but none of them are accessible commercially.
They became more of an intellectual effort than a practical configuration.

Fig. 2 Single -instruction, multiple -data (SIMD) architecture.
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Fig. 3 Multiple -instruction, single -data (MISD) architecture.
3. Multiple -instruction, multiple -data (MIMD) systems
● A MIMD computing system is a multiprocessor machine ability of
executing multiple instructions o n multiple data sets shown in figure 4.
Each processing element in the MIMD model has individual
instruction and data streams, Therefore machines built using this
model are well matched to any kind of application.
● As opposed to SIMD and MISD machines, proc essing elements in
MIMD machines work asynchronously.
● MIMD machines are mainly classified into shared -memory MIMD and
distributed -memory MIMD based on the way processing elements are
coupled to the main memory.
● In the Shared memory MIMD machines, MIMD mo del, all the
processing elements are connected to a single global memory and they
all have access to it shown in figure 4.
● Systems established on this model are also called tightly coupled
multiprocessor systems. The communication between processing
elemen ts in this model takes place through the shared memory;
modification of the data stored in the global memory by one
processing element is noticeable to all other processing elements.
● Presiding representative shared memory MIMD systems are Silicon
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Fig. 4 Multiple -instructions, multiple -data (MIMD) architecture.
Approaches to parallel programming
● A sequential program is one that executes on a single processor and
has a single line of control.
● To m ake many processors cumulative work on a single program, the
program must be split into smaller independent chunks so that each
processor can work on separate chunks of the problem.
● The program decay in this way is a parallel program. An extensive
variety of parallel programming approaches are available.
● The most important between them are the following:
○ Data parallelism
○ Process parallelism
○ Farmer -and-worker model
● These types of models are all suitable for task level parallelism.
● In the point of data par allelism, the divide and conquer technique is
used to divide data into multiple sets, and each data set is processed on
different processing elements using the identical instruction.
● This approach is highly compatible for processing on machines based
on th e SIMD model. In the case of process parallelism, a given
operation has multiple activities that can be processed on multiple
processors.
● In the example of the farmer and worker model, a task distribution
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21 remaining processing elements are designated as slaves; the master
allocates jobs to slave processing elements and, on fulfillment, they
tell the master, which in turn collects results.
Levels of parallelism
● Levels of parallelism are ma rked based on the lumps of code (like a
grain size) that can be a probable candidate for parallelism. Below
Table lists the categories of code granularity for parallelism.
● All these approaches have a common goal:
○ To boost processor efficiency by hiding l atency.
○ To conceal latency, there must be another thread ready to run every
time a lengthy operation occurs.
The plan is to execute concurrently two or more single -threaded
applications, such as compiling, text formatting, database searching, and
device simulation.
● As shown in the table and depicted in figure 5, parallelism within an
application can be discovered at several levels.
○ Large grain (or task level)
○ Medium grain (or control level)
○ Fine grain (data level)
○ Very fine grain (multiple -instruction iss ue)
Levels of Parallelism
Grain Size Code Item Parallelized By
Large Separate and heavyweight
process Programmer
Medium Function or procedure Programmer
Fine Loop or instruction block Parallelizing compiler
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Fig. 5 Levels of parallelism in an application.
2.3 ELEMENTS OF DISTRIBUTED COMPUTING
● In elements of distributed computing, extend these concepts and
explore how multiple activities can be done by exploiting systems
collected from multiple heterogene ous machines and systems.
● Here we will learn the most common guidelines and patterns for
implementing distributed computing systems from the perspective of
the software designer.
● Distributed computing learning the models, architectures, and
algorithms used for building and managing distributed systems.
● “A distributed system is a collection of independent computers that
appears to its users as a single coherent system.”
● The various types of distributed computing systems that are mainly
focused on unified usa ge and aggregation of distributed resources.
● Communication is a fundamental feature of distributed computing.
● Distributed systems are composed of more than one computer that
participate together, it is necessary to enable some sort of data and
informatio n exchange between them, which generally occurs through
the network
● A distributed system is one in which components discovered at
networked computers communicate and coordinate their actions only
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23 ● The components of a distributed system communicate with some sort
of message passing. This is a term that encloses several
communication models.
Components of a distributed system
● A distributed system is the result of the interconnection of several
components that traverse the entire computing stack from hardware to
software.
● It comes out from the collaboration of several elements that by
working in conjunction give users the illusion of a single coherent
system.
● Figure 6 shows an overview of the different layers that are involved in
providing the services of a distributed system.

Fig. 6 A layered view of a distributed system.
● At the bottom layer, computer and network hardware represent the
physical infrastructure, these components are directly controlled by the
operating system, which provid es the basic services for interprocess
communication (IPC), process scheduling and management, and
resource management in terms of file system and local devices.
● The middleware layer strengthens such services to build a uniform
environment for the develop ment and deployment of distributed
applications. This layer supports the programming paradigms for
distributed systems.
● The top of the distributed system stack is acted by the applications and
services designed and developed to use the middleware. These ca n obey
several purposes and often expose their features in the form of
graphical user interfaces (GUIs) approachable locally or through the
Internet via a Web browser.

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24 Architectural styles for distributed computing
● Architectural styles are mainly used to find the vocabulary of
components and connectors that are used as instances of the style
together with a set of constraints on how they can be combined.
● Architectural styles for distributed systems are helpful in
understanding the different roles of compo nents in the system and how
they are distributed across multiple machines.
● Organization of the architectural styles into two major classes:
○ Software architectural styles
○ System architectural styles
● The first class has the relation to the logical organizat ion of the
software, the second class contains all those styles that express the
physical organization of distributed software systems in terms of their
major components.
Component and connectors
● These are the basic elements with which architectural styles are
defined.
● A component represents a unit of software that encapsulates a function
or a feature of the system.
● Examples of components can be programs, objects, processes, pipes,
and filters.
● A connector is a communication mechanism that enables cooper ation
and coordination among components.
● Differently from components, connectors are not encapsulated in a
single entity, but they are implemented in a distributed manner over
many system components.
Software architectural styles
● Software architectural st yles are based on the logical arrangement of
software components.
● They are helpful because they provide an intuitive view of the whole
system, despite its physical deployment.
● They also recognize the main abstractions that are used to shape the
component s of the system and the expected interaction patterns
between them.
● These models represent the foundations on top of which distributed
systems are designed from a logical point of view.
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25 Category Most Com mon Architectural Styles
Data -centered Repository Blackboard
Data flow Pipe and filter Batch sequential
Virtual machine Rule -based system Interpreter
Call and return
Main program and subroutine call/top -down
systems Object -oriented systems La yered systems
Independent
components Communicating processes Event systems

2.4 TECHNOLOGIES FOR DISTRIBUTED
COMPUTING
2.4.1 Remote procedure call
● RPC is the fundamental abstraction that allows the execution of
procedures on client’s request.
● RPC allo ws increasing the concept of a procedure call completely
outside the boundaries of a process and a single memory address
space.
● The called procedure and calling procedure may reside on the same
system or they may be on different systems in a network.
● Figure 7 shows the crucial components that enable an RPC system.

Fig. 7 The RPC reference model.
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26 ● Therefore, developing a system strengthening RPC for IPC contain the
following steps:
○ Design and implementation of the server procedures that will be
uncovered for remote invocation.
○ Registration of remote procedures with the RPC server on the node
where they will be made accessible.
○ Design and implementation of the client code that invokes the remote
procedures (RPC).
2.4.2 Distributed object frameworks
1. Distrib uted object frameworks enhance object -oriented programming
systems by allowing objects to be distributed across a heterogeneous
network and provide facilities so that they can clearly act as though
they were unavailable on the same address space.
2. Distribu ted object frameworks strengthen the basic mechanism
introduced with RPC and extend it to enable the remote invocation of
object methods and to keep watch on references to objects made
available through a network connection.
3. With respect to the RPC model, the infrastructure manages types that
are exposed through well known interfaces rather than procedures.
Therefore, the common interaction pattern will be like this:
a. The server process keeps track of a registry of active objects that are
made available to other processes. On the report of the specific
implementation, active objects can be published using interface
definitions / class definitions.
b. The client process, with a given addressing scheme, obtains a
reference to the active remote object. This refere nce is acted by a
pointer to an instance that is of a shared type of interface and class
definition.
c. The client process invokes the methods on the active object by calling
them through the reference previously secured. Parameters and return
values are mars haled to take place in the case of RPC.
Object activation and lifetime
● The life span of an object instance is a crucial element in distributed
object -oriented systems.
● The single memory address space scenario, objects are definitely
created by the program mer, and their references are made available by
passing them from one object instance to another.
● A distributed framework introduces additional issues that require a
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27

Com mon object request broker architecture (CORBA)
● “CORBA is a specification described by the Object Management
Group (OMG) for providing cross platform and cross -language
interoperability between distributed components.” The specification
was fundamentally de signed to provide an interoperation standard that
could be effectively used at the industrial level.
● A main and important component in the CORBA architecture is the
Object Request Broker (ORB), which reacts as a central object bus.
● A CORBA object registe rs with the ORB the interface it is uncovering,
and clients can obtain a reference to that interface and invoke methods
on it.
Distributed component object model (DCOM/COM1)
● DCOM, behind time integrated and developed into COM1, is the
solution provided by Microsoft for distributed object programming
before the introduction of .NET technology.
● DCOM allows a set of features allowing the use of COM components
beyond the process boundaries.
● A COM object recognizes a component that encapsulates a set of and
related operations; it was designed to be easily clubbed into another
application to strengthen the features disclosed through its interface.
Java remote method invocation (RMI)
● Java RMI is a standard technology provided by Java Oracle for
enabling RPC cal l among distributed Java objects.
● RMI defines an infrastructure that enables the invocation of methods
on objects that are found on different Java Virtual Machines (JVMs)
residing either on the local node or on a remote one.
.NET remoting
● .NET Remoting is the technology enabling IPC among .NET
applications.
● It provides developers with a uniform platform for retrieving remote
objects from within any application developed in any of the languages
supported by .NET.
Service -oriented computing
● Service oriente d computing arrange distributed systems in terms of
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28 ● Service orientation expresses applications and software systems as
aggregations of services that are correlated within a service -oriented
architecture (SOA).
● A service encapsulates a software component that enables a set of
coherent and related functionalities that can be reused and integrated
into huge and more complex applications. The term service is a
general abstraction that encomp asses various different
implementations using different technologies and protocols.
● Four major characteristics that identify a service:
1. Boundaries are explicit.
2. Services are autonomous
3. Services divide the schema and contracts, not class or interface
definitions.
4. Service compatibility is determined based on policy.
Service -oriented architecture
● SOA is an architectural style supporting service orientation.
● It arranges a software system into a collection of interacting services.
● SOA encloses a set of desig n principles that structure system
development and provide means for integrating components into a
coherent and decentralized system.
● SOA based computing packages functionalities into a set of
interoperable services, which can be non -discriminatory into di fferent
software systems belonging to individual business domains.
● The following guiding principles which characterize SOA platforms,
are winning features within an enterprise context:
○ Standardized service contract.
○ Loose coupling
○ Abstraction.
○ Reusability.
○ Autonomy
○ Lack of state
○ Discoverability
○ Composability
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29 2.5 LET US SUM UP
● Parallel and distributed computing emerged as a solution for solving
complex
● Parallel computing introduces models and architectures for performing
multiple tasks within a single co mputing node or a set of tightly
coupled nodes with homogeneous hardware.
● Parallelism is achieved by leveraging hardware capable of processing
multiple instructions in parallel.
● Distributed systems constitute a large umbrella under which several
differen t software systems are classified.
2.6 LIST OF REFERENCES
● Mastering Cloud Computing, RajkumarBuyya, Christian Vecchiola, S
ThamaraiSelvi, Tata McGraw Hill Education Private Limited, 2013.
2.7 UNIT END EXERCISES
1. What is the difference between parallel and distributed computing?
2. What is a SIMD architecture?
3. Describe the different levels of parallelism that can be obtained in a
computing system.
4. What is a distributed system? What are the components that
characterize it?

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30 3
CLOUD COMPUTING ARCHITECTURE
Unit Structure
3.0 Objective
3.1 Introduction
3.2 Cloud Computing Architecture
3.3 The cloud reference model
3.4 Cloud Computing Services: SAAS, PAAS, IAAS
3.5 Types of clouds.
3.6 Summary
3.7 Reference for further reading
3.8 Unit End Exercises
3.0 OBJECTIVE
● To understand the architecture of cloud computing.
● To understand the different types of cloud computing servcies.
● To understand the enterprise architecture used in cloud computing.
● To study the different types of clouds.
3.1 INTRODUCTION
● Cloud Computing can be defined as the exercise of using a network of
remote servers hosted on the Internet to store, manage, and process
data, alternatively a local server or a may be a personal computer.
● Organizations offering such types of cloud computing services are
called cloud providers and charge for cloud computing services based
on their usage.
● Grids and clusters are the base for cloud computing.
3.2 CLOUD COMPUTING ARCHITECTURE
● In the representation, a cloud is implemented usi ng a datacenter, a
collection of clusters, or a heterogeneous distributed system which is
composed of desktop personal computers, workstations, and servers.
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31 ● When we deliver the specific service t o the end user, different layers
can be stacked on top of the virtual infrastructure like a virtual
machine manager, a development platform, or a specific application
middleware.
● The cloud computing paradigm came out as an output of the
convergence of vari ous existing models, technologies, and concepts
that switch the way we deliver and use IT services.
● A definition of Cloud computing:
“Cloud computing is a utility -oriented and Internet -centric way of
delivering IT services on demand. These services cover the entire
computing stack: from the hardware infrastructure packaged as a set of
virtual machines to software services such as development platforms and
distributed applications.”
3.3 THE CLOUD REFERENCE MODEL
● IT service can be consumed as a utility and delivered through a
network
● Cloud computing supports these IT services, most likely the Internet.
● The characterization in cloud computing includes various aspects:
infrastructure, development platforms, application and services.
4.3.1 Architecture of Clou d Computing
● The cloud computing a layered view covering the whole stack from
hardware appliances to software systems.
● Cloud resources in this layer are implemented using a datacenter in
which hundreds and thousands of nodes are stacked in conjunction.
● Cloud infrastructure can be heterogeneous in nature because it contains
a variety of resources, like clusters and even networked personal
computers, can be used to build it.
● Database systems and other storage services can also be a portion of the
infrastruc ture.
● The physical infrastructure is handled by the middleware, the objectives
of which are to provide a suitable runtime environment for applications
and to utilize the resources.
● At the bottom layer of the stack, virtualization technologies are used to
assure runtime environment customization, application isolation,
sandboxing, and quality of service.
● Hardware virtualization is one of the most commonly used at this level.
● Hypervisors control the small resources and show the distributed
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32 ● With the use of virtual machine technology it is enable to elegantly
partition the hardware resources for example CPU and memory and to
virtualize specific devices, thus fulfilling the requirements of users and
applicat ions.

Fig. 1 The cloud computing architecture.
● Cloud computing solutions are generally matched with storage and
network virtualization plans of action, which enable the infrastructure
to be fully virtualized and controlled.
● As per the particular service provided to the end users, other
virtualization technology can be used, for example, programming -level
virtualization helps in creating a flexible runtime environment where
applications can be executed and controlled.
● This implies that applications hoste d on the cloud developed with a
specific type of technology or a programming language, such as Java,
.NET, or Python.
● Infrastructure management is the main function of core middleware,
which provides support such as debate of the quality of service,
admis sion control, execution management and monitoring, accounting,
and billing.
● The cloud hosting platforms and resources are generally classified as a
○ Infrastructure -as-a-Service (IaaS) solution.
It provides both the management layer and the physical infrast ructure;
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33 management layer is frequently integrated with other IaaS solutions that
provide physical infrastructure and adds value.
● IaaS solutions are appropriate for designing the system infrastructure
but it provides limited services to develop applications. This type of
service is provided by cloud programming environments and tools,
● The span of tools consist of Web -based interfaces, command -line
tools, and frameworks for concurrent an d distributed programming. In
this outline, users develop their applications specifically for the cloud
by using the API reveal at the user -level middleware. For this reason,
this method is known as Platform -as-a-Service.
● The top most layer of the referenc e model consists of services
delivered at the application level. These are called Software -as-a-
Service.
● Web -based applications depend on the cloud to provide service to end
users. The cloud provided by IaaS and PaaS solutions permit
independent software vendors to deliver their application services over
the Internet.
● Behavior automatically is an implementation of SaaS which should
feature, whereas PaaS and IaaS provide this functionality as a part of
the API shows to users.
● The reference model also descr ibes the concept of everything as a
Service. This is one of the most prime elements of cloud computing:
Cloud services from different providers can be combined to provide a
completely large integrated solution covering all the computing stack
of a system.
3.4 CLOUD COMPUT ING SERVICES: SAAS, PAAS,
IAAS
Software as a service (SaaS)
● Software -as-a-Service (SaaS) is a software delivery model that gives
access to applications through the Internet as a Web Based service.
● It provides free users from complex hardw are and software
management by offloading such tasks to third parties, which build
applications accessible to multiple users through a Web browser.
● Example:customers neither need to install anything on their premises
nor have to pay costs to buy the softw are and the need licenses. They
directly access the application website, enter their username and
password and other billing details, and can immediately use the
application.
● On the source side, they keep maintaining specific details and features
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34 ● SaaS is a software delivery model, (one -to-many) whereby an
application is shared across multiple users.
● Example includes CRM3 and ERP4 applications that add up common
needs for almost all enterprises, from small to medium -sized and large
businesses.
● This structure relives the development of software platforms that
provide a general set of features and support specialization and ease of
integration of new components.
● SaaS applications are naturally multitenant.
● The term SaaS was then invented in 2001 by the Software Information
& Industry Association (SIIA).
● The analysis done by SIIA was mainly aligned to cover application
service providers (ASPs) and all their variations, which imprison th e
concept of software applications consumed as a service in a wide
sense.
● ASPs Core characteristics of SaaS:
○ The product sold to customers is an application approach.
○ The application is centrally managed.
○ The service delivered is one -to-many.
○ The servi ce provides is an integrated solution delivered on the
contract, which means provided as promised
Platform as a service
● Platform -as-a-Service (PaaS) which provides a development and
deployment platform for running applications in the cloud.
● They compose t he middleware on top of which applications are built.
● Following figure shows a general overview of the features
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35

Fig.2. The Platform -as-a-Service reference model
● Application management is the key functionality of the middleware
systems.
● PaaS provides applications with a runtime environment and does not
shows any service for managing the underlying infrastructure.
● They automate the process of deploying applications to the
infrastructure, configuring application components, provis ioning and
configuring supporting technologies such as load balancers and
databases, and managing system change based on policies set by the
user.
● The core middleware is responsible for managing the resources and
scaling applications on demand, according to the adherence made with
users.
● The core middleware exposes interfaces that enable programming and
installing applications on the cloud.
● The PaaS model provides a complete object model for representing an
application and provides a programming language -based approach.
● In this point the traditional development environments can be used to
design and develop applications, which are then deployed on the cloud
by using the APIs revealed by the PaaS provider.
● PaaS offers middleware for developing applications together with the
infrastructure.

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36 Infrastructure as a service or hardware as a service
● Infrastructure as a Service is the most popular model and developed
market segment of cloud computing.
● They deliver customizable infrastructure on request.
● The IaaS offers single servers for entire infrastructures, including
network devices, load balancers, and database and Web servers.
● The main aim of this technology used to deliver and implement these
solutions is hardware virtualization:
○ one or more virtual machi nes configured and interconnected
○ Virtual machines also constitute the atomic components that are
installed and charged according to the specific features of the virtual
hardware:
■ memory
■ number of processors, and
■ disk storage
● IaaS shows all the benefit s of hardware virtualization:
○ workload partitioning
■ application isolation
■ sandboxing, and
■ hardware tuning
● HaaS allows better utilization of the IT infrastructure and provides a
more safe environment for executing third party applications.
● Figure 2 sh ows a total view of the components setup an Infrastructure -
as-a-Service.
● It is possible to identified three principal layers:
○ the physical infrastructure
○ the software management infrastructure
○ the user interface
● At the top layer the user interface allow to access the services exposed
by the software management infrastructure. This types of an interface
is generally based on Web technologies:
○ Web services
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37 ○ mash -ups
● These automation allow applications or final users to access the
services exposed by the underlying infrastructure.
● A central role of the scheduler, is in charge of allocating the execution
of virtual machine instances. The scheduler communicates with the
other components that perform a variety of tasks.

Fig.3. Infrastructur e-as-a-Service reference implementation
3.5 TYPES OF CLOUDS
● Clouds compose the primary outcome of cloud computing.
● They are a type of parallel and distributed system, physical and virtual
computers conferred as a unified computing asset.
● Clouds set up t he infrastructure on top of services that are
implemented and delivered to customers. Such infrastructures can be
of different types and provide useful information about the nature and
the services offered by the cloud.
● A more convenient classification is given according to the
administrative domain of a cloud: It identifies the boundaries within
which cloud computing services are implemented, provides hints on
the underlying infrastructure take on to support such services, and
qualifies them. It is then p ossible to evolve four different types of
cloud:
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38
● Public clouds.
○ The cloud is open to the wider public.
● Private clouds.
○ The cloud is executed within the private property of an institution and
generally made accessible to the members of the institution
● Hybrid clouds.
○ The cloud is a combination of the two previous clouds and most likely
identifies a private cloud that has been augmented with services hosted
in a public cloud.
● Community clouds.
○ The cloud is distinguished by a multi administrative domai n consisting
of different deployment models (public, private, and hybrid).
Public clouds
● Public clouds account for the first expression of cloud computing.
● They are an awareness of the canonical view of cloud computing in
which the services provided are m ade available to anyone, from
anywhere, and at any time through the Network.
● From a structural point of view they are a distributed system, most
likely composed of one or more data centers connected together, on
top of which the specific services offered by the cloud are
implemented.
● Any customer can easily agree with the cloud provider, enter her
username and password and billing details.
● They extend results to reduce IT infrastructure costs and serve as a
viable option for handling peak loads on the loc al infrastructure.
● They are used for small enterprises, which are able to initiate their
businesses without large up -front investments by completely relying
on public infrastructure for their IT needs.
● A public cloud can recommend any type of service suc h as
infrastructure, platform, or applications. For example, Amazon EC2 is
a public cloud that delivers infrastructure as a service. Google
AppEngine is also called public cloud that provides an application
development platform as a service; and SalesForce service.com is a
public cloud that provides software as a service.

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39 Private clouds
● Private clouds, which are the same as public clouds, but their resource
provisioning model is restricted within the boundaries of an
organization.
● Private clouds have the b enefit of keeping the core business operations
in house by depending on the existing IT infrastructure and reducing
the cost of maintaining it once the cloud has been set up.
● The private cloud can provide services to a different range of users.
● private cl ouds is the possibility of testing applications and systems at a
comparatively less price rather than public clouds before implementing
them on the public virtual infrastructure.
● The main advantages of a private cloud computing infrastructure:
1. Customer in formation protection.
2. Infrastructure ensuring SLAs.
3. Compliance with standard procedures and operations.

Fig.4. Private Clouds hardware and software stack.
Hybrid clouds
● A hybrid cloud could be an attractive opportunity for taking advantage
of the best of the private and public clouds. This shows the
development and diffusion of hybrid clouds.
● Hybrid clouds enable enterprises to utilize existing IT infrastructures,
maintain sensitive information within the area, and naturally increase
and reduce by prov isioning external resources and releasing them
when they’re no longer needed.
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40 ● Figure 5 demonstrate the a general overview of a hybrid cloud:
○ It is a heterogeneous distributed system consisting of a private cloud
that integrates supplementary services or resources from one or more
public clouds.
○ For this intention they are also called heterogeneous clouds.
○ Hybrid clouds look into scalability issues by leveraging external
resources for exceeding

Fig.5. Hybrid/heterogeneous cloud overview.
Community cloud s
● Community clouds are distributed systems created by integration of
services of different clouds to handle the specific requirement of an
industry, a community, or a business sector.
● The National Institute of Standards and Technologies characteristic
community clouds as follows:
○ The infrastructure is shared by different organizations and supports a
certain community that has shared concerns.
○ It may be controlled by the organizations or a third party and may
exist on premise or off premise.
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41

Fig. 6 gene ral view community clouds
● Figure 6 shows a view of the usage scenario of community clouds,
jointly with reference architecture.
● The users of a distinct community cloud fall into a well identified
community, sharing the same concerns or needs such as gover nment
bodies, industries, or even simple users, but all of them concentrate on
the same problem for their interaction with the cloud.
● Community clouds are the services that are generally delivered within
the institution that owns the cloud.
● Candidate dist rict for community clouds are as follows:
○ Media industry
■ Where Companies are finding low -cost, agile, and simple solutions to
better the efficiency of content production.
■ Most media involve an expanded ecosystem of partners.
■ Community clouds can provide a shared environment where services
can ease business to business participation and give the horsepower in
terms of aggregate bandwidth, CPU, and storage required to efficiently
support media production.
○ Healthcare industry.
■ In the healthcare industry, there are different storyline in which
community clouds are used.
■ Community clouds provide a global platform on which to share
information and knowledge without telling sensitive data maintained
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42 ■ The naturally hybrid dep loyment model of community clouds supports
the storing of patient data in a private cloud while using the shared
infrastructure for noncritical services and automating processes within
hospitals.
○ Energy and other core industries.
■ These industries concer n different service providers, vendors, and
organizations, a community cloud can give the right type of
infrastructure to create an open and upright market.
○ Public sector.
■ The public sector can limit the adoption of public cloud offerings.
■ governmental p rocesses involve several institutions and agencies
■ Aimed at providing strategic solutions at local, national, and
international administrative levels.
■ involve business -to-administration, citizen -to-administration, and
possibly business -to-business process es.
■ Examples, invoice approval, infrastructure planning, and public
hearings.
○ Scientific research.
■ THis is an interesting example of community clouds.
■ In this point, the common interest in handling and using different
organizations to split a large dist ributed infrastructure is scientific
computing.
The Advantages of community clouds:
● Openness.
Clouds are open systems in which fair competition between different
solutions can occur.
● Community.
Providing resources and services, the infrastructure turns out to be more
scalable.
● Graceful failures.
There is no single provider & vendor in control of the infrastructure, there
is no chance of a single point of failure.
● Convenience and control.
There is no dispute between convenience and control because the cloud is
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43 ● Environmental sustainability.
These clouds tend to be more organic by increasing and shrinking in a
symbiotic relationship to support the demand of the community.
3.6 SUMMARY
● Three service models. Software -as-a-Service (SaaS), Platform -as-a-
Service (PaaS), and Infrastructure -as-a-Service (IaaS).
● Four deployment models. Public clouds, private clouds, community
clouds, and hybrid clouds.
● Clou d computing has been rapidly adopted in industry, there are
several open research challenges in areas such as management of cloud
computing systems, their security, and social and organizational
issues.
3.7 REFERENCE FOR FURTHER READING
● Enterprise Cloud Co mputing Technology, Architecture, Applications,
GautamShroff, Cambridge University Press, 2010
● Mastering In Cloud Computing, RajkumarBuyya, Christian Vecchiola
And ThamariSelvi S, Tata Mcgraw -Hill Education, 2013
● Cloud Computing: A Practical Approach, Anth ony T Velte, Tata
Mcgraw Hill, 2009
3.8 UNIT END EXERCISES
1. What does Infrastructure -as-a-Service refer to?
2. What are the main characteristics of a Platform -as-a-Service solution?
3. What does the acronym SaaS mean? How does it relate to cloud
computing?
4. Classi fy the various types of clouds.
5. Give an example of the public cloud.

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44 4
VIRTUALIZATION
Unit Structure
4.0 Objective
4.1 Introduction
4.2 Characteristics of Virtualized Environments
4.3 Taxonomy of Virtualization Techniques.
4.4 Summary
4.5 Reference for further reading
4.6 Unit End Exercises
4.0 OBJECTIVE
● To understand the fundamental components of cloud computing
● To study the application running on an execution environment using
virtualization.
● To understand the different virtualization techniques.
● To study the characteristics of Virtualized Environments.
4.1 INTRODUCTION
● Virtualization is a large universe of technologies and concepts of an
abstract environment whether virtual hardware or an operating system
to run applications.
● The word virtualization is often synonymous with hardware
virtualization, which plays a fundame ntal role in effectively delivering
Infrastructure -as-a-Service (IaaS) solutions for cloud computing.
● Virtualization technologies provide virtual environments at the
operating system level, the programming language level, and the
application level.
● Virtu alization technologies provide a virtual environment for not only
executing applications but also for storage, memory, and networking.
1. Increased performance and computing capacity .
a. At present, the average end -user desktop computer is powerful enough
to meet almost all the requirements of everyday computing, with extra
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45 b. All these desktop computers have resources enough to host a virtual
machine manager and execute a virtual machine with by far acceptable
performance.
c. The same deliberation applies to the high -end side of the PC market,
where supercomputers can provide huge compute power that can make
room for the execution of hundreds or thousands of virtual machines.
2. Underutilized hardware and software resources.
a. Hardware and software underutilization is occurring due to
i. Increased performance and computing capacity
ii. The effect of finite use of resources.
3. Lack of space
a. The ongoing need for additional capacity, whether storage or compute
power, makes data centers grow rapidly.
b. Companies such as Google and Microsoft expand their infrastructures
by building data centers as large as football fields that are able to host
thousands of nodes.
c. Although this is viable for IT giants, in most cases enterprises cannot
afford to build another data center to accommodate additional resource
capacity.
d. This condition, along with hardware underutilization, has led to the
diffusion of a technique called server consolidation,1 for which
virtualization technologies are fundamental.
4. Greening initiativ es.
a. Nowadays, companies are increasingly looking for ways to reduce the
amount of energy they consume and to reduce their carbon footprint.
b. Data centers are one of the major power consumers; they contribute
consistently to the impact that a company has o n the environment.
c. Preserving a data center operation not only involves keeping servers on,
but a great deal of energy is also consumed in keeping them cool.
d. Infrastructures for cooling have a significant impact on the carbon
footprint of a data center.
e. Hence, reducing the number of servers through server consolidation
will surely reduce the impact of cooling and power consumption of a
data center. Virtualization technologies can provide an efficient way of
consolidating servers.

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46 5. Rise of administrative c osts.
a. Power consumption and cooling costs become higher than the cost of
IT equipment nowadays.
b. The increased demand for extra capacity, which translates into more
servers in a data center.
c. Which is responsible for a significant increment in administrativ e
costs.
d. Common system administration duties consist of hardware
monitoring, defective hardware replacement, server setup and updates,
server resources monitoring, and backups.
e. These are labor -intensive operations, and the higher the number of
servers th at have to be managed, the higher the administrative costs.
f. Virtualization helps to reduce the number of required servers for a
given workload, thus reducing the cost of the administrative
manpower.
4.2 CHARACTERISTICS OF VIRTUALIZED
ENVIRONMENTS
● Virtual ization is a big concept that refers to the creation of a virtual
version of something, whether hardware, a software environment,
storage, or a network.
● A virtualized environment has three major components: guest, host,
and virtualization layer.
● The gues t acts for the system component that communicates with the
virtualization layer rather than with the host, as would normally
happen.
● The host shows the original environment where the guest is expected
to be managed.
● The virtualization layer is controlling for recreating the same or a
different environment where the guest will operate shown in figure 1.
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47

Figure 1 . Virtualization reference model.
● The most instinctive and popular is represented by hardware
virtualization, which also composes the original re alization of the
virtualization concept.
● In the hardware virtualization, the guest is represented by a system
image made up of an operating system and installed applications.
These are fixed on top of virtual hardware that is handled and managed
by the vi rtualization layer, also called as the virtual machine manager.
The host is represented by the physical hardware, and the operating
system, that describe the environment where the virtual machine
manager is running.
● In the case of virtual storage, the gue sts might be client applications or
users that interact with the virtual storage management software
deployed on top of the real storage system.
● Virtual networking is also similar as above: The guest applications and
users communicate with a virtual networ k, such as a VPN, which is
managed by specific software (also called VPN client) that employs
the physical network available on the node. VPNs are functional for
creating the illusion of being within a different physical network and
thus acquiring the reso urces in it, which would otherwise not be
available.
4.2.1 Increased security
● The capability to handle the execution of a guest in a completely clear
manner opens new potential for delivering a secure, controlled
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48 ● The virtual machin e shows an emulated environment in which the
guest is accomplished.
● All the operations of the guest are normally performed opposite to the
virtual machine, which then translates and reflects them to the host.
● This level of dissimulation enables the virtua l machine manager to
control and filter the activity of the guest, thus avert some harmful
operations from being performed.
● Resources exposed by the host can then be hidden or simply secured
from the guest.
● Besides, sensitive information that is contained in the host can be
naturally hidden without the need to install complex security policies.
● Increased security is a requirement when coordinating with untrusted
code.
● The JVM and the .NET runtime provide substantial security policies
for customizing the e xecution environment of applications.
● Hardware virtualization solutions like VMware Desktop, VirtualBox,
and Parallels provide the ability to create a virtual computer with
customized virtual hardware on top of which a new operating system
can be installe d.
● The file system exposed by the virtual computer is completely
different from the one of the host machine.
● This is the perfect environment for running applications without
influencing other users in the environment.
4.2.2 Managed execution
● Virtualizat ion of the execution environment not only enables increased
security, but a wider range of features also can be implemented.
● The sharing, aggregation, emulation, and isolation are the most
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Figure 2 . Functio ns enabled by managed execution.
1. Sharing.
a. Virtualization enables the formation of a separate computing
environment within the same host.
b. In this way it is possible to fully utilize the capabilities of a powerful
guest, which would otherwise be underutiliz ed.
c. Sharing is an important feature in virtualized data centers, where this
basic feature is used to reduce the number of active servers and limit
power consumption.
2. Aggregation.
a. Virtualization also enables aggregation, which is the opposite action.
b. A group of different hosts can be bound together and represented to
guests as a single virtual host.
c. This function is naturally implemented in middleware for distributed
computing, with a classical example represented by cluster
management software, which ha rnesses the physical resources of a
homogeneous group of machines and represents them as a single
resource.
3. Emulation.
a. Guest programs are executed inside an environment that is controlled
by the virtualization layer, which ultimately is a program.
b. This en ables controlling and tuning the environment that is revealed to
guests. For illustration, a completely different environment with
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50 guest programs needs specific characteristics that are no t available in
the physical host.
c. This feature becomes very important for testing purposes, where a
specific guest has to be authenticated against different platforms or
architectures and the wide range of options is not easily attainable during
the devel opment.
4. Isolation.
a. Virtualization enables guests whether they are OS, applications, or
other entities with a completely different environment, in which they
are carried out.
b. The guest program accomplishes its activity by interacting with an
abstraction l ayer, which gives access to the underlying resources.
c. Isolation comes with several benefits; for example, it enables multiple
guests to run on the one and the same host without interfering with each
other.
d. Second, it provides a segregation between the ho st and the guest.
e. The virtual machine can sieve the activity of the guest and prevent
harmful operations against the host.
4.2.3 Portability
● The concept of portability registers in different ways according to the
specific type of virtualization considered .
● In the point of a hardware virtualization solution, the guest is filled
into a virtual image that, in most cases, can be securely moved and
executed on top of various virtual machines.
● Virtual images are generally exclusive formats that need a specific
virtual machine manager to be executed. In the programming level
virtualization, as implemented by the JVM or the .NET runtime, the
binary code act for application components can be run without any
recompilation on any implementation of the corresponding virtual
machine.
● This makes the application development cycle more pliable and
application deployment very straightforward: One version of the
application, in most cases, is able to run on different platforms with no
updates.
● Last, portability allows you r own system to always be with you and
ready to use as long as the required virtual machine manager is
available.
● This requirement is, in general, less rigorous than having all the
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51 4.3 T AXONOMY OF VIRTUALIZATION TECHNIQUES
● Virtualization covers an extensive range of emulation techniques that
are applied to different areas of computing.
● A classification of these techniques helps us better recognize their
characteristics and use shown in f igure 3.

Figure 3 . A taxonomy of virtualization techniques.
● The first classification disfavours against the service or entity that is
being emulated. Virtualization is generally used to emulate execution
environments, storage, and networks.
● Among these c ategories, execution virtualization constitutes the oldest,
most popular, and most developed area.
● The execution virtualization techniques are divided into two major
categories by considering the type of host they require.
● Process -level techniques are im plemented on top of an existing
operating system, which has full power of the hardware.
● System -level techniques are implemented directly on hardware and
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52 ● Above two categories we can li st out various techniques that provide
the guest a different type of virtual computing environment: bare
hardware, operating system resources, low -level programming
language, and application libraries.
Execution virtualization
● Execution virtualization con sists of all methods that aim to emulate an
execution environment that is different from the one hosting the
virtualization layer.
● All these techniques focus their interest on providing support for the
execution of programs, whether these are the operatin g system, a
binary specification of a program compiled against an abstract
machine model, or an application.
● Hence execution virtualization can be executed directly on top of the
hardware by the OS, an application, or libraries dynamically or
statically c onnected to an application image.
1. Machine reference model
● Virtualizing an execution environment at different levels of the
computing stack requires a reference model that defines the interfaces
between the levels of abstractions, which hide implementation details.
● From this viewpoint, virtualization techniques actually replace one of
the layers and intercept the calls that are directed toward it.
● Therefore, a clear uncoupling between layers clarify their
implementation, which only requires the emulation of the interfaces
and a proper interaction with the underlying layer.
● Modern computing systems can be represented in terms of the
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Figure 4 A machine reference model.
2. Hardware -level virtualization
● Virtualization tech nique that enables an abstract execution
environment in terms of computer hardware on peak of which a guest
operating system can be run.
● In this model, the guest is actuated by the OS, the host by the physical
computer hardware, the virtual machine by its emulation, and the
virtual machine manager by the hypervisor shown in figure 5.
● The hypervisor is generally a program or a combination of application,
software and hardware that allows the abstraction of the underlying
physical hardware.

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54 ● Hardware -level virtualization is also called system virtualization, since
it supply ISA to virtual machines, which is the characterization of the
hardware interface of a system.
● This is to differentiate it from proce ss virtual machines, which expose
ABI to virtual machines.
Hypervisors
● An elementary element of hardware virtualization is the hypervisor. It
re-form a hardware environment in which guest operating systems are
installed.
● Types of hypervisor:
○ Type I hyper visors execute on top of the hardware. Therefore, they
grasp the place of the OS and communicate directly with the ISA
interface exposed by the underlying hardware, and they imitate this
interface in order to permit the management of guest operating
system s. This hypervisor is also called a native virtual machine.
○ Type II hypervisors need the support of an operating system to enable
virtualization services. Its mean programs controlled by the OS, which
communicate with it through the ABI and emulate the ISA of virtual
hardware for guest operating systems. Shown in figure 6.

Figure 6 Hosted (left) and native (right) virtual machines.
Hardware virtualization techniques
● Hardware -assisted virtualization.
○ This term refers to a framework in which the hardware provides
architectural aid for creating a virtual machine manager which is able
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55 ○ This technique was initially introduced in the IBM System 370.
Examples is the extensions to the x86 -64 bit architecture introduced
with Intel VT and AMD V.
● Full virtualization.
○ Full virtualization is the ability to run a program and application, such
as an operating system, which resides directly on top of a virtual
machine and without any alteration, as though it were ru n on the raw
hardware.
● Paravirtualization.
○ This is a not -transparent virtualization solution that enables execution
of thin virtual machine managers.
○ Paravirtualization methods expose a software interface to the virtual
machine that is moderately change d or up -to- date from the host and,
as a consequence, guests need to be modified. .
● Partial virtualization.
○ Partial virtualization enables a partial emulation of the primary
hardware, thus not permitting the complete execution of the guest
operating syst em in complete isolation.
○ Partial virtualization enables many applications to run translucency,
but not all the features of the OS can be supported.
Operating system -level virtualization
● Operating system -level virtualization creates different and separat ed
execution environments for applications that are controlled and
handled concurrently.
● Operating systems supporting this type of virtualization are general -
purpose, time shared operating systems with the capability to provide
stronger namespace and resou rce isolation.
Programming language -level virtualization
● Programming language level virtualization is mainly used to attain
ease of deployment of applications, managed implementation and
portability across different platforms and operating systems.
3. Appli cation -level virtualization
● Application -level virtualization allows applications to be executed in
runtime environments that do not natively help all the features required
by such applications.

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56 4.4 SUMMARY
● The term virtualization is a large umbrella un der which a variety of
technologies and concepts are classified.
● The common root of all forms of virtualization is the ability to provide
the illusion of a specific environment, whether a runtime environment,
a storage facility, a network connection, or a remote desktop, by using
some kind of emulation or abstraction layer.
4.5 REFERENCE FOR FURTHER READING
● Enterprise Cloud Computing Technology, Architecture, Applications,
GautamShroff, Cambridge University Press, 2010
● Mastering In Cloud Computing, Rajkum arBuyya, Christian Vecchiola
And ThamariSelvi S, Tata Mcgraw -Hill Education, 2013
● Cloud Computing: A Practical Approach, Anthony T Velte, Tata
Mcgraw Hill, 2009
● https://www.inst ructables.com/How -to-Create -a-Virtual -Machine/
● https://www.redhat.com/en/topics/virtualization/what -is-
KVM#:~:text=Kernel%2Dbase d%20Virtual%20Machine%20 (KVM,
KVM%20is%20part%20of%20Linux.
● https://u -next.com/blogs/cloud -computing/challenges -of-cloud -
computing/
4.6 UNIT END EXERCISES
1. What is virtualization and what are its benefits?
2. What are the characteristics of virtualized enviro nments?
3. Discuss classification or taxonomy of virtualization at different levels.


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VIRTUALIZATION & CLOUD
COMPUTING
Unit Structure
5.0 Objective
5.1 Introduction
5.2 Virtualization and Cloud Computing
5.3 Pros and Cons of Virtualization
5.4 Virtualization using KVM
5.5 Creating virtual machines
5.6 Virt - management tool for virtualiz ation environment
5.7 Open challenges of Cloud Computing
5.8 Summary
5.9 Reference for further reading
5.10 Unit End Exercises
5.0 OBJECTIVE
● Understand the concept of virtualization and cloud computing.
● To study the pros and cons of virtualization.
● To stud y virtualization using KVM.
● To understand the open challenges of cloud computing.
5.1 INTRODUCTION
● Virtualization is the “creation of a virtual version of something, such
as a server, a desktop, a storage device, an operating system or
network resources”.
● Another Way, Virtualization is a technique, which allows to share a
single physical instance of a resource or an application among multiple
customers and organizations.
● It does this by assigning a logical name to a physical storage and
providing a pointer to that physical resource when demanded.
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58 5.2 VIRTUALIZATION AND CLOUD COMPUTING
● Virtualization plays an important role in cloud computing since it
allows for the appropriate degree of customization, security, isolation,
and manageability that are fundam ental for delivering IT services on
demand.
● Virtualization technologies are primarily used to offer configurable
computing environments and storage.
● Network virtualization is less popular and, in most cases, is a
complementary feature, which is naturally needed in building virtual
computing systems.
● Particularly important is the role of the virtual computing environment
and execution virtualization techniques. Among these, hardware and
programming language virtualization are the techniques adopted in
cloud computing systems.
● Hardware virtualization is an enabling factor for solutions in the
Infrastructure -as-a-Service (IaaS) market segment, while programming
language virtualization is a technology leveraged in Platform -as-a-
Service (PaaS) offerings.
● In both cases, the capability of offering a customizable and sandboxed
environment constituted an attractive business opportunity for
companies featuring a large computing infrastructure that was able to
sustain and process huge workloads.
● Moreover, virtuali zation also allows isolation and a finer control, thus
simplifying the leasing of services and their accountability on the
vendor side.
● Besides being an enabler for computation on demand, virtualization
also gives the opportunity to design more efficient c omputing systems
by means of consolidation, which is performed transparently to cloud
computing service users.
● Since virtualization allows us to create isolated and controllable
environments, it is possible to serve these environments with the same
resour ce without them interfering with each other.
● This opportunity is especially attractive when resources are not
effectively used, because it decreases the number of active resources
by aggregating virtual machines over a smaller number of resources
that bec ome fully utilized.
● This exercise is also known as server consolidation, while the
movement of virtual machine instances is called virtual machine
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Figure 1 Live migration and server consolidation
5.3 PROS AND CONS OF VIRTUALIZATIO N
● Virtualization has become very popular and extensively used,
especially in cloud computing.
● The primary reason for its wide success is the elimination of
technology barriers that prevented virtualization from being an
effective and viable solution in th e past.
● The most relevant barrier has been performance.
● Nowadays virtualization is a compulsive opportunity to deliver on -
demand IT infrastructure and services. Notwithstanding its renewed
popularity, this technology has benefits and also drawbacks.
5.3.1 Advantages of virtualization
● Managed execution and isolation are maybe the most important
advantages of virtualization.
● The creation of virtualized execution environments are the
characteristics that allow building secure and controllable computing
environments.
● A virtual execution environment can be designed as a sandbox, thus
avert any harmful operation to cross the borders of the virtual host.
● This allows fine tuning of resources, which is very prime in a server
consolidation scenario and is also a r equirement for effective quality of
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60 ● Portability is one more advantage of virtualization, especially for
execution virtualization techniques.
● Virtual machine instances are normally represented by one or more
files that can be easily carried with respect to physical systems.
● Portability and self -containment simplify their administration. Java
code is compiled once and runs everywhere. This needs the Java
virtual machine to be installed on the host.
● Portability and self -containment helps to reduce the costs of
maintenance.
● Multiple systems can securely coincide and share the resources of the
underlying host, without interfering with each other.
● This is essential for server strengthening, which allows adjusting the
number of active physical resource s dynamically according to the
current load of the system, thus creating the opportunity to save in
terms of energy consumption and to be less impacting on the
environment.
5.3.2 Disadvantages of virtualization
● Virtualization also has drawbacks. The most e vident is represented by
a performance decrease of guest systems as a result of the
intermediation performed by the virtualization layer.
● The abstraction layer established by virtualization management
software can lead to a very inefficient utilization of the host.
5.3.2.1 Performance degradation
● Performance is definitely one of the crucial concerns in using
virtualization technology. Since virtualization insinuates an abstraction
layer between the guest and the host, the guest can experience
increased lat encies.
● The causes of performance degradation can be traced back to the
overhead introduced by the following pursuit.
○ Maintaining the status of virtual processors
○ Support of privileged instructions
○ Support of paging within VM
○ Console functions
5.3.2.2 I nefficiency and degraded user experience
● Virtualization can sometimes lead to an unsuitable use of the host.
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61 ● In hardware virtualiz ation, the virtual machine can from time to time
simply provide a default graphic card that maps only a subset of the
features available in the host.
● In the course of programming level virtual machines, some of the
features of the underlying operating sys tems may become inaccessible
unless specific libraries are used.
● Example is the first version of Java the support for graphic
programming was very finite and the look and feel of applications was
very needy compared to native applications.
● These problems have been resolved by providing a new framework
called java swing for designing the user interface, and further
development has been done by integrating support for the OpenGL
libraries in the software development kit.
5.3.2.3 Security holes and new threa ts
● Virtualization opens the door to a new and unpredicted form of
phishing.
● The potential of emulating a host in a completely transparent manner
led the way to malicious programs that are designed to extract
sensitive information from the guest.
● In hardwa re virtualization, malicious programs can preload one self
before the OS and act as a thin virtual machine manager toward it.
● The operating system is then managed and can be altered to extract
importatnt information of interest to third parties.
● Examples of malware are BluePill and SubVirt.
5.4 VIRTUALIZATION USING KVM
● Kernel Virtual Machine (KVM) is an open source virtualization
technology developed into Linux.
● KVM become Linux into a hypervisor that enables a host machine to
run multiple isolated virt ual environments called guests / virtual
machines (VMs).
● KVM belongs to Linux .
● KVM was first declared in 2006 and merged into the mainline Linux
kernel version a year later.
● KVM is part of existing Linux code, it abruptly benefits from each
new Linux fea ture, fix, and advancement except additional
engineering.
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62 Working of KVM
● KVM converts Linux into a type -1 hypervisor.
● All hypervisors require some OS -level part like a memory manager,
process scheduler, input or output (I/O) stack, device drivers, securi ty
manager, a network stack, and more to run VMs.
● KVM consists of all these components because it’s part of the Linux
kernel.
● Every VM is implemented as a regular Linux process, arranged by the
standard Linux scheduler, with fixed virtual hardware like a network
card, graphics adapter, CPU(s), memory, and disks.
KVM features
KVM is part of Linux. Linux is part of KVM. Everything Linux has,
KVM has too. But there are certain features that form KVM, an
enterprise's preferred hypervisor.
● Security
KVM employs a combination of security enhanced Linux and secure
virtualization (sVirt) for enhanced VM security and isolation.
● Storage
KVM is capable of using any storage supported by Linux, including some
local disks and network -attached storage (NAS).
● Hardware su pport
KVM can use a broad variation of certified Linux supported hardware
platforms.
● Memory management
Kernal VM inherits the memory management features of Linux, including
non-uniform memory access and kernel same -page merging.
● Live migration
Kernel VM helps live migration, which is the ability to proceed a running
VM between physical hosts with no service onstrution.
● Performance and scalability
Kernel VM inherits the performance of Linux, scaling to match demand
load if the number of guest machines and requests increases.
● Scheduling and resource control
In the KVM model, a VM is a Linux process, scheduled and managed by
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63
● Lower latency and higher prioritization
The Linux kernel features real -time extensions that allow VM -based apps
to run a t lower latency with better prioritization (compared to bare metal).
● Managing KVM
It’s possible to manually manage a handful of VM fires on a single
workstation without a management tool.
5.5 CREATING VIRTUAL MACHINES
Step 1: Download and Install Virtual Box

Keep all of the default settings. You will be prompted to install several
Oracle components. Install all of them .
Step 2: Create a Virtual Machine
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64 Start VirtualBox and Click on 'New' in the menu. Enter the Name of your
VM. This is how you will iden tify it in VirtualBox so name it something
meaningful to you. Select Type and Version. This depends on what OS you
are installing.
Step 3: Allocate Memory

This depends on how much memory you have on your host computer.
Never allocate more than half of yo ur available RAM. If you are creating
a Windows VM I recommend at least (1 -2 GB)
If you are creating a Linux VM I recommend at least (512 MB)
Step 4: Setup the Hard Drive

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65 If you already have an existing VM that you want to add select "Use an
existing Vi rtual hard drive file." Otherwise select "Create a virtual hard
drive now."
Step 5: Select Hard Drive File Type

Select 'VDI.' This is usually the best option. The VM will be stored in a
single file on your computer with the .vdi extension.
Step 6: Select Storage on Physical Hard Drive

I recommend you choose "Dynamically allocated." This will save space on
your computer.

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66 Step 7: Setup File Location and Size

By default, Virtualbox selects the minimum size you should choose.
Depending on what you want to do with the VM you may want to select a
bigger size .
Step 8: Install the Operating System


Double click on your newly created VM (It will be on the left hand side
and will have the name you gave it in Step 2). Browse to your installation
media or .iso file. Finish installation .


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67 5.6 OVIRT - MANAGEMENT TOOL FOR
VIRTUALIZATION ENVIRONMENT
● OVirt is an open source data center virtualization platform developed
and encouraged by Red Hat. OVirt, which provides large -scale,
centralized management for server and desktop virtualization, was
planned as an open source alternative to VMware vCenter.
● OVirt gives kernel based virtual machine management for multi -node
virtualization. Kernel -based Virtual Machines (KVMs) are a
virtualization infrastructure that chang es the Linux kernel into a
hypervisor.
● Features of oVirt
○ OVirt enables centralized management of VMs, networking
configurations, hosts, and compute and storage resources from the web
based front end.
○ OVirt also provides features for disaster recovery (DR) and hyper
converged infrastructure deployments.
○ Features for the management of compute resources include:
■ CPU pinning,
■ same -page merging and
■ memory over commitment.
○ VM management features include
■ live migrations,
■ live snapshots,
■ the creation of VM t emplates and VMs,
■ automated configuration
○ DR features consist of inputting storage domains to different types.
○ OVirt utilizes both self -hosted and Gluster Storage domains for
centralized management.

Components of oVirt

1. oVirt engine
a. The oVirt engine ac ts as the control center for oVirt environments.
b. The engine enables admins to define hosts and networks, as well as to
add storage, create VMs and manage user permissions.
c. Included in the oVirt engine is a graphical user interface (GUI), which
manages oV irt infrastructure resources.
d. The oVirt engine can be installed on a stand -alone server or in a node
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68 2. oVirt node
a. The oVirt node is a server that runs on CentOS, Fedora or Red Hat
Enterprise Linux with a virtual desktop and server manager ( VDSM)
daemon and KVM hypervisor.
b. The VDSM controls the resources available to the node, including
compute, networking and storage resources.
5.7 OPEN CHALLENGES OF CLOUD COMPUTING
1. Security
● The main concern in investing in cloud services is security iss ues in
cloud computing.
It is because your data gets stored and processed by a third -party
vendor and we cannot see it.
● We listen about broken authentication, compromised credentials,
account hacking, data breaches, etc. in a particular organization. It
makes you a little more doubtful.
2. Password Security
● As large numbers of people access cloud accounts, it sometimes
becomes vulnerable. Anybody who knows the password or hacks into
the cloud will be able to access confidential information.
● Nowadays orga nizations should use multiple level authentications and
make sure that the passwords remain secured. Also, the passwords
should be updated regularly, especially when a particular employee
leaves the job or leaves the organization.
3. Cost Management
● Cloud computing allows access to application software over a fast
internet connection and lets save on investing in costly computer
hardware, software, management, and maintenance.
4. Lack of expertise
● With the increasing workload on cloud technologies and regu larly
improving cloud tools, management has become very difficult.
● There has been a consistent order for a trained workforce who can
coordinate with cloud computing tools and services.
● Firms required training their IT staff to minimize this challenge.
5. Internet Connectivity
● Cloud services are mainly dependent on a high -speed internet
connection.
● Hence businesses that are small and face connectivity problems should
perfectly first invest in a good internet connection so that no downtime
happens.
● It is because internet downtime might incur infinite business losses. munotes.in

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69 6. Control or Governance
● One more ethical issue in cloud computing is maintaining proper
control over asset management and maintenance.
● There should be an individual team to make sure that the assets used to
implement cloud services are used according to concur policies and
dedicated procedures.
7. Compliance
● Another major risk of cloud computing is maintaining compliance.
● By compliance using mean, a set of rules about what data is permit ted
to be moved and what should be kept in house to maintain compliance.
● The organizations hence follow and respect the compliance rules set by
various government bodies.
8. Multiple Cloud Management
● Companies have begun to invest in multiple public cloud s, multiple
private clouds or a combination of both is called the hybrid cloud.
● This has expanded rapidly in recent times.
● So it has become important to list the various challenges faced by such
types of organizations and find solutions to grow with the trend.
9. Creating a private cloud
● Implementing an internal cloud is beneficial. This is because all the
data remains secure in house.
● But the challenge here is that the IT team should build and fix
everything by themselves. Also, the team is required to ensure the
smooth working of the cloud.
● They are required to automate maximum manual tasks to be dynamic.
The execution of tasks should be in the proper order.
10. Performance
● When business applications migrate to a cloud or a third -party vendor,
the bus iness performance starts to depend on the service provider as
well.
● Another major issue in cloud computing is investing in the right cloud
service provider.
11. Migration
● Migration is nothing but updating an application and a new
application or an existi ng application to a cloud. In the case of a new
application, the process is good and straightforward.

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70 5.8 SUMMARY
● Virtualization has become very popular and extensively used,
especially in cloud computing.
● All these concepts play a fundamental role in b uilding cloud
computing infrastructure and services in which hardware; IT
infrastructure, applications, and services are delivered on demand
through the Internet or more generally via a network connection.
● OVirt is an open source data center virtualization platform developed
and encouraged by Red Hat. OVirt, which provides large -scale,
centralized management for server and desktop virtualization, was
planned as an open source alternative to VMware vCenter.
5.9 REFERENCE FOR FURTHER READING
● Enterprise Cloud Computing Technology, Architecture, Applications,
GautamShroff, Cambridge University Press, 2010
● Mastering In Cloud Computing, RajkumarBuyya, Christian Vecchiola
And ThamariSelvi S, Tata Mcgraw -Hill Education, 2013
● Cloud Computing: A Practical Approach, A nthony T Velte, Tata
Mcgraw Hill, 2009
● https://www.instructables.com/How -to-Create -a-Virtual -Machine/
● https://www.redhat.com/en/topics/virtualization/what -is-
KVM#:~:text=Kernel%2Dbased%20Virtual%20Machine%20 (KVM,
KVM%20is%20part%20of%20Linux.
● https://u -next.com/blogs/cloud -computing/challenges -of-cloud -
computing/
5.10 UNIT END EXERCISES
1. What are the pros and cons of cloud computing?
2. Discuss Virtualization using KVM?
3. Explain how to create a virtual machine?
4. What are the open challenges of cloud computing?


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71 6
OPEN STACK
Unit Structure
6.1 Objectives
6.2 Introduction to Open Stack
6.3 OpenStack test -drive
6.4 Basic Open Stack operations
6.5 OpenStack CLI and APIs
6.6 Tenant model operations
6.7 Quotas, Private cloud building blocks
6.8 Controller deployment
6.9 Networking deployment
6.10 Block Storage deployment
6.11 Compute deployment
6.12 Deploying and utilizing OpenStack in production environments
6.13 Building a production environment
6.14 Application orchestration using OpenStack Heat
6.15 Summary
6.16 Questions
6.17 References
6.1 OBJECTIVES
At the end of this unit, the student will be able to
 Understand the open stack and its components.
 Describe various parameters of openstack
6.2 INTRODUCTION TO OPENSTACK
1. OpenStack is an open -source cloud computing pla tform that provides a
set of software tools for building and managing public, private, and
hybrid clouds. It was initially released in 2010 as a joint project of
NASA and Rackspace, and it has since become one of the most
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72 2. OpenStack consists of a set of interrelated components, each of which
provides a specific function in the cloud computing environment.
These components include:

 Compute (Nova): This component provides virtualization services and
manages the creation and scheduling of virtual machines.

 Networking (Neutron): This component provides network connectivity
services and manages the creation and configuration of virtual
networks.

 Storage (Cinder and Swift): These components provide storage
services and manage the creation and management of block and object
storage.

 Identity (Keystone): This component provides authentication and
authorization services and manages the creation and management of
user accounts.

 Dashboard (Horizon): This component prov ides a web -based user
interface for managing the cloud computing environment.

 Orchestration (Heat): This component provides automated deployment
and management of cloud applications.

 Telemetry (Ceilometer): This component provides monitoring and
metering services for the cloud computing environment.

3. OpenStack is designed to be highly scalable and flexible, allowing it to
be used in a wide range of cloud computing environments. It is also
modular, which means that it can be easily customized and extended to
meet the specific needs of individual organizations.

4. OpenStack has a large and active community of developers, users, and
vendors, who contribute to the development and support of the
platform. This community has created a wide range of tools and
plugi ns that can be used with OpenStack to extend its functionality and
make it easier to use.
6.3 OPENSTACK TEST -DRIVE
1. To test -drive OpenStack, you can use one of the available OpenStack
distributions or deploy your own OpenStack environment. Here are the
gene ral steps to follow:

2. Choose an OpenStack distribution: Several vendors offer pre -packaged
OpenStack distributions, such as Red Hat OpenStack, Canonical
OpenStack, and MirantisOpenStack. You can also choose to deploy
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73 3. Set up a testing environment: You will need a testing environment
with adequate resources to deploy OpenStack, such as a dedicated
server or a virtual machine. You can use a cloud provider like AWS or
Google Cloud to set up the testing environment.

4. Install OpenStack: Follow the installation instructions provided by the
OpenStack distribution or the official OpenStack documentation to
install the necessary components.

5. Configure OpenStack: Once OpenStack is installed, you will need to
configure it to suit your needs. This includes setting up users, roles,
and permissions; configuring network settings; and defining storage
policies.

6. Use OpenStack: Once OpenStack is up and running, you can use it to
create virtual machines, configure networks, and store dat a. You can
use the OpenStack dashboard or the command -line interface to
manage the cloud computing environment.

7. Test OpenStack: To test OpenStack, you can create and deploy virtual
machines, test network connectivity, and simulate workload scenarios
to test the performance and scalability of the environment.

8. Keep in mind that deploying and configuring OpenStack can be a
complex process, and it requires some level of expertise in cloud
computing and networking. You may want to seek assistance from the
Open Stack community or a professional services provider to ensure a
smooth and successful deployment.

9. Pre-built OpenStack environment: Several companies offer pre -built
OpenStack environments that you can use to test -drive the platform.
These environments are typically available as virtual appliances or
cloud images that you can download and run on your own computer or
cloud environment. Some examples of pre -built OpenStack
environments include:
 MirantisOpenStack Express
 Canonical's Ubuntu OpenStack
 Red Hat Op enStack Platform

10. Deploy your own OpenStack environment: If you want to deploy your
own OpenStack environment, you can use tools such as DevStack or
Packstack. DevStack is a script that automates the installation of
OpenStack on a single machine, while Pac kstack is a similar tool that
can be used to deploy OpenStack on multiple machines. To deploy
OpenStack on your own, you will need to have a server or virtual
machine that meets the hardware and software requirements for
OpenStack.
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74 11. Once you have a test en vironment set up, you can use the OpenStack
web interface (Horizon) or command -line interface (CLI) to create
virtual machines, networks, and storage resources. You can also
explore the different OpenStack components and their functionality,
such as the co mpute (Nova) and networking (Neutron) components.
6.4 BASIC OPENSTACK OPERATIONS
Some basic OpenStack operations include:
1. Creating instances: OpenStack instances are virtual machines that can
be used to run applications and services. To create an instance, you can
use the OpenStack web interface (Horizon) or command -line interface
(CLI). You will need to specify the flavor (CPU, memory, and disk
configuration), image (operating system and software), network, and
security settings for the instance.

2. Managing networks: OpenStack provides a networking service
(Neutron) that allows you to create and manage virtual networks. To
create a network, you can use the OpenStack web interface or CLI and
specify the network name, subnet, and IP address range. You can also
attach instances to networks and configure security settings for the
network.

3. Managing storage: OpenStack provides two storage services, Cinder
(block storage) and Swift (object storage). To create a block storage
volume, you can use the OpenStack web in terface or CLI and specify
the volume size, type, and other settings. To create an object storage
container, you can use the Swift CLI and specify the container name
and access settings.

4. Managing users and projects: OpenStack provides an identity service
(Keystone) that allows you to create and manage users, projects, and
roles. Users are granted roles that define their level of access to
OpenStack resources. To create a user, you can use the OpenStack
web interface or CLI and specify the user name, passwo rd, and other
settings. To create a project, you can also use the OpenStack web
interface or CLI and specify the project name and description.

5. Monitoring and logging: OpenStack provides several tools for
monitoring and logging OpenStack resources. The tel emetry service
(Ceilometer) provides monitoring and metering of OpenStack
resources, while the logging service (Logstash) provides centralized
logging for OpenStack components. You can use these tools to
monitor performance, detect errors, and troubleshoot issues in your
OpenStack environment.

6. These are just a few examples of basic OpenStack operations.
OpenStack provides a wide range of functionality, and the operations
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75 7. Here are some basic O penStack operations that you can perform using
the Horizon web interface or the OpenStack command -line interface
(CLI):

 Launch an instance: You can create a new virtual machine instance by
selecting the Compute tab in the Horizon dashboard and clicking on
"Launch Instance." You will be prompted to select a flavor (virtual
machine size), an image (operating system), and other configuration
options.

 To launch an instance using the CLI, you can use the openstack server
create command and specify the necessar y parameters.

 Create a network: You can create a new network for your instances by
selecting the Network tab in the Horizon dashboard and clicking on
"Create Network." You will be prompted to specify the network type,
subnet details, and other configurati on options.

 To create a network using the CLI, you can use the openstack network
create command and specify the necessary parameters.

 Attach a volume: You can attach a volume to an instance to provide
additional storage by selecting the Compute tab in th e Horizon
dashboard, clicking on the instance, and selecting "Attach Volume."
You will be prompted to select the volume and specify the device
name.

 To attach a volume using the CLI, you can use the openstack server
add volume command and specify the nece ssary parameters.

 Manage security groups: You can manage security groups to control
incoming and outgoing traffic to your instances by selecting the
Compute tab in the Horizon dashboard and clicking on "Access &
Security." You can create new security grou ps, add rules, and associate
them with instances.

 To manage security groups using the CLI, you can use the openstack
security group create and openstack security group rule create
commands.

 Resize an instance: You can resize an instance to a different fl avor
(virtual machine size) by selecting the Compute tab in the Horizon
dashboard, clicking on the instance, and selecting "Resize Instance."
You will be prompted to select the new flavor.

 To resize an instance using the CLI, you can use the openstack ser ver
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76 6.5 OPENSTACK CLI AND APIS
1. OpenStack provides a command -line interface (CLI) and APIs that
allow you to manage and automate your cloud resources.

2. The OpenStack CLI is a tool that allows you to inter act with
OpenStack services from the command line. It is a powerful tool that
allows you to automate tasks and perform complex operations.

3. The CLI uses the OpenStack API to communicate with the OpenStack
services. The CLI is available for all OpenStack s ervices, including
Compute, Networking, Identity, Image, and Block Storage.

4. To use the OpenStack CLI, you need to install the OpenStack client on
your local machine. The client is available for Linux, macOS, and
Windows. Once you have installed the client , you can use the
openstack command to interact with OpenStack services.

5. The OpenStack APIs are a set of RESTful APIs that allow you to
programmatically interact with OpenStack services. The APIs provide
a standardized way of accessing OpenStack services and can be used
by developers to create custom applications and tools that interact with
OpenStack services.

6. The OpenStack APIs are available for all OpenStack services,
including Compute, Networking, Identity, Image, and Block Storage.
The APIs are based on industry standards such as JSON, XML, and
HTTP. You can use any programming language that supports HTTP to
interact with the OpenStack APIs.

7. OpenStack also provides software development kits (SDKs) for
popular programming languages such as Python, Jav a, and Ruby. The
SDKs provide a higher -level interface to the OpenStack APIs and
make it easier to build applications that interact with OpenStack
services.

8. Overall, the OpenStack CLI and APIs are powerful tools that allow
you to manage and automate your cloud resources. Whether you prefer
to use the CLI or APIs, OpenStack provides a flexible and extensible
platform for building and managing cloud infrastructure.
6.6 TENANT MODEL OPERATIONS
1. The tenant model is a core concept in OpenStack that enables multi -
tenancy within a cloud environment. Tenants are logical groups of
resources that are isolated from each other, allowing multiple
organizations to share the same infrastructure without interfering with
each other.
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77 2. Here are some basic OpenStack tenant mode l operations:

 Creating a tenant: You can create a new tenant using the OpenStack
CLI or APIs. When you create a tenant, you specify a name and an
optional description.

 Creating users: Once you have created a tenant, you can create one or
more users withi n that tenant. Users are granted access to the resources
associated with their tenant.

 Assigning roles: You can assign roles to users within a tenant. Roles
are used to define what actions a user can perform on a specific
resource. For example, you might assign a user the role of "admin" for
a particular project, giving them full access to all resources within that
project.

 Creating projects: Projects are containers for resources within a tenant.
You can create one or more projects within a tenant, and as sign users
and roles to those projects.

 Managing quotas: OpenStack allows you to set quotas for resources
within a tenant, such as the number of instances or the amount of
storage that can be used. You can set and manage quotas using the
OpenStack CLI or APIs.

 Monitoring usage: OpenStack provides tools for monitoring resource
usage within a tenant, allowing you to track usage and ensure that
tenants are not exceeding their quotas.

 Managing user access to tenants: You can control which users have
access t o a tenant's resources by assigning roles to those users. You
can assign multiple roles to a user, and you can assign roles to users at
the tenant level or the project level.

 Managing resources: Once you have created a tenant, you can create
and manage re sources within that tenant. You can create instances,
volumes, networks, and images, and you can assign those resources to
the tenant.

3. Overall, the tenant model is a powerful feature of OpenStack that
allows you to create a secure and scalable multi -tenan t cloud
environment. By using tenants, users, roles, and projects, you can
create a flexible and customizable cloud infrastructure that meets the
needs of your organization.

4. In OpenStack, a tenant is a logical grouping of resources that allows
you to isol ate and control access to those resources. A tenant can be a
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78 OpenStack has its own set of resources, including instances, volumes,
networks, and images.

5. Overall, the tenant model in O penStack provides a flexible and
powerful way to manage and control access to cloud resources. By
using tenants, you can isolate resources and control access to those
resources, which makes it easier to manage and secure your cloud
infrastructure.
6.7 QUOT AS, PRIVATE CLOUD BUILDING BLOCKS
1. Quotas in OpenStack are limits that are imposed on the amount of
resources that a tenant can use. Quotas are used to prevent a tenant
from using too many resources and degrading the performance of the
cloud infrastructure. Quotas can be set for individual resources, such
as instances, volumes, and networks, as well as for aggregate
resources, such as CPU cores and RAM.

2. Here are some examples of quotas that can be set in OpenStack:

 Instance quotas: This sets a limit on the number of instances that a
tenant can create.

 Volume quotas: This sets a limit on the amount of storage that a tenant
can allocate to volumes.

 Network quotas: This sets a limit on the number of networks and
subnets that a tenant can create.

 Floating IP quotas: This sets a limit on the number of floating IPs that
a tenant can allocate.

3. Private cloud building blocks are the components that are used to build
a private cloud infrastructure. These components include the physical
hardware, such as servers an d storage devices, as well as the software,
such as OpenStack, that is used to manage the cloud infrastructure.

4. Here are some examples o f private cloud building blocks

 Compute nodes: These are the physical servers that are used to host
virtual machines.

 Storage nodes: These are the physical servers that are used to provide
storage for the cloud infrastructure.

 Networking hardware: This includes switches and routers that are used
to connect the cloud infrastructure to the external network.
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79  Virtualizatio n software: This is the software that is used to create and
manage virtual machines.

 Cloud management software: This includes OpenStack and other
software tools that are used to manage the cloud infrastructure.

5. Overall, the private cloud building blocks are the foundation of a
private cloud infrastructure, and they must be carefully selected and
configured to ensure that the cloud infrastructure is reliable, scalable,
and secure. Quotas play an important role in ensuring that tenants use
resources respons ibly and that the cloud infrastructure performs well.

6. Quotas in OpenStack are used to limit the amount of resources that a
tenant or user can consume. You can set quotas for different resources
such as CPU, memory, storage, and network usage. Quotas can b e set
at the tenant level or the user level, and you can customize the quotas
based on your specific needs.

7. Setting quotas helps to prevent overutilization of resources and ensure
fair resource allocation among different tenants and users. Quotas can
be m anaged using the OpenStack CLI or APIs.

8. A private cloud is a cloud infrastructure that is dedicated to a single
organization. Private clouds offer several benefits, including enhanced
security, greater control over resources, and increased flexibility.

9. Here are some common building blocks of a private cloud
infrastructure:

 Hypervisor: A hypervisor is the software that enables virtualization of
physical servers. It allows multiple virtual machines to run on a single
physical server.

 Storage: Storage is a critical component of a private cloud
infrastructure. You can use different types of storage, such as block
storage, object storage, and file storage, depending on your specific
needs.

 Networking: Networking is essential for connecting different
componen ts of a private cloud infrastructure. You can use software -
defined networking (SDN) to create and manage virtual networks,
subnets, and routers.

 Orchestration: Orchestration is the automation of the deployment and
management of cloud resources. You can us e tools such as OpenStack
Heat or AWS CloudFormation to automate the creation and
management of resources in your private cloud.
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80  Identity and Access Management (IAM): IAM is used to manage user
access to cloud resources. You can use IAM tools such as Open Stack
Keystone to authenticate and authorize users and assign roles and
permissions.

Monitoring and Management: Monitoring and management tools are
used to ensure that your private cloud infrastructure is running
smoothly. You can use tools such as Nagios or Zabbix to monitor
system performance and detect issues before they become problems.

10. Overall, these building blocks are the foundation of a private cloud
infrastructure, and they enable you to create a flexible, scalable, and
secure cloud environment t hat meets your organization's needs.
6.8 CONTROLLER DEPLOYMENT
1. In OpenStack, the controller node is a critical component of the
infrastructure. It is responsible for managing and coordinating all the
other nodes in the OpenStack deployment, such as compute , storage,
and network nodes.

2. The controller node typically runs the following OpenStack services:

 Identity (Keystone): Provides authentication and authorization services
for OpenStack services and tenants.

 Image (Glance): Stores and retrieves virtual machine images.

 Dashboard (Horizon): Provides a web -based user interface for
OpenStack services.

 Orchestration (Heat): Provides an API for defining and automating the
deployment of infrastructure resources.

 Telemetry (Ceilometer): Collects metrics and d ata on OpenStack
services.

 Networking (Neutron): Provides networking services for virtual
machines and other OpenStack components.

3. Here are some general steps for deploying the controller node:

 Install the base operating system: The first step is to ins tall the
operating system on the server that will become the controller node.
Many OpenStack distributions provide pre -configured images that you
can use.
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81  Install OpenStack packages: Next, you need to install the OpenStack
packages on the controller node. This can be done using package
managers like yum or apt -get.

 Configure the services: Once the OpenStack packages are installed,
you need to configure the services on the controller node. This
includes setting up the database for each service, configuring the
messaging system, and configuring the service endpoints.

 Verify the installation: After the services are configured, you can
verify that they are working properly by running various tests and
checks. For example, you can use the OpenStack CLI to chec k that
you can authenticate and access OpenStack services.

 Configure additional services: Finally, you may want to configure
additional services on the controller node, such as load balancing or
firewall services.

4. It's important to note that the controll er node deployment process can
vary depending on the specific OpenStack distribution and version you
are using, as well as the requirements of your environment. It's always
a good idea to consult the documentation and follow best practices for
your particu lar deployment.

5. In OpenStack, the controller node is the central management
component of the cloud infrastructure. It provides the API services that
enable users to interact with the cloud infrastructure, as well as the
scheduling and orchestration of res ources.

6. Here are the steps for deploying an OpenStack controller node:

 Prepare the controller node: The first step is to prepare the controller
node by installing the operating system and configuring the network
interfaces. You should also configure the hostname, domain name, and
time zone.

 Install the OpenStack packages: The next step is to install the
OpenStack packages, including the identity service (Keystone), the
image service (Glance), the compute service (Nova), the network
service (Neutron), and the dashboard (Horizon). You can use the
package manager of your operating system (e.g., apt -get or yum) to
install the packages.

 Configure the services: After installing the packages, you need to
configure the services. For example, you need to configur e Keystone
to authenticate users and Neutron to provide network connectivity.
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82  Configure the database: OpenStack uses a database to store
configuration information and metadata about resources. You need to
configure the database service (e.g., MySQL or MariaDB) and create
the necessary databases and users.

 Configure the message queue: OpenStack uses a message queue (e.g.,
RabbitMQ or Qpid) to communicate between the different components
of the infrastructure. You need to configure the message queue service
and create the necessary users and permissions.

 Start the services: After configuring the services, you can start them on
the controller node using the service manager of your operating syste m
(e.g., systemctl or service).

 Verify the installation: Finally, you should verify that the OpenStack
services are running correctly by using the OpenStack CLI or API to
create and manage resources.

7. Overall, deploying an OpenStack controller node requir es careful
planning and configuration, but it is a critical step in creating a
functional and scalable cloud infrastructure.
6.9 NETWORKING DEPLOYMENT
1. In OpenStack, the networking component is responsible for providing
network connectivity to instances (vi rtual machines). The networking
deployment process involves configuring the networking services and
components, such as the OpenStack Networking (Neutron) service, the
Open vSwitch (OVS) agent, and network nodes.

2. Here are the steps for deploying networkin g in OpenStack:

 Install and configure the Neutron service: The first step is to install the
Neutron service on the controller node and configure it to provide
network connectivity. This involves configuring the Neutron server,
the Neutron API, and the Neu tron plugin (e.g., ML2). You also need to
configure the Neutron database and the message queue service.

 Configure the OVS agent: The next step is to configure the Open
vSwitch (OVS) agent, which provides virtual network connectivity to
instances. This inv olves configuring the OVS service, creating the
necessary bridges and ports, and configuring the OVS firewall.

 Configure network nodes: If you have multiple network nodes, you
need to configure them to provide network connectivity to instances.
This invol ves configuring the network node, the OVS agent, and the
Neutron agent.

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83  Create networks, subnets, and routers: Once the Neutron service and
OVS agent are configured, you can create networks, subnets, and
routers. A network is a logical abstraction that p rovides connectivity
between instances, while a subnet is a range of IP addresses that can be
used by instances in a network. A router is a virtual device that
connects two or more networks.

 Create security groups and rules: To control network access and
security, you can create security groups and rules. A security group is
a set of firewall rules that define the allowed inbound and outbound
traffic for instances.

 Launch instances: Finally, you can launch instances and attach them to
the networks and sec urity groups you created. The instances should be
able to communicate with each other and with the external network
through the router.

3. Overall, deploying networking in OpenStack requires careful planning
and configuration, but it is a critical step in cr eating a functional and
scalable cloud infrastructure.
6.10 BLOCK STORAGE DEPLOYMENT
1. In OpenStack, block storage provides persistent storage for instances
(virtual machines) that requires data to persist beyond the lifetime of
the instance.

2. The block sto rage deployment process involves configuring and
deploying the Cinder service, which manages the creation, deletion,
and management of block storage volumes.

3. Here are the steps for deploying block storage in OpenStack:

 Install and configure the Cinder se rvice: The first step is to install the
Cinder service on the controller node and configure it to provide block
storage. This involves configuring the Cinder server, the Cinder API,
the Cinder scheduler, and the Cinder volume service.

 Configure the storag e backends: Once the Cinder service is installed
and configured, you need to configure the storage backends that will
provide the physical storage for block volumes. OpenStack supports a
variety of storage backends, including local disks, iSCSI, NFS, and
Ceph. You need to configure the appropriate drivers for your storage
backend.

 Create storage pools: A storage pool is a group of storage devices that
are managed together. You need to create storage pools for each
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84  Create vol ume types: A volume type is a way to define the
characteristics of a block volume, such as the size, performance, and
availability. You need to create volume types that reflect the different
needs of your applications.

 Create block volumes: Once the stora ge backends and volume types
are configured, you can create block volumes. A block volume is a
persistent block storage device that can be attached to an instance.

 Attach block volumes to instances: Finally, you can attach block
volumes to instances. This allows the instance to access the persistent
storage provided by the block volume.

 Configure the storage backend: The next step is to configure the
storage backend, which is the physical storage device that provides the
block storage. There are different types of storage backends that can be
used with Cinder, such as LVM, Ceph, and NFS. You need to
configure the backend based on the type of storage you are using.

 Create storage pools and volumes: Once the Cinder service and storage
backend are configured , you can create storage pools and volumes. A
storage pool is a group of storage devices that are used to create
volumes, while a volume is a block -level storage device that can be
attached to an instance.

 Create volume types and encryption: To provide ad vanced features
and security, you can create volume types and enable encryption. A
volume type is a set of characteristics that define a volume, such as its
size, performance, and availability. Encryption is a feature that
encrypts the data stored on the v olume to provide additional security.

 Attach volumes to instances: Finally, you can attach the volumes to
instances and use them as persistent storage. The volumes can be
attached and detached from instances as needed, and they can be used
to store data t hat needs to persist across instance reboots or
terminations

4. Overall, deploying block storage in OpenStack requires careful
planning and configuration, but it is a critical step in creating a
functional and scalable cloud infrastructure.

5. Overall, deployi ng Block Storage in OpenStack requires careful
planning and configuration, but it is a critical step in providing
persistent storage to instances and enabling advanced features and
security.


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85 6.11 COMPUTE DEPLOYMENT
1. Compute deployment, deploying and util izing OpenStack in
production environments

2. Compute deployment is a critical component of deploying and
utilizing OpenStack in production environments. Here are the steps
involved in deploying and utilizing OpenStack Compute in a
production environment:

 Install and configure the Nova compute service: The first step is to
install and configure the Nova compute service on each compute node.
This involves installing the necessary packages, configuring the Nova
compute service, and setting up the networking.

 Configure the hypervisor: Next, you need to configure the hypervisor,
which is the software layer that enables virtualization on the compute
nodes. There are different types of hypervisors that can be used with
OpenStack Compute, such as KVM, Xen, and VMwa re. You need to
configure the hypervisor based on the type of virtualization you are
using.

 Create and manage instances: Once the Nova compute service and
hypervisor are configured, you can create and manage instances. An
instance is a virtual machine tha t runs on the compute node and
provides computing resources to users. You can create instances using
the OpenStack dashboard, CLI, or API.

 Configure security and networking: To ensure security and
connectivity, you need to configure security groups, firew alls, and
networking. Security groups are sets of firewall rules that define which
traffic is allowed in and out of an instance. Networking involves
configuring the network interfaces and IP addresses of the instances.

 Monitor and troubleshoot: Finally, y ou need to monitor and
troubleshoot the compute environment to ensure it is running
smoothly. This involves monitoring the performance of the instances
and the compute nodes, as well as identifying and resolving any issues
that arise.
6.12 DEPLOYING AND UT ILIZING OPENSTACK IN
PRODUCTION ENVIRONMENTS

1. Deploying and utilizing OpenStack Compute in a production
environment requires careful planning, configuration, and
management. It is important to follow best practices and security
guidelines to ensure the com pute environment is secure, reliable, and
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86 2. Deploying OpenStack Compute (Nova) involves installing and
configuring the Nova services and components, including the Nova
API, Nova compute nodes, Nova scheduler, and the Nova database.
Here are the ste ps involved in deploying Nova:

 Install and configure the Nova services: The first step in deploying
Nova is to install and configure the Nova services on the controller
node. This involves configuring the Nova API, the Nova conductor,
and the Nova databas e.

 Install and configure the Nova compute nodes: The next step is to
install and configure the Nova compute nodes. This involves
configuring the Nova compute service, setting up networking, and
configuring the hypervisor.

 Configure the Nova scheduler: Th e Nova scheduler is responsible for
selecting the appropriate compute node for a given instance. You can
configure the scheduler to use different algorithms to select the node
based on various criteria, such as available resources, affinity, and
anti-affin ity.

 Create flavors: Flavors are predefined templates that define the size,
CPU, memory, and disk specifications of an instance. You can create
different flavors based on the requirements of your applications and
workloads.

 Create and manage instances: O nce Nova is deployed, you can create
and manage instances using the Nova API or the OpenStack
dashboard. You can select the appropriate flavor for your instances,
attach storage volumes, and configure networking.

3. To deploy and utilize OpenStack in product ion environments, it is
essential to follow best practices and ensure high availability,
scalability, and security. Here are some tips for deploying and utilizing
OpenStack in production:

 Use high availability (HA) deployment: To ensure high availability
and minimize downtime, it is recommended to deploy OpenStack in an
HA configuration. This involves setting up multiple instances of the
services, load balancers, and databases.

 Configure security: OpenStack provides several security features, such
as role -based access control (RBAC), network security groups (NSGs),
and encryption. It is essential to configure these features based on your
security requirements to protect your cloud environment from
unauthorized access.

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87 your OpenStack resources regularly. You can use OpenStack
monitoring tools such as Ceilometer, Aodh, and Gnocchi to monitor
the performance of your resources.

 Plan for scalability: OpenStack is designed to scale horizontally, which
means you can add more nodes to handle increased workloads. It is
essential to plan for scalability and ensure that your deployment can
handle future growth.

 Ensure backup and disaster recovery: It is essential to ensure backup
and disaster recovery of your OpenStack environment to protect
against data loss and minimize downtime in the event of a disaster.
You can use OpenStack backup and recovery tools such as Freezer and
Barman to back up and recover your OpenStack environment.

4. Overall, deploying and utilizing OpenStack in production
environments requires careful planning, configuration, and
management. By following best practices and utilizing OpenStack's
features and tools, you can bu ild a robust, scalable, and secure cloud
infrastructure that meets your business requirements.
6.13 BUILDING A PRODUCTION ENVIRONMENT
1. Building a production environment for OpenStack involves several
steps and considerations. Here are some key steps:

 Plann ing: Before starting the deployment, plan the architecture of the
production environment. This includes defining the number of nodes
required for each component, network topology, storage requirements,
and security considerations.

 Hardware Requirements: E nsure that the hardware meets the minimum
requirements for running OpenStack. Consider using hardware that is
scalable and can be easily upgraded.

 Operating System: Choose the operating system for the nodes, and
ensure that it is compatible with the OpenS tack version.

 Networking: Set up the networking infrastructure for the environment.
Consider using redundant network paths, VLANs, and subnets.

 Storage: Choose the storage solution for the environment, and ensure
that it is compatible with OpenStack. Con sider using redundant storage
systems for high availability.

 Install OpenStack: Install the OpenStack components on the nodes.
Follow the documentation for the version of OpenStack being
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88  Configure OpenStack: After installation, configure OpenSt ack
according to the requirements of the production environment. This
includes configuring compute, networking, and storage.

 Testing: After configuration, test the environment thoroughly to ensure
that all components are working correctly.

 Monitoring: Se t up monitoring for the production environment to
ensure that it is running smoothly. Consider using monitoring tools
such as Nagios, Zabbix, or Prometheus.

 Maintenance: Perform regular maintenance tasks such as patching,
upgrades, and backups.

2. Building a production environment for OpenStack can be complex and
time-consuming, but proper planning and execution can result in a
highly scalable, flexible, and reliable cloud platform.
6.14 APPLICATION ORCHESTRATION USING
OPENSTACK HEAT
1. OpenStack Heat is a serv ice that provides orchestration capabilities to
OpenStack. Heat enables automated provisioning of infrastructure and
applications on top of OpenStack, by defining templates that describe
the desired configuration of the resources.

2. Application orchestratio n using OpenStack Heat involves the
following steps:

 Create a Heat template: A Heat template is a text file that defines the
resources required to deploy an application. The template is written in
YAML or JSON format and includes a description of the reso urces,
their dependencies, and their configuration.

 Upload the template to Heat: Once the template is created, it needs to
be uploaded to Heat. This can be done through the OpenStack CLI or
web interface.

 Launch the stack: After the template is uploaded, it can be used to
launch a stack. A stack is a collection of resources that are created and
managed by Heat. The stack creation process involves validating the
template, creating the necessary resources, and configuring them
according to the template.

 Monitor the stack: After the stack is launched, it can be monitored
through the OpenStack web interface or CLI. Heat provides visibility
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89  Update the sta ck: If changes need to be made to the stack, the Heat
template can be modified and uploaded to Heat. Heat will then update
the stack by making the necessary changes to the resources.

3. By using Heat for application orchestration, it is possible to automate
the deployment and management of complex applications on
OpenStack. Heat provides a standardized way of defining
infrastructure and application resources, making it easier to manage
and scale deployments.

3.15 SUMMARY
In this chapter we learned about openstack and its components. The
summing of all points as follows
 OpenStack has a large and active community of developers, users, and
vendors, who contribute to the development and support of the
platform.

 The OpenStack APIs are available for all OpenStack servi ces,
including Compute, Networking, Identity, Image, and Block Storage.
The APIs are based on industry standards such as JSON, XML, and
HTTP.

 Deploying block storage in OpenStack requires careful planning and
configuration, but it is a critical step in cr eating a functional and
scalable cloud infrastructure.

 Building a production environment for OpenStack can be complex and
time-consuming, but proper planning and execution can result in a
highly scalable, flexible, and reliable cloud platform.

3.16 QUESTIONS

1. What is openstack?
2. Write a short note on
i. OpenStack test -drive
ii. Basic OpenStack operations
iii. OpenStack CLI and APIs
iv. Tenant model operations
v. Quotas, Private cloud building blocks
3. Explain the following concepts in detail.
i. Controller deployment
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90 iii. Block Storage deployment
iv. Compute deployment
v. deploying and utilizing OpenStack in production environments
4. Illustrate the concept of Building a production environment and
Application orchestration using OpenStack Heat?
6.17 REFERENCES
1. OpenStack Esse ntials, Dan Radez, PACKT Publishing, 2015

2. OpenStack Operations Guide, Tom Fifield, Diane Fleming, Anne
Gentle, Lorin Hochstein, Jonathan Proulx, Everett Toews, and Joe
Topjian, O'Reilly Media, Inc., 2014

3. https://www.openstack.org

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