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Cloud Computing
Chapter 1
Dr. Nivine Guler
nivine.guler@ucentralasia.org

Course Contents from Cloud Computing with AWS by
Pravin Mishra
1. Chapter 1: Introduction to Cloud Computing
2. Chapter 2: Getting started with AWS
3. Chapter 3: AWS Identity and Access Management
4. Chapter 4: AWS Storage Services
5. Chapter 5: Virtual Private Cloud (VPC)
6. Chapter 6: Elastic Compute Cloud (EC2)
7. Chapter 7: High-Level Architecture
8. Chapter 8: Databases
9. Chapter 10: AWS Security and Management Services
2

Chapter 1:
 What is cloud computing?
 What are the different types of cloud deployment models?
 What are data centers and how did cloud computing come
into existence?
 What are the different types of cloud service models?
 What are some important concepts related to the cloud?
 What are the different providers that provide cloud services?
 What are the benefits of cloud computing over traditional
methods?
3

What is Cloud Computing?
 What do you think?
 There are four core cloud computing services:
• Compute
• Storage
• Database
• networking

What is Cloud Computing?
Cloud computing is an on-demand information technology (IT) paradigm that enables ubiquitous
access to shared pools of configurable system resources and higher-level services that can be rapidly
provisioned with minimal management effort, often over the Internet. Cloud computing relies on
sharing of resources to achieve coherence and economies of scale, similar to a public utility.
https://en.wikipedia.org/wiki/Cloud_computing
Cloud computing refers to the delivery of various computing services, including servers, storage,
databases, networking, software, and analytics, over the Internet, commonly known as “the cloud.”
Organizations that provide these services are called cloud providers and usually operate on a pay-
as-you-go model, where users are billed based on their resource consumption, similar to how
utilities like electricity or gas are charged in households.
https://azure.microsoft.com/en-gb/overview/what-is-cloud-computing/
5

Compute
Compute is the processing power
of your machine. For example,
suppose you are creating a
PowerPoint presentation for your
final year project. You need a lot
of information for your project, so
you open a few web browser
tabs. You love music, so you are
playing music as well.
With finite computation power, what will you experience? Your computer starts lagging,
so you close a couple of tabs and stop the music player.
Solution? a good processor and more RAM are essential to running heavy applications
or games.

Storage
Suppose you need to save your work. What will happen if your hard disk
crashes?
What happens if you run out of space?
Solution?
Using the cloud storage to save your data either permanently or
Temporarily

Database
Suppose you open Excel sheet to store your
data which is structured. What will you do if
you have huge amount of data?
Solution: To store structure huge amount of
data on cloud, you need to use one of the
databases: MySQL, ORACLE, SQL Server
which you choose based on the type of data
you want to store.

Networking
All the services on the cloud are connected. A networking service
provides connectivity among different services.

Cloud Computing
Cloud computing enables on-demand computing services such as
database, storage, compute, and networking over the Internet.

Fundamentals of the Cloud
 Different types of cloud deployment
models: Based on each organization
requirements and level of control on their
cloud infrastructure, there exist various types
of cloud deployment models.
 Each model offers a different level of
management, security, and cost to the users.
 Deployment of cloud model is related to:
• Where is the cloud infrastructure located?
• Who controls it?
• Who can access and use it?

Fundamentals of the Cloud
 Cloud infrastructure not only involves
cloud services, but also involves
hardware, building, power, cooling, and
so on.

Cloud Deployment Models
 Cloud computing offers three cloud deployment models:
Private clouds
Public clouds
Hybrid clouds

Private Clouds
 A private cloud is a cloud computing infrastructure that is exclusively dedicated
to a particular organization.
 In the private cloud computing model, cloud services such as compute, storage,
database, and network are available to an organization and its users only.
 In Private Cloud, the infrastructure can be maintained by the organization itself,
or by the third party that is providing the cloud services. Similarly, the hardware
can be located on-site or on the third-party site.
 Cost: Private clouds cost more than public clouds, as companies need to expend
a huge upfront capital investment to set them up and maintain them.
 Security: They are generally more secure than public clouds. Therefore,
organizations that want to run their mission-critical applications prefer private
clouds due to security reasons.

Public Clouds
 Public clouds are cloud computing infrastructures that are maintained and
operated by cloud service providers and that are available for public use.
 The public cloud is available from a number of providers, including Amazon
Web Services (AWS), IBM, Alibaba, Google Cloud, and Microsoft Azure.
 In the public cloud computing model, cloud services such as compute,
storage, database, and network are available over the Internet, and anyone
can use them. It means a startup, a big organization, or even an individual
can use public cloud services
 It is the cloud service provider’s responsibility to maintain the physical
infrastructure that supports their cloud services, such as the building, its
power and cooling systems, as well as those that encounter hardware
failures

Hybrid Clouds
 A hybrid cloud is a cloud computing infrastructure that benefits
from the public and private models and enables organizations to
use both.
 A hybrid cloud incorporates a private cloud and a public cloud and
allows applications and data to be shared among the two.

IT companies when started in garages
 Companies started in a
garage where each
deploy their website on a
single computer. While
the companies grow, they
have to deploy more
computers and this made
the limited-space garage
packed with computers.
 Hence, they moved to bigger place called data center
that include computer systems, hardware required for
their websites , apps, IT infrastructure.

Challenges involved with data centers
 Setting up a data center involves a huge upfront
investment in building, hardware, cooling, power,
ventilation equipment. In addition to spending a
significant amount on maintenance as well.
A. Costs

 Demand should always be met by any organization. It’s hard
to predict the actual hardware requirement. If businesses
grow five times, you need five times more servers.
 Also, if it doesn’t grow at the expected rate, you will have extra
servers. Due to this unexpected demand, most of the time,
developers end up over-provisioning the servers, which leads
to wasted computing space, cooling, electricity, and so on.
At the end of the day, it is all about COST.
B. Capacity Planning

C. Staffing and Technical Skill Sets
To monitor the data centers and troubleshoot them, you
need a skilled staff, which leads to additional cost.

Question Is there a way to reduce this hassle of
setting up and maintaining a data center?
Solution: Organizations start working with third-party data
center service providers to rent space on the provider’s
facility, where they either keep their servers or rent servers
from them. They pay the service provider for managing
their servers.
That’s a better way to offload some challenges, like
staffing and training; however, capacity planning and
upfront investment would still be major issues.

Solution Cloud Computing is the solution
 Organizations no longer need to spend money and
resources on physical space and maintenance.
 With cloud computing, the cloud services such as
compute, storage, database, and network become on
demand without having to worry about setting up and
maintaining data centers.

Cloud Service Models
 There exist various ways to deploying applications on the
cloud.
 Cloud computing is offered in three service models, each
satisfying a unique business requirement:
o IaaS (Infrastructure as a Service)
o PaaS (Platform as a Service)
o SaaS (Software as a Service)

Cloud Service Models
 Running an application at on-premise data centers,
organizations have to manage the following:
1. The application itself.
2. This application’s database for the data.
3. It must be developed in a programming language, right?
So they need a web or application server, called a Runtime.
4. A programming language and some middleware
software to run the application.
5. An operating system (OS).
6. Virtualization
7.The physical server, which is virtualized with a
hypervisor to run multiple operating systems. That helps
run multiple applications on a single physical server.
Virtualization is covered in Chapter 5.
8. Storage, for saving data.
9. Networking to connect IT systems like routers,
switches, other computers, and the Internet.

Cloud Concepts
 Scalability (vertical and horizontal scaling)
 Elasticity
 Agility
 High availability
 Fault tolerance

Scalability
Assume there exist an application on a VM. The more users accessing the
application, the more computing power is required (CPU and memory).
What to do?
Scaling:To meet demand, you can scale your virtual machine or infrastructure by:
a.Vertical Scaling (Scaling Up/Down):Scaling Up: Increasing the size or power of
the existing virtual machine. Scaling Down: Decreasing the size or power of the
existing virtual machine. Movement along a vertical line.
b.Horizontal Scaling (Scaling Out/In):Scaling Out: Adding more virtual
machines to your infrastructure. Scaling In: Reducing the number of virtual
machines. Movement along a horizontal line.

Scalability
Vertical Scaling: Increasing or decreasing the computing power of a
single machine.
Horizontal Scaling: Increasing or decreasing the number of machines in
the infrastructure.

Elasticity
If the load on your application varies throughout the day. There is more
traffic during the daytime and less at night. Hence you need to increase the
compute power to meet the demand.
Definition: The ability to scale the virtual machines based on the demand of
the application is known as elasticity.
Basically, you design the system so that it can allocate and deallocate virtual
machines whenever necessary. When the process is automated, this is called
automatic scaling. Elasticity is the ability of the system to scale dynamically.

Elasticity
To make it more clear to you:
Automatic Scaling is like a thermostat that turns the heater on or off
when the temperature crosses set thresholds.
Dynamic Elasticity is like a smart heating system that adjusts the
temperature smoothly and continuously based on real-time weather
and room occupancy.

Agility
Let’s take the same application example again. Whether you want to
achieve scalability or elasticity for your application, you need more
virtual machines.
Right?
The question is how quickly can you get virtual machines when you
need them. One

Delivery models
Infrastructure as a Service (IaaS)
Software as a Service (SaaS)
Platform as a Service (PaaS)
Deployment models
Private cloud
Hybrid cloud
Public cloud
Community cloud
Defining attributes
Massive infrastructure
Accessible via the Internet
Utility computing. Pay-per-usage
Elasticity
Cloud computing
Resources
Networks
Compute & storage servers
Services
Applications
Infrastructure
Distributed infrastructure
Resource virtualization
Autonomous systems
Cloud Computing Models, Resources, Attributes
32

Early Models of Cloud Computing
 Basic reasoning: information and data processing can be done more efficiently
on large farms of computing and storage systems accessible via the Internet.
 Two early models:
1. Grid computing – initiated by the National Labs in the early 1990s; targeted
primarily at scientific computing.
 “Grid computing is the collection of computer resources from multiple locations to reach a
common goal. The grid can be thought of as a distributed system with non-interactive
workloads that involve a large number of files.” from Wikipedia
2. Utility computing – initiated in 2005-2006 by IT companies and targeted at
enterprise computing.
 “Utility computing is a service provisioning model in which a service provider makes computing
resources and infrastructure management available to the customer as needed, and charges
them for specific usage rather than a flat rate.” from Wikipedia
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Cloud computing - Characteristics
“Cloud Computing offers on-demand, scalable and elastic computing (and storage
services). The resources used for these services can be metered and users are charged
only for the resources used. “ from the Book
Shared Resources and Resource Management:
1.
Cloud uses a shared pool of resources
2.
Uses Internet techn. to offer scalable and elastic services.
3.
The term “elastic computing” refers to the ability of dynamically and on-demand
acquiring computing resources and supporting a variable workload.
4.
Resources are metered and users are charged accordingly.
5.
It is more cost-effective due to resource-multiplexing. Lower costs for the cloud
service provider are past to the cloud users.
34

Cloud computing (cont’d)
Data Storage:
6.Data is stored:
 in the “cloud”, in certain cases closer to the site where it is used.
 appears to the users as if stored in a location-independent manner.
7.The data storage strategy can increase reliability, as well as security, and
can lower communication costs.
Management:
8.The maintenance and security are operated by service providers.
9.The service providers can operate more efficiently due to specialisation
and centralisation.
35

Cloud Computing Advantages
1. Resources, such as CPU cycles, storage, network bandwidth, are shared.
2. When multiple applications share a system, their peak demands for
resources are not synchronised thus, multiplexing leads to a higher
resource utilization.
3. Resources can be aggregated to support data-intensive applications.
4. Data sharing facilitates collaborative activities. Many applications
require multiple types of analysis of shared data sets and multiple
decisions carried out by groups scattered around the globe.
36

Cloud Computing Advantages
5. Eliminates the initial investment costs for a private computing
infrastructure and the maintenance and operation costs.
6. Cost reduction: concentration of resources creates the opportunity to
pay as you go for computing.
7. Elasticity: the ability to accommodate workloads with very large peak-
to-average ratios.
8. User convenience: virtualization allows users to operate in familiar
environments rather than in idiosyncratic ones.
37

Types of clouds
1. Public Cloud - the infrastructure is made available to the general public or a
large industry group and is owned by the organization selling cloud services.
2. Private Cloud – the infrastructure is operated solely for an organization.
1. Hybrid Cloud - composition of two or more Clouds (public, private, or
community) as unique entities but bound by a standardised technology that
enables data and application portability.
2. Other types: e.g., Community/Federated Cloud - the infrastructure is shared
by several organizations and supports a community that has shared concerns.
38

Why cloud computing is (could) be successful
when other paradigms have failed?
 It is in a better position to exploit recent advances in
software, networking, storage, and processor
technologies promoted by the same companies who
provide Cloud services.
 Economical reasons: It is used for enterprise computing;
its adoption by industrial organizations, financial
institutions, government, and so on has a huge impact
on the economy.
 Infrastructures Management reasons:
 A single Cloud consists of a mostly homogeneous (now more
heterogeneous) set of hardware and software resources.
 The resources are in a single administrative domain (AD).
Security, resource management, fault-tolerance, and quality of
service are less challenging than in a heterogeneous
environment with resources in multiple ADs. 39

Challenges for cloud computing
1. Availability of service: what happens when the service provider
cannot deliver?
2. Data confidentiality and auditability, a serious problem.
3. Diversity of services, data organization, user interfaces available at
different service providers limit user mobility; once a customer is
hooked to one provider it is hard to move to another.
4. Data transfer bottleneck; many applications are data-intensive.
40

More challenges
5. Performance unpredictability, one of the consequences of resource sharing.
 How to use resource virtualization and performance isolation for QoS guarantees?
 How to support elasticity, the ability to scale up and down quickly?
6. Resource management: It is a big challenge to manage different workloads
running on large data centers. Are self-organization and self-management the
solution?
7. Security and confidentiality: major concern for sensitive applications, e.g.,
healthcare applications.
Addressing these challenges is on-going work!
41

Cloud Delivery Models
1. Software as a Service (SaaS) (high level)
2. Platform as a Service (PaaS)
3. Infrastructure as a Service (IaaS) (low level)
42
source Wikipedia

Infrastructure-as-a-Service (IaaS)
Infrastructure is compute resources, CPU, VMs, storage, etc
The user is able to deploy and run arbitrary software, which can include operating systems and
applications.
The user does not manage or control the underlying Cloud infrastructure but has control over
operating systems, storage, deployed applications, and possibly limited control of some
networking components, e.g., host firewalls.
Services offered by this delivery model include: server hosting, storage, computing hardware,
operating systems, virtual instances, load balancing, Internet access, and bandwidth provisioning.
Example: Amazon EC2
43

Platform-as-a-Service (PaaS)
 Allows a cloud user to deploy consumer-created or acquired applications using
programming languages and tools supported by the service provider.
 The user:
 Has control over the deployed applications and, possibly, application hosting environment
configurations.
 Does not manage or control the underlying Cloud infrastructure including network,
servers, operating systems, or storage.
 Not particularly useful when:
 The application must be portable.
 Proprietary programming languages are used.
 The hardware and software must be customised to improve the performance of the
application.
 Examples: Google App Engine, Windows Azure
44

Software-as-a-Service (SaaS)
 Applications are supplied by the service provider.
 The user does not manage or control the underlying Cloud
infrastructure or individual application capabilities.
 Services offered include:
 Enterprise services such as: workflow management, communications, digital
signature, customer relationship management (CRM), desktop software,
financial management, geo-spatial, and search.
 Not suitable for real-time applications or for those where data is not
allowed to be hosted externally.
 Examples: Gmail, Salesforce
45

The Three delivery models of Cloud Computing
46

Cloud activities
 Service management and provisioning including:
 Virtualization.
 Service provisioning.
 Call center.
 Operations management.
 Systems management.
 QoS management.
 Billing and accounting, asset management.
 SLA management.
 Technical support and backups.
47

Cloud activities (cont’d)
 Security management including:
 ID and authentication.
 Certification and accreditation.
 Intrusion prevention.
 Intrusion detection.
 Virus protection.
 Cryptography.
 Physical security, incident response.
 Access control, audit and trails, and firewalls.
48

Cloud activities (cont’d)
 Customer services such as:
 Customer assistance and on-line help.
 Subscriptions.
 Business intelligence.
 Reporting.
 Customer preferences.
 Personalization.
 Integration services including:
 Data management.
 Development.
49

Ethical issues
 Paradigm shift with implications on computing ethics:
 The control is relinquished to third party services.
 Data is stored on multiple sites administered by several
organizations.
 Multiple services interoperate across the network.
 Implications:
 Unauthorised access.
 Data corruption.
 Infrastructure failure, and service unavailability.
50

De-perimeterisation
 Systems can span the boundaries of multiple organisations and cross
the security borders.
 The complex structure of Cloud services can make it difficult to
determine who is responsible in case something undesirable happens.
 Identity fraud and theft are made possible by the unauthorised access
to personal data in circulation and by new forms of dissemination
through social networks and they could also pose a danger to Cloud
Computing.
51

Privacy issues
 Cloud service providers have already collected petabytes of
sensitive personal information stored in data centers around
the world. The acceptance of Cloud Computing therefore will be
determined by privacy issues addressed by these companies
and the countries where the data centers are located.
 Privacy is affected by cultural differences; some cultures favour
privacy, others emphasise community. This leads to an
ambivalent attitude towards privacy in the Internet which is a
global system.
52

Cloud Vulnerabilities
 Clouds are affected by malicious attacks and failures of the
infrastructure, e.g., power failures.
 Such events can affect the Internet domain name servers and
prevent access to a Cloud or can directly affect the Clouds:
 in 2004 an attack at Akamai caused a domain name outage and a
major blackout that affected Google, Yahoo, and other sites.
 in 2009, Google was the target of a denial of service attack which
took down Google News and Gmail for several days;
 in 2012 lightning caused a prolonged down time at Amazon.
53

Back to Basics -- Parallel Computing
 “Parallel computing is a form of computation in which many
calculations are carried out simultaneously, operating on the
principles that large problems can often be divided into smaller ones,
which are then solved concurrently (in parallel).” Wikipedia
 Hardware and software systems allow us to:
 Solve problems demanding resources not available on a single
system.
 Reduce the time required to obtain a solution.
54

Parallel Computing – Amdahl’s Law
 The speedup S measures the effectiveness of parallelisation:
S(N) = T(1) / T(N)
 T(1)  the execution time of the sequential computation.
 T(N)  the execution time when N parallel computations are executed
 Amdahl's Law: if α is the fraction of running time a sequential program spends
on non-parallelisable segments of the computation then:
S ≅ 1/ α
 This is a theoretical upper bound on the best speedup we can get from
parallelising a certain program.
55

Back to Basics -- Distributed systems
 Collection of autonomous computers, connected through a network and
distribution software (often) called middleware which enables computers to
coordinate their activities and to share system resources for a common goal.
 Characteristics:
1. The users perceive the system as a single, integrated computing facility.
2. The components are autonomous.
3. Scheduling and other resource management and security policies are implemented by each
system.
4. There are multiple points of control and multiple points of failure.
5. The resources may not be accessible at all times.
6. Can be scaled by adding additional resources.
7. Can be designed to maintain availability even at low levels of hardware/software/network
reliability.
56

Summary
 What is Cloud Computing?
 Early models of Cloud Computing.
 Delivery models and services.
 Ethical issues in Cloud Computing.
 Cloud vulnerabilities.
 Parallel Computing and Distributed Systems (brief)
57

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