Cloud Computing Fundamentals and building blocks

1. CLOUD COMPUTING
Dr.Selvaraj Kesavan

2. Contents
2
▪ Introduction to Cloud Computing
▪ Origins and Motivation
▪ Types of Clouds and models
▪ Cloud Infrastructure and Deployment

3. Cloud Computing - History
➢ In 1950’s mainframe computers were huge, occupying entire
rooms.
➢ Due to the cost of buying and maintaining mainframes,
organizations couldn’t afford to purchase one for each user.
➢ The solution was “time sharing” in which multiple users
shared access to data and CPU time. The term “time sharing”
is the premise of cloud computing.
➢ 1960- The Advanced Research Projects Agency
Network (ARPANET) was an early packet switching network
and the first network to implement the TCP/IP protocol suite
➢ 1970 – IBM introduced VM’s (virtual machine’s) run on single
physical machine 3

4. Cloud Computing - History
➢ In 1990 – Telecommunication companies offered virtualize
private network connections to allow more users through
shared access to the same physical infrastructure.
➢ First accepted use of it in the relevant context was by
professor Ramnath Chellappa in an Information Systems
lecture at the University of Texas in 1997
➢ In 2006 former CEO of Google Eric Schmidt used the term
‘cloud computing’ to describe the upcoming Google Docs
➢ Amazon started working from 2002 and publicly launched on
March 19, 2006 with S3,SQS and EC2
➢ Microsoft Azure released in 2010
➢ Google Cloud platform released on April, 2008 4

5. Cloud Computing
5
▪ Local Computing
▪ Concepts and technologies for network-centric computing and
content evolved through the years and led to several large-scale
distributed system developments
▪ Information processing can be done more efficiently on large
farms of computing and storage systems accessible via the
Internet.
▪ Advancements in networking and other areas are responsible for
the acceptance of the new computing models
▪ Web opened a new era in data sharing and ultimately led to the
concept of network-centric content.

6. Cloud Computing
6
▪ Grid computing (1990) – Distributed computing
• Distributed architecture where many computers are connected to
resolve given problem. All systems are linked and connected using
WAN and independent tasks are assigned to each system. Reach
common goal to solve single task.
▪ Utility Computing (2005) - Delivering computing as a utility.
• Business model for on-demand delivery of computing power;
consumers pay providers based on usage (“pay as- you-go”). It often
requires a cloud-like infrastructure

7. Cloud Computing
▪ Sophisticated on-demand computing services
▪ Cloud is a parallel and distributed computing system consisting
of a collection of inter-connected and virtualized computers that
are dynamically provisioned and presented as one or more
unified computing resources based on service-level agreements
(SLA)
▪ Cloud computing is the on-demand delivery of compute power,
database storage, applications, and IT resources through a
services platform via the internet with pay-as-you-go pricing.
▪ It is the delivery of computing as a service rather than product
where shared resources, software and information are provided
to users as an utility.
▪ Moving from traditional to on-Demand model. 7

8. Cloud Computing
8
▪ Scientific and engineering applications, data mining,
computational financing, gaming, and social networking as well
as many other computational and data-intensive activities can
benefit from cloud computing.
▪ A broad range of data, from the results of high-energy physics
experiments to financial or enterprise management data to
personal data such as photos, videos, and movies, can be stored
on the cloud.

9. Cloud Computing - Enablers
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▪ Virtualization
▪ Web 2.0 and social networking
▪ Web Scaling
▪ Hardware costs
▪ Evolution of high speed communication technologies

10. Virtualization
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• Traditional environment
• 50 applications ,DB’s require multiple machines based on Architecture
/platform
• High infrastructure and hardware cost
• Increasing complexity and High maintenance
• Multiple development environment
• Virtualization
• Isolation & encapsulation
• Scalability
• Containers
• software technology providing additional layer of abstraction and over OS
virtualization.
• Build once and deploy many times.

11. Virtualization
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• Hardware Virtualization (system Virtualization)
• Guest running on the top of hardware
• Guest - operating system, Host -Physical computer hardware
• Virtual machine Manager(Hypervisor) allows the abstraction of the underlying physical
hardware
• It is program or a combination of software and hardware
• Provides direct ISA mapping to Virtual machines
• Type 1 (bare metal) and Type 2 (on OS) Hypervisor
• Hardware Assisted (Xen,VMWare) Full and Paravirtualization (Xen,VMWare, Wind
River).
• OS Virtualization
• Create different and separated execution environments for applications concurrently.
• OS kernel allows for multiple isolated user space instances.
• Directly use OS calls without emulation
• Ex: Containers,
• Key building block in IaaS
• Programming language-level virtualization

12. Cloud Computing –Essential Characteristics
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Essential Characteristics
Resource
pooling
Broad network
access
Measured
Service
Rapid
Elasticity
On-demand
Self-service
Scalability:
• Ability to system to handle increasing workload by increasing in
proportion the amount of resource capacity.
• Architecture allows on-demand resources for increasing
workload
Elasticity:
• Dynamically Commissioning and decommissioning of resources
• Speed at which resources are provisioned on demand and usage
of resources

13. Cloud Computing - Deployment models
Private Cloud
Public Cloud
Hybrid Cloud
Private Cloud: The infrastructure is operated solely for an organization. It may
be managed by the organization or a third party and may exist on or off the
premises of the organization.
Public Cloud: The infrastructure is made available to the general public or a
large industry group and is owned by an organization selling cloud services.
Hybrid Cloud: The infrastructure is a composition of two or more clouds
(private, community, or public) that remain unique entities but are bound together
by standardized or proprietary technology that enables data and application
portability.
Community Cloud: The infrastructure is shared by several organizations and
supports a specific community that has shared concerns (e.g., mission, security
requirements, policy, and compliance considerations). It may be managed by the
organizations or a third party and may exist on premises or off premises.
Community Cloud

14. Deployment models -Limitations
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• Public Cloud
• Customers on public clouds share the
same infrastructure pool, often with
limited configurations, perceived security
protections and availability variances
• Customers don’t control the security of a
public cloud, though all of their data
remains separate from others.
• Private Cloud
• A private cloud does not have the on-
demand scalability of hyper-scale private
• To expand the physical footprint of a
private cloud takes time and capital.
Hybrid Cloud
• Initial deploying cost of a hybrid cloud exceeds as compared to the setup
cost
• Specific hardware is required to deploy on premises, and that’s what shaves
off a large chunk of the budget.
• Performance Degradation due to capacity mismatch

15. Cloud Computing- Service models
SaaS
Software-as-a-Service
applied to
Applications
e.g. email, productivity, CRM
PaaS
Platform-as-a-Service
applied to
App Infrastructure
e.g. app runtimes,
middleware, dev tools
IaaS
Infrastructure-as-a-Service
applied to
System Infrastructure
e.g. VMs, containers, storage,
network
Access the services from provider. consumer uses an
application, but does not control the operating system,
hardware or network infrastructure on which it's running
The consumer uses a hosting environment for their
applications. The consumer controls the applications that
run in the environment but does not control the operating
system, hardware or network infrastructure on which they
are running. Provides the middleware framework
The consumer uses fundamental computing resources such
as processing power, storage, networking components

16. SaaS PaaS IaaS
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17. 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, group-ware and
collaborative, supply chain, communications, digital signature, customer
relationship management (CRM), desktop software, financial management,
geo-spatial, and search.
• Web 2.0 applications such as: metadata management, social networking, blogs,
wiki services, and portal services.
• Not suitable for real-time applications or for those where data is not allowed to be
hosted externally.
• Examples: Gmail, Google search engine.

18. 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 customized to improve the performance of
the application.

19. IaaS
• 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,
• Web servers,
• storage,
• computing hardware,
• operating systems,
• virtual instances,
• load balancing,
• Internet access,
• bandwidth provisioning.

20. Major Benefits
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Speed to Market
Cost Reduction
Elasticity / Scalability
Agility
• Lower capital and operational costs
• Pay-per-use
• Economies of scale
• Reduction of time to pilot and test
projects
• New geographies
• Broad geographic availability
• Faster availability to customers
• Capacity only when you need it
• Ability to handle sudden load changes
• Survive infrastructure failures
• Productivity & Speed
• Deploy faster; Iterate faster
• React faster to changing business
needs
• “Infinite” computing capacity
Backup and Disaster Recovery
• Quick data backup and reduced recovery time
• Don’t let your competitors overtake business
• Avoid to compromise the business reputation
• Drastic reduction of restore times and lower RTO & RPO

21. Cloud Computing Platform/Services
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22. Cloud Computing Platform/Services
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23. Cloud environment -Major Services
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Major cloud
platform
services
Machine Learning

24. Security
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• SSO/MFA
• Username/
Password
• API Security
• Data At
Transit
• Data At Rest
• Firewall
• DoS
prevention
• Certificate/
Encryption
Authentication :
- Allow Apps to authenticate on behalf of users
- Allow users
Authorization:
- Fine-grained access control
- Attribute management
- Policy evaluation
- Policy Management
Implementation:
• SSO( Single Sign On)
• Web Federated Identity

25. Challenges for cloud computing
▪ Availability of service; what happens when the service provider cannot deliver?
▪ 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. Standardization efforts at NIST!
▪ Data confidentiality and auditability, a serious problem.
▪ Data transfer bottleneck; many applications are data-intensive.
▪ Performance unpredictability, one of the consequences of resource sharing.
▪ How to use resource virtualization and performance isolation for QoS guarantees
▪ the ability to scale up and down quickly
▪ Resource management;
▪ Security and confidentiality; major concern.

26. Summary
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▪ Cloud Computing – Introduction
▪ Key Enablers
▪ Essential Characteristics
▪ Cloud Deployment Models
▪ Cloud Service Models
▪ Benefits
▪ Challenges

27. Thank You
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