The document discusses the evolution and components of cloud computing, highlighting three primary layers: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). It explains the target audiences and examples for each layer, illustrating how these services are delivered and managed over the internet. Additionally, it addresses barriers to cloud adoption, including security concerns, governance, and potential vendor lock-in.

1. Cloud
Computing
101
Otto I. Mora
Georgia Tech MBA IT Club

2. Computing Paradigm Evolution
Personal
Mainframe Computing Client/Server Mobile Cloud
Computing Computing Computing Computing

3. Cloud Computing has 3 layers:
Software and
Application services
Operating System
on which to build
Platform and run your
applications.
Physical Hardware
on which to run
Infrastructure the Operating
System.
... and all 3 can be delivered and managed over the internet as a service.

4. Software as Service (SaaS)
• Software delivery model in which software
and its associated data are hosted centrally
(typically in the Internet cloud).
• No need to pay license, subscription model
(pay as you go like utility bill).
SaaS Provider
Thin “Cloud Clients”

5. Software as Service (SaaS)
• Key target audience: End Users (both
companies and consumers).
• Examples:
SaaS Customer Relationship
Management (CRM) provider. Google Apps: SaaS provider of
email, calendar and office
documents (spreadsheet, word
processing, etc)
Online Exchange Server (email), Sharepoint (document
collaboration and sharing and Office Web Apps.

6. Platform as Service (Paas)
• Provides both a computing platform and a
solution stack as a service.
Build Host Scale
Build the Host it in the PaaS Cloud OS systems
application the in provider’s are able to
PaaS provider’s OS computing dynamically scale
platform. hardware. according to
demand.

7. Platform as Service (Paas)
• Key target audience: Developers (“come run
your code on our platform”) and Companies
(“port your applications to our platform”).
• Examples:
One of the pioneers in PaaS, originally built on
Ruby. First to implement “polyglot” (support for Google Cloud Engine: Allows
several programming languages). Popular use of Python, Java, PHP, JRuby and
NoSQL. others. Uses GQL instead of SQL
(google specialized database
system). Wide availability of APIS .
MS Solution, able to run .NET, Java, PHP and
others. Worldwide CDN across 24 datacenters.

8. Infrastructure as a Service (Saas)
• Made possible by Virtualization: Computers
are able “emulate” others. Think of a “a dream
inside a dream”, or translating from one
language to another in your head, or running
SNES games on your pc. The PC “emulates”
the SNES hardware.

9. Infrastructure as a Service (Saas)
• Well… if you can run one Nintendo inside your
pc… You can probably run two if you have a
powerful enough computer….

10. Infrastructure as a Service (Saas)
• …. Or several with a powerful server.
• The necessary requirement is only
that we “package” these virtual
computers so that they are able to
run independently and
concurrently on the same
hardware. Virtual computers are
packaged into virtual “image files”.

11. Infrastructure as a Service (Saas)
• Cloud providers offer computers – as physical
or more often as virtual machines, as an on
demand service from large pools of hardware
resources in their data center.
• Cloud users then install operating system
images on the machines as well as their
application software
Linux
Mail
Oracle
Server
Database
Server
Windows
Sharepoint
Server

12. Infrastructure as a Service (Saas)
• Key target audience: IT Departments (“don’t
buy and own your own hardware
infrastructure instead rent it from us on a per
use basis”)
• Examples:
Virtual Infrastructure management Amazon EC2 allows users to rent
tool. Used by Rackspace and Nasa. virtual computers on which to run
Allows companies to provide cloud their own computer applications. The
computing services using commodity underlying infrastructure uses the Xen
hardware. Virtual Hypervisor.

13. Barriers to Adoption of the Cloud
• Education and expertise (to move beyond the
marketing abuse of the word cloud).
• Data security concerns (results in “private
clouds”).
• Governance (lack of tools to easily manage
scaling up and down).
• Economies of scale (pooling of enough demand
together to create momentum).
• Danger of “lock in”, need ability to easily transfer
from one provider to another.