The document discusses the evolution of information technology platforms from Platform 1.0 to Platform 3.0. Platform 1.0 referred to centralized mainframe computing (1980s-1990s). Platform 2.0 introduced distributed processing and the internet (2000-2010). Platform 3.0 is defined by cloud computing, mobile integration, internet of things, big data, analytics and devops (2010-present). Key aspects of Platform 3.0 include cloud infrastructure, application programming interfaces, open data, big data technologies like Hadoop, and the growing internet of things.

1. By Crishantha Nanayakkara
Head Of Technology, ICTA
@crishantha (Twitter)
Global Trends
in
Information Technology

2. Platform 1.0Platform 1.0Platform 1.0Platform 1.0
Platform 2.0Platform 2.0Platform 2.0Platform 2.0
Platform 3.0Platform 3.0Platform 3.0Platform 3.0
(1980s to 1990s)
(2000 - 2010)
(2010 onwards)

3. Platform 1.0Platform 1.0Platform 1.0Platform 1.0
●
Centralized processing platform
●
The Main­Frame era
●
IBM domination
●
Hardware companies dominated
●
Still there are platform 1.0 implementations

4. Platform 2.0Platform 2.0Platform 2.0Platform 2.0
●
Distributed processing platform
●
Rapid improvement in low cost computers / servers
●
Invention of TCP/IP and the Internet
●
Middleware, Messaging Systems, App Servers, Web
Servers, etc
●
Software only companies started to grow

5. The Layered Architecture

6. MiddlewareMiddleware
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise ApplicationEnterprise Application
Enterprise Application

7. 7
SOA
Source: Open Source SOA

8. SOA

9. Platform 2.0 IssuesPlatform 2.0 IssuesPlatform 2.0 IssuesPlatform 2.0 Issues
●
Platform 2.0 infrastructure was not able to handle the
scalability aspect for the increased growth in demand
for the services
●
Social media pushed to store more unstructured data
than the structured data, which traditional databases
could not handle
●
With the heavy load of data, the demand for a real
time analytical systems were needed

10. Platform 3.0Platform 3.0Platform 3.0Platform 3.0
●
Processing Data in the Cloud (Cloud Computing)
●
Integrate mobile devices with the enterprise APIs
●
Incorporate new sources of data to the Internet of
things (IoT)
●
Manage and share data that has high volume (Big
Data)
●
Turn the data into usable information through
analytics (Big Data Analytics)
●
Ability to build software cheaply and fast, deploy it
instantly (DevOps)
- The Modern Generation

11. Cloud ComputingCloud Computing

12. 12
● Built on the Virtualization concept
● Virtualization Software creates virtual
servers with pooled resources
● It is easy..
– To create virtual servers
– To provide resources on demand
– To manage
– To self provision
– To meter / bill the usage

13. 13

14. 14
Source: http://www.zdnet.com/article/what-is-docker-and-why-is-it-so-darn-popular/

15. 15
Traditional HW Model vs Cloud
Model

16. 16
The Deployment Models
Public
Cloud
Private
Cloud
Hybrid
Cloud

17. 17
The Deployment Models

18. 18
The Service Models
IaaS
(Infrastructure As
A Service)
PaaS
(Platform As
A Service)
SaaS
(Software As
A Service)
Amazon EC2
GoGrid
WSO2 Stratos
CloudFoundry
Windows Azure
Amazon EC2
GoGrid
Rackspace
Joyent
SalesForce
Network Architects Application Developers End Users

19. 19

20. Application Program Interfaces (APIs)Application Program Interfaces (APIs)

21. ●
An API is a set of programming instructions and
standards for accessing a Web­based software
application or Web tool.
●
A software company releases its API to the public so
that other software developers can design products
that are powered by its service.
●
Mobile applications are heavily using these
lightweight APIs

22. Source: http://www.programmableweb.com/news/who-belongs-to-api-billionaires-club

23. 23

25. Open DataOpen Data

26. Open Data

29. Big DataBig Data

30. ●
Facebook is one of big data's biggest
champions, and it claims to operate the largest
single Big Data clusters anywhere, with more
than 100 petabytes of disk space
●
The site stores more than 250 billion photos,
with 350 million new ones uploaded every day
●
Uses Hadoop, Hive and Hbase as the core
technologies in the back end

31. A new generation of technologies and
architectures, designed to economically
extract VALUE from very large VOLUMES of a
wide variety of data by enabling high­
VELOCITY capture, discovery, and/or analysis.

32. The Three Vs of Big Data
●
Volume – Big
●
Variety – From different sources and types
●
Velocity – Frequency of its generation: how
quickly the data arrives and is stored, and how
quickly it can be retrieved

33. The Three Vs of Big Data

34. The Digital Universe
● From 2005 to 2020, the digital universe will grow from 130
exabytes to 40,000 exabytes, or 40 trillion gigabytes.

35. According to IDC, the Big Data technology and service market was about
US$4.8 billion in 2011. The market is projected to grow at a compound annual
growth rate (CAGR) of 37.2% between 2011 and 2015.
By 2015, the market size is expected to be US$16.9 billion.
[Source: IDC. Worldwide Big Data Technology and Services 2012­2015 Forecast.]

36. Gartner reported that more than 65 billion devices were connected
to the internet by 2010. By 2020, this number will go up to 230 billion
[Source: https://www.gartner.com/doc/1799626]

37. ●
Over a history that spans more than 30 years, SQL
database servers have traditionally held gigabytes of
information — and reaching that milestone took a
long time.
●
In the past 15 years, data warehouses and enterprise
analytics expanded these volumes to terabytes.
●
And in the last 5 years, the distributed file systems
that store Big Data now routinely house petabytes of
information.
The Statistics

38. p
Reference: Hadoop In Action
Hadoop Architecture

39. HDFS

40. Hadoop Eco System

41. NoSQL

42. Internet Of ThingsInternet Of Things
(IOT)(IOT)
The next mega era in Computing

43. IoT is a network of uniquely identifiable
endpoints/objects that communicate using IP
connectivity without human interaction.
Here, all the objects will be “on­line” and ready
to serve you automatically.
(World Wide IOT Taxonomy, 2015 ­ IDC)

46. AT&T Digital Life Tablet App

47. ●
A number of important technology changes
have coincided to enable the rise of the IOT,
– including cheap sensors,
– inexpensive bandwidth,
– cheap processing,
– smart phones,
– wireless coverage,
– big data,
– open­source technology,
– IPv6

48. ●
The worldwide IoT market will grow from
$655.8 billion in 2014 to $1.7 trillion in 2020
(IDC).
●
Today 43% of world wide IoT revenue comes
from manufacturing, transportation and smart
cities
●
Within next 5 years all industries should come
up with a business plan for an IoT initiative

49. ●
By 2018, 60% of IT solutions will be “Open
Sourced” allowing IoT markets to form
Because Open Sourced products are
– Open
– No vendor locking
– Better Community based development, which is
good for complex systems like IoT
– Most Big Data options are open source.

50. Thank YouThank You