By Crishantha Nanayakkara Head Of Technology, ICTA @crishantha (Twitter) Global Trends in Information Technology
By Crishantha NanayakkaraHead Of Technology, ICTA
@crishantha (Twitter)
Global Trends in
Information Technology
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)
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
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
The Layered Architecture
MiddlewareMiddleware
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise ApplicationEnterprise Application
Enterprise Application
7
SOA
Source: Open Source SOA
SOA
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
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
Cloud ComputingCloud Computing
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
14
Source: http://www.zdnet.com/article/what-is-docker-and-why-is-it-so-darn-popular/
15
Traditional HW Model vs Cloud Model
16
The Deployment Models
PublicCloud
PrivateCloud
HybridCloud
17
The Deployment Models
18
The Service Models
IaaS(Infrastructure As
A Service)
PaaS(Platform AsA Service)
SaaS(Software As
A Service)
Amazon EC2GoGrid
WSO2 StratosCloudFoundryWindows Azure
Amazon EC2GoGridRackspaceJoyent
SalesForce
Network Architects Application Developers End Users
19
Application Program Interfaces (APIs)Application Program Interfaces (APIs)
● 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
Source: http://www.programmableweb.com/news/who-belongs-to-api-billionaires-club
23
Open DataOpen Data
Open Data
Big DataBig Data
● 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
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.
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
The Three Vs of Big Data
The Digital Universe● From 2005 to 2020, the digital universe will grow from 130
exabytes to 40,000 exabytes, or 40 trillion gigabytes.
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.]
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]
● 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
p
Reference: Hadoop In Action
Hadoop Architecture
HDFS
Hadoop Eco System
NoSQL
Internet Of ThingsInternet Of Things(IOT)(IOT)
The next mega era in Computing
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)
AT&T Digital Life Tablet App
● 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
● 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
● 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.
Thank YouThank You