This is a guest lecture done at SLIIT Matara branch for the second year BSc IT students

1. Expectations of the IT
Industry

2. 2
About me
●
Name: Crishantha Nanayakkara
●
Designation: Vice President – Technology, Auxenta
●
Blog: www.crishantha.com
●
LinkedIn: https://www.linkedin.com/in/crishantha/
●
Twitter: @crishantha

3. 3

4. 4
Top 10 Strategic Trends in 2018
Source: Top 10 Strategic Technology Trends for 2018, Gartner

5. 5
15 Top Paying IT Certifications
Source: 15 Top Paying IT Certifications In 2018, Forbes

6. ● The Enterprise Architecture (EA)
●
The Enterprise Design Patterns and Development Frameworks
● Enterprise System Evolution (Monolithic SOA → →
Microservices)
● Cloud Native Applications (Containerization)
● Serverless Computing
●
Data Intensive Applications (Big Data)
●
Machine Learning / Artificial Intelligence
●
Decentralized Applications (Blockchain)
Agenda

7. Enterprise Architecture

8. 8
Enterprise Architecture

9. Enterprise Architecture is the complete expression of the
Enterprise.
It is a description of the goals of an organization, how these goals are
realized by business processes, and how these business processes can
be better served through technology.
Source: TOGAF 9.2
Phase 0 – Preliminary
Phase A – Architecture Vision
Phase B – Business Architecture
Phase C – Information Systems Architecture
Phase D – Technology Architecture
Phase E – Opportunities and Solutions
Phase F – Migration Planning
Phase G – Implementation Governance
Phase H – Architecture Change Management

10. Enterprise Design Patterns

11. 11
Object Oriented Design

12. 12
Enterprise Design Patterns

13. 13
Why Frameworks?

14. 14
Source: Stackoverflow Annual survey 2018
Popular Programming Languages

15. 15
Source: Stackoverflow Annual survey 2018
Popular Frameworks, Libraries

16. 16
Source: TIOBE Index, 2018
Popular Programming Languages

17. 17
Popular Programming Languages

18. Enterprise System Evolution

19. Pre­SOAPre­SOA
(Monolithic)(Monolithic)
Pre­SOAPre­SOA
(Monolithic)(Monolithic)
SOA SOA
(Monolithic)(Monolithic)
SOA SOA
(Monolithic)(Monolithic)
MicroservicesMicroservices MicroservicesMicroservices
(1990s)
(2000s)
(2010s)
Enterprise System Evolution
Cloud Enabled
On Premise

20. Reference: Microservices: The resurgence of SOA principles and an alternative to the monolith (PWC)
Enterprise System Evolution

21. 1.0 Pre­SOA
(Monolithic)

24. Monolithic application has single code base with multiple modules.
Modules are divided as either for business features or technical
features. It has single build system which build entire application
and/or dependency. It also has single executable or deployable binary
Single code base with multiple modules
On-premise or VM based cloud deployment

25. 2.0 SOA Monolithic

26. The Enterprise
Enterprise Application
Silos
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise ApplicationEnterprise Application
Enterprise Application

27. MiddlewareMiddleware
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise Application
Enterprise Application

28. 28
SOA
(Service Oriented Architecture)
Source: Open Source SOA

29. Enterprise Service BusEnterprise Service Bus
Cloud Infrastructure
48 Ministries 60 Departments 8 Provincial
Councils
271 DS Offices
Application
Application
Services
Application
Services
32 Provincial
Ministries
16 Provincial
Departments
Application
Services
Message
BrokerBPS
Service
Registry
An Example ­ SOA
Smart Pipe

31. 31
Enterprise Security

32. 3.0 Microservices

33. Is Microservices SOA?
Source: https://www.youtube.com/watch?v=wgdBVIX9ifA

34. ●
Cloud Native Applications
– Microservices
– Containers
– DevOps
●
Data Intensive Applications
– Big Data
– Data Lakes / Data Warehousing
– Machine Learning / Deep Learning
Microservices

35. 3.1 Cloud Native Applications

36. IaaS Cloud Market Share

38. ●
Cloud Native Applications
– Microservices
– Containers
– DevOps
– CI/CD
●
The Cloud Native Computing Foundation (CNCF)
Source: https://pivotal.io/cloud-native
Cloud Native Applications

39. “It is an approach that builds software applications as
microservices and runs them on a containerized and
dynamically orchestrated platform to utilize the
advantages of the cloud computing model.”
Cloud Native Applications

40. 40
Source: https://github.com/cncf/landscape/blob/master/landscape/CloudNativeLandscape_v0.9.2.jpg

41. Microservices
1. Domain Driven Design (DDD) ­ Stateless
2. Single Responsibility Principle (SRP)
3. Having a separate data store
4. Published Service Contracts (Swagger /RAML)
5. Container based Deployment (independent, lightweight)
6. Lightweight Communications (REST/HTTP, Websockets)
7, Dumb Pipes, Smart Endpoints
8. Horizontal Scaling (Y­Scale)

42. MSA
(Micro­Services Architecture)
Reference: Getting Started with Microservices – By Arun Gupta

43. Service Mesh
Source: http://philcalcado.com/2017/08/03/pattern_service_mesh.html

44. Netflix started Microservices implementation with the Cloud Migration

45. Integrating Microservices with
Legacy / Monolithic Systems

46. Containers (Docker)
1. They are fast, lightweight, consistent
2. Solves the deployment problems by deploying your application
with all dependencies into a single container

47. ● Container Orchestration will help to
– Monitor your system
– Trigger the startup and shutting down the containers
– Balance the load between the active application
instances
– Handle authentication between instances
● Current available Orchestration Solutions:
– Kubernettes, Docker Swarm, Apache Mesos, AWS ECS
Container Orchestration

48. Kubernetes
●
The most popular open source community
based framework at the moment
●
Kubernetes extends the Docker functionalities
by having following features:
– Managing Docker containers across the cluster
– Co­location of Docker containers
– Service Discovery
– Replication Control

49. Microservices Deployment

50. Serverless Design
●
Moving away from servers and infrastructure concerns and
allowing developers to primarily focus on the code is the
ultimate goal of being serverless.

51. 3.2 Data Intensive (Big Data)
Applications

52. ● Big Data
– Variety (Text, Audio, Video, etc)
– Volume (Tera and Peta bytes)
– Velocity (Data Frequency, Not under your control)
Big Data

53. ● What lead to Big Data?
– Cloud Adoption, Social Media, Mobile Usage, Sensor
Data
What lead to Big Data?

54. ● What is a Big Data Application?
– Data must be in Tera or Peta bytes
– More than one source / form
– Huge processing loads
– Real time stream processing
– Process and Persist in scalable and flexible data stores
– APIs for query purposes
– Provide advanced analytics
Big Data Applications / Solutions

55. ● What are Big Data Technologies?
– Numerous companies. Numerous products
– Mainly open source
– Cloud focused
– Mostly immature (It is a good thing!)
Big Data Technologies

56. 56
Big Data Open Source Stack

57. The Big Data Evolution
(The Open Source Stack)
Batch
Processing
Stream
Processing
Artificial
Intelligence

58. The Big Data Evolution
(The AWS Cloud Stack)
Batch
Processing
Stream
Processing
Artificial
Intelligence

59. The Big Data Pipeline

60. The AWS Big Data Pipeline

61. 61
Data Intensive Design

62. 62
Decentralized Applications (DApps)

63. Thank YouThank You