The document provides an overview of modern cloud architecture. It discusses key cloud concepts like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It also covers architectural considerations for cloud applications like multi-tenancy, load balancing, scaling, security, monitoring, and metering. Microservices architecture and containerization are introduced as approaches for building applications for the cloud. Data-intensive architectures like lambda architecture are also summarized.

1. Modern Architecture
Giragadurai Vallirajan
CTO@Bluemeric
@Girag
https://www.linkedin.com/in/Girag

2. Agenda
• What is Cloud?
• Softwares in Cloud?
• Architecting for Cloud
• Application
• Micro Services
• Data Intensive
• Questions

3. Cloud

4. “Cloud computing enables companies to
consume compute resources as a utility (like
electricity) rather than having to build and
maintain computing infrastructures in-house.”
Three of the main benefits of cloud computing include:
• Self-service provisioning: End users can spin up
computing resources for almost any type of workload
on-demand.
• Elasticity: Companies can scale up as computing
needs increase and then scale down again as
demands decrease.
• Pay per use: Computing resources are measured at a
granular level, allowing users to pay only for the
resources and workloads they use.
Cloud

5. CloudLayers
PAAS
SAAS
IAAS
Build
On It
Migrate
to It
Consume
It
Software As Service
Platform As Service
Infra As Service
Compute
Network
Storage
Server
load balancer
Firewalls
IP
Application Server Web Server
Runtime Database Queue
Monitoring Games
Collaboration
Finance
Communication CRM

7. Architecting
(SAAS)

8. Factors
• Multi-tenancy
• Load Balancing
• Scaling
• Security
• Monitoring and Metering
• Pricing

9. Tenancy
Shared Nothing Shared Few Shared Everything
☺ ☺ ☺ ☺ ☺ ☺ ☺ ☺ ☺ ☺ ☺ ☺
app app app app Application Application
Databasedb db db db db db db db

10. Load Balancing

11. Scaling

13. Scale cube
http://microservices.io/articles/scalecube.html

14. X-axis scaling consists of running multiple copies of an
application behind a load balancer.
/report
/report
/report

15. Y-axis axis scaling splits the application into multiple, different
services. Each service is responsible for one or more closely
related functions.
/login
/purchase
/report

16. /login
/purchase
/report
MixingIt…

17. Using Z-axis scaling each server runs an identical copy of the
code, however handle subset of data
/purchase[A-K]
/purchase[L-Q]
/purchase[R-Z]
Products (A-K)
Products (L-Q)
Products (R-Z)

18. Monitoring and Metering Cloud application
metrics for health tracking and also pricing
• CPU Utilization
• Network (Inbound / Outbound)
• DiskOps, Bytes (Read/Write)
• ServerThroughput (In/Out)
• Service API Usage Count
• Delays
Metering

19. Pricing

20. Pricing
• Focusing solely on registering accounts with free trials increases
dependency and ultimately, conversions.
• Presenting 5 plans clearly enforces the level of seriousness, capability,
and value increase by price plan, without doubting higher price points.
• Focusing on team size directly validates price differences.
• Pairing a free trial with necessary quotes allows potential customers to
experience the service first-hand and validate higher-priced plan
propositions.
• Transparency and customisation in pricing information allow potential
customers to determine an appropriate plan and increase comfort
level.

21. SAAS
Application
PAAS
IAAS Metering
EndPoints
Collector
(by Profile)
Billing
Engine
Metrics
&
Metering
Profile

22. Security
Reference : AWS Documentation on Security

23. Security
Top 10 security issues to be addressed,
• SQL, operating system or LDAP injection
• Insecure authentication and session management
• Cross-site scripting because of lack of data validation
• Insecure exposure to references like files and directories
• Incorrectly configured (from a security perspective) databases, middleware and operating systems
• Exposing sensitive data like user IDs, passwords and personal identification information
• Checking for access inside the business logic on the server side
• Cross-site request forgery
• Using components with known vulnerabilities
• Unvalidated redirects and forwards

24. Deployment

25. Assignment
Questionnaire App
We have to design an SAAS based application for helping customer who like
to post a survey, poll, census to study their customer expectation, business
reachability or quiz competitions.
Functionality,
1. An Account can have many survey and track them
2. Participant can be Anonymous (survey) or known (quiz)
3. Statistical analytics of individual survey
4. Every campaign stay active for duration
5. API Service for custom integration
6. Charges
Factors to be noted,
1. Scale, end user must get seamless feeling even the load high
2. Multi-Tenancy
3. Security

26. Application
(microservices)

27. Micro Service Architecture is an architectural concept
that aims to decouple a solution by decomposing
functionality into discrete services.
µServices
Reference
http://www.pwc.com/us/en/technology-forecast/2014/cloud-computing/features/microservices.jhtml

28. • the microservice architectural style is an approach to
developing a single application as a suite of small services,
each running in its own process and communicating with
lightweight mechanisms, often an HTTP resource API.
• These services are built around business capabilities and
independently deployable by fully automated deployment
machinery.
• There is a bare mininum of centralized management of
these services, which may be written in different
programming languages and use different data storage
technologies.
Anatomy

29. Design
Monolithic Application Microservices Application

30. Deployment
Microservices Application
Message Bus

31. Reference
http://www.pwc.com/us/en/technology-forecast/2014/cloud-computing/features/microservices.jhtml

32. Operating-system-level virtualization is a server-virtualization method
where the kernel of an operating system allows for multiple isolated user-
space instances, instead of just one. Such instances, which are
sometimes called containers, software containers, virtualization engines
(VEs) or jails, may look and feel like a real server from the point of view of
its owners and users.
On Unix-like operating systems, one can see this technology as an
advanced implementation of the standard chroot mechanism. In addition
to isolation mechanisms, the kernel often provides resource-management
features to limit the impact of one container's activities on other
containers.
~wikipedia
Containers

33. Server
Host OS
Guest
OS
Bin/Lib
APP
Bin/Lib
APP
Bin/Lib
APP APP APP
VMStack
Hypervisor
Guest
OS
Guest OS

34. Server / Hypervisor
Host OS
Container Engine
(Docker, Rocket)
Bin/Lib
APP
Bin/Lib
APP
Bin/Lib
APP APP APP
ContainerStack
Containers

35. Hypervisor
Bin/Lib
APP
Bin/Lib
APP
Bin/Lib
APP APP APP
Uni-kernelStack
OS OS OS
Containers

36. ContainerLayout
Layer 1 (Shared)
Layer 2 (Shared)
Layer 3 (A) Layer 3 (B) Layer 3 (C)
APP APP APP

37. • Lightweight resource utilisation: instead of virtualising an entire
operating system, containers isolate at the process level and use the
host’s kernel.
• Portability: all of the dependencies for a containerised application are
bundled inside of the container, allowing it to run on any container
engine host (Docker).
• Predictability: The host does not care about what is running inside of
the container and the container does not care about which host it is
running on. The interfaces are standardised and the interactions are
predictable.
Advantage

38. https://www.mindmeister.com/389671722/open-container-ecosystem-formerly-docker-ecosystem
Refer following link for latest up-to-date Ecosystem

39. https://msdn.microsoft.com/en-us/virtualization/windowscontainers/about/container_ecosystem
Microsoft

40. • Kubernetes
• Fleet
• Swarm
• Mesos
• Marathan
Scheduler

41. • Google Container Engine
• Amazon EC2
• Azure Container System
• Microsoft Service Fabrics
CloudOffering

42. Assignment
REST API
Passenger
Management
Billing
Payment
Trip
Management
Notification
Driver
Management
WEB UI
MySQL
Adaptor
Payment
Adaptor
SendGrid
Adaptor
KooKoo
Adaptor
Driver
Passenger

43. Application
(Data Intensive)

44. Reference : Tiecon Bigdata Landscape

45. Reference : IBM Infographics

46. Architecture

47. Infrastructure
Big-data Framework
Build Cluster

48. Infrastructure
Big-data Framework
Ingress
Batch
Ingest
Event
Ingest

49. Infrastructure
Big-data Framework
Ingress
Batch
Event
Staging
Storage
Format
Data
Partition
Access
Control

50. Infrastructure
Big-data Framework
Ingress
Batch
Event
Staging
Storage
Format
Data
Partition
Access
Control
Data Processing Data
Transformation
Analytics

51. Infrastructure
Big-data Framework
Ingress
Batch
Event
Staging
Storage
Format
Data
Partition
Access
Control
Data Processing
Data
Transformation
Analytics
Orchestrate
Manage
Workflow

52. Infrastructure
Big-data Framework
Ingress
Batch
Event
Staging
Storage
Format
Data
Partition
Access
Control
Data Processing
Data
Transformation
Analytics
Orchestrate
Management
Workflow

53. Infrastructure
Big-data Framework
Ingress
Batch
Event
Staging
Storage
Format
Data
Partition
Access
Control
Data Processing
Data
Transformation
Analytics
Orchestrate
Management
Workflow
Egress
RDBMS
Data
JSON
File
Data Pipeline

54. Cloud / Virtual Machine / Network / Cluster
Hadoop Framework
Ingress Staging Data Processing Orchestrate Egress
Data Pipeline
Flume
Sqoop
HDFS
HTTPFS
AVRO
ETL
ACL
YARN
STROM
SPARK
MapReduce
Oozie
CDH
Navigator
RDBMS
Data
JSON
XML

55. Lambda
Architecture

56. Speed Layer
Batch Layer Service Layer
Query
Query
Reference : Bigdata Lambda Architecture

57. Reference : http://www.slideshare.net/mjft01/big-data-landscape-matt-turck-may-2014

58. Assignment Recommendation System
Analysis of social media activity is one of the most important. Everyone a
on social media these days, whether they're "liking" company pages on
Facebook or tweeting complaints about products on Twitter. A Big Data
solution built to harvest and analyze social media activity, Social media
can provide real-time insights into how the market is responding to
products and campaigns. With those insights, companies can adjust their
pricing, promotion, and campaign placement on the fly for optimal results.
Functionality,
1. Recognise my taste like What Would customer buy in near
feature (Personal)
2. Recognise the Market trend in a Particular city (Geo)
3. Feed from FB Pages, Twitter, Review sights
Factors to be noted,
1. Accuracy of result

59. Q&A