Datacenter and cloud architectures continue to evolve to address the needs of large-scale multi-tenant data centers and clouds. These needs are centered around dimensions such as scalability in computing, storage, and bandwidth, scalability in network services, efficiency in resource utilization, agility in service creation, cost efficiency, service reliability, and security. Data centers are interconnected across the wide area network via routing and transport technologies to provide a pool of resources, known as the cloud. High-speed optical interfaces and dense wavelength-division multiplexing optical transport are used to provide for high-capacity transport intra- and inter-datacenter. This presentation will provide some brief descriptions on the working principles of Cloud & Data Center Networks.

1. CLOUD & DATA CENTER
NETWORKING
H.M.V.T.W Bandara
14/AS/PS/001
Ep 1996

2. CONTENT
 Cloud Computing
 Five Essential Characteristics of Cloud Model
 Cloud Computing Service Models
 Cloud Deployment Models
 Data Center Networking
 What are Data Centers?
 Why Data Center Networking
 Server Rack Design and Server Infrastructure
 Data Center NetworkingTopologies
 Data Center MultiTier Design Overview
 Cloud Applications
 Big Data Example : Hadoop Ecosystem
 ModernWeb Applications
 References

3. CLOUD COMPUTING
 Delivery of computing services, including
servers, storage, databases, networking,
software, analytics and intelligence over the
internet or the cloud, offering faster innovation,
flexible resources and economies of scale.
 Cloud computing is a model for enabling
convenient, on-demand network access to a
shared pool of configurable computing
resources (e.g., networks, servers, storage,
applications, and services) that can be rapidly
provisioned and released with minimal
management effort or service provider
interaction. (NIST – National Institute of
Standards & Technology, US) Fig 1 : What is cloud computing

4. Fig 2 : Edge Computing to Centralized Cloud

5. Modified Cloud Data Center Architecture
Fig 3 : Modified Cloud Data Center Architecture

6. 1. On-demand self-service – No
manual intervention is required for
normal changes to service.
2. Broad network access – Cloud
services are made available with
network access.
3. Resource pooling – Many resources
are pooled to reap economies of scale.
4. Rapid elasticity – Ability to scale up
and down availability of the amount of
computing resources, to meet the
demand and to ensure energy/cost
efficiency.
5. Measured Service – Measuring of
the usage, typically on the basis of time
and type of resource used
Source: NIST
Five Essential Characteristics of Cloud Model
Fig 4 : Five essential characteristics of cloud model

7. Cloud Computing Service Models
Software as a Service – Providing quick access to cloud based
applications running on a cloud infrastructure and these applications
are accessible over different devices such as mobile, thin client or
personal computer. (Ex: Google Apps, Dropbox, Concur,
Salesforce, Cisco WebEx, GoToMeeting)
Platform as a Service – Providing cloud based service to the
consumer which allows to develop, test and organize different
applications according to the requirement. (Ex: AWS Elastic
Beanstalk, Windows Azure, Heroku, Force.com, Google App
Engine,Apache Stratos, OpenShift)
Infrastructure as a Service – Virtual provision of computing
resources such as processing power, storage, networks etc. over the
cloud enabling the consumer to deploy and run arbitrary software
which can include operating systems and applications. (Ex:
DigitalOcean, Linode, Rackspace, Amazon Web Services
(AWS), Cisco Metapod, Microsoft Azure, Google Compute
Engine (GCE))
Fig 5 : A layered view of cloud service models

8. Cloud Deployment Models
Private Cloud – The cloud infrastructure is provisioned
for exclusive use by a single organization comprising
multiple consumers (e.g., business units). It may be
owned, managed, and operated by the organization, a
third party, or some combination of them, and it may
exist on or off premises.
Fig 6 : Outsourced private cloud
Public Cloud – The cloud infrastructure is provisioned
for open use by the general public. It may be owned,
managed, and operated by a business, academic, or
government organization, or some combination of them.
It exists on the premises of the cloud provider.
Fig 7 : Public Cloud

9. Cloud Deployment Models – Contd.
Community Cloud – The cloud infrastructure is provisioned for exclusive
use by a specific community of consumers from organizations that have shared
concerns (e.g., mission, security requirements, policy, and compliance
considerations). It may be owned, managed, and operated by one or more of
the organizations in the community, a third party, or some combination of
them, and it may exist on or off premises.
Hybrid Cloud - The cloud infrastructure is a composition of two or more
distinct cloud infrastructures (private, community, or public) that remain
unique entities, but are bound together by standardized or proprietary
technology that enables data and application portability (e.g., cloud bursting for
load balancing between clouds).

10. DATA CENTER NETWORKING
What are Data Centers?
• Centralized locations where computing
and networking equipment is
concentrated for the purpose of collecting,
storing, processing, distributing or allowing
access to large amounts of data.
Fig 8 : Inside of a Data Center

11. Why Data Center Networking?
• The data center is home to the computational power, storage, and applications necessary to support an
enterprise business. The data center infrastructure is central to the IT architecture, from which all content
is sourced or passes through. Proper planning of the data center infrastructure design is critical, and
performance, resiliency, and scalability need to be carefully considered.
• Data Center Network (DCN) holds a pivotal role in a data center, as it interconnects all of
the data center resources together. DCNs need to be scalable and efficient to connect tens or even
hundreds of thousands of servers to handle the growing demands of Cloud computing.

12. Fig 9 : A non-descript example of a data center building Fig 10 : InteriorView of a typical data center

13. Server Rack Design & Sever Infrastructure
• Data center equipment or the server rack
equipment play an important role in data
centers in terms of managing the space
inside data center buildings, keeping track
of heat generation from each device and
for easy troubleshooting.
• Having properly arranged and managed
server rack equipment in a data center
will reduce the complexity of managing
servers and also will be helpful in
performing equipment audits which is one
of the important steps in migration
planning process.Fig 11 : Data center rack design related to openCompute project

14. Inside of a server
Fig 12 - A : Inside of a sever
Fig 13 - B : Inside of a sever
Fig 14: Sever Motherboard

15. Sever Motherboard Design
Fig 15 : Block Diagram of a Server motherboard

16. Other related Equipment in a sever rack
Fig 16 : CISCO – SLM2048 – 48 Port
10/100/1000 Gigabit Smart Switch
Fig 17: CISCO 1800 Series Router
• Router - Connects two or more different
networks together (WAN)
• Switch - Allows data to enter from one
source, and then directs it to a specific
device (LAN)

17. Other Supporting Equipment in a sever rack
Fig 18 : Patch Panels
Fig 19 : Rail
Fig 20 : Blanking Panels
Fig 21 : Cable management bars

18. Data Center Networking : NetworkTopology
A generic diagram for enterprise intranet or
network inside a data center is shown here.
RFC7365
Fig 22 :A diagram of a generic data center network (RFC7365)

19. Conventional Data Center NetworkingTopology
Fig 23 : Conventional Data Center Networking Topology

20. Data Center Multi-Tier Design Overview
The multi-tier model is the
most common model used in
the enterprise today. This design
consists primarily of web,
application, and database server
tiers running on various
platforms including blade
servers, one rack unit (1RU)
servers, and mainframes.
Source : CiscoWebsite

21. Core layer
• Provides the high-speed packet switching backplane for all flows going
in and out of the data center.
• Provides connectivity to multiple aggregation modules and provides a
resilient Layer 3 routed fabric with no single point of failure.
• Runs an interior routing protocol, such as OSPF or EIGRP, and load
balances traffic between the campus core and aggregation layers using
Cisco Express Forwarding-based hashing algorithms.

22. Aggregation layer
• Provide functions, such as service module integration, Layer 2
domain definitions, spanning tree processing, and default gateway
redundancy.
• Server-to-server multi-tier traffic flow occurs through the
aggregation layer and can use services, such as firewall and server
load balancing, to optimize and secure applications.

23. Access layer
• Servers physically attach to the network within this layer
• The server components consist of 1RU servers, blade servers with
integral switches, blade servers with pass-through cabling, clustered
servers, and mainframes with OSA adapters.
• The access layer network infrastructure consists of modular switches,
fixed configuration 1 or 2RU switches, and integral blade server
switches.
• Switches provide both Layer 2 and Layer 3 topologies, fulfilling the
various server broadcast domain or administrative requirements.

24. CLOUD APPLICATIONS
Almost all common network enabled applications which we use
today are run on a cloud implemented data center residing
somewhere on the planet. These include search engines such as
Google, Bing, and Yahoo, network mail such as Gmail and
various social networks such as Facebook, Instagram,
Twitter, Pinterest, etc.

25. Big Data Example : Hadoop Ecosystem
•HDFS: Hadoop Distributed File System
•YARN:Yet Another Resource Negotiator
•MapReduce: Programming based Data Processing
•Spark: In-Memory data processing
•PIG, HIVE: Query based processing of data services
•HBase: NoSQL Database
•Mahout, Spark MLLib: Machine
Learning algorithm libraries
•Solar, Lucene: Searching and Indexing
•Zookeeper: Managing cluster
•Oozie: Job Scheduling
Hadoop Ecosystem is a platform or a suite which provides various services to solve the big data problems. It includes
Apache projects and various commercial tools and solutions.
Fig 24 : Hadoop Ecosystem

26. Here’s just a small list of Hadoop users from the Hadoop wiki (note that this is volunteered information and
may not represent current usage)
o Yahoo
More than 100,000 CPUs in >40,000 computers running Hadoop. Our biggest cluster: 4500 nodes (24cpu boxes w
41TB disk & 16GB RAM). Used to support research for Ad Systems andWeb Search
o Hulu
13 machine cluster (8 cores/machine, 4TB/machine)
o Adobe
We currently have about 30 nodes running HDFS, Hadoop and HBase in clusters ranging from 5 to 14 nodes on both
production and development.We plan a deployment on an 80 nodes cluster.”
o EBay
532 nodes cluster (8 * 532 cores, 5.3PB).
o Facebook
Currently we have 2 major clusters:A 1100-machine cluster with 8800 cores and about 12 PB raw storage.A 300-
machine cluster with 2400 cores and about 3 PB raw storage. Each (commodity) node has 8 cores and 12 TB of
storage.

27. Modern Web Applications
Many classic web applications such as Word Press blogs and Drupal based sites are based on some type of LAMP
(Linux, Apache, MySQL, PHP) software stack which is basically based on cloud computing and data center
networks.
1. An operating system, classically Linux, on which to run the
software components and furnish the networking stack.
2. A web server, classically the Apache web server, but many other
webservers are now used.
3. A data persistence system, classically the MySQL database.This is
needed for dynamic web sites for storage and retrieval of user and
other data. Besides other relational database systems there are
many choices with newer NoSQL databases.
4. A programming language that works with the webserver to
provide the application logic for dynamic requests. Classically this
was done with the languages Perl or PHP but many other
languages are popular on the server including Ruby, Python, server
side JavaScript, etc.
Fig 24 : LAMP Stack

28. REFERENCES
• Data Center Networking. (n.d.). Retrieved 12 21, 2019, from www.grotto-networking.com:
https://www.grotto-networking.com/BBNetVirtualizationDataCenter.html
• Data Center Networking Explained. (n.d.). Retrieved 12 21, 2019, from www.sdxcentral.com:
https://www.sdxcentral.com/data-center/definitions/data-center-networking-explained/
• Data Center Blade Server Integration Guide. (n.d.). Retrieved 12 28, 2019, from www.cisco.com:
https://www.cisco.com/c/en/us/td/docs/solutions/Enterprise/Data_Center/DC_BladeServer/DCBladServ/
BSrv_Ch1.html

29. THANKYOU!