1. Internet and Web Simple client-server model
a number of clients served by a single server
performance determined by “peak load”
doesn’t scale well (e.g., server crashes), when # of clients suddenly increases -- “flash crowd”
From single server to blade server to server farm (or data center)

2. web rendering, request routing,
Internet and Web …
From “traditional” web to “web service” (or SOA)
no longer simply “file” (or web page) downloads
pages often dynamically generated, more complicated “objects” (e.g., Flash videos used in YouTube)
HTTP is used simply as a “transfer” protocol
many other “application protocols” layered on top of HTTP
web services & SOA (service-oriented architecture)
A schematic representation of “modern” web services
database, storage, computing, …
web rendering, request routing,
aggregators, …
front-end
back-end

3. Data Center and Cloud Computing
Data center: large server farms + data warehouses
not simply for web/web services
managed infrastructure: expensive!
From web hosting to cloud computing
individual web/content providers: must provision for peak load
Expensive, and typically resources are under-utilized
web hosting: third party provides and owns the (server farm) infrastructure, hosting web services for content providers
“server consolidation” via virtualization
VMM
Guest OS
App
Under client web service control

4. Cloud Computing Cloud computing and cloud-based services:
beyond web-based “information access” or “information delivery”
computing, storage, …
Cloud Computing: NIST Definition
"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."
Models of Cloud Computing
“Infrastructure as a Service” (IaaS), e.g., Amazon EC2, Rackspace
“Platform as a Service” (PaaS), e.g., Micorsoft Azure
“Software as a Service” (SaaS), e.g., Google Apps

5. Overall Data Center Design Goal
Agility – Any service, Any Server
Turn the servers into a single large fungible pool
Let services “breathe” : dynamically expand and contract their footprint as needed
We already see how this is done in terms of Google’s GFS, BigTable, MapReduce
Benefits
Increase service developer productivity
Lower cost
Achieve high performance and reliability
These are the three motivators for most data center infrastructure projects!

6. Achieving Agility … Workload Management Storage Management
means for rapidly installing a service’s code on a server
dynamical cluster scheduling and server assignment 
E.g., MapReduce, Bigtable, …
virtual machines, disk images 
Storage Management
means for a server to access persistent data
distributed file systems (e.g., GFS) 
Network Management
Means for communicating with other servers, regardless of where they are in the data center
Achieve high performance and reliability

7. Data center networks
10’s to 100’s of thousands of hosts, often closely coupled, in close proximity:
e-business (e.g. Amazon)
content-servers (e.g., YouTube, Akamai, Apple, Microsoft)
search engines, data mining (e.g., Google)
challenges:
multiple applications, each serving massive numbers of clients
managing/balancing load, avoiding processing, networking, data bottlenecks
Inside a 40-ft Microsoft container,
Chicago data center

8. Networking Objectives
Uniform high capacity
Capacity between servers limited only by their NICs
No need to consider topology when adding servers
=> In other words, high capacity between two any servers no matter which racks they are located !
Performance isolation
Traffic of one service should be unaffected by others
Ease of management: “Plug-&-Play” (layer-2 semantics)
Flat addressing, so any server can have any IP address
Server configuration is the same as in a LAN
Legacy applications depending on broadcast must work

9. Today’s General DC Network Arch
Leaf-Spine Topology as the basic building block

10. Today’s Data center networks
load balancer: application-layer routing
receives external client requests
directs workload within data center
returns results to external client (hiding data center internals from client)
Internet
Border router
Load
balancer
Load
balancer
Access router
Tier-1 switches B A C
Tier-2 switches
TOR switches
Server racks 1 2 3 4 5 6 7 8

11. Data center networks rich interconnection among switches, racks:
increased throughput between racks (multiple routing paths possible)
increased reliability via redundancy
Server racks
TOR switches
Tier-1 switches
Tier-2 switches 1 2 3 4 5 6 7 8

12. Facebook DC Network Arch
Three tiers: TOR-switch, Fabric Switches (“spine”), and Spine Switches (“core”)
+ edge switches for inter-DC, outside Internet & other network connectivity
Server Pod: contains 48 TOR + 4 fabric switches
each TOR sw with 4 40Gbps
ports + m 10 Gbps ports (where
m: # servers per rack, say,
m=24 or 48, 96)
fabric switch: 48 “inports”
+ 48 “output ports”: 40 Gbps

13. Facebook DC Network Arch
Each DC: 4 spline planes + up to 48 server pods

14. Facebook DC Network Arch
Each DC building and wiring layout: