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)

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

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

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

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!

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

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

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

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

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

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

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 https://code.facebook.com/posts/360346274145943/introducing-data-center-fabric-the-next-generation-facebook-data-center-network/

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

Facebook DC Network Arch Each DC building and wiring layout: