P5 cloud economics_v1
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P5 cloud economics_v1

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P5 cloud economics_v1 P5 cloud economics_v1 Presentation Transcript

  • CO M PU TI G PA RA D I M D I N G SRU PTI N S OM or t e han j a t ust ech shi … com peli busi ft lng ness case TECH N O LO G Y BU SI ESS CA SE N M A I FRA M E N • Centralized  multipurpose compute  • Usable for business, Optimized for  & storage, thin clients efficiency due to high cost CLI T-SERVER EN • Optimized for agility due to low cost  • PCs and servers for distributed  and ease of use. compute, storage, GUI, etc. CLO U D • Large DCs, commodity HW, scale‐out,  • Order of magnitude better efficiency  multiple devices and agility
  • Cloud computing is a pay-per-use model for enabling available, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, services) that can be rapidlyprovisioned and released with minimal management effort or service provider interaction (NIST – National Institute of Standards & Technology).
  • Application runs Application runs at a hoster Application runs using cloud on-premises platform Pay someone to host myBuy my own hardware, and application using hardware manage my own data that I specify center
  • Publc Cl i oud Bus nes Cas i s e s rLes Cont oloverdata
  • Traditional Infrastructure Platform Software (as a Service) (as a Service) (as a Service) You manage Applications Applications Applications Applications You manage Data Data Data Data Runtime Runtime Runtime Runtime Managed by provider Managed by providerYou manage Middleware Middleware Middleware Middleware O/S O/S O/S O/S Managed by provider Virtualization Virtualization Virtualization Virtualization Servers Servers Servers Servers Storage Storage Storage Storage Networking Networking Networking Networking Operations Operations Operations Operations
  • Studies show that a 100,000‐server datacenter can have 80% lower total cost of ownership (TCO) compared to a 1,000‐server datacenter. 
  • Modern Cloud DCs Microsoft Average PUE Targets for  New DCs 2.200 2.000 1.800 1.600 1.400 1.200 1.000 2006 2008 2010 2012 PUETypical DCs PUE : 4Best in class enterprise DC PUE : 2
  • Com pute Com pute A verage U sage A verage U sage Ti e m Ti e m e eCom put Com put Inact vi y i t Per od i A verage U sage A verage U sage Ti e m Ti e m
  • Dicus i – Pot i Cl s son ental oud Usage Pat er t ns Pat er t n Areas of i er nt est 1 Transf ence : er • Com pany Em ai,W eb Sie. l t Taki exi tng on- em i e app and m ovi i t t ng s i pr s ng t o he • N ew bus nes m odel – SaaS. i s s cloud. • Aler i s t ar depl t natve of w e oym ent m odel . s 2 Scal & M ul i e t -Tenancy: • Tes i t m ar . tng he ket Abiiy t handl w eb l lt o e oad w ihoutf lcapial t ul t i nves m entf om day 1. t r 3 Burst Com pute: • H PC applcatons s utons i i / ol i . Abiiy t handl addii lt o e tonalcom put on an as needed e • Scal lt t tng applcatons abiiy es i i i . bas s i. 4 El i St age: ast c or • Bus nes nt lgence. i si eli Cr i an applcaton w her s or eatng i i e t age can grow • Genom i . cs exponentaly. il • Load t tng on l ge dat es i ar abas . es 5 I er r nt -O gani i Com m uni i zat on cat ons: • D i t i ed devel s rbut opm ent. Applcaton t has t abiiy t com m uni e i i hat he lt o cat • Colabor i R& D. l atve bet een or w gani i us ng t cl zatons i he oud as t pr he e- defned hub. i
  • St andar and Choi i Devel ds ce n opm ent W S-Eventng i At Pub om W S- us Tr t SO AP RSSSAM L Azure Platform ™ REST H TTP W S- an M O penI D Standar bas i er ds ed nt oper lt abiiy
  • • Shift to “Cloud First” policy. Each agency will identify three “must move” services within three months, and move one of those services to the cloud within 12 month and the remaining two within 18 months.• The three-part strategy on cloud technology will revolve around using commercial cloud technologies where feasible, launching private government clouds, and utilizing regional clouds with state and local governments where appropriate.• Reduce number of Federal data centers by at least 800 by 2015
  • Customization Development ToolsValue Middleware (EAI, EII, ETL) Core Platforms (DB, App Server) Operating System (Windows, Linux, Mainframe) Virtual Machine, Management Tools Hardware
  • Software Services and Innovation Development Tools Software as a Service (SaaS)Value Middleware (EAI, EII, ETL) Platform as (DB, App Server) Core Platforms a Service (PaaS) Operating System (Windows, Linux, Mainframe) Virtual Machine, Management Tools Infrastructure as a Service (IaaS) Hardware