Cloud Computing Driving Infrastructure Innovation Intel DCSG Distinguished Speaker Series



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Transcription:

Cloud Computing Driving Infrastructure Innovation Intel DCSG Distinguished Speaker Series James Hamilton, 2012/9/25 VP & Distinguished Engineer, Amazon Web Services email: James@amazon.com web: mvdirona.com/jrh/work blog: perspectives.mvdirona.com

Agenda Cloud Computing Scaling & Costs Cloud Computing Economics Infrastructure Innovation Power Distribution Mechanical Systems Data Center Building Design Networking Storage Cloud Computing Drives H/W Feature Use 2012/9/25 http://perspectives.mvdirona.com 2

Pace of Innovation Datacenter pace of innovation increasing More innovation in last 5 years than previous 15 Driven by cloud service providers and very high-scale internet applications like search Cost of infrastructure dominates service cost Not just a cost center High focus on infrastructure innovation Driving down cost Increasing aggregate reliability Reducing resource consumption footprint 2012/9/25 http://perspectives.mvdirona.com 3

Perspective on Scaling Each day Amazon Web Services adds enough new capacity to support all of Amazon.com s global infrastructure through the company s first 5 years, when it was a $2.76B annual revenue enterprise 2012/9/25 http://perspectives.mvdirona.com 4

The Cloud Scales: Amazon S3 Growth Peak Requests: 500,000+ per second >1 Trillion 762 Billion 262 Billion 2.9 Billion 14 Billion 40 Billion 102 Billion Q4 2006 Q4 2007 Q4 2008 Q4 2009 Q4 2010 Q4 2011 Q4 2012 Total Number of S3 Objects 2012/9/25 http://perspectives.mvdirona.com 5

AWS Datacenters in 8 Regions US GovCloud (US ITAR Region -- Oregon) US West x 2 (N. California and Oregon) US East (Northern Virginia) Europe West (Dublin) Asia Pacific Region (Singapore) Asia Pacific Region (Tokyo) >10 datacenters In US East alone LATAM (Sao Paola) 8 AWS Regions and growing 21 AWS Edge Locations for CloudFront (CDN) & Route 53 (DNS)

Where Does the Money Go? Assumptions: Facility: ~$88M for 8MW critical power Servers: 46,000 @ $1.45k each Commercial Power: ~$0.07/kWhr Power Usage Effectiveness: 1.45 18% 13% Monthly Costs 4% Servers 57% Networking Equipment Power Distribution & Cooling Power 8% Other Infrastructure 3yr server & 10 yr infrastructure amortization Observations: 31% costs functionally related to power (trending up while server costs down) Networking high at 8% of overall costs & 19% of total server cost (many pay more) From: http://perspectives.mvdirona.com/2010/09/18/overalldatacentercosts.aspx 2012/9/25 http://perspectives.mvdirona.com 7

Agenda Cloud Computing Scaling & Costs Cloud Computing Economics Infrastructure Innovation Power Distribution Mechanical Systems Data Center Building Design Networking Storage Cloud Computing Drives H/W Feature Use 2012/9/25 http://perspectives.mvdirona.com 8

Utilization & Economics Server utilization problem 30% utilization VERY good &10% to 20% common Expensive & not good for environment Solution: pool number of heterogeneous services Non-correlated peaks & law of large numbers Pay as you go & pay as you grow model Don t block the business Don t over buy Transfers capital expense to variable expense Apply capital for business investments rather than infrastructure Charge back models drive good application owner behavior Cost encourages prioritization of work by application developers High scale needed to make a market for low priority work 2012/9/25 http://perspectives.mvdirona.com 9

Data Center Efficiency Datacenter design efficiency Average datacenter efficiency low with PUE over 2.0 (Source: EPA) Many with PUE over 3.0 High-scale cloud services in 1.2 to 1.5 range Lowers computing cost & better for environment Multiple datacenters At scale multiple datacenters can be used Close to customer Cross datacenter data redundancy Address international markets efficiently Avoid upfront datacenter cost with years to fully utilize Scale supports pervasive automation investment 2012/9/25 http://perspectives.mvdirona.com 10

Scale Effects Custom service-optimized hardware ODM sourced Purchasing power at volume Supply chain optimization Shorter supply chain drives higher server utilization Predicting next week easier than 4 to 6 months out Less over buy & less capacity risk Networking transit costs strongly rewards volume Cloud services unblocks new business & growth Remove dependence on precise capacity plan 2012/9/25 http://perspectives.mvdirona.com 11

Amazon Cycle of Innovation 15+ years of operational excellence Managing secure, highly available, multi-datacenter infrastructure Experienced at low margin cycle of innovation: Innovate Listen to customers Drive down costs & improve processes Pass on value to customers 19 AWS price reductions so far Expected to continue 2012/9/25 http://perspectives.mvdirona.com 12

Agenda Cloud Computing Scaling & Costs Cloud Computing Economics Infrastructure Innovation Power Distribution Mechanical Systems Data Center Building Design Networking Storage Cloud Computing Drives H/W Feature Use 2012/9/25 http://perspectives.mvdirona.com 13

208V Power Distribution High Voltage Utility Distribution ~11% lost in distribution.997*.94*.98*.98*.99 = 89% IT Load (servers, storage, Net, ) Generators UPS & Gen often on 480V 115kv Sub-station 13.2kv UPS: Rotary or Battery Transformers Transformers ~1% loss in switch gear & conductors 13.2kv 13.2kv 480V 0.3% loss 99.7% efficient 6% loss 94% efficient, ~97% available 2% loss 98% efficient 2% loss 98% efficient Note: Two more levels of power conversion at server 2012/9/25 http://perspectives.mvdirona.com 14

Cold Hot Mechanical Systems Blow down & Evaporative Loss at 8MW facility: ~200,000 gal/day Cooling Tower CWS Pump Heat Exchanger (Water-Side Economizer) A/C Condenser A/C Compressor Primary Pump A/C Evaporator Server fans 6 to 9W each Diluted Hot/Cold Mix leakage cold fans Overall Mechanical Losses ~22% Computer Room Air Handler Air Impeller 2012/9/25 http://perspectives.mvdirona.com 15

Innovative Building Designs Evaporative cooling only Right: High pressure misting Below: Wet media cooler Ductless full building cooling Facebook Prineville above & below EcoCooling 2012/9/25 http://perspectives.mvdirona.com 16

Modular and Pre-fab DC Designs Microsoft ITPAC Fast & economic deployments Sub-1.15 PUE designs Air-side economized No mechanical cooling ISO standard shipping containers offered by Dell, HP, SGI, IBM, Amazon Perdix 2012/9/25 http://perspectives.mvdirona.com 17

Sea Change in Networking Current networks over-subscribed Forces workload placement restrictions Goal: all points in datacenter equidistant Mainframe model goes commodity Competition at each layer over vertical integ. Get onto networking on Moores Law path ASIC port count growth at near constant cost Competition: Broadcom, Marvell, Fulcrum, 2012/9/25 http://perspectives.mvdirona.com 18

HDD: Capacity Capacity growth continues unabated Capacity isn t the problem What about bandwidth and IOPS? Source: Dave Anderson/Seagate 2012/9/25 http://perspectives.mvdirona.com 19

HDD: Rotational Speed RPM contributes negatively to: rotational vibration Non-Repeating Run Out (NRRO) Power cubically related to RPM >15k RPM not economically viable no improvement in sight RPM not improving & seek times only improving very slowly IOPS improvements looking forward remain slow Even sequential BW growth insufficient Source: Dave Anderson 2012/9/25 http://perspectives.mvdirona.com 20

HDD Random BW vs Sequential BW 120 100 80 60 Sequential BW (MB/s) Random BW (MB/s) 40 20 0 1983 1990 1994 1998 2003 2007 Disk sequential BW growth slow Disk random access BW growth roughly 10% of sequential Storage Chasm widening BW a long term problem &IOPS growth very slow Source: Dave Patterson with James Hamilton updates 2012/9/25 http://perspectives.mvdirona.com 21

Disk Becomes Tape Random access disk latency increasingly impractical Random read 4TB disk: 41.3 days @ 140 IOPS with 8kb page Disk increasingly impractical for random workloads Sequential read is over 11 hours Trending below tape price point Tape only cost effective at very high scale Disk wins at top and scales down better 2012/9/25 http://perspectives.mvdirona.com 22

Flash Becomes Disk All random workloads to Flash Flash 4 to 6x more expensive capacity Log structured block store Compress De-dupe Sparse provision Approaches HDD capacity price point 2012/9/25 http://perspectives.mvdirona.com 23

Client Storage Migration Client device disk replaced by semiconductor caches Much higher performance, Lower power dissipation, smaller form factor, greater shock resistance, scale down below HDD cost floor, greater humidity range, wider temp range, lower service costs, Flash is primary client storage media Clients storage drives cloud storage Value added services, many data copies, shared access, indexed, classified, analyzed, monetized, reported, Overall client storage continuing to expand rapidly but primarily off device in the cloud 2012/9/25 http://perspectives.mvdirona.com 24

Enterprise to Cloud Many Enterprise Deployments Fewer Large Cloud Providers Cloud computing 5x to 10x improved price point Low margin, high volume business Yet still profitable, sustainable, & supporting re-investment Incompatible with on-premise enterprise S/W & H/W profit margins Expect many cloud winners rather than single provider Direct component supplier relationship with major operators rather than via distribution channel Custom server & networking equipment 2012/9/25 http://perspectives.mvdirona.com 25

Agenda Cloud Computing Scaling & Costs Cloud Computing Economics Infrastructure Innovation Power Distribution Mechanical Systems Data Center Building Design Networking Storage Cloud Computing Drives H/W Feature Use 2012/9/25 http://perspectives.mvdirona.com 26

Accelerating Compute & Storage Growth Rapidly declining cost of computing Driven by technology improvements & cloud computing economies of scale Traditional transactional systems scale with business Purchases, ad impressions, pages served, etc. Computational trading & machine-to-machine transactions limited only by value of transaction & cost of infrastructure Warehousing & analytical systems scale inversely with cost Cheaper storage allows more data to be analyzed Lower compute costs allows deeper analysis 2012/9/25 http://perspectives.mvdirona.com 27

Questions? Perspectives Blog: http://perspectives.mvdirona.com/ Email: James@amazon.com 2012/9/25 http://perspectives.mvdirona.com 28