1. Flash 1st A powerful data centre optimization and consolidation approach1Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai

2. 2009: More Apps On Virtual Infrastructure17,500,00015,000,000The Tipping PointVirtual Machines12,500,000 Physical Hosts10,000,0007,500,0005,000,0002,500,000200520062007 2008 2009 2010 2011 20122013Source: IDC2 Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 3. Virtualization Changes EverythingSLA optimization has shifted from Point-in-Time to Real-TimeMANUAL PROCESS100% AUTOMATED OracleExchange SQL server server serverOracle Exchange SQLOracleI ExchangeISQLIAutomated TieringSSDSASNL-SAS Static Association of Dynamic, Self-optimizing Disk Groups to ApplicationsStorage Pools based on best guess based on actual data activity 3Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 4. Information Tipping Point AheadThis decade will be nothing like the last140,000120,000 Data 100X100,000A 10TB data center in 200180,000growing at 60% YoY will be a120 Petabyte data center by60,000 MORE DATA2021, but IT budgets remain flatEACH DECADE Automation40,00020,000 Budget 0 2000 2003 2006 2009 20122015201820214Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 5. Most Data Will be Stone ColdWhile we increasingly cant erase data, we can store it better4,123 100 X 37.5TB TB 2011 2021 HotWarm Cold Evolution of 50 TBs in 10 Years 5Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 6. The CPU to HDD Performance GapCPU improves 100 times every decade disk speed hasntMoores Law will continue to improveCPU performance while disk drive performance will remain flat. As a result, applications will suffer moreand more unless we rapidly move to FLASH 10,000 times FLASHimproved 100 times improved 20002010 2020 6Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 7. Clicker QuestionHave you faced the following challenges.A. Due to performance requirements your storage solution was built of a huge number of spinning drives whereas your capacity requirement was much lower?B. You still prefer 15K spindles and have your arrays totally filled up?C. You were forced to do incremental purchases over the life span of your infrastructure to meet performance SLAs.? 7Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 8. Anatomy of an Enterprise FLASH DriveDesigned for reliability, data integrity and performance Controller SLC NAND FLASHSAS or SATA ports DRAM End to End CRC8Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 9. 9Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 10. Comparing Associated CostsWhich technology is the most efficient?Capacity Acquisition CostCapacity Power Cost $- $10 $20 $30 $400 51015 20 253015K HDD 15K HDD 7200 HDD 7200 HDD FLASHFLASHFLASH7200 HDD15K HDD FLASH 7200 HDD15K HDD$/GB$34.80$0.43 $1.63 mWatt/GB25628 Transaction Acquisition CostTransaction Power Cost $-$2 $4 $6$8 $10 $120.050.0 100.0150.015K HDD15K HDD 7200 HDD 7200 HDD FLASH FLASHFLASH7200 HDD 15K HDD FLASH7200 HDD15K HDD$/IOPS$1.99 $9.56 $5.44 mWatt/IOPS 1.4 133.3 94.4 10 Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 11. How?11Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 12. The FLASH 1st Data StrategyHot data on fast FLASH SSDscold data on dense disksHothigh activityHighly active data isAs data ages, activity stored onfalls, triggering automaticFLASH SSDs formovement to high capacity fastestdisk drives for lowest cost response timeData Activity FLASHHigh Cap.SSD HDD Movement TriggerColdlow activity Data Age (5 years)12 Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 13. Clicker QuestionHave you had discussion with your solution suppliers aroundthe mix of flash and spinning drives Yes we had detailed discussions and some sizing methodswere implemented No we had no discussions 13Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 14. How Much FLASH?Used dynamically with Automated tiering Size of FLASH FIFO Older data is constantly being replaced by newAmount of Data being highly active datacreated daily The amount of FLASH required is determined by: The amount of data createdFLASH Capacityeach day, and The period of time it takes tocool Number of Days of High Data Activity14 Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 15. How Much FLASH?3 fundamental business questions How much data are you storing today? 50 TBs How much is your data growing each year? 50% YoY How long does your data stay hot? 60 days15Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 16. Calculating Needed FlashNet new is a function of amount of starting data and growth 50% of 50TB is 25TB The average amount of data50% growth rate generated each day:80 25 X 1024 GB / 365 = 70 GB per day6025 FLASH Capacity:40 60 days X 70 GB = 50 50 4,200 GB200 FLASH Percentage:StartYear 1 FLASH Capacity/Total Capacity 4,200 GB/(75 X 1024) GB X 100: 6%16Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 17. Clicker QuestionWhat has been your biggest hindrance to flash 1 st strategy.A. We feel flash is too expensiveB. We preferred continuing with spinning spindles as it was tried and testedC. We need help to ascertain our workloadsD. We feel with flash and advanced tiering there is complexity. 17Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 18. Workload Skew Defines Configuration and benefitsTake Advantage of Workload SkewHeavy SkewModerate SkewLow SkewZero Skew 95% of I/O on90% of I/O on80% of I/O on 50% of I/O on5% of data 10% of data20% of data 50% of dataConfiguration AConfiguration BConfiguration CConfiguration D 3% EFD 3% EFD 3% EFD25% FC 15 K 43% FC 15 K80% FC 15 K 97% SATA72% SATA54% SATA20% SATA30% More40% More 20% More Same Performance PerformancePerformance Performance80% Fewer Disks60% Fewer Disks50% Fewer Disks17% Fewer Disks20% Lower Costs15% Lower Costs Same Cost 13% Lower Costs18Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 19. Automatic Data Optimization FAST VPThe benefit of FLASH without the cost Easy and Effective Implementations Per-application Policies, modeled by professional tools Works with everything, validated against real workloadsActiveInactive5%95% Data FLASHDisk Data Exclusion policies SLA based Tiering Promote/Demote policies SSDHDD Granular Data Management Minimum chunk of movement Batch vs realtime , frequency of analysis Advanced Controls Time controls for performance and movement 3 Tiers, dynamic, online90% utilization19 Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 20. FAST Cache Fully automatic application accelerator System-wide resource, immediate impact No extensive pre-planning neededFAST Cache Helps both Read and Write operations Quick adjustment to changing usage patterns Up to 2TBFlash Fibre Turbo-charge performance improvement in ChannelOracle, Microsoft SQL Server, and VMware Viewenvironments Turbo-charge performanceSATABenefits Easy to manage and monitor20Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 21. Disk Utilization Application was experiencing higher response time-Disk Utilization touching 80%Before FAST CacheAfter FAST CacheApplication response time improvedDrive utilization reduced. Response time increasedAdditional Headroom 21 Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved. 17-18 November 2011. Grand Hyatt - Mumbai 22. Lets change the way we procure IT Faster Response Times Smaller FootprintLess PowerLower Cost 22Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai 23. THANK YOU Thank You 23Cloud Meets Big Data Copyright 2011 EMC Corporation. All rights reserved.17-18 November 2011. Grand Hyatt - Mumbai