2012 Enterprise Strategy Group. Enterprise Strategy Group Getting to the bigger truth. TM

Transcription

1 2012 Enterprise Strategy Group Enterprise Strategy Group Getting to the bigger truth. TM

2 Enterprise Strategy Group Getting to the bigger truth. TM Virtualization Evolution and Storage Requirements Kim Wang Senior Analyst, ESG 2012 Enterprise Strategy Group

3 Presentation Outline Data Center Evolution Virtualization Maturity Model Virtualization Maturity Factors Virtualization Market Trend Top Storage Challenges for Virtualization Tier-1 Storage, Key Evaluation Factors

4 Data Center Evolution Dynamic Multitenants Continuity Cloud Agility Utilization Enterprise-Class Dynamic Resources Resources Integration Testing and Development Virtualization 2012 Enterprise Strategy Group 5

5 ESG s Virtualization Maturity Model 2012 Enterprise Strategy Group 6

6 The Four Dimensions of ESG s Server Virtualization Maturity Dimension: Scope of deployment Metric: Percent of servers that have been virtualized Dimension: Virtual production ratio Metric: Percent of VMs in production Dimension: Efficiency Metric: Consolidation ratio Dimension: Workload penetration Metric: Deployment across multiple workloads Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group 7

7 Group 1 Group 2 Group 3 ESG Server Virtualization Maturity Model Segmentation More servers, higher density, more production and tier one applications in virtualization Laggards Low percent of physical servers virtualized (typically less than 20%) Low percent of VMs deployed in production (12% average) Low virtual-to-physical consolidation ratio (typically less than 5) Deployment across limited and/or basic workloads (13% have deployed mission-critical production workloads) Followers Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group Medium percent of physical servers virtualized (typically 10% - 30%) Medium percent of VMs deployed in production (35% average) Medium virtual-to-physical consolidation ratio (typically 5-10) Deployment across more workloads, but mostly tier- 2 (37% have deployed mission-critical production workloads) Leaders High percent of physical servers virtualized (typically 40% +) High percent of VMs deployed in production (67% average) High virtual-to-physical consolidation ratio (typically more than 10) Deployment across many/tier-1 workloads (75% have deployed mission-critical production workloads)

8 Percentage of x86 Servers That Have Been Virtualized 40% 35% Of all the potential x86 servers in your organization that can be virtualized, approximately what percentage of these systems have actually been virtualized to date? How do you expect this to change over the next 24 months? Today (Percent of respondents, 24 months from N=463) now 38% 30% 25% 20% 15% 10% 12% 21% 9% 25% 11% 17% 15% 11% 20% 14% 5% 0% 2% Less than 10% of servers 10% to 20% of servers 21% to 30% of servers 31% to 40% of servers 41% to 50% of servers More than 50% of servers 1% 3% Don t know Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group

9 Number of Virtualized Applications/Workloads, by Length of Server Virtualization Deployment Number of applications/workloads virtualized to date, by length of server virtualization deployment. (Percent of respondents) More than 50 applications / workloads 26 to 50 applications / workloads 10 to 25 applications / workloads Less than 10 applications / workloads More than 5 years (N=70) 47% 27% 23% 3% 4 to 5 years (N=83) 37% 31% 28% 4% 1 to 3 years (N=252) 18% 19% 50% 13% Less than 12 months (N=40) 63% 38% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group

10 Average Number of Virtual Machines per x86 Server 40% 35% 30% 25% 20% 15% 10% 5% 0% What would you estimate is the average number of virtual machines per physical x86 server in your environment today? How do you expect this to change over the next 24 months? (Percent of respondents, N=463) Today 24 months from now 26% 8% Less than 5 virtual machines per physical x86 server 36% 24% 5 to 10 virtual machines per physical x86 server 23% 11 to 25 virtual machines per physical x86 server 30% 31% 12% More than 25 virtual machines per physical x86 server 3% 7% Don t know Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group

11 Average Number of Virtual Machines per x86 Server, by Length of Server Virtualization Deployment Average number of virtual machines per physical x86 server, by length of server virtualization deployment. (Percent of respondents) More than 25 virtual machines per physical x86 server 11 to 25 virtual machines per physical x86 server 5 to 10 virtual machines per physical x86 server More than 5 years (N=70) 31% 29% 33% 7% 4 to 5 years (N=83) 13% 39% 36% 12% 1 to 3 years (N=255) 8% 19% 40% 33% Less than 12 months (N=39) 3% 13% 31% 54% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group

12 Correlation Between Server Virtualization and Storage Virtualization Source: ESG Research Report: The Evolution of Server Virtualization, November Enterprise Strategy Group 13

13 Top Three Storage Challenges for Virtualization Evolution Performance Continuity Utilization Assure virtualized application performance, business continuity and long term high performance/cost ratio 2012 Enterprise Strategy Group 14

14 Storage Performance Challenges Higher VM density & mobility IO Load balance Management Performance for Structure and unstructured Mixed workload Production and tier-1 Application Automation Performance Reliability Continuity Unpredictable performance Dynamic optimization Auto tier 2012 Enterprise Strategy Group 15

15 Storage High Availability Challenges No single point failure Prevention Failover Fast rebuilt Always-on data, continuity during failure, technology upgrading or maintenance 2012 Enterprise Strategy Group 16

16 Storage Utilization Challenges Storage consumed by 0 DR and Business continuity Under utilized provisioned storage Storage consumption Deleted files or de-commission VMs 2012 Enterprise Strategy Group 17

17 Tier 1 Storage Key Evaluation Factors Multitenants automation Dynamic Resilience Optimized Performance/ cost 2012 Enterprise Strategy Group 18

18 Thank You 谢谢 Getting to the bigger truth. TM 2012 Enterprise Strategy Group

19 21 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

20 3PAR Core business differentiators Graham Kitchener HP Storage Presales Consultant, HP 22 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

21 3PAR Utility Storage for Virtual Server Environments Buy 50% fewer physical servers Spend 90% less time managing storage Cut storage capacity requirements by 50% 23 Wide Striping Mixed Workload Support Integration w/vmware Adaptive Queue Depth VAAI plug-in Increase Consolidation Guaranteed Autonomic Groups Management Plug-In Recovery Manager Site Recovery Adapter Common platform Simplify Administration Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Thin Provisioning Thin Conversion Thin Persistence Adaptive Optimisation Fast RAID Technologies Maximize Savings - Lower Storage Cost Guaranteed

22 Defining Tier-1 Storage in the Modern Data Center Tier-1 Storage Criteria in the Age of Virtualization, Clouds, & IT Agility Scalable Multitenancy Virtualized and Federated Resource Pooling Scale-out Infrastructure Sub-LUN Optimization Secure Multitenancy Self- Configuration Optimized Asset Utilization Dynamic Volume Provisioning High Availability and Planned Resilience Self-optimizing and Tuning 24 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

23 Storage architecture born for best performance Unique differentiators core to the 3PAR approach to storage Fine grained virtualisation Extreme efficiency Complete striping Predictable performance Mesh-active controller design Extreme consolidation of business workloads 25 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

24 HOW? Thin Tech s Wide Striping Virtual Copies 3PAR ASIC Recovery Manager s/w Full Copies A Virtual Lock & Virtual Domains Peer Motion Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. A Remote Copies A A B B Automated Tiers Tier 0 SSD Tier 1 FC Tier 2 Nearline

25 --- R1 Raidlet R1 Raidlet --- 3PAR Hardware features deliver tier-1 MC support Fast Rebuilds Shelf independent RAID End to End integrity checking Fast RAID No Downtime Persistent Cache Mirroring Active-Active Cluster 27 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

26 Mixed workload support Application Data Control Info. (metadata) ESX Server Heavy THROUGHPUT Host Interface Processor Disk Interface Heavy TRANSACTION Issue: small io s wait for large io s An environment like this will not allow hundreds / thousands of applications to happily coexist 28 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

27 Mixed workload support Application Data Control Info. (metadata) An environment like this allows hundreds / thousands of applications to happily coexist - efficiently ESX Server Heavy THROUGHPUT Host Interface 3PAR ASIC Disk Interface Heavy TRANSACTION Answer: control and data are pathed and processed separately! Control Processor 29 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

28 Autonomic Tiering and Savings Tier 0 SSD Tier 1 Fibre Channel Tier 2 Nearline (Enterprise SATA) - Region Dynamic Optimization Autonomic Data Movement Adaptive Optimization (AO) Autonomic Tiering and Data Movement 30 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

29 3PAR Thin Provisioning Leadership Manageability No pool management No need for consulting services Symantec thin API integration Thin Persistence with integration Efficiency No upfront reservations Fine units of capacity allocation Variable QoS for snapshots Thin Conversion for simple thin landing Scalability Implemented on a scalable platform No performance impact Integrated with all, not some, other functionality 31 (e.g. RC, VC, DO, AO) Volume Written Data Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 3PAR Thin Provisioning - with thin built-in - Volume Volume Written Data Written Data Purchased Physical Capacity Free Chunklet Pool

30 3PAR gets De-duplication! Thin persistence with zero-detect is effective de-duplication 3PAR focuses here and achieves 100% de-dupe of zero s Volume Volume free space Volume free space averages 50% Volume free space Volume Volume Volume free space 3PAR Thin Provisioned volume with Zero detect NetApp focuses here and achieves maybe 20 50% efficiency Written Data Written Data Written Data What would you prefer? - 100% of average 50% with no overhead - OR ~20% of 50% with huge overhead 32 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

31 Thank you Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.