Architecting Cloud Solutions


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Matt Kimball, AMD Server Solutions Marketing presentation on "Architecting Cloud Solutions" at Dell World.

What makes the difference between a successful cloud implementation and one that doesn’t live up to expectations? Explore how the underlying architecture can translate into performance gains and cost savings.

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Architecting Cloud Solutions

  1. 1. ARCHITECTING CLOUDSOLUTIONSMatt KimballProduct Marketing ManagerDell World 2012Austin, TexasDecember 13, 2012
  2. 2. THE EVOLVING ENTERPRISE – GLOBAL MEGATRENDS Evolving Business Models 1 Technology 2 Advancements 3 Changing Workforce2 | Cutting Big Data Down to Size | Dell World – December 2012 |
  3. 3. DATA EXPLOSION DRIVES NEW ARCHITECTURESNumber of Users Web 2.0 & Cloud Unstructured x Mobile Internet ComputingContent Uploaded + e-CommerceStructure of Content Data Web Browsers Structured 1995 2000 2005 2009 2015 Virtualized infrastructure Cloud datacenters Serial processing Power, cooling, managing managing/mining/securing Parallel processing Homogeneous architecture users increases complexity data, growing problems Heterogeneous architecturesInformation based on AMD perspective 3 | Cutting Big Data Down to Size | Dell World – December 2012 |
  4. 4. WEB HOSTING/CLOUD COMPUTING SOFTWARE ECOSYSTEM Application Layer (SaaS) Google Apps Middleware Layer (PaaS) OS and/or Hypervisor (IaaS)4 | Cutting Big Data Down to Size | Dell World – December 2012 |
  5. 5. CLOUD WORK LOAD PATTERNS “On and Off “ “Growing Fast“ Comput Comput e e Inactivity Average Period Usage Average Usage Time Time On and off workloads (e.g. batch job) Successful services needs to grow/scale Over provisioned capacity is wasted Keeping up w/growth is big IT challenge Time to market can be cumbersome Complex lead time for deployment “Unpredictable Bursting“ “Predictable Bursting“ Compute Compute Average Usage Average Usage Time Time Unexpected/unplanned peak in demand Services with micro seasonality trends Sudden spike impacts performance Peaks due to periodic increased demand Can’t over provision for extreme cases IT complexity and wasted capacity5 | Cutting Big Data Down to Size | Dell World – December 2012 |
  6. 6. HOW DO CLOUD WORKLOADS SCALE? Cloud workloads are very different than traditional data center loads Cloud work is “spiky” in nature, you must be able to account for both the peaks (with more cores) and the valleys (with more power efficiency) Heavy Computation Cores Matter Power Efficiency Matters Low computation6 | Cutting Big Data Down to Size | Dell World – December 2012 |
  7. 7. SUPPORTING WORKLOADS IN THE CLOUD Modular Low Power Servers Example: Low power small form factor servers deployed in larger numbers Platform attributes: Low power, small form factor, fabric enabled, focus on lowest power, not performance CPU requirements: Low power, medium core counts Dense Standard Servers Example: 2P twin solutions, 8-16 cores per node Platform attributes: Low power, focus on performance per watt CPU requirements: Low power, higher core counts, sustained processing Traditional Rack Servers Example: 2P/4P “traditional IT”, high throughput Platform attributes: 1U/2U chassis, high core density, focus on performance/watt and higher performance CPU requirements: High core counts, scalability, high memory throughput7 | Cutting Big Data Down to Size | Dell World – December 2012 |
  8. 8. THE NEW AMD OPTERON™ 6300 SERIES PROCESSOR AMD Opteron™ 6300 Series Processors Next Generation “Piledriver” CoreScalability Up to 4 sockets with up to 16 cores 4 DDR-3 memory channels: up to 1866 MHz memoryMemory Up to 1.5 TB capacity in 4P configurations Up to 3.5 GHz base frequencyFrequency Up to 3.8 GHz using AMD Turbo CORE technology L1 – 16 KB data per core + 64 KB instruction per moduleCache L2 – 1 MB per core L3 – 16 MB per socket Consistency with AMD Opteron™ 6200 Series Four x 16 HyperTransport™ technology 3.0 links • Same power/thermalsI/O @ up to 6.4GT/s per link • Same socket • Same software certificationsPower 85W to 140W TDP8 | Cutting Big Data Down to Size | Dell World – December 2012 |
  9. 9. AMD PROCESSORS IN A CLOUD WORLD AMD-V™ Technology Greater Resources Per Processor Tagged TLB - Efficient switching between virtual More resources to pool in your virtualized converged infrastructure machines for better application responsiveness. Rapid Virtualization Indexing (RVI) - Hardware- based virtual machine memory management. AMD-V™ Extended Migration – Helps enable live migration of VMs between all available AMD Opteron™ processor generations. I/O Virtualization - Enables direct device access by Up to 16 Four memory Power a virtual machine for increased integrity and security. cores channels Management Easier To Deploy Easier To Manage Easier To Move Larger pool of resources enables Common architecture makes Extended Migration delivers greater VM consolidation managing virtual pools easier greater flexibility9 | Cutting Big Data Down to Size | Dell World – December 2012 |
  10. 10. DRIVING DOWN THE COST OF CLOUD Total Cost of Ownership Performance & Scalability Energy Efficiency Cost Effectiveness  Near native performance  Up to 40% higher performance  Low acquisition costs per watt than previous  Maintain SLAs – even at high generation2  The right performance at the utilization right price  Flexible power management  Reliably manages spiky demand of cloud application10 | Cutting Big Data Down to Size | Dell World – December 2012 |
  11. 11. VIRTUALIZATION/PRIVATE CLOUD TCO OPTIMIZATIONSAMPLE DEPLOYMENT: 800 VIRTUAL MACHINES Cost per VM for VMmark Configurations (lower is better) $800.00 30% Lower Cost per VM (Hardware w/vSphere™ Enterprise Plus) $600.00 $400.00 Save $130,000 per Rack (42U – 21 x 2P/2U) $200.00 $0.00 30 VMs 40 VMs Dell PE R715, AMD Opteron™ Model 6284SE Dell PE R720, Intel Xeon™ Model 26902 x AMD Opteron™ processors Model 6284SE Dell PE R715 server, 128GB (8x16 GB DDR3-1600) memory, 1x7.2K 500GB SATA HD, base warranty2 x Intel Xeon E5-2690 processors in Dell PE R720 server, 256GB (16x16 GB DDR3-1600) memory, 1x7.2K 500GB SATA HD, base warrantySystem prices as of 8/5/2012 | Cutting Big Data Down to Size | Dell World – December 2012 |
  12. 12. AMD OPTERON™ PROCESSORS FOR THE CLOUD Consolidate platforms, meet SLAs, lower TCO – Competitive performance – Scalable performance – even at very high CPU utilization – Large memory footprints – Cost effective performance 10% lower hardware acquisition cost* 6% lower overall TCO* AMD Opteron 6300 Series raises the bar12 | Cutting Big Data Down to Size | Dell World – December 2012 |
  13. 13. For more information on AMD Cloudsolutions, please visit | Cutting Big Data Down to Size | Dell World – December 2012 |
  14. 14. DISCLAIMER The information presented in this document is for informational purposes only and may contain technical inaccuracies, omissions and typographical errors. The information contained herein is subject to change and may be rendered inaccurate for many reasons, including but not limited to product and roadmap changes, component and motherboard version changes, new model and/or product releases, product differences between differing manufacturers, software changes, BIOS flashes, firmware upgrades, or the like. AMD assumes no obligation to update or otherwise correct or revise this information. However, AMD reserves the right to revise this information and to make changes from time to time to the content hereof without obligation of AMD to notify any person of such revisions or changes. AMD MAKES NO REPRESENTATIONS OR WARRANTIES WITH RESPECT TO THE CONTENTS HEREOF AND ASSUMES NO RESPONSIBILITY FOR ANY INACCURACIES, ERRORS OR OMISSIONS THAT MAY APPEAR IN THIS INFORMATION. AMD SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT WILL AMD BE LIABLE TO ANY PERSON FOR ANY DIRECT, INDIRECT, SPECIAL OR OTHER CONSEQUENTIAL DAMAGES ARISING FROM THE USE OF ANY INFORMATION CONTAINED HEREIN, EVEN IF AMD IS EXPRESSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. ATTRIBUTION © 2012 Advanced Micro Devices, Inc. All rights reserved. AMD, the AMD Arrow logo, Radeon, and combinations thereof are trademarks of Advanced Micro Devices, Inc. Other names and logos are used for informational purposes only and may be trademarks of their respective owners.14 | Cutting Big Data Down to Size | Dell World – December 2012 |
  15. 15. BACK-UP15 | Cutting Big Data Down to Size | Dell World – December 2012 |
  16. 16. AMD SERVER STRATEGY Execution Innovation Investment SoC Methodology Heterogeneous Computing Acquisition of Fabric and to accelerate to bring the right IP/ISA to System-Level IP to enable time to market the workloads of interest dense, power efficient servers16 | Cutting Big Data Down to Size | Dell World – December 2012 |
  17. 17. CLOUD PLATFORM REQUIREMENTSTransaction ProcessingCores, memory, and I/O capabilities to handlelarge amounts of users and dataEnergy EfficiencyLow power consuming CPUs and platformsfor “scale out” cloud server farmsPerformance and ScalabilityCPUs with predictable performance tohandle peaks in traffic Security Hardware assisted security to keep out intruders and protect sensitive dataVirtualizationHardware assisted virtualization for reducedoverhead and increased isolation of VMs17 | Cutting Big Data Down to Size | Dell World – December 2012 |
  18. 18. VIRTUALIZATION – TO – PRIVATE CLOUD Enterprise and mid-market customers expanding their virtualization footprint or upgrading their virtualization infrastructureLow acquisition costsShift from capital-intensive to operational cost modelsPerformance to run a fixed number of VMs per server (20 – 40 VMs) at a fixed utilization rateMaintain or improve existing SLAs Easier, more flexible managementSoftware licensing not based on coreAbility to migrate VMs18 | Cutting Big Data Down to Size | Dell World – December 2012 |