From Grid to Cloud

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From the Gaming Scalability event, June 2009 in London (http://gamingscalability.org).

Simon will discuss some of the key components of a compute grid infrastructure and highlight some of the key challenges organisations have to meet as their compute grids expand. Simon will also discuss one organisation within the spread betting industry who has recently started using grid technology. Finally Simon will describe how compute grids within the capital markets are beginning to resemble private clouds, and how the underlying infrastructure needs to change to enable these organisation to support a much wider range of applications running on the grid.

Simon Waterer is a Senior Solutions Architect with Platform Computing, a leading provider of HPC software. Since joining Platform, Simon has worked with a number of clients within the capital markets and insurance industry to understand their grid computing requirements. Recently Simon has worked with leading organisations within the spread betting industry who also have distributed processing requirements. Prior to working with grid technology Simon has had experience working with a number of other middleware technologies including data caching, messaging middleware and event stream processing.

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From Grid to Cloud

  1. 1. From Grid To Cloud<br />Online Gaming High Scalability SIG<br />Presented by:Simon Waterer<br />Solution Architect, Platform Computing<br />July 2009<br />
  2. 2. Are Compute Grids Morphing Into Clouds?<br />13/07/2009<br />2<br />How Many Of You Are Using Compute Grid Technology?<br />Do Cloud Infrastructures Share Features Found In Grids?<br />
  3. 3. Platform in the Gaming Industry<br />13/07/2009<br />3<br />Feed Handler, Grid Client<br />TIP-EX<br />Trader/Modeller<br />Wholesale Channel<br />Compute Grid<br />Data Cache<br />Client Web Site<br />Client Mobile<br />……….<br />Oracle<br />Excel Instances Running <br />on The Grid<br />
  4. 4. Running Excel On the Grid<br />Grid Client<br />Spreadsheet serialised at client and passed by grid middleware to grid node<br />Dialog Sniffer used for debugging spreadsheets that are to be run on the grid<br />Scheduler<br />Grid Service/Engine<br />Grid Node/Host. Multiple Service/Engines run per CPU/core<br />Excel Instance<br />
  5. 5. The Advantages of Grid?<br />Handles allocation of resources<br />Automatic<br />Shared Resources<br />Handle Failures<br />The grid provides redundancy<br />So What?<br />Run more workload using fewer resources<br />13/07/2009<br />5<br />
  6. 6. Grid Components<br />13/07/2009<br />6<br />Input<br />Output<br />Application<br />Input<br />Output<br />Client<br />Service<br />Grid Infrastructure<br />
  7. 7. Grid Components<br />Application on-boarding<br />Scheduler<br />Middleware<br />Workload monitoring<br />Workload management<br />Data Grid<br />Reporting<br />Resource allocation<br />Resource policy<br />Cluster management<br />Reporting<br />13/07/2009<br />7<br />Application Orchestration<br />Resource Orchestration<br />
  8. 8. Phases of Grid Adoption<br />13/07/2009<br />8<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />A<br />Phase 1<br />Phase 2<br />Phase 3<br />Phase 4<br />LOB<br />LOB<br />LOB<br />LOB<br />LOB<br />LOB<br />LOB<br />LOB<br />A<br />Phase 1:Silo Grid – Grid enable application running on a commodity cluster<br />Phase 2:LOB Grid – Resource sharing among multiple applications <br />Phase 3:Enterprise Analytics Grid – Utility computing; enterprise scale and management<br />Phase 4:Enterprise Grid – Beyond analytics: commercial applications on grid<br />
  9. 9. Grid As A Service<br />13/07/2009<br />9<br />Dev/Test<br /><ul><li>Developers and testers get environments in 15 minutes, instead of waiting 2 weeks
  10. 10. IT administrators eliminate manual setup and repurposing work
  11. 11. Automated tracking of utilization with accurate billing to the LOB’s for what they use</li></ul>FX, Equities, Credit Derivatives<br />Grid Infrastructure<br /><ul><li>Integrated cloud for Test/Dev through to production application deployment
  12. 12. Self-service environment reservation with automated, policy-driven VM placement</li></li></ul><li>7/13/2009<br />10<br />Feb Contract: 16 machines<br />Feb Contract: 6 machines<br />Feb Contract: 12 machines<br />LOB C<br />LOB B<br />LOB A<br />Jan Contract: 12 machines<br />Jan Contract: 14 machines<br />Jan Contract: 10 machines<br />Self-Service Resource Re-allocation<br />Self-Service Resource Re-allocation<br />Compute Grid<br />Dev Network<br />UAT Network<br />Prod Network<br />Free Pool<br />Dev/UAT/Production & Production/Production Sharing<br />10<br />
  13. 13. Bursting to non-HPC Servers<br /><ul><li>Calendar-driven startup/shutdown of VMs
  14. 14. Dynamic addition of non-HPC VMs to HPC Grid</li></ul>Non-HPC servers<br />HPC Grid<br />VM<br />VM<br />VM<br />VM<br />11<br />
  15. 15. Cloud Bursting For Peak Demand<br />Web 2.0Partner App<br /><ul><li>Public Clouds used for cloud-bursting applications</li></ul>DetectWhenResources Are Exhausted<br />ProvisioiningAdaptor<br />Grid<br />Infrastructure<br />Private Data Centre<br />Web 2.0Customer App<br />GridOverflow Pool<br />Public Clouds<br />12<br />12<br />13/07/2009<br />
  16. 16. Public & Private Cloud<br />Grid<br /><ul><li>Dynamic workload using static resources
  17. 17. Policy-based scheduling</li></ul>VM Cluster<br /><ul><li>Homogeneous server consolidation
  18. 18. Limited apps
  19. 19. Basic VM mgmt</li></ul>Enterprise<br />Workgroup<br />/ LOB<br />3 Paths to Cloud Adoption<br />Scope of sharing<br />Cloud – “A pool of abstracted, highly scalable, and managed infrastructure capable of hosting end-customer applications and billed by consumption” (Forrester)<br />Client/Server<br />Silos<br />Time<br />2015<br />2009<br />2003<br />13<br />
  20. 20. Public Cloud<br />Company X<br />Private Cloud<br />Company Y<br />Private and Public Cloud<br />Public Cloud by Service Providers<br /><ul><li>Non-mission critical SLAs
  21. 21. In-house IT has limited scale, scope or expertise --- SMEs</li></ul>Private Cloud by Corporate IT<br /><ul><li>Maximize value of underutilized resources
  22. 22. Mission critical SLAs
  23. 23. High security & compliance requirements
  24. 24. Enterprise-specific services</li></ul>14<br />
  25. 25. Enterprise Adoption of Cloud<br />$<br />$<br />$<br />$<br />$<br />$<br />Private Cloud Augmented by Public Cloud<br /><ul><li>IT delivering faster services with uniform UIs
  26. 26. Increased utilization of existing resources
  27. 27. Controlled overflow to Public clouds to meet unpredictable workload spikes
  28. 28. Lower CapEx & OpEx</li></ul>Company X<br />15<br />
  29. 29. 7/13/2009<br />16<br />Different Cloud Services<br />Software-as-a-Service (SaaS)<br />Platform-as-a-Service (PaaS)<br />Infrastructure-as-a-Service (IaaS)<br />Private<br />Public<br />
  30. 30. IaaS Usage Model<br />Cloud Admin<br />User<br />Application Manager<br />ESX<br /><ul><li>Define resource inventory
  31. 31. Publish & deliver services
  32. 32. Manage costs</li></ul>Virtual Machine<br />Virtual Machine<br />Virtual Machine<br />Virtual Machine<br />Virtual<br />Machines<br /><ul><li>Sign up for services
  33. 33. Prioritize & allocate resource quotas</li></ul>IaaS Cloud<br />Virtual Machine<br />Virtual Machine<br /><ul><li>Request & use resources, subject to quota</li></ul>Physical<br />Machines<br />17<br />
  34. 34. IaaS Benefits<br />User<br />CXO<br /> Cloud Admin<br />Application Manager<br /><ul><li>Get machines in minutes instead of days/weeks
  35. 35. Lower costs, pay by actual usage
  36. 36. Prioritize my application needs</li></ul>IaaS Cloud<br /><ul><li>Lower IT costs
  37. 37. Faster response to business
  38. 38. Timely delivery
  39. 39. Increased utilization
  40. 40. Lower CapEx & OpEx
  41. 41. Reduced human errors</li></ul>18<br />
  42. 42. 7/13/2009<br />19<br />IaaS Components<br />Manual<br />Service Delivery<br />Creating a shared computing infrastructure from physical & virtual heterogeneous resources<br />Delivering app environments according to workload-aware & resource-aware policies<br />Allocation Engine<br />Resource Integrations<br />
  43. 43. Questions?<br />
  44. 44. Summary<br /><ul><li>Grids
  45. 45. Exhibiting cloud tendencies
  46. 46. Private Clouds
  47. 47. Resource and workload aware allocation are key
  48. 48. Policy driven
  49. 49. Platform Symphony
  50. 50. www.platform.com
  51. 51. Platform ISF Beta
  52. 52. Launched July
  53. 53. Head in The Cloud</li></ul>YouTube, Amazon, Stanford University<br />13/07/2009<br />21<br />

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