CloudMonitor: Profiling Power Usage

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A presentation I gave at IEEE Cloud 2012 – one of the premier conferences on Cloud Computing for a paper by Ali Khajeh-Hoessini and myself.

The paper is entitled “CloudMonitor: Profiling Power Usage” and discusses the CloudMonitor software and how it could be used to create an energy tariff for Cloud providers.

I’m very grateful to my supervisor Prof Ian Sommerville for encouraging me to go to the conference, to LSCITS for funding the trip and for Google for giving me the time off!

More information on CloudMonitor can be found here: http://jws7.net/cloudmonitor

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CloudMonitor: Profiling Power Usage

  1. 1. University of St Andrews School of Computer ScienceProfiling Power at Cloud scaleJames SmithAli Khajeh-HosseiniJonathan Ward @jws7Ian Sommerville or can we charge for Energy? 1
  2. 2. University of St Andrews School of Computer ScienceProfiling Power at Cloud scaleC loudMon itorJames SmithAli Khajeh-HosseiniJonathan Ward @jws7Ian Sommerville or can we charge for Energy? 2
  3. 3. University of St Andrews School of Computer ScienceOperational costs exceeding purchase costs 3
  4. 4. University of St Andrews School of Computer ScienceOperational costs exceeding purchase costs Even over a relatively short lifespan (3-5 years). Mainly driven by energy costs 4
  5. 5. University of St Andrews School of Computer ScienceOperational costs exceeding purchase costs Even over a relatively short lifespan (3-5 years). Mainly driven by energy costsWe need realistic Energy estimations 5
  6. 6. University of St Andrews School of Computer ScienceOperational costs exceeding purchase costs Even over a relatively short lifespan (3-5 years). Mainly driven by energy costsWe need realistic Energy estimations 6 not just included in “infrastructure”
  7. 7. University of St Andrews School of Computer Science MonitoringIf you cannot measure something “then you cannot improve it...” - Lord Kelvin 7
  8. 8. University of St Andrews School of Computer Science MonitoringIf you cannot measure something “then you cannot improve it...” - Lord Kelvin 13.4% of organisations monitor their energy consumption! 8
  9. 9. University of St Andrews School of Computer ScienceDatacentres 9
  10. 10. University of St Andrews School of Computer ScienceDatacentres 10
  11. 11. University of St Andrews School of Computer ScienceDatacentres 11
  12. 12. University of St Andrews School of Computer Science DatacentresMonitoring at Scale is hard especially when you need additional hardware! 12
  13. 13. University of St Andrews School of Computer ScienceCloudMonitor 13
  14. 14. University of St Andrews School of Computer ScienceCloudMonitor Use SIGAR library to gather resource usage 14
  15. 15. University of St Andrews School of Computer ScienceCloudMonitor Use SIGAR library to gather resource usage Correlate with Power Meter readings 15
  16. 16. University of St Andrews School of Computer Science CloudMonitor Use SIGAR library to gather resource usage Correlate with Power Meter readingsGenerate Power 16 Model
  17. 17. University of St Andrews School of Computer ScienceSo what? 17
  18. 18. University of St Andrews School of Computer Science So what?Generate power modelon one machine. Rollout to 1,000 18
  19. 19. University of St Andrews School of Computer Science So what?Generate power modelon one machine. Rollout to 1,000 of the same configuration 19
  20. 20. University of St Andrews School of Computer Science Previous work• by Bohra, Ata & Chaundary - VMeter • linear power model is workload-specific • our work is workload-independent • calculate once - valid for all machines of the same configuration *Husain Bohra, Ata E, and Vipin Chaudhary. “VMeter: power modelling for virtualized clouds.” 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW) (April 2010): 1-8. 20
  21. 21. University of St AndrewsSchool of Computer Science 21
  22. 22. University of St AndrewsSchool of Computer Science 22
  23. 23. University of St Andrews School of Computer ScienceNot perfect 23
  24. 24. University of St Andrews School of Computer Science Not perfectbut pretty close... 24
  25. 25. University of St Andrews School of Computer Science The lesson?Experiments show 96%accuracy of SoftwarePredictions againstPDU Measurements 25
  26. 26. University of St Andrews School of Computer ScienceAn Energy Tariff for Cloud 26
  27. 27. University of St Andrews School of Computer ScienceAn Energy Tariff for CloudEnergy rates arerising at 15% pa 27
  28. 28. University of St Andrews School of Computer ScienceAn Energy Tariff for CloudEnergy rates arerising at 15% pa36 month costof test system: 28
  29. 29. University of St Andrews School of Computer ScienceAn Energy Tariff for CloudEnergy rates arerising at 15% pa36 month cost $2,767of test system: 29
  30. 30. University of St Andrews School of Computer ScienceShop for Cloud 30
  31. 31. University of St Andrews School of Computer ScienceAmazon AWS EU Cloud Category Cost Data Transfer $58,084 VM hours $40,568 Storage $2,325 Storage I/O $2,293 Total $103, 270 31
  32. 32. University of St Andrews School of Computer ScienceHypothetical Cloud that charges for Energy Category Cost Data Transfer $58,084 VM hours $40,568 Energy $2,767 Storage $2,325 Storage I/O $2,293 Total $106, 037 32
  33. 33. University of St Andrews School of Computer Science The lesson?Energy would accountfor 2.6% of the totalcosts 33
  34. 34. University of St Andrews School of Computer Science The lesson?Energy would accountfor 2.6% of the totalcosts and is likely to rise in the future 34
  35. 35. University of St Andrews School of Computer Science Summary Power Models DistributedCloudMonitor Monitoring Platform Resource Usage 35
  36. 36. University of St AndrewsSchool of Computer Science 36
  37. 37. University of St Andrews School of Computer ScienceEverybody benefits! 37
  38. 38. University of St Andrews School of Computer ScienceThanks for listening @jws7 jws7.net/cloudmonitor 38

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