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Dicas e truques para ser um bom inquilino no Cloud
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Dicas e truques para ser um bom inquilino no Cloud

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Palestra no QConSP 2012, em 04/08/2012.

Palestra no QConSP 2012, em 04/08/2012.

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  • unidades computacionais\n
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  • shares, IaaS vs. PaaS\n
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  • fair share only what’s IN THE QUEUE\nMinimum perf. + Burstability\n
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  • SMP applications assume they are running on physical CPUs\n
  • +vCPUs = harder to schedule\n
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  • any order, locks are held\ncpu stacking\nSMP kernel has concurrency, spinlocks, etc\n
  • make a good use of your CPU time (do not spend it with context switches)\n
  • hard to share I/O resources\nhard to fair share -> async\n
  • I/O is also heavily impacted by this\nisolate I/O components, attached resources\n\n
  • attachable resources\nbe prepared to scale-out\nvariability\n
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  • data oriented discussions\n
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  • internal, nagios\n
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  • help drive product decisions\n
  • absolute values are ok, be careful with bucket aggregators\n
  • URL or ALIAS DNS entries\n
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Dicas e truques para ser um bom inquilino no Cloud Presentation Transcript

  • 1. dicas e truques para ser um bom inquilino ... no CloudFabio Kung
  • 2. inquilino?
  • 3. AB C D multitenancy
  • 4. IaaS PaaS Containers/Zones
  • 5. considere ...espalhar seus processos
  • 6. weightedfair scheduling [1]
  • 7. App AP1 P2 P3 20 App BP4 P5 P6 P7 40 App CP8 40
  • 8. App A App B App C1 2 3 0 4 5 6 7 0 8 0 20 40 40 fator de “justiça”
  • 9. App B App C4 5 6 7 0 8 0 40 40
  • 10. App B App C App A4 5 6 7 0 8 0 1 2 3 30 40 40 20
  • 11. App C App A8 0 1 2 3 30 40 20
  • 12. App C App B App A8 0 4 5 6 7 40 1 2 3 30 40 40 20
  • 13. App B App A4 5 6 7 40 1 2 3 30 40 20
  • 14. App B App A App C4 5 6 7 40 1 2 3 30 8 80 40 20 40
  • 15. App A App C1 2 3 30 8 80 20 40minimum + bursting
  • 16. co-scheduling
  • 17. SMP
  • 18. VM A VM B VM CvCPU vCPU vCPU vCPU vCPU
  • 19. synchronization costs
  • 20. VM A VM B VM CvCPU vCPU vCPU vCPU vCPU
  • 21. CPU stacking [2]
  • 22. evite I/O ... se puder
  • 23. I/O intensiveapplications need their own domain [3]
  • 24. espalhe seus processos http://www.12factor.net/concurrency
  • 25. efemeridade
  • 26. eu acho...
  • 27. PROVE!
  • 28. blá blá blá ... monitoração ... blá blá blá
  • 29. logs => event stream
  • 30. pipeline Archive, dashboards incApp id logs en ts t s even LogApp metrics logs router Pager eve nt s logsApp Event nts ide processor inc
  • 31. Log routers • https://github.com/heroku/logplex • https://github.com/fluent/fluentd events-to-metrics• https://github.com/heroku/pulse
  • 32. archives + querieshttps://twitter.com/danicuki/statuses/228170302515982336
  • 33. Librato
  • 34. the pager
  • 35. pipeline Archive, dashboards incApp id logs en ts t s even LogApp metrics logs router Pager eve nt s logsApp Event nts ide processor inc
  • 36. pipeline Archive, dashboards incApp id en ts t s even ExternalApp metrics events Monitor Pager eve nt sApp Event nts ide processor in c
  • 37. média
  • 38. %til
  • 39. naked domainshttps://devcenter.heroku.com/articles/avoiding-naked-domains-dns-arecords
  • 40. more...http://www.12factor.net
  • 41. References1. Groves, Taylor, Jeff Knockel and Eric Schulte. “BFS vs. CFS -Scheduler Comparison”. 11 Dec 2009. 2 Aug 2012 <http://slimjim.cs.unm.edu/~eschulte/data/bfs-v-cfs_groves-knockel-schulte.pdf>2. Sukwong, Orathai and Hyong S. Kim. “Is Co-scheduling TooExpensive for SMP VMs?”. EuroSys 2011 12 Apr 2011, Carnegie MellonUniversity. 29 Jul 2012 <http://eurosys2011.cs.uni-salzburg.at/pdf/eurosys2011-sukwong-slides.pdf>3. Ongaro, Diego, Alan L. Cox and Scott Rixner. “Scheduling I/O inVirtual Machine Monitors”. Rice University. 2 Aug 2012 <http://www.cs.rice.edu/CS/Architecture/docs/ongaro-vee08.pdf>4. Pijewski, Bill. “Our ZFS I/O Throttle”. Bill Pijewskis Blog.March 1, 2011. August 3, 2012 <http://dtrace.org/blogs/wdp/2011/03/our-zfs-io-throttle/>
  • 42. Obrigado!@fabiokung