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Managing elasticity across Multi-cloud providers
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Managing elasticity across Multi-cloud providers


International conference on Multi-cloud computing.

International conference on Multi-cloud computing.

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  • 1. Managing Elasticity Accross Multi-Cloud Providers 1 Fawaz Paraïso, Philippe Merle, Lionel Seinturier 1st International workshop on multi-cloud applications and federated clouds (2013) University Lille1 & Inria Lille – Nord Europe (France)
  • 2. 2 Introduction & Motivation Challenges Contribution Implementation Validation Conclusion 2 Agenda
  • 3. 3 Introduction & Motivation Elasticity is the capability to rapidly provision, in some cases automatically, to quickly scale out, and rapidly release resources APP APP APP APP APP APP APP APP APP
  • 4. 4 Introduction & Motivation
  • 5. 5 Introduction & Motivation Cloud provider What happened & why What impactWhen Amazon [8] The Amazon Elastic Load Balancing (ELB) Service down in US-East region affected the applications using the ELB. 21 April 2011 Offline for more than 10 hours. Companies affected: reddit, Quora, Hoot Suite. Windows Azure [9] A networking problem during a routine software update interfered with hosted project deployment. 13 March 2009 Offline for 22 hours.
  • 6. 6 Introduction & Motivation Cloud provider Electricity provider Unavailability: 7.5 hours average per year Unavailability: 15 minutes average per year Total of 585 hours cost > 71.7 million [1] [1] International Working Group on Cloud Computing Resiliency. http://www.iwgcr.org
  • 7. 7 Introduction & Motivation Multiple servers #1 Data centre Cloud provider Load balancer
  • 8. 8 Introduction & Motivation Multiple data centres #2 Load balancer Data centre A Data centre B Data centre C Cloud provider
  • 9. 9 Usage of multiple cloud providers in a uniform way. Multi-Cloud service Cloud B Cloud CCloud A Multiple Clouds #3 Introduction & Motivation
  • 10. 10 Introduction & Motivation Challenges Contribution Implementation Validation Conclusion 10 Agenda
  • 11. 11 Challenges How to guarantee high availability? How to automate elasticity through multiple clouds? How to provide transparency?
  • 12. 12 Introduction & Motivation Challenges Contribution Implementation Validation Conclusion 12 Agenda
  • 13. 13 Contribution Manage elasticity problem in Multi-Cloud environment Provide necessary resources when the system needs Full instrumentation for monitoring workloads Unpredictible environment Why ?What ?
  • 14. 14 Contribution Overview of the Multi-Cloud-PaaS Architecture
  • 15. 15 Contribution Deployment of the Multi-Cloud-PaaS Architecture
  • 16. 16 Contribution Independent of Cloud Flexible architecture Automation
  • 17. 17 Introduction & Motivation Challenges Contribution Implementation Validation Conclusion 17 Agenda
  • 18. 18 Implementation Implementation FraSCAti (SCA Model) Multi-Cloud-PaaS SCA-Based Components
  • 19. 19 The Multi-Cloud-PaaS (MCP) has been deployed on ten IaaS/PaaS providers. Deployment
  • 20. 20 Use case Application responsible for checking if the JPG format is correct. App First case App Second case
  • 21. 21 Evaluation Overhead Implementation Avg. exec. Time LB overhead APP 13.93 sec - APP + LB 14.10 sec 1.45% There is a negligeable overhead introduced by the LB First case Second case To evaluate the overhead of the LB instance, 10,000 pictures were sent to the application. Performance We generate 134, 021 requests and continuously connects to one instance of LB Session rate Concurrency Data rate Failures Avg. Time 850 283 4560 kB/s 0 3 ms Given the low resources used by the LB, the results obtained in are satisfactory
  • 22. 22 Conclusion This paper provides solution to manage elasticity across multiple cloud providers Independent of Cloud  Flexible architecture We plan to Evaluate the other Multi-Cloud-PaaS architecture components Investigate for optimization opportunities of cloud application deployment
  • 23. 23 Thank you! Fawaz.paraiso@inria.fr