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Novel Models and Techniques for Monitoring and Analysis of Software-defined Elastic Systems -- SummerSOC 2014

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Presentation given in PhD Session of advanced School on Service Oriented Computing 30 June – 5 July, 2014, Hersonissos Crete Greece (http://www.summersoc.eu/program/)

Contains in last slide embedded video of the given talk.

Overview of techniques for analyzing elasticity of both cloud offered services and running cloud services, towards supporting the design, and control of elastic cloud services.

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Novel Models and Techniques for Monitoring and Analysis of Software-defined Elastic Systems -- SummerSOC 2014

  1. 1. Novel Models and Techniques for Monitoring and Analysis of Software-defined Elastic Systems Daniel Moldovan Distributed Systems Group, Vienna University of Technology d.moldovan@dsg.tuwien.ac.at http://www.infosys.tuwien.ac.at/staff/dmoldovan/ SummerSoc 2014 1
  2. 2. Agenda • Analyzing Elasticity of cloud offered services • Quantifying elasticity of cloud offered services • Monitoring elastic cloud services • Analyzing Elasticity of cloud services • Elasticity Space, Boundaries and Pathway • Elasticity Dependencies SummerSoc 2014 2
  3. 3. Analyzing Elasticity of cloud offered services Motivation SummerSoc 2014 3 What cloud offered service provides appropriate elasticity for me?
  4. 4. Analyzing Elasticity of cloud offered services Motivation Load balancer Cost: /H & / GB SummerSoc 2014 4 For non-elastic components easier to select service
  5. 5. Analyzing Elasticity of cloud offered services Motivation Load balancer ... Cost: /H & / GB ? SummerSoc 2014 5 What cloud offered service provides appropriate elasticity?
  6. 6. Analyzing Elasticity of cloud offered services Motivation Load balancer t1.micro EBS + ... Cost: /H & / GB ? ... Cost: - OnDemand - Spot - Reserved (1/3 years) Cost: /size/month SummerSoc 2014 6 Should I select one service with higher Cost elasticity (more cost options), but with a mandatory dependency?
  7. 7. Analyzing Elasticity of cloud offered services Motivation Load balancer t1.micro EBS + i2.xlarge EBS + ... Cost: /H & / GB ? ... Cost: - OnDemand - Spot - Reserved (1/3 years) Cost: /size/month Cost: - OnDemand - Reserved (1/3 years) Cost: /size/month SummerSoc 2014 7 Should I go with a service with less Cost elasticity but an optional dependency on another service?
  8. 8. Analyzing Elasticity of cloud offered services Approach SummerSoc 2014 8
  9. 9. Elasticity Capability Elasticity DependenciesService Unit Analyzing Elasticity of cloud offered services Modelling Elasticity Capabilities Costm1.tiny OnDemand Reserved 1Y light Spot ... SummerSoc 2014 9
  10. 10. Analyzing Elasticity of cloud offered services Customizable Elasticity Quantification Coefficients • Elasticity Phase Quantification Coefficients • 𝐸𝑙𝑃ℎ𝑎𝑠𝑒𝑄 𝑝 = 𝑣𝑖 ∶ 𝑖𝑓 𝐼𝑛𝑠𝑡𝑎𝑛𝑡𝑖𝑎𝑡𝑖𝑜𝑛 𝑇𝑖𝑚𝑒 𝑣𝑟 ∶ 𝑖𝑓 𝑅𝑢𝑛 𝑇𝑖𝑚𝑒 𝑣𝑖𝑟 ∶ 𝑖𝑓 𝐵𝑜𝑡ℎ • Elasticity Dependency Type Quantification Coefficients • 𝐸𝑙𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦𝑄 𝑑 = 𝑣 𝑜 ∶ 𝑖𝑓 𝑂𝑝𝑡𝑖𝑜𝑛𝑎𝑙 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑖𝑜𝑛 𝑣 𝑚 ∶ 𝑖𝑓 𝑀𝑎𝑛𝑑𝑎𝑡𝑜𝑟𝑦 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑖𝑜𝑛 • Elasticity Dependency Volatility Quantification Coefficients • 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦𝑄(𝑑) • Elasticity Capability Quantification Function • 𝐸𝐶𝑄 𝑐 = 𝐸𝑙𝑃ℎ𝑎𝑠𝑒𝑄 𝑐. 𝑝ℎ𝑎𝑠𝑒 ∗ 𝑑 ∈𝑐.𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑖𝑒𝑠 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦𝑄 𝑑 ∗ 𝐸𝑙𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦𝑄(𝑑) • Elasticity Quantification Function • 𝐸𝑄 𝑠 = 𝑑 ∈ 𝑐𝑜𝑠𝑡, 𝑞𝑢𝑎𝑙𝑖𝑡𝑦, 𝑟𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑊 𝑑 ∗ 𝑐 ∈ 𝑠.𝑐𝑎𝑝𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠(𝑑) 𝐸𝐶𝑄 𝑐 SummerSoc 2014 10
  11. 11. Analyzing Elasticity of cloud offered services Example: Elasticity of Amazon EC2 IaaS Services SummerSoc 2014 11 • Elasticity Phase Quantification Coefficient • 𝐸𝑙𝑃ℎ𝑎𝑠𝑒𝑄 𝑝 = 1 ∶ 𝑖𝑓 𝐼𝑛𝑠𝑡𝑎𝑛𝑡𝑖𝑎𝑡𝑖𝑜𝑛 𝑇𝑖𝑚𝑒 2 ∶ 𝑖𝑓 𝑅𝑢𝑛 𝑇𝑖𝑚𝑒 3 ∶ 𝑖𝑓 𝐵𝑜𝑡ℎ • Elasticity Dependency Volatility Quantification Coefficient • 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦𝑄 𝑑 = 1/𝑚𝑖𝑛𝑆𝑒𝑟𝑣𝑖𝑐𝑒𝐿𝑖𝑓𝑒𝑡𝑖𝑚𝑒𝐼𝑛𝐻𝑜𝑢𝑟𝑠 • Elasticity Dependency Type Quantification Coefficient • 𝐸𝑙𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦𝑄 𝑑 = 1: 𝑖𝑓 𝑂𝑝𝑡𝑖𝑜𝑛𝑎𝑙 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑖𝑜𝑛 −1: 𝑖𝑓 𝑀𝑎𝑛𝑑𝑎𝑡𝑜𝑟𝑦 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑖𝑜𝑛
  12. 12. Analyzing Elasticity of cloud offered services SummerSoc 2014 12
  13. 13. • Analyzing Elasticity of cloud offered services • Quantifying elasticity of cloud offered services • Monitoring elastic cloud services • Analyzing Elasticity of cloud services • Elasticity Space, Boundaries and Pathway • Elasticity Dependencies SummerSoc 2014 13
  14. 14. Monitoring elastic cloud services Service Level Monitoring Response time Number of clients Other specific metrics System Level Monitoring Ganglia, Nagios, etc. CPU usage Memory usage Network transfer 14 User-Defined Requirements violation: - Cost per client too high Reasons: - Too much logging? Monitoring chatter? - Too expensive VMs? Which one can be downsized? - Not enough clients? Why? Controlling the service’s elasticity SummerSoc 2014 Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, MELA: Monitoring and Analyzing Elasticity of Cloud Services, 5'th International Conference on Cloud Computing, CloudCom. Bristol, UK, 2-5 December, 2013, http://dx.doi.org/10.1109/CloudCom.2013.18
  15. 15. Monitoring elastic cloud services Structuring monitoring information 15 Monitoring Data Service Structure SummerSoc 2014
  16. 16. Monitoring elastic cloud services Structuring monitoring information 16 Monitoring Data Service Structure Impose service structure over collected monitoring data SummerSoc 2014
  17. 17. Monitoring elastic cloud services Structuring and enriching monitoring information 17SummerSoc 2014 Compute number of used virtual machines per unit
  18. 18. Monitoring elastic cloud services Structuring and enriching monitoring information 18SummerSoc 2014 Compute number of used virtual machines per unit
  19. 19. Monitoring elastic cloud services Structuring and enriching monitoring information 19SummerSoc 2014 Enrich metric with COST information COST/VM * numberOfVMs
  20. 20. Monitoring elastic cloud services Structuring and enriching monitoring information 20SummerSoc 2014 Propagate activeConnections from LoadBalancer service unit
  21. 21. Monitoring elastic cloud services Structuring and enriching monitoring information 21SummerSoc 2014 Compute cost/client/h
  22. 22. • Analyzing Elasticity of cloud offered services • Quantifying elasticity of cloud offered services • Monitoring elastic cloud services • Analyzing Elasticity of cloud services • Elasticity Space, Boundaries and Pathway • Elasticity Dependencies SummerSoc 2014 22
  23. 23. SummerSoc 2014 23 Data Controller Event Processing clients Load Balancer Data Node Analyzing elasticity of cloud services Motivation Elastic Service User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, MELA: Monitoring and Analyzing Elasticity of Cloud Services, 5'th International Conference on Cloud Computing, CloudCom. Bristol, UK, 2-5 December, 2013, http://dx.doi.org/10.1109/CloudCom.2013.18
  24. 24. SummerSoc 2014 24 Data Controller Event Processing clients Load Balancer Data Node Analyzing elasticity of cloud services Motivation Elastic Service • When to scale Event Processing? • Requirements for Event Processing? User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, MELA: Monitoring and Analyzing Elasticity of Cloud Services, 5'th International Conference on Cloud Computing, CloudCom. Bristol, UK, 2-5 December, 2013, http://dx.doi.org/10.1109/CloudCom.2013.18
  25. 25. SummerSoc 2014 25 Data Controller Event Processing clients Load Balancer Data Node Analyzing elasticity of cloud services Motivation Elastic Service • When to scale Event Processing? • Requirements for Event Processing? • When to scale Data Node? • Requirements for Data Node? User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, MELA: Monitoring and Analyzing Elasticity of Cloud Services, 5'th International Conference on Cloud Computing, CloudCom. Bristol, UK, 2-5 December, 2013, http://dx.doi.org/10.1109/CloudCom.2013.18
  26. 26. 26 User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s SummerSoc 2014 Analyzing elasticity of cloud services Elasticity Space, Boundaries and Pathway Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, MELA: Monitoring and Analyzing Elasticity of Cloud Services, 5'th International Conference on Cloud Computing, CloudCom. Bristol, UK, 2-5 December, 2013, http://dx.doi.org/10.1109/CloudCom.2013.18
  27. 27. 27 User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s SummerSoc 2014 Analyzing elasticity of cloud services Elasticity Space, Boundaries and Pathway Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, MELA: Monitoring and Analyzing Elasticity of Cloud Services, 5'th International Conference on Cloud Computing, CloudCom. Bristol, UK, 2-5 December, 2013, http://dx.doi.org/10.1109/CloudCom.2013.18
  28. 28. Elasticity Space Snapshot Elasticity Space “Clients/h” Dimension Elasticity Space “Response Time” Dimension Analyzing elasticity of cloud services Elasticity Space and Boundary User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s SummerSoc 2014 28
  29. 29. Elasticity Space Snapshot Elasticity Space “Clients/h” Dimension Elasticity Space “Response Time” Dimension Analyzing elasticity of cloud services Elasticity Space and Boundary User-Defined Elasticity Requirements Cost <= 2.5 $/Month/Client Response Time <= 1 s SummerSoc 2014 29
  30. 30. Event Processing service unit Elasticity Pathway Analyzing elasticity of cloud services Elasticity Pathway 30SummerSoc 2014
  31. 31. Agenda • Analyzing Elasticity of cloud offered services • Quantifying elasticity of cloud offered services • Monitoring elastic cloud services • Analyzing Elasticity of cloud services • Elasticity Space, Boundaries and Pathway • Elasticity Dependencies SummerSoc 2014 31
  32. 32. Analyzing elasticity of cloud services Elasticity Dependencies 32SummerSoc 2014 Enforce Elasticity Capability (scale in/our, reconfigure) Effect ? Change in Load
  33. 33. Conclusions • Concepts • Elasticity Space, Boundary, Pathway • Elasticity Dependencies • Elasticity Capabilities • Mechanisms • Quantifying elasticity of cloud offered services • Constructing cross-layer monitoring snapshots • Analyzing elasticity • Framework/Tools • QUELLE: a Framework for Accelerating the Development of Elastic Systems (http://tuwiendsg.github.io/QUELLE) • MELA: Monitoring and analyzing elasticity of cloud services (http://tuwiendsg.github.io/MELA/) Work partially supported by the European Commission in terms of the CELAR FP7 project (http://www.celarcloud.eu/) Distributed Systems Group (http://dsg.tuwien.ac.at/) Vienna University of Technology (http://www.tuwien.ac.at/) SummerSoc 2014 33

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