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Dynamically Scaling Applications in the Cloud

Dynamically Scaling Applications in the Cloud. Presented by Paul. Problem. The cloud offers Near infinite computing capabilities Near infinite storage On-demand access to new VMs Pay-as-you-go model But how do you build an application to automatically take advantage of those resources?.

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Dynamically Scaling Applications in the Cloud

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  1. Dynamically Scaling Applications in the Cloud Presented by Paul

  2. Problem • The cloud offers • Near infinite computing capabilities • Near infinite storage • On-demand access to new VMs • Pay-as-you-go model • But how do you build an application to automatically take advantage of those resources? [1]

  3. Overview of scaling options [1]

  4. Horizontal Scaling • VM Replication • Duplicate servers and create load balancers to distribute incoming request • Most common approach to scaling • Will look in more detail... • Network Scalability • As an application scales up, the bandwidth requirements for intercloud communication and app requests increases, [1] assesses the possibility of requesting network resources in conjunction with cloud resources Network as a Server (NaaS) [1]

  5. Vertical Scaling • VM resizing (live) • Taking a VM with given processing power, and upgrading it with more resources while it's still running • VM replacement • Replacing less powerful VM with more powerful VM (shutting down original VM) • Might require reboots, and application tolerance [1]

  6. "Rule of thumb" • CPU-Intensive • Best to load balance and split computation among many instances • Network intensive • Better to use single CPU heavy instance • More network intensive • DNS-based load balancing on powerful CPUs [1]

  7. Decisions, decisions • 1 Cloud to rule them all? • Do you want to use multiple cloud providers? • Does part of your application require running on private cloud? • How much control over automated scaling would you like? • If you don't want any control, maybe PaaS is better option • Do you simply want horizontal scaling, and will handle load balancing on your own? • How much $$$ do you have?

  8. Methods for Scaling • Automatic VM Scaling • Dynamic Workload-pattern Matching • Whole Application Scaling • Non-scalable Load Balancing (e.g. Elastic Load Balancing) • DNS-based Load Balancing [1]

  9. Basic: Automatic VM Scaling • Services that scale based on predefined VM-related performance metrics • Offered by Amazon and Rightscale • Amazon Autoscaling comes with Cloudwatch • Set conditions based on Cloudwatch variables, react to latency, CPU speed, etc. • What you might imagine for scaling - like a state machine • If conditions a,b,c are met, do x,y,z [1]

  10. The "Controller"

  11. "Non-Scalable" Load Balancers • Amazon offers load balancing service (Elastic Load Balancing) • The reason it's "non-scalable" is this is a single load balancer • Could be used in conjunction with horizontal scaling • Scale up/down the number of instances, configure load balancer to balance across running instances

  12. Elastic Beanstalk • Automatically scale up your application depending on services it's using, and beanstalk controller parameters • Only pay for underlying AWS resources • Can upload .NET, PHP/Python, and Java apps for integration with Elastic Beanstalk • Closer in function to a PaaS • Still have access to AWS instances, can interact with elastic beanstalk controller

  13. Whole Application Scaling [3]

  14. Whole Application Scaling [3]

  15. Dynamic Workload-pattern Matching [2] Scalability Controller

  16. Dynamic Workload-pattern Matching [2]

  17. Final Observations • You must first decide how many clouds you want to use • Scaling is still an art • Systems for automated scaling still in their infancy • At the core, there is always a scaling controller • Either you configure and operate the controller, or the IaaS provider does (e.g. Elastic Beanstalk) • You pay for automation • Either with your time or your money • More customized automation == more complexity

  18. Sources [1] L. M. Vaquero, L. Rodero-Merino, and R. Buyya. "Dynamically scaling applications in the cloud," SIGCOMM Comput. Commun. Rev., 41:45-52. [2] P. Marshall, K. Keahey, and T. Freeman, "Elastic site:Using clouds to elastically extend site resources," Cluster Computing and the Grid, IEEE International Symposium on, vol. 0, pp. 43-52, 2010. [3]R. Buyya, R. Ranjan, and R. Calheiros, “Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services.” in ICA3PP 2010: The 10th International Conference on Algorithms and Architectures for Parallel Processing, 2010, pp. 19–24.

  19. Links for papers [1] http://www.cloudbus.org/papers/ScalabilityInCloud2011.pdf [2] http://www.nimbusproject.org/files/elasticsite_ccgrid_2010.pdf [3] http://arxiv.org/pdf/1003.3920.pdf

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