Efficient Cloud Computing Strategies for Dynamic Workload Demand
Explore the challenges and solutions of scaling applications in cloud computing to meet dynamic workload demands. Learn about autoscaling, 3-tier architecture, metrics, and more in this insightful survey by Anshul Gandhi.
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Presentation Transcript
CSE 591: Energy-Efficient Computing Lecture 17 SCALING: survey Anshul Gandhi 347, CS building anshul@cs.stonybrook.edu
Cloud scenario Businesses have started moving to the cloud for their IT needs reduces capital cost of buying servers allows for elastic resizing of applications that have dynamic workload demand Cloud Service Providers (CSPs) offer monitoring and rule-based triggers to enable dynamic scaling of applications Microsoft Azure Watch Amazon auto scaling Demand Time
Challenges The values have to be determined by the user requires expert knowledge of application (CPU, memory, n/w thresholds) requires performance modeling expertise (when and how to scale) How to set these values ?? Microsoft Azure Watch Amazon auto scaling
Challenges The values have to be determined by the user requires expert knowledge of application (CPU, memory, n/w thresholds) requires performance modeling expertise (when and how to scale) 95% Resp. time (ms) Offline benchmarking Trial-and-error Expert application knowledge 400 ms Not possible for CSPs ! arrival rate (req/s) 60 req/s
