Reshaping the Physical Footprint of Virtual Machines Jason Sonnek - - PowerPoint PPT Presentation

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Reshaping the Physical Footprint of Virtual Machines Jason Sonnek - - PowerPoint PPT Presentation

Virtual Putty: Reshaping the Physical Footprint of Virtual Machines Jason Sonnek and Abhishek Chandra Department of Computer Science University of Minnesota 1 University of Minnesota Cloud Environments Applications VM Pool Resource Pool


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University of Minnesota

Virtual Putty: Reshaping the Physical Footprint of Virtual Machines

Jason Sonnek and Abhishek Chandra

Department of Computer Science University of Minnesota

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University of Minnesota

Cloud Environments

 Pool of resources for hosting applications

 Virtual Machines: Application containers

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Resource Pool VM Pool Applications

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University of Minnesota

Cloud Management Challenge

 Cloud Provider: High Consolidation

 Power, cost savings

 Cloud User: Robust performance

 Isolation from other hosted applications

 Goal: Exploit VM characteristics to meet best of

both worlds

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University of Minnesota

Physical Footprint of VM

 Physical Resource Consumption

 Memory usage, disk I/O, network

bandwidth, energy usage, etc.

 Impacts:

 Degree of consolidation  Application Performance

 Question: Is the physical footprint rigid?

 Independent of location, environment?

Memory CPU Network

VM

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University of Minnesota

Physical Footprint is Malleable

 Communicating VMs sitting locally vs. remotely

Number of File Transfers (K) Transfer Time (s)

  • Xen 3.3.0 VMs, 100

Mbps LAN, 100 KB Files

 Network footprint dependent on VM location and affinities

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University of Minnesota

Virtual Putty

 Reshape the physical footprints of Virtual Machines  Achieve: Higher performance, energy savings, …  Key Idea: Exploit affinities and conflicts

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Reshaping

VM1 VM2 VM1 VM2

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University of Minnesota

Problem 1: Estimating the Footprint

 VM has a “virtual” footprint

 Memory contents, I/O requests, communication

patterns, etc.

 Can be molded to desired “physical” footprint

 Challenges:

 How to estimate non-intrusively?  How to represent the virtual footprint efficiently?  How to handle dynamism?

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University of Minnesota

Problem 2: Reshaping the Footprint

 Enhance migration/placement decisions

 Reduce data redundancy  Place VMs near data  Exploit statistical multiplexing

 Challenges:

 How to reconcile multi-dimensional tradeoffs?  How to achieve system-wide reshaping in a

scalable, agile manner?

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University of Minnesota

Summary

 Physical Footprint of VM is malleable  Can be reshaped using affinities and conflicts  Footprint reshaping can lead to better

consolidation, performance

 Project URL: http://vputty.cs.umn.edu