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Sandpiper : Black box and Gray-Box resource management for Virtual Machines Journal : Computer Networks: The International Journal of Computer and Telecommunications Networking , 2009. Vinayak Gagrani. Introduction. Overloaded Data Center can be handled in two ways :-

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Vinayak gagrani

Sandpiper : Black box and Gray-Box resource management for Virtual MachinesJournal : Computer Networks: The International Journal of Computer and Telecommunications Networking, 2009

Vinayak Gagrani


Introduction

Introduction

  • Overloaded Data Center can be handled in two ways :-

    • Reallocation of resources within the physical machines

    • Migration of one or multiple VMs to distribute the load

  • Manual Migration is error prone and lacks immediate response

  • Sandpiper introduces technique for monitoring VMs:

    • Black Box : externally monitor VMs, without knowledge of applications executing within them

    • Gray Box : use metrics from OS on applications for more information

  • Uses prediction to decide the utilization possible in future

  • Uses greedy approach to decide which VMs to move around


Sandpiper archietecture

Sandpiper Archietecture


Resource provisioning

Resource Provisioning

  • Need to estimate the additional resource requirements by VM

  • Black Box :-

    • High percentile of the tail distribution as initial estimate

    • VM is over using its fair share

    • VM is using its fair share completely , denotes less requirements

      • Scaling (How much to scale ?)

  • Gray Box :-

    • Better provisioning using service rate, response rate and drop rate

    • Applications modeled as G/G/1 queuing system

    • Allows to reduce the memory allocated in case its not being used fully


Hotspot detection mitigation

Hotspot Detection & Mitigation

  • Hotspot Detection

    • Black box – per physical server, Gray box – per virtual server

    • Prolonged exceeding of hotspot (k in N) as well as next predicted value then only hotspot are marked

    • Conservative or Aggressive approach ( based on k and N )

    • Prediction of future values using auto-regressive predictors

  • Hotspot Mitigation

    • VM Resizing

    • Migration

      • NP Hard

      • Capturing Multi-dimension loads – Volume of server

      • Migration phase

      • Swap phase


Positives and negatives

Positives and Negatives

  • Positives

    • Very good demonstration of using one technology (live migration) into other (resource management)

    • Lot of figures and graphs to assist text

    • Very detailed description, efficient and ready to be used

  • Negatives

    • Separate machine is to be dedicated as control plane

    • Lot of data to be kept for predicting and profiling for each VM

    • Possible bottleneck (?)

    • Algorithms in mitigation could have been more structured

    • Does not describe how to determine ‘k’ lowest VSR VMs in swapping phase


Points to ponder

Points to ponder

  • Memory resizing in black box approach

    • Issues and possible solution

  • Quantify the load of a machine

    • Problem with current metric for volume

    • Alternatives ?

  • Experiments ?


Future work

Future Work

  • Multiple Control Planes ?

    • Instead of one control plane use multiple planes whichinteract with each other

    • Utilize features of distributed computations

    • Remove bottleneck in monitoring(?)

    • Reduce chances of failure on central machine (?)

  • Any Other ?


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