Resource Central: Understanding and Predicting Workloads ...

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Resource Central: Understanding and PredictingWorkloads for Improved Resource Management inLarge Cloud Platforms Eli BondeMicrosoft MuzioITA, BianchiniMicrosoft research to date has lacked data on the characteris-tics of the production virtual machine (VM) Workloads oflarge cloud providers. A thorough Understanding of thesecharacteristics can inform the providers Resource manage-ment systems, VM scheduler, power manager, serverhealth manager. In this paper, we first introduce an exten-sive characterization of Microsoft Azure s VM workload,including distributions of the VMs lifetime, deployment size,and Resource consumption.

duction VMs can be accurately predicted for better resource management. Thus, there is a need for software that can produce such predictions and enable the providers’ resource management systems (e.g., the VM scheduler, the server health manager) to leverage them. Some prediction-serving systems [5, 6, 10]

  Resource, Schedulers