Resource Central: Understanding and Predicting Workloads ...

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. We then show that certain VMbehaviors are fairly consistent over multiple lifetimes, is an accurate predictor of future behavior.

1 INTRODUCTION Motivation. Cloud computing has been expanding at a fast pace, especially as enterprises continue to move their opera-tions to large cloud providers such as Microsoft Azure, Ama-zon Web Services (AWS), and Google Cloud Platform (GCP). Due to heated marketplace competition, providers have been

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  Introduction, Cloud, Microsoft

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