Transcription of Resource Central: Understanding and Predicting Workloads ...
{{id}} {{{paragraph}}}
Example: stock market
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. Based onthis observation, we next introduce Resource Central (RC),a system that collects VM telemetry, learns these behaviorsoffline, and provides predictions online to various resourcemanagers via a general client-side library.
VM workloads, synthetic VM workloads, and/or focused on managing resources via general but often impractical tech-niques for a large cloud provider. For example, many papers explore (sometimes offline) workload profiling and aggres-sive online resource reallocation, via dynamic monitoring, scheduling, and/or live VM migration [2, 7, 20, 21, 24 ...
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: