<  Back to the Polytechnique Montréal portal

Low overhead hardware-assisted virtual machine analysis and profiling

Suchakrapani Datt Sharma, Geneviève Bastien, Hani Nemati and Michel Dagenais

Paper (2016)

Open Access document in PolyPublie
[img]
Preview
Open Access to the full text of this document
Accepted Version
Terms of Use: All rights reserved
Download (236kB)
Show abstract
Hide abstract

Abstract

Cloud infrastructure providers need reliable performance analysis tools for their nodes. Moreover, the analysis of Virtual Machines (VMs) is a major requirement in quantifying cloud performance. However, root cause analysis, in case of unexpected crashes or anomalous behavior in VMs, remains a major challenge. Modern tracing tools such as LTTng allow fine grained analysis - albeit at a minimal execution overhead,and being OS dependent. In this paper, we propose HAVAna,a hardware-assisted VM analysis algorithm that gathers and analyzes pure hardware trace data, without any dependence on the underlying OS or performance analysis infrastructure. Our approach is totally non-intrusive and does not require any performance statistics, trace or log gathering from the VM. We used the recently introduced Intel PT ISA extensions on modern Intel Skylake processors to demonstrate its efficiency and observed that, in our experimental scenarios, it leads to a tiny overhead of up to 1%, as compared to 3.6-28.7% for similar VM trace analysis done with software-only schemes such as LTTng. Our proposed VM trace analysis algorithm has also been opensourced for further enhancements and to the benefit of other developers. Furthermore, we developed interactive Resource and Process Control Flow visualization tools to analyze the hardware trace data and present a real-life usecase in the paper that allowed us to see unexpected resource consumption by VMs.

Uncontrolled Keywords

Virtualization; Hardware Tracing; Intel PT; Trace Analysis; VM Analysis

Subjects: 2700 Information technology > 2700 Information technology
2700 Information technology > 2715 Optimization
Department: Department of Computer Engineering and Software Engineering
Funders: CRSNG/NSERC
Grant number: CRDPJ468687-14
PolyPublie URL: https://publications.polymtl.ca/2975/
Conference Title: 2016 IEEE Globecom Workshops (GC Wkshps)
Conference Location: Washington, DC, USA
Conference Date(s): 2016-12-04 - 2016-12-08
Publisher: IEEE
DOI: 10.1109/glocomw.2016.7848953
Official URL: https://doi.org/10.1109/glocomw.2016.7848953
Date Deposited: 12 Feb 2018 16:31
Last Modified: 20 Apr 2023 07:26
Cite in APA 7: Sharma, S. D., Bastien, G., Nemati, H., & Dagenais, M. (2016, December). Low overhead hardware-assisted virtual machine analysis and profiling [Paper]. 2016 IEEE Globecom Workshops (GC Wkshps), Washington, DC, USA (6 pages). https://doi.org/10.1109/glocomw.2016.7848953

Statistics

Total downloads

Downloads per month in the last year

Origin of downloads

Dimensions

Repository Staff Only

View Item View Item