Fine-Grained Nested Virtual Machine Performance Analysis through First Level Hypervisor Tracing

Nemati, Hani; Sharma, Suchakrapani Datt; Dagenais, Michel R.

doi:10.1109/ccgrid.2017.20

Cited by 7 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nemati [11], [12] proposed a new approach to trace guests virtual CPU states, in any virtualization layer, tracing only the host without accessing VMs. Sharma [13], used a hardware tracing monitoring-based approach to generate hypervisor metrics and exposing virtualization overhead.…”

Section: Hypervisor Monitoringmentioning

confidence: 99%

Hypertracing: Tracing Through Virtualization Layers

Benbachir

Dagenais

2021

IEEE Trans. Cloud Comput.

View full text Add to dashboard Cite

Cloud computing enables on-demand access to remote computing resources. It provides dynamic scalability and elasticity with a low upfront cost. As the adoption of this computing model is rapidly growing, this increases the system complexity, since virtual machines (VMs) running on multiple virtualization layers become very difficult to monitor without interfering with their performance. In this paper, we present hypertracing, a novel method for tracing VMs by using various paravirtualization techniques, enabling efficient monitoring across virtualization boundaries. Hypertracing is a monitoring infrastructure that facilitates seamless trace sharing among host and guests. Our toolchain can detect latencies and their root causes within VMs, even for boot-up and shutdown sequences, whereas existing tools fail to handle these cases. We propose a new hypervisor optimization, for handling efficient nested paravirtualization, which allows hypertracing to be enabled in any nested environment without triggering VM exit multiplication. This is a significant improvement over current monitoring tools, with their large I/O overhead associated with activating monitoring within each virtualization layer.

show abstract

Section: Hypervisor Monitoringmentioning

confidence: 99%

Hypertracing: Tracing Through Virtualization Layers

Benbachir

Dagenais

2021

IEEE Trans. Cloud Comput.

View full text Add to dashboard Cite

show abstract

“…Early results of this work are presented in [23] [24] [25]. In these papers, we propose a technique to understand the behavior of up to one level of nested VMs.…”

Section: Related Workmentioning

confidence: 99%

virtFlow: Guest Independent Execution Flow Analysis Across Virtualized Environments

Nemati

Dagenais

2020

IEEE Trans. Cloud Comput.

Self Cite

View full text Add to dashboard Cite

An agent-less technique to understand virtual machines (VMs) behavior and their changes during the VM lifecycle is essential for many performance analysis and debugging tasks in the cloud environment. Because of privacy and security issues, ease of deployment and execution overhead, the method preferably limits its data collection to the physical host level, without internal access to the VMs. We propose a host-based, precise method to recover execution flow of virtualized environments, regardless of the level of virtualization. Given a VM, the Any-Level VM Detection Algorithm (ADA) and Nested VM State Detection (NSD) Algorithm compute its execution path along with the state of virtual CPUs (vCPUs) from the host kernel trace. The state of vCPUs is displayed in an interactive trace viewer (TraceCompass) for further inspection. Then, a new approach for profiling threads and processes inside the VMs is proposed. Our proposed VM trace analysis algorithms have been open-sourced for further enhancements and to the benefit of other developers. Our new techniques are being evaluated with workloads generated by different benchmarking tools. These approaches are based on host hypervisor tracing, which brings a lower overhead (around 1%) as compared to other approaches.Index Terms-Execution flow analysis, nested virtual machine, performance analysis, tracing, reverse engineering.

show abstract

“…A vCPU state detection algorithm based on host hypervisor is proposed in [7], [8], and [9]. They built different states for the running processes and threads.…”

Section: Related Workmentioning

confidence: 99%

Wait analysis of virtual machines using host kernel tracing

Nemati

Bastieny

Dagenaisz

2018

2018 IEEE International Conference on Consumer Electronics (ICCE)

Self Cite

View full text Add to dashboard Cite

An agent-less method to understand virtual machines (VMs) behavior its evolution during the VM life-cycle is an essential task for IaaS provider. It allows the IaaS provider to better scale the VMs resources by properly allocating the physical resources. On the other hand, because of privacy, security, ease of deployment and execution overhead issues, the method presented limits its data collection to the physical host level, without internal access to the VMs.We propose a host-based, precise method to recover wait states for the virtual CPUs (vCPUs) of a given VM. The Wait Analysis Algorithm (W2A) computes the state of vCPUs through the host kernel trace. The state of vCPUs is displayed in an interactive trace viewer (TraceCompass) for further inspection. Our proposed VM trace analysis algorithm has been open-sourced for further enhancements and to the benefit of other developers. Our new technique is being evaluated with representative workloads, generated by different benchmarking tools. These approaches are based on host hypervisor tracing, which brings a lower overhead (around 0.03%) as compared to other approaches.

show abstract

Fine-Grained Nested Virtual Machine Performance Analysis through First Level Hypervisor Tracing

Cited by 7 publications

References 7 publications

Hypertracing: Tracing Through Virtualization Layers

Hypertracing: Tracing Through Virtualization Layers

virtFlow: Guest Independent Execution Flow Analysis Across Virtualized Environments

Wait analysis of virtual machines using host kernel tracing

Contact Info

Product

Resources

About