Virtual CPU state detection and execution flow analysis by host tracing

Cloud computing offers to the end user the ability of accessing a pool of resources with the Pay as Use (PaU) model. By leveraging this technology, users can benefit from hardware virtualization for on-demand resource acquisition and rapid elasticity. However, there is no effective tool to analyze virtual hardware performance, especially when isolation between these virtual resources is not adequate. The existing tools need to access and trace the whole activity of the VM and host. However, in most cases, tracing the virtual machine (VM) is not possible because of security issues and the added overhead. Therefore, there is a need for a tool to troubleshoot unexpected behavior of VMs without internal access for tracing or debugging. In this paper, we propose a new method to study the state of CPUs inside VMs without internal access. Our tool can detect unexpected delays and their root causes. We developed a virtual CPU (vCPU) state analyser to detect the state of vCPUs along with the reason for being in that state. This approach relies on host tracing, thus adding less overhead to VMs as compared to existing approaches. Then we propose a new approach for profiling threads inside the VMs by host tracing. We implemented different views for the TraceCompass trace viewer to let the administrator visually track different threads and their states inside the VMs. Our tool can detect different problems such as overcommitment of resources.

Mots clés

virtualization; KVM; performance analysis; vCPU states; LTTng; TraceCompass