A Host Kernel-Based Approach for Tracing and Analyzing vCPUs in Virtual Machines

Virtual machines (VMs) are a crucial technology for cloud computing, permitting multiple operating systems to run on a single physical host. Here, we propose a method for analyzing the performance of virtual machines in a cloud computing environment. The current approach of tracing both the host and virtual machines can be inefficient and may not be feasible for various reasons, such as security and privacy issues. We propose a host-only kernel tracing technique that uses only trace data generated on the host system. The trace data is then analyzed using the TraceCompass tool and two algorithms: Virtual CPU State Finder (VSF) and State Time Analysis (STA). The VSF algorithm generates a graphical view of the state of each thread running inside virtual machines for the identification of latency and performance degradation. The STA algorithm calculates the amount of time each virtual CPU spends in different states, providing important insights into the resource utilization and performance of virtual resources. In addition, our usage of the Trace Compass tool and EASE scripting allows more manageable analysis and visualization of the tracing data, making it accessible to a broader range of users. This method provides cloud providers with valuable information to maintain QoS and SLA parameters and improve the overall performance of running VMs.