Red Hat SummitChapitre 13. Optimizing virtual machine performance
Virtual machines (VMs) always experience some degree of performance deterioration in comparison to the host. The following sections explain the reasons for this deterioration and provide instructions on how to minimize the performance impact of virtualization in RHEL 9, so that your hardware infrastructure resources can be used as efficiently as possible.
13.1. What influences virtual machine performance
VMs are run as user-space processes on the host. The hypervisor therefore needs to convert the host’s system resources so that the VMs can use them. As a consequence, a portion of the resources is consumed by the conversion, and the VM therefore cannot achieve the same performance efficiency as the host.
The impact of virtualization on system performance
More specific reasons for VM performance loss include:
- Virtual CPUs (vCPUs) are implemented as threads on the host, handled by the Linux scheduler.
- VMs do not automatically inherit optimization features, such as NUMA or huge pages, from the host kernel.
- Disk and network I/O settings of the host might have a significant performance impact on the VM.
- Network traffic typically travels to a VM through a software-based bridge.
- Depending on the host devices and their models, there might be significant overhead due to emulation of particular hardware.
The severity of the virtualization impact on the VM performance is influenced by a variety factors, which include:
- The number of concurrently running VMs.
- The amount of virtual devices used by each VM.
- The device types used by the VMs.
Reducing VM performance loss
RHEL 9 provides a number of features you can use to reduce the negative performance effects of virtualization. Notably:
-
The
TuneDservice can automatically optimize the resource distribution and performance of your VMs. - Block I/O tuning can improve the performances of the VM’s block devices, such as disks.
- NUMA tuning can increase vCPU performance.
- Virtual networking can be optimized in various ways.
Tuning VM performance can have adverse effects on other virtualization functions. For example, it can make migrating the modified VM more difficult.
