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Supported limits

You can refer to tested object maximums when planning your OKD environment for OKD Virtualization. However, approaching the maximum values can reduce performance and increase latency. Ensure that you plan for your specific use case and consider all factors that can impact cluster scaling.

For more information about cluster configuration and options that impact performance, see the OKD Virtualization - Tuning & Scaling Guide in the Red Hat Knowledgebase.

Tested maximums for OKD Virtualization

The following limits apply to a large-scale OKD Virtualization 4.x environment. They are based on a single cluster of the largest possible size. When you plan an environment, remember that multiple smaller clusters might be the best option for your use case.

Virtual machine maximums

The following maximums apply to virtual machines (VMs) running on OKD Virtualization. These values are subject to the limits specified in Virtualization limits for Red Hat Enterprise Linux with KVM.

Objective (per VM) Tested limit Theoretical limit

Virtual CPUs

216 vCPUs

255 vCPUs

Memory

6 TB

16 TB

Single disk size

20 TB

100 TB

Hot-pluggable disks

255 disks

N/A

Each VM must have at least 512 MB of memory.

Host maximums

The following maximums apply to the OKD hosts used for OKD Virtualization.

Objective (per host) Tested limit Theoretical limit

Logical CPU cores or threads

Same as Fedora

N/A

RAM

Same as Fedora

N/A

Simultaneous live migrations

Defaults to 2 outbound migrations per node, and 5 concurrent migrations per cluster

Depends on NIC bandwidth

Live migration bandwidth

No default limit

Depends on NIC bandwidth

Cluster maximums

The following maximums apply to objects defined in OKD Virtualization.

Objective (per cluster) Tested limit Theoretical limit

Number of attached PVs per node

N/A

CSI storage provider dependent

Maximum PV size

N/A

CSI storage provider dependent

Hosts

500 hosts (100 or fewer recommended) [1]

Same as OKD

Defined VMs

10,000 VMs [2]

Same as OKD

  1. If you use more than 100 nodes, consider using Red Hat Advanced Cluster Management (RHACM) to manage multiple clusters instead of scaling out a single control plane. Larger clusters add complexity, require longer updates, and depending on node size and total object density, they can increase control plane stress.

    Using multiple clusters can be beneficial in areas like per-cluster isolation and high availability.

  2. The maximum number of VMs per node depends on the host hardware and resource capacity. It is also limited by the following parameters:

    • Settings that limit the number of pods that can be scheduled to a node. For example: maxPods.

    • The default number of KVM devices. For example: devices.kubevirt.io/kvm: 1k.

Additional resources