Memory overhead per infrastructure node ≈ 150 MiB
Review this section before you install OpenShift Virtualization to ensure that your cluster meets the requirements.
You can use any installation method, including user-provisioned, installer-provisioned, or assisted installer, to deploy OpenShift Container Platform. However, the installation method and the cluster topology might affect OpenShift Virtualization functionality, such as snapshots or live migration.
If you install your cluster in FIPS mode, no additional setup is required for OpenShift Virtualization.
Review the following hardware and operating system requirements for OpenShift Virtualization.
On-premise bare metal servers
Amazon Web Services bare metal instances
Installing OpenShift Virtualization on an AWS bare metal instance is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see https://access.redhat.com/support/offerings/techpreview/.
Bare metal instances or servers offered by other cloud providers are not supported.
Supported by Red Hat Enterprise Linux (RHEL) 8
Support for Intel 64 or AMD64 CPU extensions
Intel VT or AMD-V hardware virtualization extensions enabled
NX (no execute) flag enabled
Supported by OpenShift Container Platform
Red Hat Enterprise Linux CoreOS (RHCOS) installed on worker nodes
RHEL worker nodes are not supported.
OpenShift Virtualization is an add-on to OpenShift Container Platform and imposes additional overhead that you must account for when planning a cluster. Each cluster machine must accommodate the following overhead requirements in addition to the OpenShift Container Platform requirements. Oversubscribing the physical resources in a cluster can affect performance.
The numbers noted in this documentation are based on Red Hat’s test methodology and setup. These numbers can vary based on your own individual setup and environments.
Calculate the memory overhead values for OpenShift Virtualization by using the equations below.
Memory overhead per infrastructure node ≈ 150 MiB
Memory overhead per worker node ≈ 360 MiB
Additionally, OpenShift Virtualization environment resources require a total of 2179 MiB of RAM that is spread across all infrastructure nodes.
Memory overhead per virtual machine ≈ (1.002 * requested memory) + 146 MiB \ + 8 MiB * (number of vCPUs) \ (1) + 16 MiB * (number of graphics devices) (2)
|1||Number of virtual CPUs requested by the virtual machine|
|2||Number of virtual graphics cards requested by the virtual machine|
If your environment includes a Single Root I/O Virtualization (SR-IOV) network device or a Graphics Processing Unit (GPU), allocate 1 GiB additional memory overhead for each device.
Calculate the cluster processor overhead requirements for OpenShift Virtualization by using the equation below. The CPU overhead per virtual machine depends on your individual setup.
CPU overhead for infrastructure nodes ≈ 4 cores
OpenShift Virtualization increases the overall utilization of cluster level services such as logging, routing, and monitoring. To account for this workload, ensure that nodes that host infrastructure components have capacity allocated for 4 additional cores (4000 millicores) distributed across those nodes.
CPU overhead for worker nodes ≈ 2 cores + CPU overhead per virtual machine
Each worker node that hosts virtual machines must have capacity for 2 additional cores (2000 millicores) for OpenShift Virtualization management workloads in addition to the CPUs required for virtual machine workloads.
If dedicated CPUs are requested, there is a 1:1 impact on the cluster CPU overhead requirement. Otherwise, there are no specific rules about how many CPUs a virtual machine requires.
Use the guidelines below to estimate storage overhead requirements for your OpenShift Virtualization environment.
Aggregated storage overhead per node ≈ 10 GiB
10 GiB is the estimated on-disk storage impact for each node in the cluster when you install OpenShift Virtualization.
Storage overhead per virtual machine depends on specific requests for resource allocation within the virtual machine. The request could be for ephemeral storage on the node or storage resources hosted elsewhere in the cluster. OpenShift Virtualization does not currently allocate any additional ephemeral storage for the running container itself.
As a cluster administrator, if you plan to host 10 virtual machines in the cluster, each with 1 GiB of RAM and 2 vCPUs, the memory impact across the cluster is 11.68 GiB. The estimated on-disk storage impact for each node in the cluster is 10 GiB and the CPU impact for worker nodes that host virtual machine workloads is a minimum of 2 cores.
If you install OpenShift Virtualization in a restricted environment with no internet connectivity, you must configure Operator Lifecycle Manager for restricted networks.
If you have limited internet connectivity, you can configure proxy support in Operator Lifecycle Manager to access the Red Hat-provided OperatorHub.
Live migration has the following requirements:
Shared storage with
ReadWriteMany (RWX) access mode
Sufficient RAM and network bandwidth
Appropriate CPUs with sufficient capacity on the worker nodes. If the CPUs have different capacities, live migration might be very slow or fail.
See OpenShift Virtualization storage features for snapshot and cloning requirements.
In OpenShift Container Platform clusters installed using installer-provisioned infrastructure and with MachineHealthCheck properly configured, if a node fails the MachineHealthCheck and becomes unavailable to the cluster, it is recycled. What happens next with VMs that ran on the failed node depends on a series of conditions. See About RunStrategies for virtual machines for more detailed information about the potential outcomes and how RunStrategies affect those outcomes.