Applies To:
Show Versions
BIG-IQ Cloud
- 4.2.0
BIG-IQ Device
- 4.2.0
BIG-IQ Security
- 4.2.0, 4.1.0, 4.0.0
What is BIG-IQ Virtual Edition?
BIG-IQ Virtual Edition (VE) is a version of the BIG-IQ system that runs as a virtual machine in specifically-supported hypervisors. BIG-IQ VE emulates a hardware-based BIG-IQ system running a VE-compatible version of BIG-IQ software.
About BIG-IQ VE compatibility with vCloud Director hypervisor products
BIG-IQ Virtual Edition (VE) is compatible with vCloud Director 1.5 hosts.
About the hypervisor guest definition requirements
The vCloud Director virtual machine guest environment for the BIG-IQ Virtual Edition (VE), at minimum, must include:
- 2 x virtual CPUs
- 4 GB RAM
- 1 x VMXNET3 virtual network adapter or Flexible virtual network adapter (for management)
- 1 x virtual VMXNET3 virtual network adapter (three are configured in the default deployment for dataplane network access)
- 1 x 100 GB SCSI disk, by default
- 1 x 50 GB SCSI optional secondary disk, which might be required as a datastore for specific BIG-IP modules. For information about datastore requirements, refer to the BIG-IP module's documentation.
For production licenses, F5 Networks suggests using the maximum configuration limits for the BIG-IQ VE system. Reservations can be less for lab editions. For each virtual machine, the vCloud Director virtual machine guest environment permits a maximum of 10 virtual network adapters (either 10 VMXNET3 with 1 management + 9 dataplane or 1 Flexible management + 9 VMXNET3 dataplane).
There are also some maximum configuration limits to consider for deploying a BIG-IQ VE virtual machine, such as:
- CPU reservation can be up to 100 percent of the defined virtual machine hardware. For example, if the hypervisor has a 3 GHz core speed, the reservation of a virtual machine with 2 CPUs can be only 6 GHz or less.
- To achieve licensing performance limits, all allocated RAM must be reserved.
- For production environments, virtual disks should be deployed Thick (allocated up front). Thin deployments are acceptable for lab environments.