Author: Michael Schroeder

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ESXi Configuration Restore fails with blank DCUI

Backing up and restoring an ESXi host configuration is a standard procedure that can be used when performing maintenance on the host. Not only host name, IP address and passwords are backed up, but also NIC and vSwitch configuration, Object ID and many other properties. Even after a complete reinstallation of a host, it can recover all the properties of the original installation.

Recently I wanted to reformat the bootdisk of a host in my homelab and had to fresh install ESXi for this. The reboot with the clean installation worked fine and the host got a new IP via DHCP.

Now the original configuration was to be restored via PowerCLI. To do this, first put the host into maintenance mode.

Set-VMhost -VMhost <Host-IP> -State "Maintenance"

Now the host configuration can be retored.

Set-VMHostFirmware -VMHost <Host-IP> -Restore -Sourcepath <Pfad_zum_Konfigfile>

The command prompts for a root login and then automatically reboots. At the end of the boot process, an empty DCUI was welcoming me.

I haven’t seen this before. I was able to log in (with the original password), but all network connections were gone. The management network configuration was also not available for selection (grayed out). The host was both blind and deaf.

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NSX-T vSphere-Client Integration

One of the new features of vSphere 7.0 Update 3 is that you can now manage NSX-T directly from the vSphere Client. In the new menu of the vSphere client UI, you will now find a section dedicated to NSX.

Opening this section currently brings up an NSX-T status information page. At this current stage, we are able to deploy new NSX-T instances, but existing NSX-T installations won’t be discovered.

Why is that?

As usual, a look at the Release Notes helps. There you’ll find the following statement for vCenter 7 Update 3:

You can see the vSphere Client NSX-T home page that enables the feature, but it does not work with NSX-T Data Center 3.1.x or earlier.

The most recent NSX-T version is 3.1.3 [as of 11/15/2021]. This means we have to wait for NSX-T version 3.2 until the integration works.

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VMware Validated Design Guide (VVD) discontinued

Anyone who has ever been involved in the design of IT concepts based on VMware products should be familiar with the VMware Validated Design Guide (VVD).

VMware Validated Design is a collection of data center design recommendations that span compute, storage, networking, and management which can be used as a reference guide for implementing a Software-Defined Data Center (SDDC). The VVD documentation consists of a series of documents that build on each other for all stages of the SDDC lifecycle. The VVD documentation can be used as an extension of the VMware Cloud Foundation (VCF) documentation. Each version of the VVD Guide correlates with a particular VCF version.

VMware Validated Design has been discontinued after VMware Validated Design 6.2 and VMware Cloud Foundation 4.2. VMware Validated Solutions (VVS) will take over the succession of VVD.

VMware Validated Solutions

VMware Validated Solutions are validated technical implementations designed to assist in building a secure and stable infrastructure based on VCF. Each VVS includes a detailed design with design decisions, as well as implementation instructions. VMware Cloud Foundation SDDC Manager is required to implement VMware Validated Solutions.

Finally, this means that anyone interested in a VMware validated solution in the future needs to take a look at VCF.

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GPU enabled K8s Clusters in vSphere with Tanzu

Using GPU in container workloads is an important demand by developers who work with machine learning and artificial intelligence.

You can create a custom VM class where a VI admin can define a vGPU specification for that class. Developers can use this class to assign GPU resources to the workload. The vm class will define node placement an vGPU profile.

This not only available to GPU enabled TKG clusters, but also for standalone VMs. The use of custom classes will simplify the consumption of GPU resources in ML/AI applications.

See a sample class below

kind: TanzuKubernetesCluster
apiVersion: run.tanzu.vmware.com/v1
metadata:
  name: GPU-Cluster
spec:
  topology:
    workers:
      count: 3
      class: gpu-vmclass
  distribution: v1.20.2

This class can be consumed for example in a VM

kind: VirtualMachine
metadata:
  name: gpu-vm
  namespace: tkg-dev
spec:
  networkInterfaces:
  - networkName: "dev-network"
    networkType: vsphere-distributed
  classname: gpu-vmclass
  imageName: ubuntu-custom-gpu    
  storageClass: GPU-vm-policy

This blogpost used to be part of my recent vSphere7 Update3 What’s new artice, but has been withdrawn at VMware’s request with an extended embargo until October 5 2021.