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Custom Virtual Machine Class Types with vSphere with Tanzu

10.30.2020 by William Lam // 1 Comment

When you deploy a Tanzu Kubernetes Grid (TKG) Cluster using the integrated TKG Service in vSphere with Tanzu, you can specify a Virtual Machine Class Type which determines the amount of CPU and Memory resources that are allocated for both the Control Plane and/or Worker Node VMs for your TKG Cluster.

Here is a sample YAML specification that uses the best-effort-xsmall VM class type for both Control Plane and Worker Node, but you can certainly override and choose different classes based on your requirements.

apiVersion: run.tanzu.vmware.com/v1alpha1
kind: TanzuKubernetesCluster
metadata:
  name: william-tkc-01
  namespace: primp-industries
spec:
  distribution:
    version: v1.17.8+vmware.1-tkg.1.5417466
  settings:
    network:
      cni:
        name: antrea
      pods:
        cidrBlocks:
        - 193.0.2.0/16
      serviceDomain: managedcluster.local
      services:
        cidrBlocks:
        - 195.51.100.0/12
  topology:
    controlPlane:
      class: best-effort-xsmall
      count: 1
      storageClass: vsan-default-storage-policy
    workers:
      class: best-effort-xsmall
      count: 3
      storageClass: vsan-default-storage-policy

Today, the are a total of 16 VM Class types that you can select from, however these are not customizable which is something that has been coming up more recently. The vSphere with Tanzu team is aware of this request and is working on a solution that not only makes customizing CPU and Memory easier but also supporting storage customization. As you can see from the table below, 16GB is only supported configuration today.


In the mean time, if you need a supported path for customizing your TKG Guest Clusters, one option is to use the TKG Standalone / MultiCloud CLI, which can be used with a vSphere with Tanzu Cluster. You will need to deploy an additional TKG Management Cluster (basically a few VMs), but once you have that, you can override CPU, Memory and Storage of both the Control Plane and Worker Nodes using the following environment variables:

  • VSPHERE_WORKER_NUM_CPUS
  • VSPHERE_WORKER_MEM_MIB
  • VSPHERE_WORKER_DISK_GIB
  • VSPHERE_CONTROL_PLANE_NUM_CPUS
  • VSPHERE_CONTROL_PLANE_MEM_MIB
  • VSPHERE_CONTROL_PLANE_DISK_GIB

If you are interested, the easiest way to get started is by using my TKG Demo Appliance Fling which was just recently updated to the latest TKG 1.2 release which has support for K8s v1.19 which is currently not available on vSphere with Tanzu.

Now, you might ask, would it be possible to create your own custom VM class types using vSphere with Tanzu? Well .... keep reading to find out 🙂

Disclaimer: This is not officially supported by VMware, use at your own risk. These custom changes can potentially impact upgrades or automatically be reverted upon the next update or upgrade. You have been warned.

[Read more...]

Categories // Kubernetes, VMware Tanzu Tags // vSphere Kubernetes Service

Automated Nested Lab Deployment on SDDC Part 4: Oracle Cloud VMware Solution

10.30.2020 by William Lam // Leave a Comment


In this final blog series, we are now going to take a look at deploying our Nested Lab in an Oracle Cloud VMware Solution environment. Similiar to GCVE, we also will have the ability to run Nested vSAN on top of the physical vSAN within OCVS and by default, customers are provided with the full administrator credentials. For networking, customers also have full access to the NSX-T Manager instance and this means that MAC Learning can be enabled and will allow inner-guest workloads will be able to communicate properly within and outside of the Nested Lab deployment.

Disclaimer: Nested ESXi is not officially supported on Oracle Cloud VMware Solution or by VMware.

[Read more...]

Categories // Automation, Nested Virtualization, Oracle Cloud VMware Solution, VMware Cloud Tags // Oracle VMware Cloud Solution, VMware Cloud

Automated Nested Lab Deployment on SDDC Part 3: Google VMware Cloud Engine

10.29.2020 by William Lam // 1 Comment


In Part 3 of this series, we will be taking a look at deploying our Nested Lab in a Google Cloud VMware Engine environment. One thing you may notice that is different between VMConAWS and AVS is that we are actually running a Nested vSAN on top of the physical vSAN within GCVE. In the current version of GCVE, customers have the ability to "escalate" their privileges from the default and this would allow us to configure the necessary ESXi advanced setting so that we do not have to rely on an NFS setup. For networking, customers also have full access to the NSX-T Manager instance and this means that MAC Learning can be enabled which will allow inner-guest workloads will be able to communicate properly within and outside of the Nested Lab deployment.

Disclaimer: Nested ESXi is not officially supported on Google Cloud VMware Engine or by VMware.

[Read more...]

Categories // Automation, Google Cloud VMware Engine, Nested Virtualization, VMware Cloud Tags // Google Cloud VMware Engine, VMware Cloud

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William is Distinguished Platform Engineering Architect in the VMware Cloud Foundation (VCF) Division at Broadcom. His primary focus is helping customers and partners build, run and operate a modern Private Cloud using the VMware Cloud Foundation (VCF) platform.

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