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Automated Lab Deployment Script for vSphere with Tanzu using NSX Advanced Load Balancer (NSX ALB)

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After spending a few days playing with the NSX Advanced Load Balancer (NSX ALB) APIs, I am happy to share my latest automation lab deployment script for deploying vSphere with Tanzu using the new NSX ALB which was introduced with the latest vSphere 7.0 Update 2 release.

Lab Deployment Automation

You can find the new automation script along with all the details at the following Github Repo: https://github.com/lamw/vsphere-with-tanzu-nsx-advanced-lb-automated-lab-deployment#enable-workload-management


In my environment, it took about ~32 minutes for the deployment to finish, but YMMV based on the performance of your underlying hardware.

Workload Management Automation

In addition to the automated lab deployment script above, I have also updated my community VMware.WorkloadManagement module to add support for enabling Workload Management on a vSphere Cluster using NSX ALB. This is introduced as a new function creatively called New-WorkloadManagement3. You use the Get-Help cmdlet to get a list of supported arguments or you can take a look at this example.

Disabling vSphere with Tanzu does not delete NSX Advanced Load Balancer (NSX ALB) Service Engine (SE) VMs

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While working on some automation to deploy a vSphere 7.0 Update 2 environment that has been configured with vSphere with Tanzu and NSX Advanced Load Balancer (NSX ALB), I noticed that when you disable Workload Management on a vSphere Cluster, the two NSX ALB Service Engine (SE) VMs were still left behind.


It turns out that this behavior is due to a default setting within NSX ALB that will NOT automatically delete the SE's in the case there is a scaled up event which would then cause a re-deploy to happen. Instead, by default it is configured to wait 120 minutes (2hrs) before cleaning up.

If you wish to change this behavior, you can login to NSX ALB UI and navigate to Infrastructure->Service Engine->Advanced and update the "Delete Unused Service Engines After" to your desired value. Please note, that the shortest time interval to wait is 1 minute and if you set it to 0, it means the SE's VMs not be deleted.


After saving this change, the next time you disable Workload Management, the SE VMs will automatically get cleaned based on the time interval you had configured.

How to deploy Knative to a Tanzu Kubernetes Grid (TKG) Cluster on both vSphere with Tanzu and TKG Multi-Cloud?

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This weekend I spent some time installing Knative, which is an open source framework that is built on top of Kubernetes. Knative is actually made up of two core components, serving and eventing. This quote from Ram Gopinathan, Principal Technology Architect, T-Mobile really sums up Knative quite nicely:

Knative helps our developers focus on building the business logic rather than worrying about building low-level platform capabilities such as build, deploy, autoscaling, monitoring, and observability.

There are a number of tutorials online for setting up Knative, most of which using Kubernetes in Docker (KinD) for easy local development. Since I have been spending quite a bit of time lately with both our vSphere with Tanzu and Tanzu Kubernetes Grid (TKG) Multi-Cloud solution, which both support deploying conformant and production grade Kubernetes (K8s) Clusters called a TKG Guest Cluster, I figure I might as well learn how to install Knative using these infrastructures.

The instructions below will be focus on deploying the Knative serving components. Once you have that setup, it is easy to deploy the eventing components which you can follow the official Knative documentation.

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