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Quick Tip - Automating vDefend Security Services Platform (SSP) 5.2.0 Installer & License Hub 2.0 for vDefend & Avi Load Balancer OVA Deployment

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Given the current security threats from Frontier AI, vDefend Security Services Platform (SSP) was top of mind for many attendees at the recent VMware Explore 2026. Since it had been some time since I last deployed an earlier version of SSP, I wanted to get some hands-on time with the latest release, which of course also meant writing, or rather prompting AI to write, some deployment automation. 😄

vDefend SSP 5.2 is currently the latest release, and I created a PowerCLI script called deploy_vdefend_security_services_platform.ps1 that makes it super easy to automate the deployment of the SSP Installer OVA. To use the script, simply update the variables with the values for your environment and run the script to perform the deployment.


To license vDefend SSP, you also need to deploy the new License Hub 2.0 for VMware vDefend and VMware Avi Load Balancer and I have also created a PowerCLI script called deploy_vdefend_license_hub.ps1

VCF 9.1.1 - Simplified vSphere Kubernetes Service (VKS) using VLAN-Backed VPCs without NSX Tunnel Endpoints (TEPs)

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As part of the VMware Cloud Foundation (VCF) 9.1.1 release, consuming NSX Virtual Private Cloud (VPC) has gotten simpler, especially for environments using traditional VLAN-backed networks. In VCF 9.1.0, users already had the ability to configure a VPC using a Distributed Transit Gateway (DTGW) and Distributed VLAN through the NSX Virtual Network Appliance (VNA), but this still required configuring NSX Tunnel Endpoints (TEPs) on each ESX host.

With VCF 9.1.1, the networking workflow has been further simplified with a new VLAN-backed VPC option. While it still uses DTGW and VNA, TEPs are no longer required, removing additional network requirements such as a larger MTU. As a result, environments that previously could not meet the networking requirements to configure a VPC can now deploy and consume services such as vSphere Kubernetes Service (VKS) and VCF Automation (VCFA).

It is also important to understand the different VPC consumption options and their constraints. The following table summarizes the capabilities and limitations of each option.


Note: DTGW with TEP was possible with VCF 9.0.0 but there was no support for VCFA until VCF 9.1.0.

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VCF 9.1.1 - Using VCF Private AI Services (PAIS) Models with AI Assistant for VCF

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For those following along, earlier this week I demonstrated how to configure the new AI Assistant (Tech Preview) for VCF in VMware Cloud Foundation (VCF) 9.1.1 using Google Gemini as a cloud-based LLM provider, which is a quick way to get started and explore the new capability.

Alongside VCF 9.1.1, we also released VCF Private AI Services (PAIS) 3.0, which enables users to deploy and run their own AI models locally within VCF. In my follow-up articles, I walked through setting up PAIS for an air-gapped environment and then deploying an AI model downloaded from Hugging Face, which PAIS serves through an OpenAI-compatible model endpoint.

In this final blog post, we will bring everything together by connecting AI Assistant for VCF to our PAIS Model Endpoint, allowing the AI Assistant to use an AI model running locally within our VCF environment.

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