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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 - 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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VCF 9.1.1 - Deploying Your Own AI Models with VCF Private AI Services (PAIS) 3.0

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My recent blog post on the new AI Assistant for VCF in VCF Operations 9.1.1 received a lot of positive feedback from both internal and external readers, especially from those who were not aware that this capability was available and were excited to try it out. The excitement is understandable, as this opens up many interesting possibilities for infrastructure administrators to operate and manage their environments more efficiently.

In that article, I focused on how to enable AI Assistant for VCF and quickly get started using Google Gemini as a cloud-based LLM provider. While that is certainly the fastest way to start exploring the capability, AI Assistant for VCF also supports local AI models deployed using VCF Private AI Services (PAIS) 3.0, enabling customers to take advantage of powerful AI models running securely and more cost-effectively within their own on-premises environment.

In this blog post, we will now focus on deploying and consuming local AI models with PAIS. This builds on another recent article where I walked through the setup of VCF Private AI Services (PAIS) using the Artifact Mirroring Tool (AMT) for air-gapped environments. 

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