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VCF 9.1.1 - Connecting Pi Coding Agent to VCF Private AI Services (PAIS)

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If you have used Claude Code, Cursor, or OpenAI Codex, you have already experienced Agentic AI, whether it is coding an application, creating a quick script, or debugging an issue. The use cases are infinite, and like many, you can easily burn through your token quota when using the latest state-of-the-art Frontier AI models, which are simply amazing!

While spending some time playing with our latest VCF Private AI Services (PAIS) release (here and here), I have also been trading notes with colleagues doing something similar but rolling their own local AI stack using just vSphere Kubernetes Service (VKS) running on VMware Cloud Foundation (VCF) 9.1.1. Through those conversations, I came to learn about Pi, not the number, but a lightweight coding agent and agent harness that can connect to a number of AI model providers, including those providing an OpenAI-compatible endpoint.

Since VCF PAIS provides an OpenAI-compatible endpoint that can serve one or more AI models, you can now have your own Agentic AI using Pi running within your on-premises environment using various open weight models! 😎

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Quick Tip - Automating vDefend Security Services Platform (SSP) 5.2.0 Installer 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.

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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