Platform engineering has been one of those terms that sounds great in conference talks but usually means “we built an internal portal and a Terraform wrapper.” The real promise — self-service infrastructure that’s actually safe, governed, and fast — has always been a few steps away.
The Azure team just published Part 2 of their agentic platform engineering series, and this one is all about the hands-on implementation. They call it Git-APE (yes, the acronym is intentional), and it’s an open-source project that uses GitHub Copilot agents plus Azure MCP servers to turn natural-language requests into validated, deployed infrastructure.
What Git-APE actually does
The core idea: instead of developers learning Terraform modules, navigating portal UIs, or filing tickets to a platform team, they talk to a Copilot agent. The agent interprets the intent, generates Infrastructure-as-Code, validates it against policies, and deploys — all within VS Code.
Here’s the setup:
git clone https://github.com/Azure/git-ape
cd git-ape
Open the workspace in VS Code, and the agent configuration files are auto-discovered by GitHub Copilot. You interact with the agent directly:
@git-ape deploy a function app with storage in West Europe
The agent uses Azure MCP Server under the hood to interact with Azure services. The MCP configuration in VS Code settings enables specific capabilities:
{
"azureMcp.serverMode": "namespace",
"azureMcp.enabledServices": [
"deploy", "bestpractices", "group",
"subscription", "functionapp", "storage",
"sql", "monitor"
],
"azureMcp.readOnly": false
}
Why this matters
For those of us building on Azure, this shifts the platform engineering conversation from “how do we build a portal” to “how do we describe our guardrails as APIs.” When your platform’s interface is an AI agent, the quality of your constraints and policies becomes the product.
The Part 1 blog laid out the theory: well-described APIs, control schemas, and explicit guardrails make platforms agent-ready. Part 2 proves it works by shipping actual tooling. The agent doesn’t just blindly generate resources — it validates against best practices, respects naming conventions, and applies your organization’s policies.
Clean-up is just as easy:
@git-ape destroy my-resource-group
My take
I’ll be honest — this one is more about the pattern than the specific tool. Git-APE itself is a demo/reference architecture. But the underlying idea — agents as the interface to your platform, MCP as the protocol, GitHub Copilot as the host — is where enterprise developer experience is heading.
If you’re a platform team looking at how to make your internal tooling agent-friendly, there’s no better starting point. And if you’re a .NET developer wondering how this connects to your world: the Azure MCP Server and GitHub Copilot agents work with any Azure workload. Your ASP.NET Core API, your .NET Aspire stack, your containerized microservices — all of it can be the target of an agentic deployment flow.
Wrapping up
Git-APE is an early but concrete look at agentic platform engineering in practice. Clone the repo, try the demo, and start thinking about how your platform’s APIs and policies would need to look for an agent to safely use them.
Read the full post for the walkthrough and video demos.
