AI-Assisted Provisioning on NetActuate

Modern infrastructure teams need a faster way to go from intent to deployment.

That is exactly what AI-assisted provisioning enables on NetActuate.

Instead of digging through variables, editing config files, or manually stitching together deployment steps, you can now use your coding assistant to describe what you want in plain language. With the right repository and guidance in place, your assistant can help translate that request into working infrastructure on NetActuate’s global platform.

That means requests like these can become part of your day-to-day workflow:

• Deploy a VM to LAX with 1 GB RAM and 1 CPU
• Deploy 3 VMs: one in DFW, one in AMS, one in SIN
• Deploy a VM with 4 CPU and 8 GB RAM to FRA
• Deploy a 5-node anycast cluster in LAX, DFW, AMS, SIN, and FRA

NOTE: Anycast PoPs use the local airport code for naming.

If that sounds simpler than traditional provisioning workflows, that is the point.

Making life easier for operators and developers

Provisioning infrastructure is often less about complexity and more about friction.

You already know what you want, such as a VM in a specific market, a certain amount of CPU and RAM, a standard OS image, an SSH key, or a distributed cluster deployed across multiple regions.

What takes time is translating that intent into the exact steps a toolchain expects.

AI-assisted provisioning helps remove that translation overhead.

By combining NetActuate’s infrastructure repositories with AI-aware instructions, developers and operators can work at a higher level. Instead of focusing on syntax and repetitive setup tasks, they can focus on outcomes: where workloads should run, how large they should be, and how globally distributed they need to be.

How it works

NetActuate’s AI-assisted provisioning workflow is built around infrastructure repositories that include guidance for coding assistants. These instructions help tools like Claude Code, Cursor, and GitHub Copilot understand how to work with the repository, what files matter, what values need to be set, and how to validate the deployment.

The result is a smoother path from request to running infrastructure.

You can start with a simple compute deployment, such as:

• a single VM in LAX
• a larger VM in FRA
• a set of VMs across multiple global locations

Or you can take the next step and provision a geographically distributed anycast cluster spanning major global markets.

For a detailed walkthrough, see our guide to AI-assisted provisioning.

Start with compute

A good first use case is basic VM provisioning.

Instead of manually piecing together plans, locations, variables, and commands, you can describe the instance you want in natural language and let your coding assistant help map that request to the correct configuration.

Examples include:

• “Deploy a VM to LAX with 1 GB RAM and 1 CPU”
• “Deploy a VM with 4 CPU and 8 GB RAM to FRA”
• “Deploy 3 VMs: one in DFW, one in AMS, one in HND”

This is especially useful for teams that want to move quickly without sacrificing consistency. Once your preferred defaults are set, spinning up additional infrastructure becomes much faster and more repeatable.

To explore the compute workflow, start with the NetActuate compute automation repository on GitHub: https://github.com/netactuate/netactuate-ansible-compute

Then scale up to anycast

Where AI-assisted provisioning becomes even more compelling is in multi-region and anycast deployments.

Building a global anycast footprint traditionally involves more moving parts: multiple nodes, multiple PoPs, routing configuration, service setup, validation, and cleanup. That is exactly the kind of repetitive orchestration that benefits from a more intelligent interface.

With AI-assisted provisioning, you can describe the target topology in a single request, such as:

• “Deploy a 5-node anycast cluster in LAX, AMS, SIN, LHR, and WAW”

From there, your coding assistant can help work through the repository structure and deployment flow required to bring that design to life on NetActuate.

For teams building latency-sensitive, resilient, globally distributed services, this creates a much more accessible path to deploying at the edge.

To explore the anycast workflow, see the NetActuate BGP/BIRD2 automation repository:
https://github.com/netactuate/netactuate-ansible-bgp-bird2

Why this matters

AI-assisted provisioning offers a valuable supplement to traditional infrastructure knowledge, and makes that knowledge easier to apply.

Operators still control architecture, location strategy, sizing, routing, validation, and production readiness. What changes is the amount of repetitive work required to get there.

That makes AI-assisted provisioning especially valuable for:

• teams deploying across multiple global markets
• developers who want to self-serve common infrastructure tasks
• operators standardizing repeatable deployment patterns
• organizations building globally distributed, highly available services

In short, it helps teams get from idea to infrastructure faster.

A better interface for global infrastructure

NetActuate is built for globally distributed compute and networking. AI-assisted provisioning now makes that platform even easier to use.

Get started

Read the guide:
https://www.netactuate.com/docs/guides/ai-assisted-provisioning

Explore the compute repo:
https://github.com/netactuate/netactuate-ansible-compute

Explore the anycast repo:
‍https://github.com/netactuate/netactuate-ansible-bgp-bird2