I set out to run Windows 365 from my homelab so I could keep control of local resources while trying the convenience of cloud computing. This guide shows how I balance the two. I focus on practical settings you can apply in a homelab setup, privacy settings to watch, simple automation to reduce admin tedium, and how I integrate AI features without handing over everything.
Start with identity and provisioning. Use an Azure AD account for the Cloud PC identity. Assign the Windows 365 licence and create a provisioning policy in Intune or Microsoft Endpoint Manager. Pick an image that matches your needs; for light development and testing I use 2 vCPU and 8GB RAM images, which feel snappy without blowing costs. Configure a provisioning policy that sets the OS image, one or two apps, and an assignment filter so only designated accounts get Cloud PCs. For network, choose split tunnelling so most internet traffic goes direct but sensitive traffic can route through your VPN back to the homelab. That lets a Cloud PC reach a local NAS or Pi without exposing everything to the cloud. Lock down local resource access with Intune device configuration profiles and app restrictions rather than broad firewall rules. For storage, decide if you want OneDrive as the primary home for files. If you do, use Intune policies to control sync behaviour and file types so your NAS does not get eclipsed by cloud storage.
Tidy up privacy settings from the start. Turn down diagnostic data collection in Azure AD device settings and in the provisioning image. Disable automatic sharing of telemetry where possible. Limit camera and microphone access through group policies and app permission policies. If you are experimenting with AI integration, keep a separate policy for Cloud PCs that will use Copilot or other Copilot-like features. Restrict those Cloud PCs from accessing sensitive file shares or local services. I label mine with a tag so automation can treat them differently. That way AI features get the data they need to be useful, without giving them full read access to my home machines.
Automate common tasks so the setup is repeatable. Use Microsoft Graph and PowerShell for bulk licence assignment and provisioning policy deployment. My workflow is simple: a small script that assigns a licence, tags the account, and applies the provisioning policy. Then a scheduled task checks idle Cloud PCs and shuts them down overnight. That saves compute and keeps my homelab tidy. For monitoring and optimisation use the built‑in metrics for CPU, memory and disk. Set alerts for storage thresholds and unexpected CPU spikes. If a Cloud PC shows sustained high I/O, move it to a larger disk or change the image. If you want to test AI workloads, spin up a Cloud PC with extra RAM for short runs, then tear it down automatically.
Expect trade offs. Cloud computing gives you convenience and removes the friction of local installs, but it raises dependency on a vendor and recurring costs. If absolute privacy and tight hardware control matter more than convenience, keep certain workloads on local VMs or a Linux host. For a homelab setup I keep development, backups and sensitive device management local, and put session-heavy, disposable desktops into Windows 365. That split keeps my home network under my control, lets me test AI integration, and keeps bills in check. Follow the specific steps above and you will have a repeatable, privacy-minded Windows 365 configuration that fits a homelab.
